Journal articles: 'Protein-RNA docking'

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Arnautova, Yelena A., Ruben Abagyan, and Maxim Totrov. "Protein-RNA Docking Using ICM." Journal of Chemical Theory and Computation 14, no. 9 (July 17, 2018): 4971–84. http://dx.doi.org/10.1021/acs.jctc.8b00293.

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He, Jiahua, Huanyu Tao, and Sheng-You Huang. "Protein-ensemble–RNA docking by efficient consideration of protein flexibility through homology models." Bioinformatics 35, no. 23 (May 14, 2019): 4994–5002. http://dx.doi.org/10.1093/bioinformatics/btz388.

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AbstractMotivationGiven the importance of protein–ribonucleic acid (RNA) interactions in many biological processes, a variety of docking algorithms have been developed to predict the complex structure from individual protein and RNA partners in the past decade. However, due to the impact of molecular flexibility, the performance of current methods has hit a bottleneck in realistic unbound docking. Pushing the limit, we have proposed a protein-ensemble–RNA docking strategy to explicitly consider the protein flexibility in protein–RNA docking through an ensemble of multiple protein structures, which is referred to as MPRDock. Instead of taking conformations from MD simulations or experimental structures, we obtained the multiple structures of a protein by building models from its homologous templates in the Protein Data Bank (PDB).ResultsOur approach can not only avoid the reliability issue of structures from MD simulations but also circumvent the limited number of experimental structures for a target protein in the PDB. Tested on 68 unbound–bound and 18 unbound–unbound protein–RNA complexes, our MPRDock/DITScorePR considerably improved the docking performance and achieved a significantly higher success rate than single-protein rigid docking whether pseudo-unbound templates are included or not. Similar improvements were also observed when combining our ensemble docking strategy with other scoring functions. The present homology model-based ensemble docking approach will have a general application in molecular docking for other interactions.Availability and implementationhttp://huanglab.phys.hust.edu.cn/mprdock/Supplementary informationSupplementary data are available at Bioinformatics online.

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Delgado Blanco, Javier, Leandro G. Radusky, Damiano Cianferoni, and Luis Serrano. "Protein-assisted RNA fragment docking (RnaX) for modeling RNA–protein interactions using ModelX." Proceedings of the National Academy of Sciences 116, no. 49 (November 15, 2019): 24568–73. http://dx.doi.org/10.1073/pnas.1910999116.

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RNA–protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an RNA molecule interacts with a target protein and/or engineering an RNA molecule to specifically bind to a protein could allow for rational interference with these cellular processes and the design of novel therapies. Here we present a robust RNA–protein fragment pair-based method, termed RnaX, to predict RNA-binding sites. This methodology, which is integrated into the ModelX tool suite (http://modelx.crg.es), takes advantage of the structural information present in all released RNA–protein complexes. This information is used to create an exhaustive database for docking and a statistical forcefield for fast discrimination of true backbone-compatible interactions. RnaX, together with the protein design forcefield FoldX, enables us to predict RNA–protein interfaces and, when sufficient crystallographic information is available, to reengineer the interface at the sequence-specificity level by mimicking those conformational changes that occur on protein and RNA mutagenesis. These results, obtained at just a fraction of the computational cost of methods that simulate conformational dynamics, open up perspectives for the engineering of RNA–protein interfaces.

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Pérez-Cano, Laura, Miguel Romero-Durana, and Juan Fernández-Recio. "Structural and energy determinants in protein-RNA docking." Methods 118-119 (April 2017): 163–70. http://dx.doi.org/10.1016/j.ymeth.2016.11.001.

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Zhang, Zhao, Lin Lu, Yue Zhang, Chun Hua Li, Cun Xin Wang, Xiao Yi Zhang, and Jian Jun Tan. "A combinatorial scoring function for protein-RNA docking." Proteins: Structure, Function, and Bioinformatics 85, no. 4 (February 9, 2017): 741–52. http://dx.doi.org/10.1002/prot.25253.

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Zheng, Jinfang, Xu Hong, Juan Xie, Xiaoxue Tong, and Shiyong Liu. "P3DOCK: a protein–RNA docking webserver based on template-based and template-free docking." Bioinformatics 36, no. 1 (June 7, 2019): 96–103. http://dx.doi.org/10.1093/bioinformatics/btz478.

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AbstractMotivationThe main function of protein–RNA interaction is to regulate the expression of genes. Therefore, studying protein–RNA interactions is of great significance. The information of three-dimensional (3D) structures reveals that atomic interactions are particularly important. The calculation method for modeling a 3D structure of a complex mainly includes two strategies: free docking and template-based docking. These two methods are complementary in protein–protein docking. Therefore, integrating these two methods may improve the prediction accuracy.ResultsIn this article, we compare the difference between the free docking and the template-based algorithm. Then we show the complementarity of these two methods. Based on the analysis of the calculation results, the transition point is confirmed and used to integrate two docking algorithms to develop P3DOCK. P3DOCK holds the advantages of both algorithms. The results of the three docking benchmarks show that P3DOCK is better than those two non-hybrid docking algorithms. The success rate of P3DOCK is also higher (3–20%) than state-of-the-art hybrid and non-hybrid methods. Finally, the hierarchical clustering algorithm is utilized to cluster the P3DOCK’s decoys. The clustering algorithm improves the success rate of P3DOCK. For ease of use, we provide a P3DOCK webserver, which can be accessed at www.rnabinding.com/P3DOCK/P3DOCK.html. An integrated protein–RNA docking benchmark can be downloaded from http://rnabinding.com/P3DOCK/benchmark.html.Availability and implementationwww.rnabinding.com/P3DOCK/P3DOCK.html.Supplementary informationSupplementary data are available at Bioinformatics online.

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Setny, Piotr, and Martin Zacharias. "A coarse-grained force field for Protein–RNA docking." Nucleic Acids Research 39, no. 21 (August 16, 2011): 9118–29. http://dx.doi.org/10.1093/nar/gkr636.

