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1
Walther, Dirk, and Fred E. Cohen. "Conformational attractors on the Ramachandran map." Acta Crystallographica Section D Biological Crystallography 55, no. 2 (February 1, 1999): 506–17. http://dx.doi.org/10.1107/s0907444998013353.
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Frequency distributions of protein backbone dihedral angles φ and ψ have been analyzed systematically for their apparent correlation with various crystallographic parameters, including the resolution at which the protein structures had been determined, the R factor and the free R factor, and the results have been displayed in novel differential Ramachandran maps. With improved sensitivity compared with conventionally derived heuristic Ramachandran maps, such differential maps automatically reveal conformational `attractors' to which φ/ψ distributions converge as the crystallographic resolution improves, as well as conformations tied specifically to low-resolution structures. In particular, backbone angular combinations associated with residues in α-helical conformation show a pronounced consolidation with substantially narrowed φ/ψ distributions at higher (better) resolution. Convergence to distinct conformational attractors was also observed for all other secondary-structural types and random-coil conformations. Similar resolution-dependent φ/ψ evolutions were obtained for different crystallographic refinement packages, documenting the absence of any significant artificial biases in the refinement programs investigated here. A comparison of differential Ramachandran maps derived for the R factor and the free R factor as independent parameters proved the better suitability of the free R factor for structure-quality assessment. The resolution-based differential Ramachandran map is available as a reference for comparison with actual protein structural data under WebMol, a Java-based structure viewing and analysis program (http://www.cmpharm.ucsf.edu/cgi-bin/webmol.pl).
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SZABADKA, ZOLTÁN, RAFAEL ÖRDÖG, and VINCE GROLMUSZ. "THE RAMACHANDRAN MAP OF MORE THAN 6,500 PERFECT POLYPEPTIDE CHAINS." Biophysical Reviews and Letters 02, no. 03n04 (October 2007): 267–71. http://dx.doi.org/10.1142/s1793048007000519.
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The Protein Data Bank (PDB) is the most important depository of protein structural information, containing more than 45,000 deposited entries today. Because of its inhomogeneous structure, its fully automated processing is almost impossible. In a previous work, we cleaned and re-structured the entries in the Protein Data Bank, and from the result we have built the RS-PDB database. Using the RS-PDB database, we draw a Ramachandran-plot from 6,593 "perfect" polypeptide chains found in the PDB, containing 1,192,689 residues. This is a more than tenfold increase in the size of data analyzed before this work. The density of the data points makes it possible to draw a logarithmic heat map enhanced Ramachandran map, showing the fine inner structure of the right-handed α-helix region.
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Zaman, Ahmed Bin, and Amarda Shehu. "Building maps of protein structure spaces in template-free protein structure prediction." Journal of Bioinformatics and Computational Biology 17, no. 06 (December 2019): 1940013. http://dx.doi.org/10.1142/s0219720019400134.
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An important goal in template-free protein structure prediction is how to control the quality of computed tertiary structures of a target amino-acid sequence. Despite great advances in algorithmic research, given the size, dimensionality, and inherent characteristics of the protein structure space, this task remains exceptionally challenging. It is current practice to aim to generate as many structures as can be afforded so as to increase the likelihood that some of them will reside near the sought but unknown biologically-active/native structure. When operating within a given computational budget, this is impractical and uninformed by any metrics of interest. In this paper, we propose instead to equip algorithms that generate tertiary structures, also known as decoy generation algorithms, with memory of the protein structure space that they explore. Specifically, we propose an evolving, granularity-controllable map of the protein structure space that makes use of low-dimensional representations of protein structures. Evaluations on diverse target sequences that include recent hard CASP targets show that drastic reductions in storage can be made without sacrificing decoy quality. The presented results make the case that integrating a map of the protein structure space is a promising mechanism to enhance decoy generation algorithms in template-free protein structure prediction.
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Javed, Ambreen, Gulshan Ara Trali, Hassan Burair Abbas, and Alia Sadiq. "IN SILICO CHARACTERIZATION OF HUMAN INTERFERON ALPHA/BETA RECEPTOR 2 (ISOFORM A, B AND C) PROTEIN." PAFMJ 71, no. 6 (December 31, 2021): 2091–94. http://dx.doi.org/10.51253/pafmj.v71i6.6571.
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Objective: To predict the tertiary structure of human interferon alpha/beta receptor 2 protein.
Study Design: Structure prediction by using bio informatics tools.
Place and Duration of Study: Department of Biochemistry, Swat Medical College (STMC), Saidu Shareef, Swat, Pakistan, from Aug 2019 to Dec 2019.
Methodology: All protein sequences of human interferon alpha/beta receptor 2 (isoforma, b and c) (IFNAR-2) were retrieved through the BLAST search (The Basic Local Alignment Search Tool) from available databases ‘NCBI’ (National Centre for Biotechnology Information) and ‘Uni Prot KB’ (The Universal Protein Resource). Sequence alignment was conducted by using Clustal Omega, to get the consensus sequence for IFNAR-2 protein. Consensus protein sequence of human IFNAR-2 was used for the prediction of the three-dimensional structure by employing Swiss-Model Server. Moreover, subcellular localization analysis was also performed by using CELLO2GO program.
Results: Structural model of human IFNAR-2 protein was predicted and evaluated by Ramachandran dimension. Cellular localization of tertiary topological domains of the predicted models were revealed probability of localization of IFNAR-2 protein (isoform a, b & c) is highest in the plasma membrane due to the presence of the transmembrane alpha helical regions.
Conclusion: This study predicted the tertiary structural dimensions of human IFNAR-2 protein, including the specific topological domains that contribute towards the subcellular compartmentalization and functional characteristics.
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Malagón Bernal, Rafael Eduardo, Manuel Alejandro Fernández Navas, and Orlando Emilio Acevedo Sarmiento. "Modelo molecular teórico del receptor serotoninérgico 5HT2A acoplado a proteína G." Universitas Scientiarum 17, no. 2 (June 1, 2012): 119. http://dx.doi.org/10.11144/javeriana.sc17-2.tmmo.
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<strong>Objective</strong> Build a theoretical molecular model of the tertiary structure of the Homo sapiens 5HT2A receptor from experimentally obtained structures as templates. <strong>Materials</strong> <strong>and methods</strong> In the construction of the theoretical model we considered the protocol established by Ballesteros and Weinstein for the construction of the G-protein coupled receptor, by the alignment of the amino acid sequence, hydrophobicity profiles, refinement of loops by spatial restrictions and energy minimization with the force field OPLS_2005. <strong>Results</strong> The resulting model was validated by the Ramachandran plot with 91.7% of amino acids within the limits set for angles phi and psi and a RMSD of 0.95 Å with respect to bovine rhodopsin. <strong>Conclusions</strong> We obtained a validated theoretical model useful in studies of ligand-receptor docking.<br /><strong>Key words</strong>: G protein receptor, hydrophobicity profile, Ramachandran plot, orthosteric site, molecular modelling.
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Aslam, Shakira, Hafiz Muzzammel Rehman, Muhammad Zeeshan Sarwar, Ajaz Ahmad, Nadeem Ahmed, Muhammad Imran Amirzada, Hafiz Muhammad Rehman, Humaira Yasmin, Tariq Nadeem, and Hamid Bashir. "Computational Modeling, High-Level Soluble Expression and In Vitro Cytotoxicity Assessment of Recombinant Pseudomonas aeruginosa Azurin: A Promising Anti-Cancer Therapeutic Candidate." Pharmaceutics 15, no. 7 (June 26, 2023): 1825. http://dx.doi.org/10.3390/pharmaceutics15071825.
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Azurin is a natural protein produced by Pseudomonas aeruginosa that exhibits potential anti-tumor, anti-HIV, and anti-parasitic properties. The current study aimed to investigate the potential of azurin protein against breast cancer using both in silico and in vitro analyses. The amino acid sequence of Azurin was used to predict its secondary and tertiary structures, along with its physicochemical properties, using online software. The resulting structure was validated and confirmed using Ramachandran plots and ERRAT2. The mature azurin protein comprises 128 amino acids, and the top-ranked structure obtained from I-TASSER was shown to have a molecular weight of 14 kDa and a quality factor of 100% by ERRAT2, with 87.4% of residues in the favored region of the Ramachandran plot. Docking and simulation studies of azurin protein were conducted using HDOCK and Desmond servers, respectively. The resulting analysis revealed that Azurin docked against p53 and EphB2 receptors demonstrated maximum binding affinity, indicating its potential to cause apoptosis. The recombinant azurin gene was successfully cloned and expressed in a BL21 (DE3) strain using a pET20b expression vector under the control of the pelB ladder, followed by IPTG induction. The azurin protein was purified to high levels using affinity chromatography, yielding 70 mg/L. In vitro cytotoxicity assay was performed using MCF-7 cells, revealing the significant cytotoxicity of the azurin protein to be 105 µg/mL. These findings highlight the potential of azurin protein as an anticancer drug candidate.
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CHEON, MOOKYUNG, MUYOUNG HEO, IKSOO CHANG, and CHOONGRAK KIM. "CLASSIFICATIONS OF AMINO ACIDS IN PROTEINS BY THE SELF-ORGANIZING MAP." International Journal of Modern Physics C 16, no. 10 (October 2005): 1609–16. http://dx.doi.org/10.1142/s0129183105008175.
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We present the clustering properties of amino acids, which are building blocks of proteins, according to their physico-chemical characters. To classify the 20 kinds of amino acids, we employ a Self-Organizing Map (SOM) analysis for the Miyazawa-Jernigan (MJ) pairwise-contact matrix, the Environment-dependent One-body energy Parameters (EOP) and the one-body energy parameters incorporating the Ramachandran angle information (EOPR) over the EOP in proteins. We provide the new result of the SOM clustering for amino acids based on the EOPR and compare that with those from the MJ and the EOP matrix. All three kinds of energy parameters capture the leading role played by the hydrophobicity and the hydrophilicity of amino acids in protein folding. Our SOM analysis generally illustrates that both the EOP and the EOPR can provide the collective clustering of amino acids by the side chain characteristics and the secondary structure information. However, EOP is better at classifying amino acids according to their side chain characteristics whereas EOPR is better with secondary structure. We show that the EOP and the EOPR matrix manifests more detailed physico-chemical classification of amino acids than those from the MJ matrix, which does not contain a local environmental information of amino acids in the protein structures.
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Adegoke, Afeez Babatunde. "Molecular Dynamic (MD) Simulation and Modeling the Bio-molecular Structure of Human UDP glucose -6-dehydrogenase Isoform 1 (hUGDH) Related to Prostate Cancer." BASRA JOURNAL OF SCIENCE 38, no. 3 (August 1, 2020): 448–66. http://dx.doi.org/10.29072/basjs.202036.
