Journal articles: 'Structural bio-Informatics'

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Et. al., Ravi Kumar A,. "A Review on Design and Development of Performance Evaluation Model for Bio-Informatics Data Using Hadoop." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 1546–63. http://dx.doi.org/10.17762/turcomat.v12i2.1432.

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The paper reviews the usage of the platform Hadoop in applications for systemic bioinformatics. Hadoop offers another system for Structural Bioinformatics to break down broad fractions of the Protein Data Bank that is crucial to high-throughput investigations of (for example) protein-ligand docking, protein-ligand complex clustering, and structural alignment. In specific, we review different applications of high-throughput analyses and their scalability in the literature using Hadoop. In comparison to revising the algorithms, we find that these organisations typically use a realized executable called MapReduce. Scalability demonstrates variable behavior in correlation with other batch schedulers, particularly as immediate examinations are usually not accessible on a similar platform. Direct Hadoop examinations with batch schedulers are missing in the literature, but we note that there is some evidence that the scale of MPI executions is better than Hadoop. The dilemma of the interface and structure of an asset to use Hadoop is a significant obstacle to the utilization of the Hadoop biological framework. This will enhance additional time as Hadoop interfaces, such as enhancing Flash, increasing the use of cloud platforms, and normalized approaches, for example, are taken up by Workflow Languages.

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Lakhrissi, Younes, Mohamed Rbaa, Burak Tuzun, Abdelhadi Hichar, El Hassane Anouar, Khadija Ounine, Faisal Almalki, Taibi Ben Hadda, Abdelkader Zarrouk, and Brahim Lakhrissi. "Synthesis, structural confirmation, antibacterial properties and bio-informatics computational analyses of new pyrrole based on 8-hydroxyquinoline." Journal of Molecular Structure 1259 (July 2022): 132683. http://dx.doi.org/10.1016/j.molstruc.2022.132683.

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Shimizu, Nobutaka, Shinya Saijyo, Hiromasa Ota, Yasuko Nagatani, Ai Kamijyo, Takeharu Mori, Takashi Kosuge, and Noriyuki Igarashi. "3P015 Bio-SAXS in the Platform for Drug Discovery, Informatics, and Structural Life Science (PDIS)(01A. Protein: Structure,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S214. http://dx.doi.org/10.2142/biophys.53.s214_3.

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George Priya Doss, C., C. Sudandiradoss, R. Rajasekaran, Rituraj Purohit, K. Ramanathan, and Rao Sethumadhavan. "Identification and structural comparison of deleterious mutations in nsSNPs of ABL1 gene in chronic myeloid leukemia: A bio-informatics study." Journal of Biomedical Informatics 41, no. 4 (August 2008): 607–12. http://dx.doi.org/10.1016/j.jbi.2007.12.004.

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Rahman, Monzilur, and Md Masud Parvege. "In silico structural analysis of Hantaan virus glycoprotein G2 and conserved epitope prediction for vaccine development." Journal of Applied Virology 3, no. 3 (September 19, 2014): 62. http://dx.doi.org/10.21092/jav.v3i3.38.

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<p>Hantaan virus (HNTV) is an etiological agent of potentially fatal hemorrhagic fever with renal syndrome (HFRS). The virus infects a large number of patients annually with a mortality rate more than 10%. However, no treatment option or vaccine is available against the virus. Between two envelope proteins, HNTV glycoprotein G2 has higher antigenicity making it a better target for vaccine development. However, 3-D structure of the protein is not available which is important for identifying epitopes that are essential for vaccine design. Therefore, this study was designed to predict a structural model of glycoprotein G2 and to predict peptide sequences for vaccine development containing conserved epitopes within the structure. Many of the physio-chemical and structural properties including secondary structure and di-sulfide linkage of the protein were predicted using a number of computational tools. <strong></strong>The 3D structure of the protein was modeled using I-TASSER online tool. The quality of the predicted models was evaluated with Ramachandran plot and Z-score. The structural and sequence information was used to predict B-cell and T-cell epitopes on glycoprotein G2. Using various bio-informatics and immuno-informatics tools, a total of 9 continuous B-cell and 22 T-cell epitopes were predicted having significant antigenicity. These antigenic epitopes were further analyzed for conservation and a total of 4 B-cells and 8 T-cell epitopes were found to be highly conserved in sequences from diverse origins. These epitopes revealed by the current study are recognized by immune system to protect host from HNTV infection can be potential targets for vaccine development.</p>

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Kumar, Archana, T. B. Sridharn, and Kamini A. Rao. "Role of Seminal Plasma Proteins in Effective Zygote Formation- A Success Road to Pregnancy." Protein & Peptide Letters 26, no. 4 (March 28, 2019): 238–50. http://dx.doi.org/10.2174/0929866526666190208112152.