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Nithin, Chandran, Sunandan Mukherjee, and Ranjit Prasad Bahadur. "A non-redundant protein-RNA docking benchmark version 2.0." Proteins: Structure, Function, and Bioinformatics 85, no. 2 (December 2, 2016): 256–67. http://dx.doi.org/10.1002/prot.25211.

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Wicaksono, Adhityo, and Arli Aditya Parikesit. "Molecular Docking and Dynamics of SARS-CoV-2 Programmed Ribosomal Frameshifting RNA and Ligands for RNA-Targeting Alkaloids Prospecting." HAYATI Journal of Biosciences 30, no. 6 (July 24, 2023): 1025–35. http://dx.doi.org/10.4308/hjb.30.6.1025-1035.

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RNA-ligand docking is a part of computational biology, which is currently lowly recognized compared to the protein-ligand docking procedure commonly applied for drug discovery. This in silico study aims to create a simplified protocol for RNA-ligand docking, which is applicable to RNA-targeting small molecular drug screening. Four alkaloids (berberine, colchicine, nicotine, and tomatine) were subjected to this study and contended against the SARS-CoV-2 genomic RNA -1 PRF component targeting control drug, merafloxacin, including two known intercalator berberine and colchicine, a small alkaloid nicotine and a large alkaloid tomatine. The alkaloids were screened for drug-likeness properties (Lipinski’s Rules of 5 or LRo5), bioavailability indexes, and synthetic accessibility values using SwissADME before docking. The docking used PyRx – Autodock Vina and re-scored for RNA-ligand scoring using AnnapuRNA. The docking results have the interactions mapped using fingeRNAt and visualized using Discovery Studio. Molecular dynamics using CHARMM36 and AMBER forcefields were simulated in NAMD. The molecular dynamics 1 ns simulation results showed that the ligand interaction over time did not cause much interference with the RNA, indicated by the low number of RMSD changes between RNA itself and the RNA-ligand complex. Additionally, CHARMM36 forcefield provided more stable fluctuation compared to AMBER. The results indicated that tomatine disobeyed LRo5 and had a low bioavailability index and bad synthetic accessibility value, while the rest alkaloids passed. In the end, berberine has an even higher docking score than the control drug. The study also shows that this protocol can be useful for future RNA-ligand computational studies.

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Li, Yaozong, Jie Shen, Xianqiang Sun, Weihua Li, Guixia Liu, and Yun Tang. "Accuracy Assessment of Protein-Based Docking Programs against RNA Targets." Journal of Chemical Information and Modeling 50, no. 6 (May 19, 2010): 1134–46. http://dx.doi.org/10.1021/ci9004157.

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Guilhot-Gaudeffroy, Adrien, Christine Froidevaux, Jérôme Azé, and Julie Bernauer. "Protein-RNA Complexes and Efficient Automatic Docking: Expanding RosettaDock Possibilities." PLoS ONE 9, no. 9 (September 30, 2014): e108928. http://dx.doi.org/10.1371/journal.pone.0108928.

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Huang, Sheng-You, and Xiaoqin Zou. "A nonredundant structure dataset for benchmarking protein-RNA computational docking." Journal of Computational Chemistry 34, no. 4 (October 10, 2012): 311–18. http://dx.doi.org/10.1002/jcc.23149.

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Marium Bibi, Marium Bibi. "Binding Pattern Analysis of Different Allosteric Inhibitors of Hepatitis C Virus (HCV) Polymerase." Journal of the chemical society of pakistan 45, no. 6 (2023): 576. http://dx.doi.org/10.52568/001393/jcsp/45.06.2023.

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To the best of our knowledge, the current study could be considered the first comprehensive one based on the application of molecular docking on the non-nucleoside thumb and palm inhibitors to nonstructural NS5B protein for the detailed evaluation of their binding patterns in the corresponding binding regions in the protein. Non-nucleoside thumb and palm inhibitors were docked into the thumb and palm sites of the nonstructural NS5B protein which is the RNA-dependent RNA polymerase, respectively. Two docking programs, AutoDock 4.2 and AutoDock Vina were employed for the docking of thumb inhibitors (filibuvir and lomibuvir) and palm inhibitors (dasabuvir and nesbuvir) into the respective binding region. The preliminary analysis of the docking performance demonstrated that AutoDock Vina was suitable for the docking of large flexible molecules as deduced from the alignment of docking conformations in all cases. Based on the docking calculation, the interaction pattern analysis was carried out for all the inhibitors which were found to reside in the respective binding region. Before the interaction pattern analysis, the best docking pose was selected based on the high binding affinity value. The interaction pattern analysis of the inhibitors revealed that hydrogen bonding and hydrophobic contacts with amino acid residues of the respective binding region were the leading force in the stabilization of these inhibitors besides other interactions. The interaction pattern analysis based on the docking calculation was also realized to be the meaningful approach to figuring out the relative stability of the protein-ligand complex formed after the inhibitor binding which eventually led to assessing the inhibitory potential of these inhibitors and could also be helpful for the future inhibitor design.

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Marwal, Avinash, Mukesh Meena, and RK Gaur. "Molecular Docking Studies of Coronavirus Proteins with Medicinal Plant Based Phytochemicals." Defence Life Science Journal 6, no. 1 (February 23, 2021): 57–63. http://dx.doi.org/10.14429/dlsj.6.15704.

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In this study, we presented an in silico molecular docking between the SARS-CoV-2 four proteins [(a) SARS-CoV-2 nucleocapsid protein N-terminal RNA binding domain (6M3M), (b) Nsp9 RNA binding protein of SARS CoV-2 (6W4B), (c) The crystal structure of COVID-19 main protease in apo form (6M03), and (d) Structure of the 2019-nCoV HR2 Domain (6LVN)] available in the PDB (Protein Data Bank), and the medicinal plant-based phytochemicals (retrieved from PubChem database) as ligand molecules i.e. Piperine (Black Pepper), Eugenol (Clove), Alliin (Garlic), Gingerol (Ginger) and Curcumin (Turmeric). All these ligand molecules showed good docking with their respective receptor molecules and their scores range from -8.195 to -5.263. DockThor Portal (a receptor ligand-docking server) which was recently developed and published this year were used in the current study. The obtained results might help in the wet lab conditions to develop better antiviral compounds against SARS-CoV-2.