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Computational methods were used to investigate both the physical and chemical properties of UDP-glucose 6-dehydrogenase (hUGDH). Secondary structure analysis of the query model was done using the Self-Optimized Prediction method With Alignment (SOPMA), the secondary structure predictions comprise of 40.69% Alpha helixes (Hh), 17.61% Extended strand (Ee), 7.69% Beta turn (Tt) and 34.01% of Random coil (Cc) with aliphatic index of 90.00 and instability index of 33.26 which classify the protein model to be thermally stable irrespective of it environment. Comparative modeling was used to predict a reliable tertiary structure for hUGDH and the obtained 3-dimensional model was validated using DOPE score profile, Ramachandran plot, and the QMEAN Z-score. The DOPE score profile shows a high similarity between the model and the template as little or no disparity was found in the profile patterns. Ramachandran plot of the model also shows that 92.5% of the amino acid residues were found at the most favored regions which make it stereo-chemically stable. The QMEAN z-score of UDP-glucose 6-dehydrogenase was predicted to be -0.15. The superimposed structure of the model and the template also gave RMSD of 0.125. All this shows that the predicted model is of good quality. An RMSD and Rg run via molecular dynamics (MD) simulation equally shows that the protein model attained stability at around 10ns. Protein – Protein interaction (PPI) network was also generated for the model with a high confidence score from UDP-glucuronic acid decarboxylase 1 (UXS1) when interacted with the other twenty proteins. In addition, the docking studies of the model and 3PRJ receptors with two prostate cancer drugs i.e. Apalutamide and Darolutamide gave similar binding affinity ranging between 6.0kcal/mol – 8.0kcal/mol for the most favored binding of the two drugs. Hence, the model can serve as a molecular target for designing new inhibitors for prostate cancer
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Saikat, Abu Saim Mohammad, Rabiul Islam, Shahriar Mahmud, Md Abu Sayeed Imran, Mohammad Shah Alam, Mahmudul Hasan Masud, and Md Ekhlas Uddin. "Structural and Functional Annotation of Uncharacterized Protein NCGM946K2_146 of Mycobacterium Tuberculosis: An In-Silico Approach." Proceedings 66, no. 1 (December 30, 2020): 13. http://dx.doi.org/10.3390/proceedings2020066013.
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The human pathogen Mycobacterium tuberculosis (MTB) is indeed one of the renowned, important, longtime infectious diseases, tuberculosis (TB). Interestingly, MTB infection has become one of the world’s leading causes of human death. In trehalose synthase, the protein NCGM 946K2 146 found in MTB has an important role. For carbohydrate transport and metabolism, trehalose synthase is required. The protein is not clarified yet, though. In this research, an in silico approach was, therefore, formulated for functional and structural documentation of the uncharacterized protein NCGM946K2_146.Three distinct servers, including Modeller, Phyre2, and Swiss Model, were used to evaluate the predicted tertiary structure. The top materials are selected using structural evaluations conducted with the analysis of Ramachandran Plot, Swiss-Model Interactive Workplace, ProSA-web, Verify 3D, and Z scores. This analysis aimed to uncover the value of the NCGM946K2_146 protein of MTB. This research will, therefore, improve our pathogenesis awareness and give us a chance to target the protein compound.
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Fahim, Ammad, Zaira Rehman, Muhammad Faraz Bhatti, Amjad Ali, Nasar Virk, Amir Rashid, and Rehan Zafar Paracha. "Structural insights and characterization of human Npas4 protein." PeerJ 6 (June 14, 2018): e4978. http://dx.doi.org/10.7717/peerj.4978.
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Npas4 is an activity dependent transcription factor which is responsible for gearing the expression of target genes involved in neuro-transmission. Despite the importance of Npas4 in many neuronal diseases, the tertiary structure of Npas4 protein along with its physico-chemical properties is limited. In the current study, first we perfomed the phylogenetic analysis of Npas4 and determined the content of hydrophobic, flexible and order-disorder promoting amino acids. The protein binding regions, post-translational modifications and crystallization propensity of Npas4 were predicted through different in-silico methods. The three dimensional model of Npas4 was predicted through LOMET, SPARSKS-X, I-Tasser, RaptorX, MUSTER and Pyhre and the best model was selected on the basis of Ramachandran plot, PROSA, and Qmean scores. The best model was then subjected to further refinement though MODREFINER. Finally the interacting partners of Npas4 were identified through STRING database. The phylogenetic analysis showed the human Npas4 gene to be closely related to other primates such as chimpanzees, monkey, gibbon. The physiochemical properties of Npas4 showed that it is an intrinsically disordered protein with N-terminal ordered region. The post-translational modification analyses indicated absence of acetylation and mannosylation sites. Three potential phosphorylation sites (S108, T130 and T136) were found in PAS A domain whilst a single phosphorylation site (S273) was present in PAS B domain. The predicted tertiary structure of Npas4 showed that bHLH domain and PAS domain possess tertiary structures while the rest of the protein exhibited disorder property. Protein-protein interaction analysis revealed NPas4 interaction with various proteins which are mainly involved in nuclear trafficking of proteins to cytoplasm, activity regulated gene transcription and neurodevelopmental disorders. Moreover the analysis also highlighted the direct relation to proteins involved in promoting neuronal survival, plasticity and cAMP responsive element binding protein proteins. The current study helps in understanding the physicochemical properties and reveals the neuro-modulatory role of Npas4 in crucial pathways involved in neuronal survival and neural signalling hemostasis.
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Cortés, Gualberto Asencio, and Jesús A. Aguilar-Ruiz. "Predicting protein distance maps according to physicochemical properties." Journal of Integrative Bioinformatics 8, no. 3 (December 1, 2011): 158–75. http://dx.doi.org/10.1515/jib-2011-181.
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SummaryThe prediction of protein structures is a current issue of great significance in structural bioinformatics. More specifically, the prediction of the tertiary structure of a protein con- sists in determining its three-dimensional conformation based solely on its amino acid sequence. This study proposes a method in which protein fragments are assembled according to their physicochemical similarities, using information extracted from known protein structures. Many approaches cited in the literature use the physicochemical properties of amino acids, generally hydrophobicity, polarity and charge, to predict structure. In our method, implemented with parallel multithreading, we used a set of 30 physicochemical amino acid properties selected from the AAindex database. Several protein tertiary structure prediction methods produce a contact map. Our proposed method produces a distance map, which provides more information about the structure of a protein than a contact map. We performed several preliminary analysis of the protein physicochemical data distributions using 3D surfaces. Three main pattern types were found in 3D surfaces, thus it is possible to extract rules in order to predict distances between amino acids according to their physicochemical properties. We performed an experimental validation of our method using five non-homologous protein sets and we showed the generality of this method and its prediction quality using the amino acid properties considered. Finally, we included a study of the algorithm efficiency according to the number of most similar fragments considered and we notably improved the precision with the studied proteins sets.
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Kishk, Safaa M., Rania M. Kishk, Asmaa S. A. Yassen, Mohamed S. Nafie, Nader A. Nemr, Gamal ElMasry, Salim Al-Rejaie, and Claire Simons. "Molecular Insights into Human Transmembrane Protease Serine-2 (TMPS2) Inhibitors against SARS-CoV2: Homology Modelling, Molecular Dynamics, and Docking Studies." Molecules 25, no. 21 (October 29, 2020): 5007. http://dx.doi.org/10.3390/molecules25215007.
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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), which caused novel corona virus disease-2019 (COVID-19) pandemic, necessitated a global demand for studies related to genes and enzymes of SARS-CoV2. SARS-CoV2 infection depends on the host cell Angiotensin-Converting Enzyme-2 (ACE2) and Transmembrane Serine Protease-2 (TMPRSS2), where the virus uses ACE2 for entry and TMPRSS2 for S protein priming. The TMPRSS2 gene encodes a Transmembrane Protease Serine-2 protein (TMPS2) that belongs to the serine protease family. There is no crystal structure available for TMPS2, therefore, a homology model was required to establish a putative 3D structure for the enzyme. A homology model was constructed using SWISS-MODEL and evaluations were performed through Ramachandran plots, Verify 3D and Protein Statistical Analysis (ProSA). Molecular dynamics simulations were employed to investigate the stability of the constructed model. Docking of TMPS2 inhibitors, camostat, nafamostat, gabexate, and sivelestat, using Molecular Operating Environment (MOE) software, into the constructed model was performed and the protein-ligand complexes were subjected to MD simulations and computational binding affinity calculations. These in silico studies determined the tertiary structure of TMPS2 amino acid sequence and predicted how ligands bind to the model, which is important for drug development for the prevention and treatment of COVID-19.
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Nambigari, Navaneetha. "Cancer Therapeutics: Structure-Based Drug Design of Inhibitors for a Novel Angiogenic Growth Factor." Mathematical Biology and Bioinformatics 18, no. 1 (March 26, 2023): 72–88. http://dx.doi.org/10.17537/2023.18.72.
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Angiogenesis, the formation of new blood vessels, is a critical and rate-limiting tumor growth step controlled by pro-angiogenic factors and specific inhibitors. Tumor angiogenesis is essential for cancer progression and metastasis. Platelet growth factors (PDGF) and their receptors (PDGFR) are associated with tumor angiogenesis through overexpression of PDGF. Inhibition of PDGF and its signaling pathway is a new approach to the discovery of anticancer therapeutic agents. The present study focuses on the PDGF-C protein in the identification of novel anti-angiogenic compounds. MODELLER 9.10 software allows users to create and refine a 3D homology model of the PDGF-C protein (345 a.a. length). Secondary structure analysis of the 3D energy model reveals 16 β sheets held together by four cation–π and one π–σ interactions, and three salt bridges. The quality of the model is assessed using the Ramachandran plot (90 percent amino acids in the favorable region) and the ProSA server (Z-score = –2.28). Active site residues are identified using Castp, QSite search engine, site map, and protein docking of the protein to its receptor. In addition, virtual screening is performed at the active site using the Glide module of the Schrodinger Suite. Glide score, glide energy and ADME are being measured to discover new benefits of pyrazolone and pyrrolidine-2,3-dione scaffolds as potent PDGF-C antagonists for anti-angiogenic cancer chemotherapy drugs.
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Khan, Khushbukhat, Sadia Safi, Asma Abbas, Yasmin Badshah, Erum Dilshad, Mehak Rafiq, Kainat Zahra, and Maria Shabbir. "Unravelling Structure, Localization, and Genetic Crosstalk of KLF3 in Human Breast Cancer." BioMed Research International 2020 (December 26, 2020): 1–15. http://dx.doi.org/10.1155/2020/1354381.
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Breast cancer is the most prevailing disease among women. It actually develops from breast tissue and has heterogeneous and complex nature that constitutes multiple tumor quiddities. These features are associated with different histological forms, distinctive biological characteristics, and clinical patterns. The predisposition of breast cancer has been attributed to a number of genetic factors, associated with the worst outcomes. Unfortunately, their behavior with relevance to clinical significance remained poorly understood. So, there is a need to further explore the nature of the disease at the transcriptome level. The focus of this study was to explore the influence of Krüppel-like factor 3 (KLF3), tumor protein D52 (TPD52), microRNA 124 (miR-124), and protein kinase C epsilon (PKCε) expression on breast cancer. Moreover, this study was also aimed at predicting the tertiary structure of KLF3 protein. Expression of genes was analyzed through real-time PCR using the delta cycle threshold method, and statistical significance was calculated by two-way ANOVA in Graphpad Prism. For the construction of a 3D model, various bioinformatics software programs, Swiss Model and UCSF Chimera, were employed. The expression of KLF3, miR-124, and PKCε genes was decreased (fold change: 0.076443, 0.06969, and 0.011597, respectively). However, there was 2-fold increased expression of TPD52 with p value < 0.001 relative to control. Tertiary structure of KLF3 exhibited 80.72% structure conservation with its template KLF4 and was 95.06% structurally favored by a Ramachandran plot. These genes might be predictors of stage, metastasis, receptor, and treatment status and used as new biomarkers for breast cancer diagnosis. However, extensive investigations at the tissue level and in in vivo are required to further strengthen their role as a potential biomarker for prognosis of breast cancer.