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Seminal plasma proteins contributed by secretions of accessory glands plays a copious role in fertilization. Their role is overlooked for decades and even now, as Artificial Reproduction Techniques (ART) excludes the plasma components in the procedures. Recent evidences suggest the importance of these proteins starting from imparting fertility status to men, fertilization and till successful implantation of the conceptus in the female uterus. Seminal plasma is rich in diverse proteins, but a major part of the seminal plasma is constituted by very lesser number of proteins. This makes isolation and further research on non abundant protein a tough task. With the advent of much advanced proteomic techniques and bio informatics tools, studying the protein component of seminal plasma has become easy and promising. This review is focused on the role of seminal plasma proteins on various walks of fertilization process and thus, the possible exploitation of seminal plasma proteins for understanding the etiology of male related infertility issues. In addition, a compilation of seminal plasma proteins and their functions has been done.

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Gheraibia, Youcef, Abdelouahab Moussaoui, Youcef Djenouri, Sohag Kabir, Peng-Yeng Yin, and Smaine Mazouzi. "Penguin Search Optimisation Algorithm for Finding Optimal Spaced Seeds." International Journal of Software Science and Computational Intelligence 7, no. 2 (April 2015): 85–99. http://dx.doi.org/10.4018/ijssci.2015040105.

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This paper develops PeSeeD, a new metaheuristic algorithm for finding optimal spaced seed. Sequences matching is a hot topic in bio-informatics, which is used in many applications such as understanding the functional, structural, or evolutionary relationships between the sequences. The most relevant sequences matching methods are based on seeds designed to match two biological sequences. The first approach which introduced seeds was facilitated via Blastn tool, the approach builds seeds of 11 length size. However, it is clear that not all local alignments have to include an identical fragment of length 11. The spaced seeds approach is one of the methods which does not require a consecutive matching position. Dynamic programming is used to solve this kind of problem and it takes quadratic time. Several approaches have then been proposed to improve the sensitivity of searching in reasonable runtime. To reduce the complexity of such approaches, other heuristics based approaches can also be reviewed. The aim is to find spaced seeds subset which improves sensitivity without increasing the computation time. In this paper, the optimal subset spaced seeds are explored using the bio-inspired approach, penguins search optimisation algorithm (‘'PeSOA'' for short). The authors further propose an efficient heuristic for computing the overlap complexity between seeds. To evaluate the efficiency of the proposed approach, they compared the obtained results with the results of several seeds based software tools. The obtained results are very promising in terms of sensitivity and computation time for the overlap complexity.

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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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Lakhrissi, Younes, Mohamed Rbaa, Burak Tuzun, Abdelhadi Hichar, El Hassane Anouar, Khadija Ounine, Faisal Almalki, Taibi Ben Hadda, Abdelkader Zarrouk, and Brahim Lakhrissi. "Corrigendum to ‘Synthesis, Structural confirmation, Antibacterial Properties and Bio-Informatics Computational Analyses of New Pyrrole Based on 8-Hydroxyquinoline’ Journal of Molecular Structure 1259 (2022) 132683." Journal of Molecular Structure 1280 (May 2023): 134988. http://dx.doi.org/10.1016/j.molstruc.2023.134988.

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Khuntia, Bharat Krushna, Vandna Sharma, Sahar Qazi, Soumi Das, Shruti Sharma, Khalid Raza, and Gautam Sharma. "Ayurvedic Medicinal Plants Against COVID-19: An In Silico Analysis." Natural Product Communications 16, no. 11 (November 2021): 1934578X2110567. http://dx.doi.org/10.1177/1934578x211056753.