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Selvaraj, Jayaraman. "Molecular docking analysis of SARS-CoV-2 linked RNA dependent RNA polymerase (RdRp) with compounds from Plectranthus amboinicus." Bioinformation 17, no. 1 (January 31, 2021): 167–70. http://dx.doi.org/10.6026/97320630017167.

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It is of interest to document the moelcular docking analysis of SARS-CoV-2 linked RNA dependent RNA polymerase (RdRp) with compounds from Plectranthus amboinicus. Hence, we report the binding features of rutin, Luteolin, Salvianolic acid A, Rosmarinic acid and p-Coumaric acid with the target protein SARS-CoV-2 linked RNA dependent RNA polymerase (RdRp) for further consideration.

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Stefaniak, Filip, and Janusz M. Bujnicki. "AnnapuRNA: A scoring function for predicting RNA-small molecule binding poses." PLOS Computational Biology 17, no. 2 (February 1, 2021): e1008309. http://dx.doi.org/10.1371/journal.pcbi.1008309.

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RNA is considered as an attractive target for new small molecule drugs. Designing active compounds can be facilitated by computational modeling. Most of the available tools developed for these prediction purposes, such as molecular docking or scoring functions, are parametrized for protein targets. The performance of these methods, when applied to RNA-ligand systems, is insufficient. To overcome these problems, we developed AnnapuRNA, a new knowledge-based scoring function designed to evaluate RNA-ligand complex structures, generated by any computational docking method. We also evaluated three main factors that may influence the structure prediction, i.e., the starting conformer of a ligand, the docking program, and the scoring function used. We applied the AnnapuRNA method for a post-hoc study of the recently published structures of the FMN riboswitch. Software is available at https://github.com/filipspl/AnnapuRNA.

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da Silva, Joyce Kelly R., Pablo Luis Baia Figueiredo, Kendall G. Byler, and William N. Setzer. "Essential Oils as Antiviral Agents, Potential of Essential Oils to Treat SARS-CoV-2 Infection: An In-Silico Investigation." International Journal of Molecular Sciences 21, no. 10 (May 12, 2020): 3426. http://dx.doi.org/10.3390/ijms21103426.

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Essential oils have shown promise as antiviral agents against several pathogenic viruses. In this work we hypothesized that essential oil components may interact with key protein targets of the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A molecular docking analysis was carried out using 171 essential oil components with SARS-CoV-2 main protease (SARS-CoV-2 Mpro), SARS-CoV-2 endoribonucleoase (SARS-CoV-2 Nsp15/NendoU), SARS-CoV-2 ADP-ribose-1″-phosphatase (SARS-CoV-2 ADRP), SARS-CoV-2 RNA-dependent RNA polymerase (SARS-CoV-2 RdRp), the binding domain of the SARS-CoV-2 spike protein (SARS-CoV-2 rS), and human angiotensin−converting enzyme (hACE2). The compound with the best normalized docking score to SARS-CoV-2 Mpro was the sesquiterpene hydrocarbon (E)-β-farnesene. The best docking ligands for SARS−CoV Nsp15/NendoU were (E,E)-α-farnesene, (E)-β-farnesene, and (E,E)−farnesol. (E,E)−Farnesol showed the most exothermic docking to SARS-CoV-2 ADRP. Unfortunately, the docking energies of (E,E)−α-farnesene, (E)-β-farnesene, and (E,E)−farnesol with SARS-CoV-2 targets were relatively weak compared to docking energies with other proteins and are, therefore, unlikely to interact with the virus targets. However, essential oil components may act synergistically, essential oils may potentiate other antiviral agents, or they may provide some relief of COVID-19 symptoms.

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Ma, Hongli, Han Wen, Zhiyuan Xue, Guojun Li, and Zhaolei Zhang. "RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites." PLOS Computational Biology 18, no. 7 (July 12, 2022): e1010293. http://dx.doi.org/10.1371/journal.pcbi.1010293.

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RNA molecules can adopt stable secondary and tertiary structures, which are essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via coarse-grained molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28B. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs.

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Yan, Yumeng, Di Zhang, Pei Zhou, Botong Li, and Sheng-You Huang. "HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy." Nucleic Acids Research 45, W1 (May 17, 2017): W365—W373. http://dx.doi.org/10.1093/nar/gkx407.

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Sharma, Arun Dev, Inderjeet Kaur, and Amrita Chauhan. "Targeting H3N2 influenza virus RNA dependent RNA polymerase dependent inhibitory activity by principal components from latex of Calotropis gigantean." Trends in Horticulture 6, no. 2 (November 17, 2023): 2940. http://dx.doi.org/10.24294/th.v6i2.2940.

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The H3N2 influenza virus is spiking dramatically, which is a major concern worldwide and in India. The multifunctional hetero-trimer influenza virus RNA-dependent RNA polymerase (RdRP) is involved in the generation of viral mRNA and is crucial for viral infectivity, which is directly related to the virus’s ability to survive. The goal of the current work was to use molecular docking to determine how the RdRP protein might be affected by powerful bioactive chemicals found in Calotropis gigantia latex. By applying CB-dock 2 analysis and 2D interactions, an in-silico docking study was conducted using a GC-FID (gas chromatography with flame-ionization detection) based composition profile. Tocospiro A (15%), Amyrin (7%), and Gombasterol A were found by GC-FID to be the main phytocompounds in the latex of Calotropis gigantia. The docking result showed that ligands were effectively bound to RdRP. According to interaction studies, RdRP/ligand complexes create hydrogen bonds, van der Waals forces, pi-alkyl bonds, alkyl bonds, and pi-Sigma bonds. Therefore, it was suggested that Calotropis gigantia latex may represent a possible herbal remedy to attenuate H3N2 infections based on the above findings of the fragrance profile and docking.

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Emmanuel Chuks Oranu, Esther Oluchukwu Eze, Adanna Ijeawele, Chisom George Obidimma, Belinda Chinecherem Umeh, Perpetua Chinonyelum Ejezie, and IC Uzochukwu. "Validation of the binding affinities and stabilities of ivermectin and moxidectin against Sars-CoV-2 receptors using molecular docking and molecular dynamics simulation." GSC Biological and Pharmaceutical Sciences 26, no. 1 (January 30, 2024): 303–14. http://dx.doi.org/10.30574/gscbps.2024.26.1.0030.