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Shafique, Qurrat ul Ain, Hafiz Muzzammel Rehman, Tahreem Zaheer, Rana Adnan Tahir, Munir Ahmad Bhinder, Roquyya Gul, and Mahjabeen Saleem. "A Computational Approach to Modeling an Antagonistic Angiogenic VEGFR1-IL2 Fusion Protein for Cancer Therapy." Bioinformatics and Biology Insights 15 (January 2021): 117793222110432. http://dx.doi.org/10.1177/11779322211043297.
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In cancer treatment, immunotherapy has great potential for improving the prognosis of patients with hematologic and solid malignancies. In this study, various bioinformatics tools and servers were used to design an antiangiogenic fusion protein. After comprehensive evaluation, an antiangiogenic fusion protein was designed using a soluble extracellular domain of human vascular endothelial growth factor receptor 1 (sVEGFR-1) and human interleukin-2 (IL-2) joined by a flexible linker. The final construct was composed of 875 amino acids. The secondary structure of the fusion protein, obtained by CFSSP, PSIPRED, and SOPMA tools, consisted of 14.17% helices, 29.71% extended strands, 4.69% beta turns and 51.43% random coils. Tertiary structure prediction by Raptor X showed that the fusion protein comprises 3 domains with 875 modeled amino acids, out of which 26 positions (2%) were considered disordered. The Ramachandran plot revealed 89.3%, 7.1%, and 3.6% amino acid residues in favored, allowed, and outlier regions, respectively. Physical features of the Molecular Dynamic (MD) simulated system such as root mean square deviation, root mean square fluctuation, solvent-on hand surface region, and radius of gyration identified the fusion construct as a stable and compact protein with few fluctuations in its overall structure. Docking of the fusion protein showed that interaction between sVEGFR-1/VEGFA and IL-2/IL-2R still exists. In silico analysis revealed that the fusion protein comprising IL-2 and sVEGFR-1 has stable structure and the selected linker can efficiently separate the two domains. These observations may be helpful in determining protein stability prior to protein expression.
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Huang, He, and Xinqi Gong. "A Review of Protein Inter-residue Distance Prediction." Current Bioinformatics 15, no. 8 (January 1, 2021): 821–30. http://dx.doi.org/10.2174/1574893615999200425230056.
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Proteins are large molecules consisting of a linear sequence of amino acids. Protein performs biological functions with specific 3D structures. The main factors that drive proteins to form these structures are constraint between residues. These constraints usually lead to important inter-residue relationships, including short-range inter-residue contacts and long-range interresidue distances. Thus, a highly accurate prediction of inter-residue contact and distance information is of great significance for protein tertiary structure computations. Some methods have been proposed for inter-residue contact prediction, most of which focus on contact map prediction and some reviews have summarized the progresses. However, inter-residue distance prediction is found to provide better guidance for protein structure prediction than contact map prediction in recent years. The methods for inter-residue distance prediction can be roughly divided into two types according to the consideration of distance value: one is based on multi-classification with discrete value and the other is based on regression with continuous value. Here, we summarize these algorithms and show that they have obtained good results. Compared to contact map prediction, distance map prediction is in its infancy. There is a lot to do in the future including improving distance map prediction precision and incorporating them into residue-residue distanceguided ab initio protein folding.
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Alam, Fardina Fathmiul, and Amarda Shehu. "Data Size and Quality Matter: Generating Physically-Realistic Distance Maps of Protein Tertiary Structures." Biomolecules 12, no. 7 (June 29, 2022): 908. http://dx.doi.org/10.3390/biom12070908.
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With the debut of AlphaFold2, we now can get a highly-accurate view of a reasonable equilibrium tertiary structure of a protein molecule. Yet, a single-structure view is insufficient and does not account for the high structural plasticity of protein molecules. Obtaining a multi-structure view of a protein molecule continues to be an outstanding challenge in computational structural biology. In tandem with methods formulated under the umbrella of stochastic optimization, we are now seeing rapid advances in the capabilities of methods based on deep learning. In recent work, we advance the capability of these models to learn from experimentally-available tertiary structures of protein molecules of varying lengths. In this work, we elucidate the important role of the composition of the training dataset on the neural network’s ability to learn key local and distal patterns in tertiary structures. To make such patterns visible to the network, we utilize a contact map-based representation of protein tertiary structure. We show interesting relationships between data size, quality, and composition on the ability of latent variable models to learn key patterns of tertiary structure. In addition, we present a disentangled latent variable model which improves upon the state-of-the-art variable autoencoder-based model in key, physically-realistic structural patterns. We believe this work opens up further avenues of research on deep learning-based models for computing multi-structure views of protein molecules.
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Rudnev, Vladimir R., Kirill S. Nikolsky, Denis V. Petrovsky, Liudmila I. Kulikova, Anton M. Kargatov, Kristina A. Malsagova, Alexander A. Stepanov, Arthur T. Kopylov, Anna L. Kaysheva, and Alexander V. Efimov. "3β-Corner Stability by Comparative Molecular Dynamics Simulations." International Journal of Molecular Sciences 23, no. 19 (October 2, 2022): 11674. http://dx.doi.org/10.3390/ijms231911674.
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This study explored the mechanisms by which the stability of super-secondary structures of the 3β-corner type autonomously outside the protein globule are maintained in an aqueous environment. A molecular dynamic (MD) study determined the behavioral diversity of a large set of non-homologous 3β-corner structures of various origins. We focused on geometric parameters such as change in gyration radius, solvent-accessible area, major conformer lifetime and torsion angles, and the number of hydrogen bonds. Ultimately, a set of 3β-corners from 330 structures was characterized by a root mean square deviation (RMSD) of less than 5 Å, a change in the gyration radius of no more than 5%, and the preservation of amino acid residues positioned within the allowed regions on the Ramachandran map. The studied structures retained their topologies throughout the MD experiments. Thus, the 3β-corner structure was found to be rather stable per se in a water environment, i.e., without the rest of a protein molecule, and can act as the nucleus or “ready-made” building block in protein folding. The 3β-corner can also be considered as an independent object for study in field of structural biology.
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Mohseni Moghadam, Zeynab, Raheleh Halabian, Hamid Sedighian, Elham Behzadi, Jafar Amani, and Abbas ali Imani fooladi. "Designing and Analyzing the Structure of DT-STXB Fusion Protein as an Anti-tumor Agent: An in Silico Approach." Iranian Journal of Pathology 14, no. 4 (September 22, 2019): 305–12. http://dx.doi.org/10.30699/ijp.2019.101200.2004.
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Background & Objective: A main contest in chemotherapy is to obtain regulator above the biodistribution of cytotoxic drugs. The utmost promising strategy comprises of drugs coupled with a tumor-targeting bearer that results in wide cytotoxic activity and particular delivery. The B-subunit of Shiga toxin (STxB) is nontoxic and possesses low immunogenicity that exactly binds to the globotriaosylceramide (Gb3/CD77). Gb3/CD77 extremely expresses on a number of human tumors such as pancreatic, colon, and breast cancer and acts as a functional receptor for Shiga toxin (STx). Then, this toxin can be applied to target Gb3-positive human tumors. In this study, we evaluated DT390-STXB chimeric protein as a new anti-tumor candidate via genetically fusing the DT390 fragment of DT538 (Native diphtheria toxin) to STxB. Methods: This study intended to investigate the DT390- STxB fusion protein structure in silico. Considering the Escherichia coli codon usage, the genomic construct was designed. The properties and the structure of the protein were determined by an in silico technique. The mRNA structure and the physicochemical characteristics, construction, and the stability of the designed chimeric protein were analyzed using computational and bioinformatics tools and servers. Hence, the GOR4 and I-TASSER online web servers were used to predict the secondary and tertiary structures of the designed protein. Results: The results demonstrated that codon adaptation index (CAI) of dt390-stxB chimeric gene raised from 0.6 in the wild type to 0.9 in the chimeric optimized gene. The mfold data revealed that the dt390-stxB mRNA was completely stable to be translated effectively in the novel host. The normal activity of the fusion protein determined by considering the secondary and tertiary structure of each construct. Energy calculation data indicated that the thermodynamic ensemble for mRNA structure was -427.40 kJ/mol. The stability index (SI) of DT390-STxB was 36.95, which is quite appropriate to preserve the stability of the construct. Ultimately, the DT390-STxB was classified as a steady fusion protein according to the Ramachandran plot. Conclusion: Our results showed that DT390-STXB was a stable chimeric protein and it can be recruited as a candidate of novel anti-tumor agents for the development of breast cancer treatment.
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Asghari, Ali, Bahareh Kordi, Bahman Maleki, Hamidreza Majidiani, Morteza Shams, and Razi Naserifar. "Neospora caninum SRS2 Protein: Essential Vaccination Targets and Biochemical Features for Next-Generation Vaccine Design." BioMed Research International 2022 (April 6, 2022): 1–13. http://dx.doi.org/10.1155/2022/7070144.
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Vaccination is a standout preventive measure to combat neosporosis among cattle herds. The present in silico study was done to evaluate the physicochemical properties and potent immunogenic epitopes of N. caninum SRS2 protein as a possible vaccine candidate. Web-based tools were used to predict physicochemical properties, antigenicity, allergenicity, solubility, posttranslational modification (PTM) sites, transmembrane domains and signal peptide, and secondary and tertiary structures as well as intrinsically disordered regions, followed by identification and screening of potential linear and conformational B-cell epitopes and those peptides having affinity to bind mouse major histocompatibility complex (MHC) and cytotoxic T lymphocyte (CTL). The protein had 401 residues with a molecular weight of 42 kDa, representing aliphatic index of 69.35 (thermotolerant) and GRAVY score of -0.294 (hydrophilic). There were 53 PTM sites without a signal peptide in the sequence. Secondary structure comprised mostly by extended strand, followed by helices and coils. The Ramachandran plot of the refined model showed 90.2%, 8.8%, 0.5%, and 0.5% residues in the favored, additional allowed, generously allowed, and disallowed regions, correspondingly. Additionally, various potential B-cell (linear and conformational), CTL, and MHC-binding epitopes were predicted for N. caninum SRS2. These epitopes could be further utilized in the multiepitope vaccine constructs directed against neosporosis.