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Even after one and a half years since the outbreak of COVID-19, its complete and effective control is still far from being achieved despite vaccination drives, symptomatic management with available drugs, and wider lockdowns. This has inspired researchers to screen potential phytochemicals from medicinal plants against SARS-CoV-2, adopting a bio-informatics approach. The current study aimed to assess anti-viral activity of the phytochemicals derived from Ayurvedic medicinal plants against SARS-CoV-2 drug targets [3-chymotrypsin-like protease (3CLpro) and RNA dependent RNA polymerase (RdRp)] using validated in silico methods.3D Structures of 196 phytochemicals from three Ayurvedic plants were retrieved from PubChem and KNApSAcK databases and screened for Absorption Distribution Metabolism Excretion and Toxicity(ADMET) to predict drug-likeness. The phytochemicals were subjected to molecular docking and only three showed promise: Acetovanillonewith a binding affinity of −4.7Kcal/mol with RdRp and −4.1 Kcal/mol with 3CL pro; myrtenol with equivalent values of −4.3 Kcal/mol with RdRP and −3.2 Kcal/mol with 3CLpro; and nimbochalcin with equivalent values of −5.0Kcal/mol with RdRp and −4.9 Kcal/mol with 3CLpro. Molecular dynamics simulation (50ns) analysis was made of 3CLpro and RdRp using Autodock Vina 1.1.2 software and VMD software. After ADMET analysis, 78 phytochemicals were found suitable for molecular docking. Three, namely acetovanillone, myrtenol and nimbochalcin from Picrorhiza kurroa, Azadirachta indica and Cyperus rotundus,respectively,exhibited good binding affinity with 3CLproand RdRp of SARS-CoV-2. Interaction analysis, molecular dynamics simulations and MM-PBSA calculations were executed for two complexes, acetovanillone_RdRp and myrtenol_3CL pro.Acetovanillone_RdRpcomplex did not display any structural change after MD simulation as compared to myrtenol_3CL pro. The overall stability of acetovanillone_6NUR was 154.7 kJ/mol, and for myrtenol_1UJ1 90.5 kJ/mol. In silico analysis revealed that acetovanillone ( Picrorhiza kurroa) and myrtenol ( Cyperus rotundus) possess anti SARS-CoV-2 activity. Further studies are needed to validate their efficacy in biological models.

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Chacko, Anita, Shankarrao Patil, Atul Upadhayay, Deepak Arya, Ashwat Nagrajan, Rakesh Khatri, Sudhir Krishna, Ramanathan Sowdhamini, Cecil Ross, and Rajesh Behl. "A High Throughput Exome Sequencing Approach To Analyse Events Within a Good Responder CML Patient Under Imatinib At Diagnosis and Under Remission." Blood 122, no. 21 (November 15, 2013): 5161. http://dx.doi.org/10.1182/blood.v122.21.5161.5161.