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Corona-viruses (CoVs), a large family of single-stranded RNA viruses, can infect animals and also humans, causing respiratory, gastrointestinal, hepatic, and neurologic disease. As the largest known RNA viruses, they are further divided into four genera: alpha-coronavirus, beta- corona- virus, gamma-corona virus and delta-coronavirus. SARS-CoV-2 belong to genus betacoronavirus. The viral genome of SARS-CoV-2 codes 4 major structural proteins: the nucleocapsid (N) protein, the transmembrane (M) protein, the envelope (E) protein, and the spike (S) protein. It also encodes 16 nonstructural proteins (NSPs) and 9 accessory proteins required for replication and pathogenesis. The Molecular docking simulations was used to determine the binding affinities of Ivermectin, Moxidectin and Molnupiravir against NSP13 receptor of SARS-CoV-2. The experimental crystal structures of the receptor was obtained from the protein data bank (PDB). The receptor was prepared using Chimera-1.10.1 and AutoDock tools-1.5.6. The 3D structure of the selected approved drugs and the reference ligand was obtained from PDB and Drugbank and prepared using AutoDock tools-1.5.6. Validation of docking protocol was done by reproducing the PDB crystal structures insilico. Molecular docking simulations were performed using AutoDockVina-4.2.6 on the Linux operating system (ubuntu) 20.04. Then the docking results were analysed and visualized using Pymol-2.3.0. Molecular dynamics of the frontrunners with the reference ligand and protein was done in 10000 ps. Moxidectin, molnupiravir and Ivermectin showed high binding affinities to the receptors. Moxidectin and Ivermectin showed stability after molecular dynamics simulation to further validate the claim. These drugs are predicted as possible antivirals in the treatment of Covid-19.

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Ivashkina, Natalia, Benno Wölk, Volker Lohmann, Ralf Bartenschlager, Hubert E. Blum, François Penin, and Darius Moradpour. "The Hepatitis C Virus RNA-Dependent RNA Polymerase Membrane Insertion Sequence Is a Transmembrane Segment." Journal of Virology 76, no. 24 (December 15, 2002): 13088–93. http://dx.doi.org/10.1128/jvi.76.24.13088-13093.2002.

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ABSTRACT The hepatitis C virus (HCV) RNA-dependent RNA polymerase (RdRp) belongs to a class of membrane proteins termed tail-anchored proteins. Here, we show that the HCV RdRp C-terminal membrane insertion sequence traverses the phospholipid bilayer as a transmembrane segment. Moreover, the HCV RdRp was found to be retained in the endoplasmic reticulum (ER) or an ER-derived modified compartment both following transient transfection and in the context of a subgenomic replicon. An absolutely conserved GVG motif was not essential for membrane insertion but possibly provides a docking site for transmembrane protein-protein interactions. These findings have important implications for the functional architecture of the HCV replication complex.

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Asadzadeh, Homayoun, Ali Moosavi, Georgios Alexandrakis, and Mohammad R. K. Mofrad. "Atomic Scale Interactions between RNA and DNA Aptamers with the TNF-α Protein." BioMed Research International 2021 (July 16, 2021): 1–11. http://dx.doi.org/10.1155/2021/9926128.

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Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF-α, as an example of a novel computational workflow for selecting the aptamer candidate with the highest binding strength to a target. We combine information from the binding free energy calculations, molecular docking, and molecular dynamics simulations to investigate the interactions of both aptamers with TNF-α. The results reveal that the RNA aptamer has a more stable structure relative to the DNA aptamer. Interaction of aptamers with TNF-α does not have any negative effect on its structure. The results of molecular docking and molecular dynamics simulations suggest that the RNA aptamer has a stronger interaction with the protein. Also, these findings illustrate that basic residues of TNF-α establish more atomic contacts with the aptamers compared to acidic or pH-neutral ones. Furthermore, binding energy calculations show that the interaction of the RNA aptamer with TNF-α is thermodynamically more favorable. In total, the findings of this study indicate that the RNA aptamer is a more suitable candidate for using as an apta-biosensor of TNF-α and, therefore, of greater potential use for the diagnosis of blood infections. Also, this study provides more information about aptamer-protein interactions and increases our understanding of this phenomenon.

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Kappel, Kalli, and Rhiju Das. "Sampling Native-like Structures of RNA-Protein Complexes through Rosetta Folding and Docking." Structure 27, no. 1 (January 2019): 140–51. http://dx.doi.org/10.1016/j.str.2018.10.001.

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Thakur, Priti, Jowad Atway, Patrick A. Limbach, and Balasubrahmanyam Addepalli. "RNA Cleavage Properties of Nucleobase-Specific RNase MC1 and Cusativin Are Determined by the Dinucleotide-Binding Interactions in the Enzyme-Active Site." International Journal of Molecular Sciences 23, no. 13 (June 24, 2022): 7021. http://dx.doi.org/10.3390/ijms23137021.

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Knowledge of the cleavage specificity of ribonucleases is critical for their application in RNA modification mapping or RNA-protein binding studies. Here, we detail the cleavage specificity and efficiency of ribonuclease MC1 and cusativin using a customized RNA sequence that contained all dinucleotide combinations and homopolymer sequences. The sequencing of the oligonucleotide digestion products by a semi-quantitative liquid chromatography coupled with mass spectrometry (LC-MS) analysis documented as little as 0.5–1% cleavage levels for a given dinucleotide sequence combination. While RNase MC1 efficiently cleaved the [A/U/C]pU dinucleotide bond, no cleavage was observed for the GpU bond. Similarly, cusativin efficiently cleaved Cp[U/A/G] dinucleotide combinations along with UpA and [A/U]pU, suggesting a broader specificity of dinucleotide preferences. The molecular interactions between the substrate and active site as determined by the dinucleotide docking studies of protein models offered additional evidence and support for the observed substrate specificity. Targeted alteration of the key amino acid residues in the nucleotide-binding site confirms the utility of this in silico approach for the identification of key interactions. Taken together, the use of bioanalytical and computational approaches, involving LC-MS and ligand docking of tertiary structural models, can form a powerful combination to help explain the RNA cleavage behavior of RNases.