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Greenbury, Sam F., Iain G. Johnston, Ard A. Louis, and Sebastian E. Ahnert. "A tractable genotype–phenotype map modelling the self-assembly of protein quaternary structure." Journal of The Royal Society Interface 11, no. 95 (June 6, 2014): 20140249. http://dx.doi.org/10.1098/rsif.2014.0249.
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The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here, we introduce a rich, intuitive and biologically realistic genotype–phenotype (GP) map that serves as a model of self-assembling biological structures, such as protein complexes, and remains computationally and analytically tractable. Our GP map arises naturally from the self-assembly of polyomino structures on a two-dimensional lattice and exhibits a number of properties: redundancy (genotypes vastly outnumber phenotypes), phenotype bias (genotypic redundancy varies greatly between phenotypes), genotype component disconnectivity (phenotypes consist of disconnected mutational networks) and shape space covering (most phenotypes can be reached in a small number of mutations). We also show that the mutational robustness of phenotypes scales very roughly logarithmically with phenotype redundancy and is positively correlated with phenotypic evolvability. Although our GP map describes the assembly of disconnected objects, it shares many properties with other popular GP maps for connected units, such as models for RNA secondary structure or the hydrophobic-polar (HP) lattice model for protein tertiary structure. The remarkable fact that these important properties similarly emerge from such different models suggests the possibility that universal features underlie a much wider class of biologically realistic GP maps.
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Yesselman, Joseph D., Sarah K. Denny, Namita Bisaria, Daniel Herschlag, William J. Greenleaf, and Rhiju Das. "Sequence-dependent RNA helix conformational preferences predictably impact tertiary structure formation." Proceedings of the National Academy of Sciences 116, no. 34 (August 2, 2019): 16847–55. http://dx.doi.org/10.1073/pnas.1901530116.
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Structured RNAs and RNA complexes underlie biological processes ranging from control of gene expression to protein translation. Approximately 50% of nucleotides within known structured RNAs are folded into Watson–Crick (WC) base pairs, and sequence changes that preserve these pairs are typically assumed to preserve higher-order RNA structure and binding of macromolecule partners. Here, we report that indirect effects of the helix sequence on RNA tertiary stability are, in fact, significant but are nevertheless predictable from a simple computational model called RNAMake-∆∆G. When tested through the RNA on a massively parallel array (RNA-MaP) experimental platform, blind predictions for >1500 variants of the tectoRNA heterodimer model system achieve high accuracy (rmsd 0.34 and 0.77 kcal/mol for sequence and length changes, respectively). Detailed comparison of predictions to experiments support a microscopic picture of how helix sequence changes subtly modulate conformational fluctuations at each base-pair step, which accumulate to impact RNA tertiary structure stability. Our study reveals a previously overlooked phenomenon in RNA structure formation and provides a framework of computation and experiment for understanding helix conformational preferences and their impact across biological RNA and RNA-protein assemblies.
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Haseeb, Muhammad, Afreenish Amir, and Aamer Ikram. "In Silico Analysis of SARS-CoV-2 Spike Proteins of Different Field Variants." Vaccines 11, no. 4 (March 27, 2023): 736. http://dx.doi.org/10.3390/vaccines11040736.
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Coronaviruses belong to the group of RNA family of viruses that trigger diseases in birds, humans, and mammals, which can cause respiratory tract infections. The COVID-19 pandemic has badly affected every part of the world. Our study aimed to explore the genome of SARS-CoV-2, followed by in silico analysis of its proteins. Different nucleotide and protein variants of SARS-CoV-2 were retrieved from NCBI. Contigs and consensus sequences were developed to identify these variants using SnapGene. Data of the variants that significantly differed from each other was run through Predict Protein software to understand the changes produced in the protein structure. The SOPMA web server was used to predict the secondary structure of the proteins. Tertiary structure details of the selected proteins were analyzed using the web server SWISS-MODEL. Sequencing results showed numerous single nucleotide polymorphisms in the surface glycoprotein, nucleocapsid, ORF1a, and ORF1ab polyprotein while the envelope, membrane, ORF3a, ORF6, ORF7a, ORF8, and ORF10 genes had no or few SNPs. Contigs were used to identify variations in the Alpha and Delta variants of SARS-CoV-2 with the reference strain (Wuhan). Some of the secondary structures of the SARS-CoV-2 proteins were predicted by using Sopma software and were further compared with reference strains of SARS-CoV-2 (Wuhan) proteins. The tertiary structure details of only spike proteins were analyzed through the SWISS-MODEL and Ramachandran plots. Through the Swiss-model, a comparison of the tertiary structure model of the SARS-CoV-2 spike protein of the Alpha and Delta variants was made with the reference strain (Wuhan). Alpha and Delta variants of the SARS-CoV-2 isolates submitted in GISAID from Pakistan with changes in structural and nonstructural proteins were compared with the reference strain, and 3D structure mapping of the spike glycoprotein and mutations in the amino acids were seen. The surprisingly increased rate of SARS-CoV-2 transmission has forced numerous countries to impose a total lockdown due to an unusual occurrence. In this research, we employed in silico computational tools to analyze the SARS-CoV-2 genomes worldwide to detect vital variations in structural proteins and dynamic changes in all SARS-CoV-2 proteins, mainly spike proteins, produced due to many mutations. Our analysis revealed substantial differences in the functionality, immunological, physicochemical, and structural variations in the SARS-CoV-2 isolates. However, the real impact of these SNPs can only be determined further by experiments. Our results can aid in vivo and in vitro experiments in the future.
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Paiz, Elisia A., Karen A. Lewis, and Steven T. Whitten. "Structural and Energetic Characterization of the Denatured State from the Perspectives of Peptides, the Coil Library, and Intrinsically Disordered Proteins." Molecules 26, no. 3 (January 26, 2021): 634. http://dx.doi.org/10.3390/molecules26030634.
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The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations. Here, we compare results from peptide-based studies of intrinsic conformational propensities and surveys of the protein coil library to those of the sequence-based analysis of heat effects on IDP hydrodynamic size, showing that a common structural and thermodynamic description of the protein denatured state is obtained.
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PAI, TUN-WEN, RUEI-HSIANG CHANG, CHIEN-MING CHEN, PO-HAN SU, LEE-JYI WANG, KUEN-TSAIR LAY, and KUO-TORNG LAN. "MULTIPLE STRUCTURE ALIGNMENT BASED ON GEOMETRICAL CORRELATION OF SECONDARY STRUCTURE ELEMENTS." New Mathematics and Natural Computation 06, no. 01 (March 2010): 77–95. http://dx.doi.org/10.1142/s1793005710001621.
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Protein structure alignment facilitates the analysis of protein functionality. Through superimposed structures and the comparison of variant components, common or specific features of proteins can be identified. Several known protein families exhibit analogous tertiary structures but divergent primary sequences. These proteins in the same structural class are unable to be aligned by sequence-based methods. The main objective of the present study was to develop an efficient and effective algorithm for multiple structure alignment based on geometrical correlation of secondary structures, which are conserved in evolutionary heritage. The method utilizes mutual correlation analysis of secondary structure elements (SSEs) and selects representative segments as the key anchors for structural alignment. The system exploits a fast vector transformation technique to represent SSEs in vector format, and the mutual geometrical relationship among vectors is projected onto an angle-distance map. Through a scoring function and filtering mechanisms, the best candidates of vectors are selected, and an effective constrained multiple structural alignment module is performed. The correctness of the algorithm was verified by the multiple structure alignment of proteins in the SCOP database. Several protein sets with low sequence identities were aligned, and the results were compared with those obtained by three well-known structural alignment approaches. The results show that the proposed method is able to perform multiple structural alignments effectively and to obtain satisfactory results, especially for proteins possessing low sequence identity.
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Mustafa, Ghulam, Hafiza S. Mahrosh, Muddassar Zafar, Syed A. Attique, and Rawaba Arif. "Exploring the antihyperglycemic potential of tetrapeptides devised from AdMc1 via different receptor proteins inhibition using in silico approaches." International Journal of Immunopathology and Pharmacology 36 (January 2022): 039463202211031. http://dx.doi.org/10.1177/03946320221103120.
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Introduction: Diabetes mellitus is a heterogenous group of chronic metabolic disorders that results due to deficiency in insulin secretion and signalling. Multiple factors held responsible for onset of diabetes due to defects in glucose metabolism and cellular signalling mechanism. Over the past few years, many plant derived bioactive compounds have been recorded with increased efficacy and fewer side-effects against variety of diseases. Methods: In the current study, molecular docking and molecular dynamics simulation approaches were employed to evaluate the tetrapeptides devised from AdMc1 protein of Momordica charantia. Due to unavailability of appropriate template for modelling of 3D structure of AdMc1 protein, I-TASSER server was employed for prediction of good quality tertiary structure. Predicted model was refined by GalaxyRefine Web and evaluated by Verify 3D, ERRAT and Ramachandran plot analysis. Next, a ready-to-dock library of fifty tetrapeptides as potent inhibitors was prepared and docked against aldose reductase (AR), protein tyrosine phosphatase 1B (PTP1B), α-glucosidase, α-amylase and glycogen synthase kinase 3-beta as receptor proteins. Molecular dynamics (MD) simulation was performed on Schrodinger’s Desmond Module to check stability of the best docking complex. Results: Top five ligands were selected against each receptor protein based on their binding pattern and docking scores. Among selected ligands (i.e. VEID, TVEV, AYAY, EEIA, ITTV, TTIT, LPSM, RGIE, TTVE and EIAR) followed all parameters in drug scanning and ADMET screening tests. The MD simulations confirmed that the best selected peptide (i.e. VEID) docked with AR and PTP1B was structurally stable. Conclusion: In the light of overall results of all analyses employed in this study, the selected ligands could be further processed as potential hypoglycaemic drug candidates.
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Nazari, Naser, Bahareh Kordi, Bahman Maleki, Morteza Shams, Esfandiar Azizi, Hamidreza Majidiani, and Razi Naserifar. "Determination of B and T Cell Epitopes in Neospora caninum Immune Mapped Protein-1 (IMP-1): Implications in Vaccine Design against Neosporosis." BioMed Research International 2022 (April 7, 2022): 1–12. http://dx.doi.org/10.1155/2022/2508050.
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Prevention of neosporosis is advantageous for cattle health and productivity. Previously, several vaccine candidates were nominated for vaccination against Neospora caninum. This study was premised on in silico evaluation of N. caninum IMP-1 in order to determine its physicochemical features and immunogenic epitopes. We employed a wide array of network-based tools for the prediction of antigenicity, allergenicity, solubility, posttranslational modification (PTM) sites, physicochemical properties, transmembrane domains and signal peptide, secondary and tertiary structures, and intrinsically disordered regions. Also, prediction and screening of potential continuous B cell peptides and those epitopes having stringent affinity to couple with mouse major histocompatibility complex (MHC) and cytotoxic T lymphocyte (CTL) receptors were accomplished. The protein had 393 residues with a molecular weight of 42.71 kDa, representing aliphatic index of 85.83 (thermotolerant) and GRAVY score of -0.447 (hydrophilic). There were 47 PTM sites without a signal peptide in the sequence. Secondary structure comprised mostly of extended strand and helices, followed by coils. The Ramachandran plot of the refined model showed 90.1%, 9.9%, 0.0%, and 0.0% residues in the favored, additional allowed, generously allowed, and disallowed regions, correspondingly. Additionally, various potential B cell (linear and conformational), CTL, and MHC binding epitopes were predicted for N. caninum IMP-1. The findings of the present study could be further directed for next-generation vaccine design against neosporosis.