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Abstract Background Genome sequencing has emerged recently as a technology that can be used to address questions regarding the clonal evolution of cancers. This has the potential to be translated into practical applications in a clinical setting. We have undertaken a case study by carrying out whole exome sequencing of a patient with CML since its clinical outcome varies amongst patients during the progression of disease. Our study is an attempt for a better understanding of why patients differ in their response to different dose of drug regimen and to determine its role in clinical outcome. Our case involves a patient with BCR–ABL positive CML. She has been responding to Imatinib, at 200 mg once a day, a dosage lower than the recommended 400mg /day. She has been taking 200 mg / day irregularly for two years and there were frequent interruptions of regular dosage schedule because of severe symptomatic cytopenias requiring blood transfusions. At the end of 2 years, there has been no progression of disease. Her bone marrow aspirate and biopsy have been normal and the BCR-ABL transcript has been below detectable levels. It was by serendipity that we happened to study the whole exome of this patient before we started her on Imatinib. As her dose response was erratic, we decided to do a longitudinal study. We examined the whole exome of the patient with CML at different points during the progression of disease. The aim of this study is to identify novel polymorphisms or variants which might be associated with the case, there by resisting the disease to progress. We were interested in the process of understanding the variability of the clinical outcome to standard treatment from a genomics perspective. Results The exome sequencing of the bone marrow aspirate was performed at the time of diagnosis and two years post treatment with Imatinib. Matched skin biopsy was used as a control. This study has been approved by the Institutional Ethical Review Board of St. John's Medical college and Hospital. The SNVs of the skin data were used as the control in this experiment to account for germ line mutations. We observe severe genome instability in terms of single nucleotide variants (SNVs) at the time of diagnosis. The counts of SNVs are observed to be drastically reduced in the treated bone marrow sample than at the time of diagnosis. No insertions or deletions were observed in this longitudinal case study. It was also observed that the SNV counts were not dominated in any particular chromosome. The SNVs picked up by exome sequencing were hence contrasted at the stage of diagnosis and post treatment. These SNVs were compared to dbSNP to retain only those which are novel and not previously reported. This finally gave rise to three discreet sets to consider: 1). The SNVs present in the genome of the patient at diagnosis 2). Post treatment, and 3). a subset common to both of them. The non-synonymous coding mutations with single base substitutions were 1,08,436 at the time of diagnosis and reduced to 163 in a stage of remission. The overlaps between these two categories were 169 in number. These hits in respective categories were further filtered based on the score of SNV call, relevance to the disease, presence within domain boundaries and final predicted impact on the function of the coded protein. We have identified novel mutations within the ABL, BCR, Kit and NOTCH genes with high probability of impact on function in the bone marrow sample at diagnosis. These will further be validated experimentally to be confirmed as a probable marker for screening patients. This study will be extended to screen a cohort of patients with similar prognosis as the patient in our case study. The novel mutations will be mapped on the protein structure to show which functional domains could be affected and to provide a structural basis for the deleterious effects of such mutations. We hence attempt to understand this clinical case with an integrated view involving basic experimental biology, bio-informatics and structural biology. These polymorphisms would provide insights on the evolution of CML and eventually allow us to use such readouts as a screen across CML patients to identify cases with better disease prognosis. With the distinct population groups and diverse spectrum of diseases, we believe that our work lays the foundation for larger studies in both CML and other diseases requiring such approaches. Disclosures: No relevant conflicts of interest to declare.

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Halim, Sobia Ahsan, Almas Gul Sikandari, Ajmal Khan, Abdul Wadood, Muhammad Qaiser Fatmi, René Csuk, and Ahmed Al-Harrasi. "Structure-Based Virtual Screening of Tumor Necrosis Factor-α Inhibitors by Cheminformatics Approaches and Bio-Molecular Simulation." Biomolecules 11, no. 2 (February 22, 2021): 329. http://dx.doi.org/10.3390/biom11020329.

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Tumor necrosis factor-α (TNF-α) is a drug target in rheumatoid arthritis and several other auto-immune disorders. TNF-α binds with TNF receptors (TNFR), located on the surface of several immunological cells to exert its effect. Hence, the use of inhibitors that can hinder the complex formation of TNF-α/TNFR can be of medicinal significance. In this study, multiple chem-informatics approaches, including descriptor-based screening, 2D-similarity searching, and pharmacophore modelling were applied to screen new TNF-α inhibitors. Subsequently, multiple-docking protocols were used, and four-fold post-docking results were analyzed by consensus approach. After structure-based virtual screening, seventeen compounds were mutually ranked in top-ranked position by all the docking programs. Those identified hits target TNF-α dimer and effectively block TNF-α/TNFR interface. The predicted pharmacokinetics and physiological properties of the selected hits revealed that, out of seventeen, seven compounds (4, 5, 10, 11, 13–15) possessed excellent ADMET profile. These seven compounds plus three more molecules (7, 8 and 9) were chosen for molecular dynamics simulation studies to probe into ligand-induced structural and dynamic behavior of TNF-α, followed by ligand-TNF-α binding free energy calculation using MM-PBSA. The MM-PBSA calculations revealed that compounds 4, 5, 7 and 9 possess highest affinity for TNF-α; 8, 11, 13–15 exhibited moderate affinities, while compound 10 showed weaker binding affinity with TNF-α. This study provides valuable insights to design more potent and selective inhibitors of TNF-α, that will help to treat inflammatory disorders.

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Lee, Cherl-Joon, Wonseok Shin, Minsik Song, Seung-Shick Shin, Yujun Park, Kornsorn Srikulnath, Dong Hee Kim, and Kyudong Han. "Comparison of digital PCR platforms using the molecular marker." Genomics & Informatics 21, no. 2 (June 30, 2023): e24. http://dx.doi.org/10.5808/gi.23008.