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Ebenezer, Oluwakemi, Nkululeko Damoyi, Maryam A. Jordaan, and Michael Shapi. "Unveiling of Pyrimidindinones as Potential Anti-Norovirus Agents—A Pharmacoinformatic-Based Approach." Molecules 27, no. 2 (January 7, 2022): 380. http://dx.doi.org/10.3390/molecules27020380.

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The RNA-dependent RNA polymerase (RdRp) receptor is an attractive target for treating human norovirus (HNV). A computer-aided approach like e-pharmacophore, molecular docking, and single point energy calculations were performed on the compounds retrieved from the Development Therapeutics Program (DTP) AIDS Antiviral Screen Database to identify the antiviral agent that could target the HNV RdRp receptor. Induced-fit docking (IFD) results showed that compounds ZINC1617939, ZINC1642549, ZINC6425208, ZINC5887658 and ZINC32068149 bind with the residues in the active site-B of HNV RdRp receptor via hydrogen bonds, salt bridge, and electrostatic interactions. During the molecular dynamic simulations, compounds ZINC6425208, ZINC5887658 and ZINC32068149 displayed an unbalanced backbone conformation with HNV RdRp protein, while ZINC1617939 and ZINC1642549 maintained stability with the protein backbone when interacting with the residues. Hence, the two new concluding compounds discovered by the computational approach can be used as a chemotype to design promising antiviral agents aimed at HNV RdRp.

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He, Jiahua, Jun Wang, Huanyu Tao, Yi Xiao, and Sheng-You Huang. "HNADOCK: a nucleic acid docking server for modeling RNA/DNA–RNA/DNA 3D complex structures." Nucleic Acids Research 47, W1 (May 22, 2019): W35—W42. http://dx.doi.org/10.1093/nar/gkz412.

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AbstractInteractions between nuclide acids (RNA/DNA) play important roles in many basic cellular activities like transcription regulation, RNA processing, and protein synthesis. Therefore, determining the complex structures between RNAs/DNAs is crucial to understand the molecular mechanism of related RNA/DNA–RNA/DNA interactions. Here, we have presented HNADOCK, a user-friendly web server for nucleic acid (NA)–nucleic acid docking to model the 3D complex structures between two RNAs/DNAs, where both sequence and structure inputs are accepted for RNAs, while only structure inputs are supported for DNAs. HNADOCK server was tested through both unbound structure and sequence inputs on the benchmark of 60 RNA–RNA complexes and compared with the state-of-the-art algorithm SimRNA. For structure input, HNADOCK server achieved a high success rate of 71.7% for top 10 predictions, compared to 58.3% for SimRNA. For sequence input, HNADOCK server also obtained a satisfactory performance and gave a success rate of 83.3% when the bound RNA templates are included or 53.3% when excluding those bound RNA templates. It was also found that inclusion of the inter-RNA base-pairing information from RNA–RNA interaction prediction can significantly improve the docking accuracy, especially for the top prediction. HNADOCK is fast and can normally finish a job in about 10 minutes. The HNADOCK web server is available at http://huanglab.phys.hust.edu.cn/hnadock/.

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Adasme, Melissa F., Katja L. Linnemann, Sarah Naomi Bolz, Florian Kaiser, Sebastian Salentin, V. Joachim Haupt, and Michael Schroeder. "PLIP 2021: expanding the scope of the protein–ligand interaction profiler to DNA and RNA." Nucleic Acids Research 49, W1 (May 5, 2021): W530—W534. http://dx.doi.org/10.1093/nar/gkab294.

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Abstract With the growth of protein structure data, the analysis of molecular interactions between ligands and their target molecules is gaining importance. PLIP, the protein–ligand interaction profiler, detects and visualises these interactions and provides data in formats suitable for further processing. PLIP has proven very successful in applications ranging from the characterisation of docking experiments to the assessment of novel ligand–protein complexes. Besides ligand–protein interactions, interactions with DNA and RNA play a vital role in many applications, such as drugs targeting DNA or RNA-binding proteins. To date, over 7% of all 3D structures in the Protein Data Bank include DNA or RNA. Therefore, we extended PLIP to encompass these important molecules. We demonstrate the power of this extension with examples of a cancer drug binding to a DNA target, and an RNA–protein complex central to a neurological disease. PLIP is available online at https://plip-tool.biotec.tu-dresden.de and as open source code. So far, the engine has served over a million queries and the source code has been downloaded several thousand times.

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NAWAZ, A., and B. IJAZ. "ANTIVIRAL SCREENING OF AZADIRACHTA INDICA PHYTOCHEMICALS AS DENGUE NS5 INHIBITOR: A MOLECULAR DOCKING APPROACH." Biological and Clinical Sciences Research Journal 2023, no. 1 (November 27, 2023): 560. http://dx.doi.org/10.54112/bcsrj.v2023i1.560.

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Dengue has been an alarming viral infection in tropical and subtropical regions of the world for the past few decades, resulting in millions of deaths. There is no effective drug to treat this arbovirus-based infection. Dengue virus non-structural protein NS5 contains N terminus methyl transferase domain and C terminus RNA-dependent RNA polymerase domain, which is involved in viral RNA replication and serves as a potential target. The current in-silico study aims to find new potential dengue virus NS5 protein inhibitors. The designed library containing eight compounds from Azadirachta Indica was used to perform molecular docking against active residues of dengue virus NS5 protein. Four compounds (Desacetyl Salanin, Azadirchtin-A, Castalagin, Vilasinin) with high negative binding energy values and zero RMSD values were selected, and their drug-likeness and ADMET analysis was performed. Among the best-docked compounds, Vilasinin (-11kcal/mol) exhibited drug-like properties as it has a molecular weight less than 500 D and has zero violation value. Moreover, it has 5 hydrogen bond donors and 10 hydrogen bond acceptors. It is well soluble in water so that it can be used as a potential inhibitor and drug candidate for the treatment of dengue infection.