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Guan, Tianzhu, Ning Li, Ya Gao, Longfei Zhang, Qin Hu, Huaxiang Li, Ming Yang, Lixia Xiao, Lei Yuan, and Zhenquan Yang. "Interaction behavior between bisphenol AP and pepsin: Insights from density functional theory, and spectroscopic and molecular dynamic simulation." Quality Assurance and Safety of Crops & Foods 14, no. 2 (April 11, 2022): 1–12. http://dx.doi.org/10.15586/qas.v14i2.1023.
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Overuse of polymer materials has caused increasing direct human exposure to bisphenol AP (BPAP). Through the contaminated environment and food chains, the adverse effects of BPAP on humans and plants induce growing concerns. In this study, the effects of BPAP on pepsin structure changes were exhaustively investigated by multi-spectral methods. Under mimic physiological conditions, BPAP caused a gradient intrinsic fluorescence quenching by inducing microenvironmental changes surrounding residues with the endogenous fluorescence in pepsin. During the ground-state complex formation, the senior structures of pepsin were altered by BPAP addition. Fourier transform infrared spectroscopy and circular dichroism spectroscopy showed that the secondary and tertiary structures of pepsin were changed after the addition of BPAP. Thermodynamic parameter analysis demonstrated that the pepsin and BPAP binding was a spontaneous process that was mainly driven by hydrophobic interaction and van der Waals force. With BPAP as the subject of density functional theory experiments, the energies of the highest occupied molecular orbital, the lowest unoccupied molecular orbital, and the electrostatic potential were calculated to evaluate the electronic distribution of BPAP. Molecular docking experiments displayed that in the specific interaction pattern, hydrogen-bonding between one of the hydroxyl groups and specific amino acids was vital in stabilizing the BPAP−pepsin complex. The root mean square deviation, total hydrogen bonds statistic, and Ramachandran map obtained by molecular dynamic simulations validated the findings and predicted the rationality of the complex structure. This study provides an experimental and theoretical basis for understanding the binding mechanism of bisphenol pollution and pepsin. It also puts forward strategies to strengthen food safety and achieve precise control of environmental contaminants in the food industry.
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Adebiyi, Marion, and Oludayo O. Olugbara. "Binding site identification of COVID-19 main protease 3D structure by homology modeling." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 3 (March 10, 2021): 1713. http://dx.doi.org/10.11591/ijeecs.v21.i3.pp1713-1721.
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The influx of coronavirus in 2019 (COVID-19) from Wuhan of China has led to a global pandemic, undesirable hiatus, and recorded millions of infection cases with several deaths worldwide. The strain of COVID-19 has neither known treatments nor vaccines, but recent studies have shown that a few of its enzymes may have been considered as potential drug target. Since its influx, the virus has been well-studied, but a lot is not known about its protease yet. The purpose of this work was to identify the binding site in-silico and present 3D structure of COVID-19 main protease (Mpro) by homology modeling through multiple alignment followed by optimization and validation. The modeling was done by Swiss-Model template library and basic local alignment search tool (BLAST). The obtained homotrimer oligo-state model was verified for reliability using structural validation software such as PROCHECK, Verify3D, MolProbity and QMEAN. The HHBlits software was used to determine the structures that matched the target sequence by evolution. Best template, 6u7h.1.A was used to build a tertiary structure for Mpro with ProMod3 3.0.0 on the Swiss-Model workspace. Self-optimized prediction method with alignment (SOPMA) was applied to compute features of the secondary structure. The verification of quality of COVID-19 structure through Ramachandran plot showed an abundance of 99.3% of amino acid residues in allowed regions while 0.1% in disallowed region. The Verify3D rated the structure a 90.87% PASS of residues having an average 3D-1D score of at least 0.2, which validates a good environment profile for the COVID-19 Mpro model. The features of the secondary structure indicated that the modeled 3D structure of Mpro contains 32.05% α-helix and 37.17% random coil with 25.92 extended strand. DeepSite algorithm elucidates the binding site area that captured local patterns in the structure and exposed the surface cavity of the binding pocket of this protein. The main result of this study suggests that blocking expression of the protein may constitute an efficient approach for transmission blockage. Hence, our thought is that Mpro of COVID-19 may be considered a potential drug target. Nevertheless, more experimental analyses, verification and validation experiments will be required as a targeted drug or vaccine design against COVID-19 virus.
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Liu, Xin, and Zhiyong Zhang. "Dynamics in the assembly of the 30S ribosomal subunit investigated by coarse-grained simulations." JUSTC 53 (2023): 1. http://dx.doi.org/10.52396/justc-2023-0064.
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The ribosome is a large biomolecular complex responsible for protein synthesis. In <i>Escherichia coli</i> (<i>E. coli</i>), a complete ribosome is composed of a 30S small subunit and a 50S large subunit. For approximately half a century, the 30S subunit has been a key model system for studying the in vitro assembly of the ribosome, and an assembly map has been proposed. However, structural details in the assembly of this protein‒RNA complex remain elusive. In this paper, we conducted a series of coarse-grained simulations following the order of the assembly map to investigate conformational dynamics during the assembly process of the 30S subunit. It has been found that the tertiary structure of naked 16S rRNA is very unstable, which is the case after binding of early-assembly proteins. The mid-assembly proteins can significantly restrict the mobility of the 16S rRNA and make the latter close to the native structure. The final binding of the late-assembly proteins would fully obtain the collective motion of the 16S rRNA. In particular, proteins S9 and S3 may have more important contributions to the assembly of the 30S subunit than other S proteins. Our strategy of coarse-grained simulations can be generally used to study assembly dynamics of large biomolecular complexes as long as the assembly map is available.
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Han, Xu, Li Li, and Yonggang Lu. "Selecting Near-Native Protein Structures from Predicted Decoy Sets Using Ordered Graphlet Degree Similarity." Genes 10, no. 2 (February 11, 2019): 132. http://dx.doi.org/10.3390/genes10020132.
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Effective prediction of protein tertiary structure from sequence is an important and challenging problem in computational structural biology. Ab initio protein structure prediction is based on amino acid sequence alone, thus, it has a wide application area. With the ab initio method, a large number of candidate protein structures called decoy set can be predicted, however, it is a difficult problem to select a good near-native structure from the predicted decoy set. In this work we propose a new method for selecting the near-native structure from the decoy set based on both contact map overlap (CMO) and graphlets. By generalizing graphlets to ordered graphs, and using a dynamic programming to select the optimal alignment with an introduced gap penalty, a GR_score is defined for calculating the similarity between the three-dimensional (3D) decoy structures. The proposed method was applied to all 54 single-domain targets in CASP11 and all 43 targets in CASP10, and ensemble clustering was used to cluster the protein decoy structures based on the computed CR_scores. The most popular centroid structure was selected as the near-native structure. The experiments showed that compared to the SPICKER method, which is used in I-TASSER, the proposed method can usually select better near-native structures in terms of the similarity between the selected structure and the true native structure.
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Gautam, Anuradha, Fatima Nazish Khan, Surabhi Priya, Krishan Kumar, Shivani Sharda, Tanushri Kaul, Ishwar Singh, Sapna Langyan, and Pranjal Yadava. "Cloning and comparative modeling identifies a highly stress tolerant Cu/Zn cytosolic super oxide dismutase 2 from a drought tolerant maize inbred line." PeerJ 11 (March 13, 2023): e14845. http://dx.doi.org/10.7717/peerj.14845.
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Plants have a complex system of stress response that deals with different types of stresses. Maize (Zea mays L.), one of the most important crops grown throughout the world, across a range of agro-ecological environments, employs complex mechanisms of gene regulation in response to drought stress. HKI 335 is a tropical maize inbred line showing remarkable adaptation to drought stress. Abiotic stresses, like drought, trigger the production of reactive oxygen species (ROS) due to the incomplete reduction or excitation of molecular oxygen, eventually leading to cell damage. Superoxide dismutase (SOD, EC 1.15.1.1) is a metalloenzyme that acts as the first line of defense against ROS. We cloned the Sod2 gene from HKI 335 inbred line and analyzed its protein through detailed in silico characterization. Our comparative modeling revealed that at the level of tertiary structure, the HKI 335 SOD2 protein is highly similar to Potentilla atrosanguinea SOD2, which had been previously identified as highly thermostable SOD that can tolerate autoclaving as well as sub-zero temperatures. We performed phylogenetic analysis, estimated physicochemical properties, post-translational modifications, protein-protein interactions, and domain composition of this SOD2. The phylogenetic analysis showed that orthologous sequences of SOD from different species were clustered into two clusters. Secondary structure prediction indicates that SOD2 is a soluble protein and no transmembrane domains have been found. Most of the beta sheets have RSA value greater than 2. The Ramachandran plot from PDBsum revealed that most of the residues fall in the highly favored region. It was estimated that the value of the instability index was less than 40, the value of the aliphatic index was extremely high and the GRAVY value lies between −2 and +2. We could identify only one phosphorylation site, located at position 20 with a score of 0.692. Overall, the unique stress-tolerant properties of the HKI 335 SOD2, may be one of the reasons contributing to the high drought tolerance trait exhibited by HKI 335 maize inbred line. Further research may reveal more insights into the drought adaptation mechanism in maize and the eventual deployment of the trait in maize hybrids.
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Aller, Stephen G., and Jere P. Segrest. "The regulatory domains of the lipid exporter ABCA1 form domain swapped latches." PLOS ONE 17, no. 2 (February 4, 2022): e0262746. http://dx.doi.org/10.1371/journal.pone.0262746.
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ABCA1 and ABCA4 are enigmatic because they transport substrates in opposite directions yet share >50% amino acid identity. ABCA4 imports lipid conjugates but ABCA1 exports lipids. Both hydrolyze ATP to drive transport, and both contain cytoplasmic regulatory domains (RDs) following nucleotide-binding domains (NBDs) in the primary structure. The tertiary structures of several ABC importers, including ABCA4, show that each RD forms a domain-swapped latch that locks onto the opposing RD and holds the NBDs close together. Crucially, sequences encoding the RDs and their bridges are among the most conserved in the entire ABC-A subfamily. In the original cryo-EM structure of ABCA1, the RDs were modeled without crossover. After close inspection of that cryo-EM density map and the recent structure of ABCA4, we propose that the RDs of ABCA1 also form a domain-swapped latch. A refined ABCA1 model containing latches exhibited significantly improved overall protein geometry. Critically, the conserved crossover sequence leading to the RD-domain swap is directly supported by the original cryo-EM density map of ABCA1 and appears to have been overlooked. Our refined ABCA1 model suggests the possibility that ABCA1, despite being an exporter, has highly restrained NBDs that suggest a transport mechanism that is distinct from ‘alternating access’.