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Assays of clinical diagnosis and species identification using molecular markers are performed according to a quantitative method in consideration of sensitivity, cost, speed, convenience, and specificity. However, typical polymerase chain reaction (PCR) assay is difficult to quantify and have various limitations. In addition, to perform quantitative analysis with the quantitative real-time PCR (qRT-PCR) equipment, a standard curve or normalization using reference genes is essential. Within the last a decade, previous studies have reported that the digital PCR (dPCR) assay, a third-generation PCR, can be applied in various fields by overcoming the shortcomings of typical PCR and qRT-PCR assays. We selected Stilla Naica System (Stilla Technologies), Droplet Digital PCR Technology (Bio-Rad), and Lab on an Array Digital Real-Time PCR analyzer system (OPTOLANE) for comparative analysis among the various droplet digital PCR platforms currently in use commercially. Our previous study discovered a molecular marker that can distinguish Hanwoo species (Korean native cattle) using Hanwoo-specific genomic structural variation. Here, we report the pros and cons of the operation of each dPCR platform from various perspectives using this species identification marker. In conclusion, we hope that this study will help researchers to select suitable dPCR platforms according to their purpose and resources.

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Luu, Rachel K., and Markus J. Buehler. "Materials Informatics tools in the context of bio-inspired material mechanics." Journal of Applied Mechanics, April 12, 2023, 1–17. http://dx.doi.org/10.1115/1.4062310.

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Abstract The analysis and design of materials is often a slow process that may take weeks, months, or years. And, many current material platforms rely on expensive raw material sources and fail to achieve sustainability goals. Meanwhile, bio-inspired Materials Informatics – fueled by emerging techniques such as multiscale modeling, machine learning and autonomous experimentation – is transforming the way materials are understood, discovered, developed, and selected. The impact of these tools is particularly noteworthy since they can be used to develop materials with fewer resources and with greater societal impact. A field that would strongly benefit from the use of Materials Informatics tools is that of structural biological materials, where mechanical properties are crucial for biological and engineering properties for species survival such as fracture resistant armor against predators, elastic recovery for repeated loadings, or mechanical actuation capacity. Generations of researchers have studied biological materials for their fascinating structure-property relationships that make up their impressive properties, including mechanical resilience. Despite the accumulation of scientific knowledge, relatively little has been translated to generating engineered bio-inspired materials. Addressing this gap, emerging Materials Informatics tools can now be used to make use of legacy data, newly collected empirical observations, and predictive models to make significant advances in this field.

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Perotin, Jeanne-Marie, Myriam Polette, Gaëtan Deslée, and Valérian Dormoy. "CiliOPD: a ciliopathy-associated COPD endotype." Respiratory Research 22, no. 1 (February 27, 2021). http://dx.doi.org/10.1186/s12931-021-01665-4.

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AbstractThe pathophysiology of chronic obstructive pulmonary disease (COPD) relies on airway remodelling and inflammation. Alterations of mucociliary clearance are a major hallmark of COPD caused by structural and functional cilia abnormalities. Using transcriptomic databases of whole lung tissues and isolated small airway epithelial cells (SAEC), we comparatively analysed cilia-associated and ciliopathy-associated gene signatures from a set of 495 genes in 7 datasets including 538 non-COPD and 508 COPD patients. This bio-informatics approach unveils yet undescribed cilia and ciliopathy genes associated with COPD including NEK6 and PROM2 that may contribute to the pathology, and suggests a COPD endotype exhibiting ciliopathy features (CiliOPD).

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"Identiﬁcation and structural comparison of deleterious mutations in nsSNPs of IL-6 gene in inflammation: A bio-informatics study." Inflammation and Cell Signaling, October 27, 2015. http://dx.doi.org/10.14800/ics.777.

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Li, Xinzhong, Peter A. Thomason, Dominic J. Withers, and James Scott. "Bio-informatics analysis of a gene co-expression module in adipose tissue containing the diet-responsive gene Nnat." BMC Systems Biology 4, no. 1 (December 2010). http://dx.doi.org/10.1186/1752-0509-4-175.

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Dash, Adyasha, Manjusha Pandey, and Siddharth Swarup Rautaray. "novel deep neural network framework for biomedical named entity recognition." International journal of health sciences, June 23, 2022, 4310–24. http://dx.doi.org/10.53730/ijhs.v6ns5.9557.