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YIP, Ryan Pak Hong, Doris Ching Ying Kwok, Louis Tung Faat Lai, Siu-Ming Ho, Ivan Chun Kit Wong, Chi-Ping Chan, Wilson Chun Yu Lau, and Jacky Chi Ki Ngo. "SRPK2 Mediates HBV Core Protein Phosphorylation and Capsid Assembly via Docking Interaction." PLOS Pathogens 20, no. 2 (February 7, 2024): e1011978. http://dx.doi.org/10.1371/journal.ppat.1011978.

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Members of the serine–arginine protein kinase (SRPK) family, SRPK1 and SRPK2, phosphorylate the hepatitis B core protein (Cp) and are crucial for pregenomic RNA encapsidation during viral nucleocapsid assembly. Among them, SRPK2 exhibits higher kinase activity toward Cp. In this study, we identified Cp sites that are phosphorylated by SRPK2 and demonstrated that the kinase utilizes an SRPK-specific docking groove to interact with and regulate the phosphorylation of the C-terminal arginine rich domain of Cp. We determined that direct interaction between the docking groove of SRPK2 and unphosphorylated Cp inhibited premature viral capsid assembly in vitro, whereas the phosphorylation of the viral protein reactivated the process. Pull-down assays together with the new cryo-electron microscopy structure of the HBV capsid in complex with SRPK2 revealed that the kinases decorate the surface of the viral capsid by interacting with the C-terminal domain of Cp, underscoring the importance of the docking interaction in regulating capsid assembly and pregenome packaging. Moreover, SRPK2-knockout in HepG2 cells suppressed Cp phosphorylation, indicating that SRPK2 is an important cellular kinase for HBV life cycle.

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Dickerhoff, Jonathan, Kassandra R. Warnecke, Kaibo Wang, Nanjie Deng, and Danzhou Yang. "Evaluating Molecular Docking Software for Small Molecule Binding to G-Quadruplex DNA." International Journal of Molecular Sciences 22, no. 19 (October 6, 2021): 10801. http://dx.doi.org/10.3390/ijms221910801.

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G-quadruplexes are four-stranded nucleic acid secondary structures of biological significance and have emerged as an attractive drug target. The G4 formed in the MYC promoter (MycG4) is one of the most studied small-molecule targets, and a model system for parallel structures that are prevalent in promoter DNA G4s and RNA G4s. Molecular docking has become an essential tool in structure-based drug discovery for protein targets, and is also increasingly applied to G4 DNA. However, DNA, and in particular G4, binding sites differ significantly from protein targets. Here we perform the first systematic evaluation of four commonly used docking programs (AutoDock Vina, DOCK 6, Glide, and RxDock) for G4 DNA-ligand binding pose prediction using four small molecules whose complex structures with the MycG4 have been experimentally determined in solution. The results indicate that there are considerable differences in the performance of the docking programs and that DOCK 6 with GB/SA rescoring performs better than the other programs. We found that docking accuracy is mainly limited by the scoring functions. The study shows that current docking programs should be used with caution to predict G4 DNA-small molecule binding modes.

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Li, Gang, Wei Zhou, Xiurong Zhao, and Ying Xie. "In Silico Molecular Docking and Interaction Analysis of Traditional Chinese Medicines Against SARS-CoV-2 Receptor." Natural Product Communications 16, no. 5 (May 2021): 1934578X2110150. http://dx.doi.org/10.1177/1934578x211015030.

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The novel coronavirus, 2019-nCoV, has led to a major pandemic in 2020 and is responsible for more than 2.9 million officially recorded deaths worldwide. As well as synthetic anti-viral drugs, there is also a need to explore natural herbal remedies. The Traditional Chinese Medicines (TCMs) system has been used for thousands of years for the prevention, diagnosis, and treatment of several chronic diseases. In this paper, we performed an in silico molecular docking and interaction analysis of TCMs against SARS-CoV-2 receptor RNA-dependent RNA polymerase (RdRp). We obtained the 5 most effective plant compounds which had a better binding affinity towards the target receptor protein. These compounds areforsythoside A, rutin, ginkgolide C, icariside II, and nolinospiroside E. The top-ranked compound, based on docking score, was nolinospiroside, a glycoside found in Ophiopogon japonicas that has antioxidant properties. Protein-ligand interaction analysis discerned that nolinospiroside formed a strong bond between ARG 349 of the protein receptor and the carboxylate group of the ligand, forming a stable complex. Hence, nolinospiroside could be deployed as a lead compound against SARS-CoV-2 infection that can be further investigated for its potential benefits in curbing the viral infection.

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Sharma, Arun Dev, and Inderjeet Kaur. "Targeting H3N2 Influenza Virus RNA-dependent RNA Polymerase by Using Bioactives from Essential Oils from Eucalyptus polybrachtea, Cymbopogon citratus and Cymbopogon khasianus." Biology, Medicine, & Natural Product Chemistry 12, no. 2 (September 15, 2023): 515–24. http://dx.doi.org/10.14421/biomedich.2023.122.515-524.

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A dramatic surge of H3N2 influenza virus is of grave concern worldwide and particularly in India. H3N2 cause acute respiratory infection, however, a few drugs are available for its mitigation. Subsequently, researchers have been involved in efforts to discover novel antiviral mechanisms that can lay the basis for new anti-influenza drugs. Influenza virus RNA-dependent RNA polymerase (RdRP) is a multi-functional hetero-trimer, implicated in the production of viral mRNA, hence plays a major role in viral infectivity thus directly associated with survival of the virus. RdRP have been cited as anappropriate target for therapeutic drug design. In the present study molecular docking was designed to estimate the effect of potent bioactive moleculesfrom essential oils from Eucalyptus polybrachtea (eucalyptus oil, EO), Cymbopogon citratus (lemon grass essential oil, LEO) and Cymbopogon khasianus (palmarosa essential oil, PEO) against RdRP protein. GC-FID (gas chromatography with flame-ionization detection) based composition profile, and in-silico docking study was conducted by using CB-dock 2 analysis followed by 2D interactions. GC-FID revealed eucalyptol, geranial and geraniolas major phytocompounds in EO, LEO and PEO respectively. The docking score indicated effective binding of ligands to RdRP. Interactions results indicated that, RdRP/ligand complexes form hydrogen, van der waals forces, pi-alkyl, alkyl, and pi-Sigma interactions. Based on above findings of aroma profile and docking, therefore, it was recommended that essential oils from above mentioned aromatic cropsmay represent potential herbal treatment to mitigate H3N2 infections.