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Manser, E. J., and P. M. Bayley. "Tubulin-nucleotide interactions. Effects of removal of exchangeable guanine nucleotide on protein conformation and microtubule assembly." Biochemical Journal 241, no. 1 (January 1, 1987): 105–10. http://dx.doi.org/10.1042/bj2410105.
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The removal of tightly bound GDP from the exchangeable nucleotide-binding site of tubulin has been performed with alkaline phosphatase under conditions which essentially retain the assembly properties of the protein. When microtubule protein is treated with alkaline phosphatase, nucleotide is selectively removed from tubulin dimer rather than from MAP (microtubule-associated protein)-containing oligomeric species. Tubulin devoid of E-site (the exchangeable nucleotide-binding site of the tubulin dimer) nucleotide shows enhanced proteolytic susceptibility of the beta-subunit to thermolysin and decreased protein stability, consistent with nucleotide removal causing changes in protein tertiary structure. Pyrophosphate ion (3 mM) is able to promote formation of normal microtubules in the complete absence of GTP by incubation at 37 degrees C either with nucleotide-depleted microtubule protein or with nucleotide-depleted tubulin dimer to which MAPs have been added. The resulting microtubules contain up to 80% of tubulin lacking E-site nucleotide. In addition to its effects on nucleation, pyrophosphate competes weakly with GDP bound at the E-site. It is deduced that binding of pyrophosphate at a vacant E-site can promote microtubule assembly. The minimum structural requirement for ligands to induce tubulin assembly apparently involves charge neutralization at the E-site by bidentate ligation, which stabilizes protein domains in a favourable orientation for promoting the supramolecular protein-protein interactions involved in microtubule formation.
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Beniac, D. R., G. J. Czarnota, T. A. Bartlett, F. P. Ottensmeyer, and G. Harauz. "Challenges of three-dimensional reconstruction of ribonucleoprotein complexes from electron spectroscopic images - Reconstructing ribosomal RNA." Proceedings, annual meeting, Electron Microscopy Society of America 54 (August 11, 1996): 52–53. http://dx.doi.org/10.1017/s0424820100162727.
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Transmission electron microscopy has been dominant in structural studies of the ribosome and its constituent ribonucleic acids and proteins. Ribosomal RNA (rRNA) has central importance in the architecture of this complex and in protein synthesis. Our work has entailed using electron spectroscopic imaging (ESI) to probe the tertiary structure of rRNA in situ in a prokaryote (Escherichia coli) and in a eukaryote (Thermomyces lanuginosus). ESI uses only electrons which have lost a specific amount of energy due to specific inner-shell ionisation interactions with the specimen to form an elemental map. In nucleoprotein complexes, a map of the phosphorus distribution represents primarily a projection of the phosphate backbone of the nucleic acid component. The visualisation of rRNA in situ in the intact ribosomal subunit by ESI was demonstrated almost a decade ago to be feasible. Our work on quantitative image analysis of ES images of E. coli and Th. lanuginosus ribosomal subunits has presented unique challenges and has resulted in new algorithmic developments generally applicable to such images. These innovations include a singular pretreatment procedure, the use of mutual correlation functions rather than cross correlation functions to reduce the effect of low spatial frequency components, and angular determination using iterative quaternion-assisted angular reconstitution to compute a three-dimensional reconstruction. These investigations have produced direct information regarding ribosomal rRNA localisation in the ribosomal subunits of E. coli and Th. lanuginosus, and the position of non-conserved sequences.
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Charretier, E., and M. Guéron. "Application de la résonance magnétique nucléaire à la détermination de la structure des protéines en solution." Biochemistry and Cell Biology 69, no. 5-6 (May 1, 1991): 322–35. http://dx.doi.org/10.1139/o91-051.
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Knowledge of three-dimensional structure is a key factor in protein engineering. It is useful, for example, in predicting and understanding the functional consequences of specific substitution of one or more amino acids of the polypeptide chain. It is also necessary for the design of new effectors or analogs of the substrates of enzymes and receptors. X-ray diffraction by crystals of the biomolecule was for a long time the only method of determining three-dimensional structures. In the last 5 years, it has been joined by a new technique, two-dimensional nuclear magnetic resonance (2D NMR), which can resolve the structure of middle-sized proteins ( < 10 kilodaltons). The technique is applied on solutions whose pH, ionic strength, and temperature can be chosen and changed. The two basic measurements, COSY and NOESY, detect respectively the systems of hydrogen nuclei, or protons, coupled through covalent bonds, and those in which the interproton distances are less than 0.5 nm. A systematic strategy leads from resonance assignments of the two-dimensional spectrum to molecular modeling with constraints and finally to the determination of the molecular structure in the solution. Much sophistication is needed even today for the first task, the assignment of the resonances. Each of the COSY and NOESY spectra is a two-dimensional map, where the diagonal line is the one-dimensional spectrum, and the off-diagonal peaks indicate connectivities between protons. Peak assignment to a specific type of amino acid is based on the pattern of scalar couplings observed in the COSY spectrum. Next, the amino acids are positioned in the primary sequence, using the spatial proximities of polypeptide chain protons, as observed in the NOESY spectrum. The principal secondary structures (α helix, β sheets, etc.) are then identified by their specific connectivities. The tertiary structure is detected by NOESY connectivities between protons of different amino acids which are far apart in the primary sequence. The distance constraints from the NOESY connectivities also provide the starting point for modeling the tertiary structure. This is then refined using distance geometry and molecular dynamics algorithms. The resolution of the structures obtained with the help of recent algorithmic developments may be comparable to that provided by X-ray diffraction. The COSY measurement can be completed or substituted by other measurements, useful albeit more complex. For example, the HOHAHA experiment, currently in wide use, gives the correlations through multiple covalent bonds. Multiquanta experiments, which select systems of a given number of coupled spins, provide spectral simplification. To help with the sequential assignment, which remains a limiting step, one may substitute amino acids isotopically labeled with 15N or 13C. Nuclear magnetic resonance of these nuclei is detected either directly or by heteronuclear proton NMR. In the latter case, heteronuclear cross-peaks indicate connectivities between protons and the isotopic nuclei, 1SN and 13C. This labeling is very useful for proteins with more than 100 amino acids and for proteins exhibiting low-resolution spectra. Resolution can also be enhanced by the combination of two-dimensional experiments, giving rise to 3D NMR. The graphic representation of a three-dimensional experiment is a cube whose sections correspond to virtual two-dimensional measurements. The 3D NMR can be homonuclear or, in the case of isotopically substituted proteins, heteronuclear. The time for a single experiment reaches several days. The memory needed for data acquisition and processing is greater than for two-dimensional experiments. Large parts of the data processing, such as peak detection or the recognition of secondary structure connectivities can be automated. Two-dimensional NMR is becoming a routine technique for peptide and protein structure determination in the laboratories of the pharmaceutical firms.Key words: protein engineering, three-dimensional structure, nuclear magnetic resonance, correlated spectroscopy, nuclear Overhauser effect spectroscopy.
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Calvete, J. J., K. Mann, M. V. Alvarez, M. M. López, and J. González-Rodríguez. "Proteolytic dissection of the isolated platelet fibrinogen receptor, integrin GPIIb/IIIa. Localization of GPIIb and GPIIIa sequences putatively involved in the subunit interface and in intrasubunit and intrachain contacts." Biochemical Journal 282, no. 2 (March 1, 1992): 523–32. http://dx.doi.org/10.1042/bj2820523.
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Human platelet glycoproteins IIb (GPIIb) and IIIa (GPIIIa) form the subunits of the Ca(2+)-dependent heterodimer GPIIb/IIIa, which belongs to the integrin family of phylogenetically related receptors mediating a wide variety of cell-cell and cell-substratum interactions. GPIIb/IIIa plays a central role in haemostasis as a receptor for fibrinogen and other adhesive proteins at the surface of activated platelets. The covalent structure of the subunits is largely known; however, the tertiary and quaternary structures of the heterodimer remain to be determined. To this end, our approach consisted of limited proteolysis of the isolated heterodimer with proteinases of different specificities, followed by protein-chemical and immunochemical analyses of the peptide fragments within each isolated proteolytic product. From the information obtained, we have drawn a rudimentary map which outlines the demarcation of compact domains and the subunit peptide stretches carrying the sequences putatively involved in intrachain, intrasubunit and intersubunit non-covalent connectivity in the heterodimer. Three compact domains have been well defined: one in the heavy (H) chain of GPIIb [GPIIbH-(600-700)], and two in GPIIIa, the N-terminal [GPIIIa-(1-52)] and the core [GPIIIa-(423-622)] domains. Between the latter two domains there is a proteolysis-susceptible region, which is partly involved in ligand binding [GPIIIa-(100-220)] and partly implicated as being in teh subunit interface of the heterodimer. Contrary to GPIIIa, GPIIbH is highly susceptible to proteolysis all along its sequence. Equally susceptible are the extracellular end of the transmembrane segment of both GPIIIa and the light (L) chain of GPIIb (GPIIbL), and the N-terminal end of GPIIbL. Three sequence stretches along the C-terminal half of GPIIbH, one sequence stretch in GPIIbL and three sequence stretches within the GPIIIa-(217-421) region were putatively involved in the subunit interface of the heterodimer. Most likely, the N-terminal end of GPIIbL is folded over the N- and C-terminal regions of GPIIbH, and the N-terminal end of GPIIbH is folded against the GPIIbH-(600-700) domain. This map of GPIIb/IIIa does not fit the current accommodation of the amino acid sequence of GPIIb and GPIIIa in the head/two-tails image of the heterodimer obtained by metal-rotary-shadowing electron microscopy.
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White, Robert A., Leigh A. Boydston, Terri R. Brookshier, Steven G. McNulty, Ndona N. Nsumu, Brandon P. Brewer, and Krista Blackmore. "Iron Metabolism Anemia hbd Mice Have a Mutation in the Sec15l1 Gene for Vesicle Docking." Blood 106, no. 11 (November 16, 2005): 3580. http://dx.doi.org/10.1182/blood.v106.11.3580.3580.