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With the dramatic improvements in the field of bio-informatics, extracting information from text and analyzing the association between the entities has received more attention in the past few years. Entity Recognition (ER) meant to extract and recognize the entities from any text. Biomedical Named Entity Recognition (BNER) gets more and more attention from the researchers since it is a fundamental task in biomedical information extraction. Various methods has been proposed to perform the task of BioNER. Different kind of approaches are dictionary based, rule based approaches, traditional machine learning approaches that combines supervised and unsupervised methods and neural network based approach. The state-of-art systems previously adopted various supervised machine learning methods Hidden Markov Models (HMMs), Maximum Entropy Markov Models (MEMMs), Support vector machines(SVM),Structural Support Vector Machines(SSVMS),Conditional Random Fields(CRF) to derive semantic and syntatic features from annotated datasets. However, CRF is one of the most successful method used for NER and it has obtained finest result because of the robustness and ability for sequence lebelling task. Recently, studies have demonstrated the application of deep learning based approaches for biomedical named entity recognition (BioNER) and shown promising results.

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Hussein, Baydaa Abed, Isaac Karimi, and Namdar Yousofvand. "Chemo- and bio-informatics insight into anti-cholinesterase potentials of berries and leaves of Myrtus communis L., Myrtaceae: an in vitro/in silico study." BMC Complementary Medicine and Therapies 23, no. 1 (November 21, 2023). http://dx.doi.org/10.1186/s12906-023-04241-z.

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Abstract Background Myrtus communis L. (MC) has been used in Mesopotamian medicine. Here, the cholinesterase (ChE) inhibitory potential of its methyl alcohol extracts has been investigated and computationally dissected. Method The ChE inhibition has been measured based on usual Ellman’s colorimetric method compared to a canonical ChE inhibitor, eserine. Through a deep text mining, the structures of phytocompounds (= ligands) of MC were curated from ChemSpider, PubChem, and ZINC databases and docked into protein targets, AChE (PDB 1EVE) and BChE (PDB 1P0I) after initial in silico preparedness and binding affinity (BA; kcal/mol) reported as an endpoint. The calculation of ADMET (absorption, distribution, metabolism, excretion, and toxicity) features of phytocompounds were retrieved from SwissADME (http://www.swissadme.ch/) and admetSAR software to predict the drug-likeness or lead-likeness fitness. The Toxtree v2.5.1, software platforms (http://toxtree.sourceforge.net/) have been used to predict the class of toxicity of phytocompounds. The STITCH platform (http://stitch.embl.de) has been employed to predict ChE-chemicals interactions. Results The possible inhibitory activities of AChE of extracts of leaves and berries were 37.33 and 70.00%, respectively as compared to that of eserine while inhibitory BChE activities of extracts of leaves and berries of MC were 19.00 and 50.67%, respectively as compared to that of eserine. Phytochemicals of MC had BA towards AChE ranging from -7.1 (carvacrol) to -9.9 (ellagic acid) kcal/mol. In this regard, alpha-bulnesene, (Z)-gamma-Bisabolene, and beta-bourbonene were top-listed low toxic binders of AChE, and (Z)-gamma-bisabolene was a more specific AChE binder. Alpha-cadinol, estragole, humulene epoxide II, (a)esculin, ellagic acid, patuletin, juniper camphor, linalyl anthranilate, and spathulenol were high class (Class III) toxic substances which among others, patuletin and alpha-cadinol were more specific AChE binders. Among intermediate class (Class II) toxic substances, beta-chamigrene was a more specific AChE binder while semimyrtucommulone and myrtucommulone A were more specific BChE binders. Conclusion In sum, the AChE binders derived from MC were categorized mostly as antiinsectants (e.g., patuletin and alpha-cardinal) due to their predicted toxic classes. It seems that structural amendment and stereoselective synthesis like adding sulphonate or sulphamate groups to these phytocompounds may make them more suitable candidates for considering in preclinical investigations of Alzheimer’s disease.

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Xie, Yixiao, Wen Liu, Ping Li, Shiqie Bai, Daxu Li, Lixia Zhang, Hong Sun, et al. "Soil bacterial community structure at different plant maturity stages in an annual grass–legume production system." Frontiers in Sustainable Food Systems 7 (April 18, 2023). http://dx.doi.org/10.3389/fsufs.2023.1145488.