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Mustafa, Ghulam, Hafiza Salaha Mahrosh, Mahwish Salman, Muhammad Ali, Rawaba Arif, Sibtain Ahmed, and Hossam Ebaid. "In Silico Analysis of Honey Bee Peptides as Potential Inhibitors of Capripoxvirus DNA-Directed RNA Polymerase." Animals 13, no. 14 (July 12, 2023): 2281. http://dx.doi.org/10.3390/ani13142281.

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The genus Capripoxvirus belongs to the Poxviridae family. The sheeppox, goatpox, and lumpy skin disease viruses are three species of this genus with 96% identity in their genomes. These are financially devastating viral infections among cattle, which cause a reduction in animal products and lead to a loss in livestock industries. In the current study, the phylogenetic analysis was carried out to reveal the evolutionary relationships of Capripoxvirus species (i.e., sheeppox virus (SPPV), goatpox virus (GTPV), and lumpy skin disease virus (LSDV)) with other viruses from the Poxviridae family with >96% query coverage to find the similarity index among all members. The three viruses (i.e., SPPV, GTPV, and LSDV) joined the clade of Capripoxvirus of the Poxviridae family in the phylogenetic tree and exhibited close evolutionary relationships. The multiple sequence alignment using ClustalOmega revealed significant variations in the protein sequences of the DNA-dependent RNA polymerase of SPPV, GTPV, and LSDV. The three-dimensional structures of five selected bee peptides and DNA-directed RNA polymerase of SPPV, GTPV, and LSDV were predicted using trRosetta and I-TASSER and used for molecular docking and simulation studies. The protein–protein docking was carried out using HADDOCK server to explore the antiviral activity of peptides as honey bee proteins against SPPV, GTPV, and LSDV. In total, five peptides were docked to DNA-directed RNA polymerase of these viruses. The peptides mellitin and secapin-1 displayed the lowest binding scores (−106.9 +/− 7.2 kcal/mol and −101.4 +/− 11.3 kcal/mol, respectively) and the best patterns with stable complexes. The molecular dynamics simulation indicated that the complex of protein DNA-dependent RNA polymerase and the peptide melittin stayed firmly connected and the peptide binding to the receptor protein was stable. The findings of this study provide the evidence of bee peptides as potent antimicrobial agents against sheeppox, goatpox, and lumpy skin disease viruses with no complexity.

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Dawood, Ali A. "Influence of SARS-CoV-2 variants’ spike glycoprotein and RNA-dependent RNA polymerase (nsp12) mutations on remdesivir docking residues." Medical Immunology (Russia) 24, no. 3 (July 13, 2022): 617–28. http://dx.doi.org/10.15789/1563-0625-ios-2486.

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Rapid emergence and evolution of novel SARS-CoV-2 variants has raised concerns about their potential impact on efficiency of currently available vaccines. Among the most significant target mutations in the virus are those of the spike glycoprotein. Remdesivir, which inhibits the polymerase activity of the RNAdependent RNA polymerase RdRp, is the only medicine approved by FDA for treatment of COVID-19 (nsp12). The docking features of the flexible ligand (remdesivir) with the stiff receptors was investigated in the present study (S protein and RdRp interaction). In various studies, the spike glycoprotein and RdRp mutations were found to have a significant influence upon viral behaviour and, as a result, affect human health. The docking position of remdesivir with the S and RdRp proteins was shown to be unaffected by mutations in the missing loops. The remdesivir can only bind the B and C chains of S protein. Some mutations can be transferred between variations, without changing the type of amino acid, such as K417N, L452R, N501Y, D614G, T716I, and S982A.

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Bui, Thanh Tung, Bao Kim Nguyen, Minh Ngoc Le, The Toan Nguyen, and The Hai Pham. "In silico screening of drug inhibitors of SARS-CoV-2RNA-dependent RNA polymerase target." Ministry of Science and Technology, Vietnam 63, no. 4 (December 15, 2021): 47–54. http://dx.doi.org/10.31276/vjste.63(4).47-54.

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Objectives: the COVID-19 pandemic triggering acute respiratory syndrome has become a major global health concern. After one year into this pandemic, special therapies for COVID-19 remain an unprecedented challenge to mankind and finding drugs to treat this disease is extremely urgent. The SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) enzyme that regulates viral replication has been examined as a potential therapeutic target for the inhibition of SARS-CoV-2 infection. In this study, the authors evaluated the ability of RNA-dependent RNA polymerase drug inhibitors by using an in silico molecular docking model. Methods: the 3D structure of RdRp enzyme (PDB ID:6M71, resolution of 2.90 Å) was derived from the Protein Data Bank RCSB. The ligand structures were collected from DrugBank for the RdRp target. Molecular docking was done by AutoDock Vina software. Lipinski’s rule of five is used to compare compounds with drug-like and non-drug-like properties. Pharmacokinetic parameters of potential compounds were evaluated using the pkCSM tool. Results: based on the DrugBank database, we collected 192 antiviral molecules and compared them to remdesivir, which has inhibitory activity with this protein target. Results showed that 26 out of 192 compounds have a higher ability to inhibit the SARS-CoV-2 RdRp enzyme than remdesivir. Next, 6 drugs were selected by visually inspecting the docking results with focus on the main interaction between crucial residues at the binding site of the SARS-CoV-2 RdRp enzyme. For the visual inspection, the existence of polar interactions with ASP760 and ASP761 were utilised as the preference criterion. Finally, Lipinski’s rule of 5 criteria and absorption, distribution, metabolism, excretion and toxicity (ADMET) profile analysis suggested five drugs that have good pharmacokinetic properties. Conclusions: these drugs were dihydroergotamine, sofosbuvir, nilotinib, tipranavir, and darunavir and may be used as anti-SARS-CoV-2 agents.