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Abstract Defects in iron absorption and utilization lead to iron deficiency and anemia. Although iron transport in transferrin receptor-mediated endocytosis is well understood, it is not clear how iron is transported from the endosome to mitochondria where it is used to synthesize heme. We undertook a positional cloning project to identify the causative mutation for the hemoglobin deficit (hbd) mouse which suffers from a microcytic, hypochromic anemia associated with a defect in reticulocyte iron uptake. The hbd locus was previously mapped to Chromosome 19 in mouse. We established a mating of B6MOLDF1-+/hbd with C57BL/6J-hbd/hbd mice to generate a high resolution map from 2,454 backcross mice. The hbd critical region was defined by the flanking marker with 6 crossover backcross mice, Kif11, at 0.24 cM on the proximal side, and by the very informative marker with only 1 crossover backcross mouse, Fer1l3 at 0.04 cM on the distal side. The calculated size of the hbd critical region is 836 kb as determined by the sequence available in GenBank contig NT 039689. Our approach for mutation analysis was to amplify exons for each gene in the hbd critical region by genomic PCR using primers derived from flanking sequence. The results were examined for gene deletions, insertions, or large rearrangements as determined by the size of the PCR product generated from normal and mutant DNA. We now report the identification of a strong candidate gene for hbd: Sec15l1, a homologue to yeast SEC15 which has been shown to be a key protein in vesicle docking. The Sec15l1 gene was the only gene in this region with a defect and was shown to have a deletion of exon 8 in hbd genomic DNA. The Sec15l1 partial deletion was verified by Southern blotting. Sec15l1 RNA expression in hbd mice was examined by RT-PCR and subsequent sequencing of the amplicon product. The exon 8 deletion leaves the coding sequence in-frame and a truncated SEC15L1 protein (3 kDa smaller) is predicted to be produced in hbd mice. The deletion in Sec15l1 removes 23 amino acids which includes two amino acids important for tertiary structure: a cysteine residue at position 283 and a proline residue at position 287. Studies of mutant hbd reticulocytes have shown that the binding of transferrin to its receptor and the formation of the endosome is normal but accumulation of iron is deficient in these cells. Iron and transferrin enter the hbd cells but iron does not build up in the cell. The efficient transfer of iron from endosome to mitochondria in normal reticulocytes has been proposed to result from the endosome traversing the cell to dock onto the mitochondria in order to directly transfer iron to it ("kiss and run" hypothesis). In hbd reticulocytes iron may not be transferred efficiently from the endosome to mitochondria because vesicle docking is impaired. This is the first known mutation of a SEC gene homologue in mammals and our findings suggest that SEC15L1 plays a crucial role in the transport of iron in the endocytosis cycle and may involve iron targeting to mitochondria.
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Ruslin, R., Suci Rahmawati Putri, and Muhammad Arba. "Pemodelan Homologi Protein Receptor Orphan Receptor-1 (ROR-1) Sebagai Target Terapi Chronic Lymphocytic Leukemia (CLL." Pharmauho:Jurnal Farmasi, Sains, dan Kesehatan 5, no. 1 (April 16, 2019). http://dx.doi.org/10.33772/pharmauho.v5i1.8992.
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Receptor Orphan Reseptor-1 (ROR-1) is a trans-membrane protein consists of 937 amino acid residues located on 1p31.3 chomosome. ROR-1 has an important role in leukemogenesis of CLL cells. Co-expressions of ROR-1 and TCL enhance leukemogenesis and caused AKT’s phosphorylation, cell’s proliferations, and resistances to apoptosis. This study had done physicochemical characteristics analysis, secondary structure and tertiary structure prediction of ROR-1 Protein using few types of bioinformation tools. The physicochemical characteristics analysis was done by using Expasy Protparam server and the prediction of secondary structure was using Sopma and Psipred. The prediction of ROR-1’s tertiary structure was done by using Modeller 9.19 software and resulting five ROR-1’s tertiary structures predicted model. The accuration of the results then evaluated using Ramachandran’s plot analysis and it was showed Model 3 is the best models wich percentage is 82%.Keywords: ROR-1, Choronic Lymphocytic Leukemia (CLL), homology modeling, Modeller, Ramachandran plot
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"Structure Prediction, Characterization, and Functional Annotation of Uncharacterized Protein BCRIVMBC126_02492 of Bacillus cereus: An In Silico Approach." American Journal of Pure and Applied Biosciences, July 27, 2020, 104–11. http://dx.doi.org/10.34104/ajpab.020.01040111.
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Bacillus cereus is enteropathogenic and widely distributed pathogen in the environment, which is mainly associated with food poisoning. In the intestine, B. cereus produces enterotoxins resulting in diarrhoea, abdominal distress and vomiting, and a range of infections in humans. BCRIVMBC126_02492 is a functional protein of B. cereus, which is related to oxidation glutathione persulfide in the mitochondria, cyanide fixation, and also has a variety of biological functions. Nevertheless, protein BCRIVMBC126_02492 is not explored. Therefore, the structure prediction, functional annotation, and characterization of the protein are proposed in this study. Modeller, Swiss-model, and Phyre2 are used for generating tertiary structures. The structural quality assessment of the protein determined by Ramachandran Plot analysis, Swiss-Model Interactive Workplace, and Verify 3D tools. Furthermore, Z-scores applied to detect the overall tertiary model quality of the protein. A comparison of the results showed that the models generated by Modeller were more suitable than Phyre2 and Swiss Models. This investigation decoded the role of this unexplored protein of B. cereus. Therefore, it can bolster the way for enriching our knowledge for pathogenesis and drug and vaccine targeting opportunities against B. cereus infection.
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Sajid, Aimen, Muhammad Shaoor Saeed, Rabbiah M. anzoor Malik, Sahar Fazal, Shaukat Malik, and Mohammad Amjad Kamal. "Prediction of Secondary And Tertiary Structure And Docking of Rb1WT And Rb1R661W Proteins." Current Biotechnology 11 (January 27, 2022). http://dx.doi.org/10.2174/2211550111666220127100203.
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Background: Retinoblastoma, a malignancy occurring in the juvenile cells of retina, responsible for the light detection. It is one of the most emerging and rare childhood and infant cancer. It is initiated by the mutation in Rb1 a first tumor suppressor gene located on chromosome 13q14. Rb1 protein is responsible for cell cycle regulation. Methods: In our study, secondary and 3D-Structural prediction of Rb1WT and Rb1R661W were done by comparative or homology modeling for finding any structural change leading to the disruption in its further interactions. Quality assurance of the structures was done by Ramachandran Plot for a stable structure. Both the proteins were then applied by docking process with proteins of interest. Results: Secondary Structure showed number of mutations in helixes, β-Hairpins of Rb1R661W. The major change was lost of β-Hairpin loop, extension and shortening of helixes. 3D comparison structure showed change in the groove of Rb1R661W. Docking results unlike to RB1WT were having different and also no interactions with some of the proteins of interest. This mutation in Rb1 protein was having a deleterious effect on the protein functionality. Conclusion: This study will help in designing the appropriate therapy and also understanding of mechanism of disease of retinoblastoma, for researchers and pharmaceuticals.
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Xu, Yong-Chang, Tian-Jun ShangGuan, Xue-Ming Ding, and Ngaam J. Cheung. "Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network." Scientific Reports 11, no. 1 (October 26, 2021). http://dx.doi.org/10.1038/s41598-021-00477-2.
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AbstractThe amino acid sequence of a protein contains all the necessary information to specify its shape, which dictates its biological activities. However, it is challenging and expensive to experimentally determine the three-dimensional structure of proteins. The backbone torsion angles play a critical role in protein structure prediction, and accurately predicting the angles can considerably advance the tertiary structure prediction by accelerating efficient sampling of the large conformational space for low energy structures. Here we first time propose evolutionary signatures computed from protein sequence profiles, and a novel recurrent architecture, termed ESIDEN, that adopts a straightforward architecture of recurrent neural networks with a small number of learnable parameters. The ESIDEN can capture efficient information from both the classic and new features benefiting from different recurrent architectures in processing information. On the other hand, compared to widely used classic features, the new features, especially the Ramachandran basin potential, provide statistical and evolutionary information to improve prediction accuracy. On four widely used benchmark datasets, the ESIDEN significantly improves the accuracy in predicting the torsion angles by comparison to the best-so-far methods. As demonstrated in the present study, the predicted angles can be used as structural constraints to accurately infer protein tertiary structures. Moreover, the proposed features would pave the way to improve machine learning-based methods in protein folding and structure prediction, as well as function prediction. The source code and data are available at the website https://kornmann.bioch.ox.ac.uk/leri/resources/download.html.
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Hasan, Rajnee, Md Nazmul Haq Rony, and Rasel Ahmed. "In silico characterization and structural modeling of bacterial metalloprotease of family M4." Journal of Genetic Engineering and Biotechnology 19, no. 1 (February 2, 2021). http://dx.doi.org/10.1186/s43141-020-00105-y.
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Abstract Background The M4 family of metalloproteases is comprised of a large number of zinc-containing metalloproteases. A large number of these enzymes are important virulence factors of pathogenic bacteria and therefore potential drug targets. Whereas some enzymes have potential for biotechnological applications, the M4 family of metalloproteases is known almost exclusively from bacteria. The aim of the study was to identify the structure and properties of M4 metalloprotease proteins. Results A total of 31 protein sequences of M4 metalloprotease retrieved from UniProt representing different species of bacteria have been characterized for various physiochemical properties. They were thermostable, hydrophillic protein of a molecular mass ranging from 38 to 66 KDa. Correlation on the basis of both enzymes and respective genes has also been studied by phylogenetic tree. B. cereus M4 metalloprotease (PDB ID: 1NPC) was selected as a representative species for secondary and tertiary structures among the M4 metalloprotease proteins. The secondary structure displaying 11 helices (H1-H11) is involved in 15 helix-helix interactions, while 4 β-sheet motifs composed of 15 β-strands in PDBsum. Possible disulfide bridges were absent in most of the cases. The tertiary structure of B. cereus M4 metalloprotease was validated by QMEAN4 and SAVES server (Ramachandran plot, verify 3D, and ERRAT) which proved the stability, reliability, and consistency of the tertiary structure of the protein. Functional analysis was done in terms of membrane protein topology, disease-causing region prediction, proteolytic cleavage sites prediction, and network generation. Transmembrane helix prediction showed absence of transmembrane helix in protein. Protein-protein interaction networks demonstrated that bacillolysin of B. cereus interacted with ten other proteins in a high confidence score. Five disorder regions were identified. Active sites analysis showed the zinc-binding residues—His-143, His-147, and Glu-167, with Glu-144 acting as the catalytic residues. Conclusion Moreover, this theoretical overview will help researchers to get a details idea about the protein structure and it may also help to design enzymes with desirable characteristics for exploiting them at industrial level or potential drug targets.
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Gupta, Neha, and Megha Bajaj. "Surface To Surface Map Algorithm For Protein - Small Molecule Matching." International Journal of Pharmacology and Pharmaceutical Technology, January 2013, 7–10. http://dx.doi.org/10.47893/ijppt.2013.1001.
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Current methods for protein analysis are based on either sequence similarity or comparison of overall tertiary structure. These conserved primary sequences or 3-dimensional structures may imply similar functional characteristics. However, substrate or ligand binding sites usually reside on or near protein surface, so, similarly shaped surface regions could imply similar functions. Our current work includes development of an algorithm that would allow surface matching over specific regions on related proteins with an output equal to the match percentage between two proteins. Initial results indicate that we can successfully match a family of related active sites, and find their similarly shaped surface regions. This method of surface analysis could be extended to help us understand functional surface relationship between the proteins within which there is no relationship in sequence or overall structure.
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Chen, Zhiqiang, Yuejie Zhu, Tong Sha, Zhiwei Li, Yujiao Li, Fengbo Zhang, and Jianbing Ding. "Design of a new multi-epitope vaccine against Brucella based on T and B cell epitopes using bioinformatics methods." Epidemiology and Infection 149 (2021). http://dx.doi.org/10.1017/s0950268821001229.