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IntroductionTo infer changes in soil function and thus determine appropriate agronomic management practices, this study evaluated the effects of plant maturity stage on root characteristics, soil chemical and enzymatic properties, and soil bacterial community composition in an annual grass–legume production system.MethodsAnnual ryegrass or rye was sown in combination with one of three legume species at a legume ratio of 50%. Eighteen plots (six plant combinations, three replicates per combination, 20 m × 25 m plots) were tilled to a depth of 20 cm after mowing. Soil samples from each plot were collected on four dates as the plants matured: January 4 (H1), March 14 (H2), April 21 (H3), and May 19 (H4). Bacterial community structures were characterized via 16S rRNA high-throught sequencing and the bio-informatics methods were used to evaluate the structural characteristics of soil bacteria.ResultsThe most abundant root growth was observed at the H3 stage. No significant differences in organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium contents (p > 0.05) were observed on any sampling date. Soil collected at the H3 stage exhibited lower acid protease and urease activities (p < 0.05) and higher nitrate reductase activity (p < 0.05). The structure of the microbial community at stage H3 differed markedly from that at other stages, as evidenced by a higher abundance of Proteobacteria, Bacteroidetes, Acidobacteria, and Verrucomicrobia (p < 0.05) and a lower abundance of Actinobacteria, Cyanobacteria, and Planctomycetes (p < 0.05). At the class level, the relative abundances of Sphingobacteria, Betaproteobacteria, and Gammaproteobacteria in soil was higher at H3 stage than those of other stages (p < 0.05). The order level for Sphingomonadales, Sphingobacteriales, and Burkholderiales and at the family level for Chitinophagaceae and Sphingomonadaceae showed the same trend toward higher.ConclusionNutrient cycling in the soil was slowed at the H3 stage, and the loss of nitrogen would also be greater. Measures may need to be taken to improve the nitrogen fertilizer utilization efficiency to reduce denitrification and nitrous oxide production at this stage (the booting stage of grasses and budding stage of legumes).

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Kukkarasapalli, Praveen, and Yellamma Kuna. "Docking Studies on Ache and Tau Proteins with Marine Bioactive Compound Squalene, A New Approach to Design Anti-Alzheimer’s Drug Targets." International Journal of Pharmaceutical Sciences Review and Research 70, no. 2 (October 15, 2021). http://dx.doi.org/10.47583/ijpsrr.2021.v70i02.031.

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Abstract:

Natural bioactive compounds of Marine origin have attracted the attention of many biologists and chemists in the world over for the last five decades because it has proven to be a rich source of structurally diverse and complex compounds exhibiting numerous interesting biological functions. At present, many research findings have provided insight into biological activities of marine natural compounds such as antioxidant- and anti-cholinesterase activity and neuroprotective effects on neurodegenerative diseases, viz. Alzheimer’s and Parkinson’s. The main pathological hallmarks of AD is the formation senile plaques, neurofibrillary tangles and the most incredible physiological and biochemical changes are reduction in acetylcholine (ACh) levels in the hippocampus and cortex of the brain and loss of memory, decaying language etc. Present study is focused on to enhance the acetylcholine levels and subsequently to prevent the formation of Senile Plaques and Neuro Fibrillary Tangles in tau protein responsible for Alzheimer’s disease by using natural bioactive compound Squalene. Computational Biology and Bio-informatics have the potential not only to speed up the drug discovery process but reduces the costs. Further, they also change the way drugs are designed by using Docking Techniques employed to dock a set of marine bioactive compounds within the active site region of 1B41 & 2V17 by using Auto Dock vina. The docking simulation clearly predicted the interaction and highest binding energy docking scores against Squalene, analogues were retrieved from ZINC database i.e. ZINC 0118 (-8.9) and ZINC 0142 (-8.3) for 4B05 & 2V17 enzymes respectively. Further, we Studied visualization aspects in PyMol and also satisfied the biological activity predictions like OSIRIS, Molinspiration and PASS Prediction results by inhibiting the activity of Tau and Acetyl Cholinesterase receptors in AD.

Journal articles on the topic 'Structural bio-Informatics'

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