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Abstract Brucellosis is one of the most serious and widespread zoonotic diseases, which seriously threatens human health and the national economy. This study was based on the T/B dominant epitopes of Brucella outer membrane protein 22 (Omp22), outer membrane protein 19 (Omp19) and outer membrane protein 28 (Omp28), with bioinformatics methods to design a safe and effective multi-epitope vaccine. The amino acid sequences of the proteins were found in the National Center for Biotechnology Information (NCBI) database, and the signal peptides were predicted by the SignaIP-5.0 server. The surface accessibility and hydrophilic regions of proteins were analysed with the ProtScale software and the tertiary structure model of the proteins predicted by I-TASSER software and labelled with the UCSF Chimera software. The software COBEpro, SVMTriP and BepiPred were used to predict B cell epitopes of the proteins. SYFPEITHI, RANKpep and IEDB were employed to predict T cell epitopes of the proteins. The T/B dominant epitopes of three proteins were combined with HEYGAALEREAG and GGGS linkers, and carriers sequences linked to the N- and C-terminus of the vaccine construct with the help of EAAAK linkers. Finally, the tertiary structure and physical and chemical properties of the multi-epitope vaccine construct were analysed. The allergenicity, antigenicity and solubility of the multi-epitope vaccine construct were 7.37–11.30, 0.788 and 0.866, respectively. The Ramachandran diagram of the mock vaccine construct showed 96.0% residues within the favoured and allowed range. Collectively, our results showed that this multi-epitope vaccine construct has a high-quality structure and suitable characteristics, which may provide a theoretical basis for future laboratory experiments.
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Maddhuri Venkata Subramaniya, Sai Raghavendra, Genki Terashi, Aashish Jain, Yuki Kagaya, and Daisuke Kihara. "Protein contact map refinement for improving structure prediction using generative adversarial networks." Bioinformatics, March 31, 2021. http://dx.doi.org/10.1093/bioinformatics/btab220.
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Abstract Motivation Protein structure prediction remains as one of the most important problems in computational biology and biophysics. In the past few years, protein residue–residue contact prediction has undergone substantial improvement, which has made it a critical driving force for successful protein structure prediction. Boosting the accuracy of contact predictions has, therefore, become the forefront of protein structure prediction. Results We show a novel contact map refinement method, ContactGAN, which uses Generative Adversarial Networks (GAN). ContactGAN was able to make a significant improvement over predictions made by recent contact prediction methods when tested on three datasets including protein structure modeling targets in CASP13 and CASP14. We show improvement of precision in contact prediction, which translated into improvement in the accuracy of protein tertiary structure models. On the other hand, observed improvement over trRosetta was relatively small, reasons for which are discussed. ContactGAN will be a valuable addition in the structure prediction pipeline to achieve an extra gain in contact prediction accuracy. Availability and implementation https://github.com/kiharalab/ContactGAN. Supplementary information Supplementary data are available at Bioinformatics online.
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Muhammad Rehman, Hafiz, Hafiz Muzzammel Rehman, Muhammad Naveed, Muhammad Tahir Khan, Muhammad Aqib Shabbir, Shakira Aslam, and Hamid Bashir. "In Silico Investigation of a Chimeric IL24-LK6 Fusion Protein as a Potent Candidate Against Breast Cancer." Bioinformatics and Biology Insights 17 (January 2023). http://dx.doi.org/10.1177/11779322231182560.
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Targeted delivery of therapeutic anticancer chimeric molecules enhances the efficacy of drug by improving cellular uptake and circulation time. Engineering the molecules to facilitate the specific interaction between chimeric protein and its receptor is critical to elucidate biological mechanism as well as accuracy in modeling of complexes. A theoretically designed novel protein-protein interfaces can serve as a bottom-up method for comprehensive understanding of interacting protein residues. This study was aimed for in silico analyses of a chimeric fusion protein against breast cancer. The amino acid sequences of the interleukin 24 (IL-24) and LK-6 peptide were used to design the chimeric fusion protein via a rigid linker. The secondary and tertiary structures along with physicochemical properties by ProtParam and solubility were predicted using online software. The validation and quality of the fusion protein was confirmed by Rampage and ERRAT2. The newly designed fusion construct has a total length of 179 amino acids. The top-ranked structure from alpha fold2 showed 18.1 KD molecular weight by ProtParam, quality factor of 94.152 by ERRAT, and a valid structure by a Ramachandran plot with 88.5% residues in the favored region. Finally, the docking and simulation studies were performed using HADDOCK and Desmond module of Schrodinger. The quality, validity, interaction analysis, and stability of the fusion protein depict a functional molecule. The fusion gene IL24-LK6 after cloning and expression in a suitable prokaryotic cell might be a useful candidate for developing a novel anticancer therapy.
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Kootery, Kaviya Parambath, and Suma Sarojini. "Structural and functional characterization of a hypothetical protein in the RD7 region in clinical isolates of Mycobacterium tuberculosis — an in silico approach to candidate vaccines." Journal of Genetic Engineering and Biotechnology 20, no. 1 (April 8, 2022). http://dx.doi.org/10.1186/s43141-022-00340-5.
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Abstract Background Mycobacterium tuberculosis has been ravaging humans by inflicting respiratory tuberculosis since centuries. Bacillus Calmette Guerine (BCG) is the only vaccine available for tuberculosis, and it is known to be poorly effective against adult tuberculosis. Proteins belonging to the ESAT-6 family and PE/PPE family show immune responses and are included in different vaccine trials. Herein, we study the functional and structural characterization of a 248 amino acid long putative protein novel hypothetical protein 1 (NHP1) present in the RD7 region of Mycobacterium tuberculosis (identified first by subtractive hybridization in the clinical isolate RGTB123) using bioinformatics tools. Results Physicochemical properties were studied using Expasy ProtParam and SMS software. We predicted different B-cell and T-cell epitopes by using the immune epitope database (IEDB) and also tested antigenicity, immunogenicity, and allergenicity. Secondary structure of the protein predicted 30% alpha helices, 20% beta strands, and 48% random coils. Tertiary structure of the protein was predicted using the Robetta server using the Mycobacterium smegmatis protein as the putative protein with homology. Structural evaluations were done with Ramachandran plot analysis, ProSA-web, and VERIFY3D, and with GalaxyWEB server, a more stable structure was validated with good stereo chemical properties. Conclusion The present study of a subtracted genomic locus using various bioinformatics tools indicated good immunological properties of the putative mycobacterial protein, NHP1. Evidence obtained from the analyses of NHP1 using structure prediction tools strongly point to the fact that NHP1 is an ancient protein having flavodoxin folding structure with ATP binding sites. Positive scores were obtained for antigenicity, immunogenicity, and virulence too, implying the possibility of NHP1 to be a potential vaccine candidate. Such computational studies might give clues for developing newer vaccines for tuberculosis, which is the need of the hour.
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Hoda, Anila, Myqerem Tafaj, and Enkelejda Sallaku. "In silico Structural, Functional and Phylogenetic Analyses of cellulase from Ruminococcus albus." Journal of Genetic Engineering and Biotechnology 19, no. 1 (April 19, 2021). http://dx.doi.org/10.1186/s43141-021-00162-x.
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Abstract Background Cellulose is the primary component of the plant cell wall and an important source of energy for the ruminant and microbial protein synthesis in the rumen. Cell wall content is digested by anaerobic fermentation activity mainly of bacteria belonging to species Fibrobacter succinogenes, Ruminicoccus albus, Ruminococcus flavefaciens, and Butyrivibrio fibrisolvens. Bacteria belonging to the species Ruminococcus albus contain cellulosomes that enable it to adhere to and digest cellulose, and its genome encodes cellulases and hemicellulases. This study aimed to perform an in silico comparative characterization and functional analysis of cellulase from Ruminococcus albus to explore physicochemical properties and to estimate primary, secondary, and tertiary structure using various bio-computational tools. The protein sequences of cellulases belonging to 6 different Ruminococcus albus strains were retrieved using UniProt. In in silico composition of amino acids, basic physicochemical characteristics were analyzed using ProtParam and Protscale. Multiple sequence alignment of retrieved sequences was performed using Clustal Omega and the phylogenetic tree was constructed using Mega X software. Bioinformatics tools are used to better understand and determine the 3D structure of cellulase. The predicted model was refined by ModRefiner. Structure alignment between the best-predicted model and the template is applied to evaluate the similarity between structures. Results In this study are demonstrated several physicochemical characteristics of the cellulase enzyme. The instability index values indicate that the proteins are highly stable. Proteins are dominated by random coils and alpha helixes. The aliphatic index was higher than 71 providing information that the proteins are highly thermostable. No transmembrane domain was found in the protein, and the enzyme is extracellular and moderately acidic. The best tertiary structure model of the enzyme was obtained by the use of Raptor X, which was refined by ModRefiner. Raptor X suggested the 6Q1I_A as one of the best homologous templates for the predicted 3D protein structure. Ramachandran plot analysis showed that 90.1% of amino acid residues are within the most favored regions. Conclusions This study provides for the first time insights about the physicochemical properties, structure, and function of cellulase, from Ruminococcus albus, that will help for detection and identification of such enzyme in vivo or in silico.
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Mehra, Vinay Kumar, Dhruba Malakar, and Satish Kumar. "Molecular characterization of α-lactalbumin (LALBA) protein in Indian buffalo(Bubalus bubalis)." Indian Journal of Dairy Science, June 22, 2022, 255–64. http://dx.doi.org/10.33785/ijds.2022.v75i03.008.
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The full open reading frame (ORF) of the buffalo beta-lactoglobulin (Bu_LALBA) gene was characterized. Results showed that Bu_LALBA ORF consisted of 429 bp long (142 aa residues) with three nucleotide variations at 111bp, 147 bp, and 291 bp but no change in amino acid sequence. The MSA showed that the Bu_LALBA was more different from the pig and human LALBA sequences. The phylogenetic tree showed that the cow, yak, and buffalo formed one cluster, while the buffalo was more closer (94%) to domestic yak (Bos grunniens). Results of ExPASy analysis showed that the Bu_LALBA protein was acidic (pI, 4.81), thermo-tolerant, and hydrophilic. However, the presence of random coil (33.80%) and α-helix (41.5%) in Bu_LALBA protein suggest that the protein was flexible and thermostable. Thirty liner motifs were identified, indicating that the Bu_LALBA act as regulatory protein. The tertiary structure of Bu_LALBA predicted by I-TASSER showed a more stabilized nature of LALBA protein. Further, the Ramachandran plot validated the 3-D structure of Bu_LALBA, which was of decent quality. The presence of four ligand-binding sites in Bu_LALBA (calcium ion, glycine, N-acetyl-L-glutamate, and N-acetylglucosamine) proposed that the LALBA binds to several fatty acids and ions. The presence of four serine, four threonine, two tyrosine residues, and six methylated lysine and five acetyl-lysine sites in Bu_LALBA indicated that the protein was involved in post-translational modification processes. IEDB analysis showed the presence of five and one epitope sites in Bu_LALBA protein for B-cell and T-cell, respectively, which suggest that this protein has certain immunological roles.