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Yamkela, Mthembu, Zingisa Sitobo, and Xolani H. Makhoba. "In Silico Analysis of SARS-CoV-2 Non-Structural Proteins Reveals an Interaction with the Host’s Heat Shock Proteins That May Contribute to Viral Replications and Development." Current Issues in Molecular Biology 45, no. 12 (December 18, 2023): 10225–47. http://dx.doi.org/10.3390/cimb45120638.

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The non-structural protein 2 (NSP2) is an RNA-binding protein involved in coronavirus genome replication, and it often decreases human immune response to promote viral invasion and development. It is believed that the NSP2 associates itself with polyamines and heat shock proteins inside the host cell to proceed with viral development. This study aimed to investigate how the SARS-CoV-2 virus’ key non-structural proteins (NSP2) utilize polyamines and heat shock proteins using a molecular docking approach and molecular dynamics (MD). ClusPro and HADDOCK servers were used for the docking and Discovery Studio, chimera, and PyMOL were used for analysis. Docking of the heat shock proteins 40 (HSP40), 70 (HSP70), and 90 (HSP90) with SARS-CoV-2 NSP2 resulted in 32, 28, and 19 interactions, respectively. Molecular dynamics revealed Arg458, Asn508, Met297, Arg301, and Trp417 as active residues, and pharmacophore modeling indicated ZINC395648, ZINC01150525, and ZINC85324008 from the zinc database as possible inhibitors for this NSP2.

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Wang Erickson, Anna F., Padraig Deighan, Shanshan Chen, Kelsey Barrasso, Cinthia P. Garcia, Santiago Martínez‐Lumbreras, Caterina Alfano, et al. "A novel RNA polymerase‐binding protein that interacts with a sigma‐factor docking site." Molecular Microbiology 105, no. 4 (June 19, 2017): 652–62. http://dx.doi.org/10.1111/mmi.13724.

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Pérez-Cano, Laura, Brian Jiménez-García, and Juan Fernández-Recio. "A protein-RNA docking benchmark (II): Extended set from experimental and homology modeling data." Proteins: Structure, Function, and Bioinformatics 80, no. 7 (May 8, 2012): 1872–82. http://dx.doi.org/10.1002/prot.24075.

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Lee, Gwangho, Gun Hyuk Jang, Ho Young Kang, and Giltae Song. "Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach." PLOS ONE 16, no. 6 (June 25, 2021): e0253760. http://dx.doi.org/10.1371/journal.pone.0253760.

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Oligonucleotide-based aptamers, which have a three-dimensional structure with a single-stranded fragment, feature various characteristics with respect to size, toxicity, and permeability. Accordingly, aptamers are advantageous in terms of diagnosis and treatment and are materials that can be produced through relatively simple experiments. Systematic evolution of ligands by exponential enrichment (SELEX) is one of the most widely used experimental methods for generating aptamers; however, it is highly expensive and time-consuming. To reduce the related costs, recent studies have used in silico approaches, such as aptamer-protein interaction (API) classifiers that use sequence patterns to determine the binding affinity between RNA aptamers and proteins. Some of these methods generate candidate RNA aptamer sequences that bind to a target protein, but they are limited to producing candidates of a specific size. In this study, we present a machine learning approach for selecting candidate sequences of various sizes that have a high binding affinity for a specific sequence of a target protein. We applied the Monte Carlo tree search (MCTS) algorithm for generating the candidate sequences using a score function based on an API classifier. The tree structure that we designed with MCTS enables nucleotide sequence sampling, and the obtained sequences are potential aptamer candidates. We performed a quality assessment using the scores of docking simulations. Our validation datasets revealed that our model showed similar or better docking scores in ZDOCK docking simulations than the known aptamers. We expect that our method, which is size-independent and easy to use, can provide insights into searching for an appropriate aptamer sequence for a target protein during the simulation step of SELEX.

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Ren, Yixin, Sihui Long, and Shuang Cao. "Molecular Docking and Virtual Screening of an Influenza Virus Inhibitor That Disrupts Protein–Protein Interactions." Viruses 13, no. 11 (November 5, 2021): 2229. http://dx.doi.org/10.3390/v13112229.

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Influenza is an acute respiratory infection caused by the influenza virus, but few drugs are available for its treatment. Consequently, researchers have been engaged in efforts to discover new antiviral mechanisms that can lay the foundation for novel anti-influenza drugs. The viral RNA-dependent RNA polymerase (RdRp) is an enzyme that plays an indispensable role in the viral infection process, which is directly linked to the survival of the virus. Methods of inhibiting PB1–PB2 (basic polymerase 1–basic polymerase 2) interactions, which are a key part of RdRp enzyme activity, are integral in the design of novel antiviral drugs, a specific PB1–PB2 interactions inhibitor has not been reported. We have screened Enamine’s database and conducted a parallel screening of multiple docking schemes, followed by simulations of molecular dynamics to determine the structure of a stable ligand—PB1 complex. We also calculated the free energy of binding between the screened compounds and PB1 protein. Ultimately, we screened and identified a potential PB1–PB2 inhibitor using the ADMET prediction model.

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Praveen, Rajkumar. "Insights from the molecular docking aided interaction analysis of HfQ with small RNAs." Bioinformation 18, no. 4 (April 30, 2022): 425–31. http://dx.doi.org/10.6026/97320630018425.

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Hfq, RNA binding protein, is widely found in most of the prokaryotes. It plays a key role in gene regulation by binding with small RNA and facilitates mRNA pairing there by suppress or boost translation according to RNA structures. Interaction between sRNAs and HfQ in Salmonella SL1344 were screened using Co-Immuno Precipitation (HfQ-CoIP) studies earlier. We have formulated an In silico approach, to model the 3D structures of 155 sRNA and studied their interactions with HfQ proteins. We have reported the key interacting PHE42, LEU7, VAL27, PHE39 and PRO21 residues of HfQ binds with many small RNAs. Further mutation of PHE42 in to ALA42 in HfQ leads to loss of sRNA binding efficiency. We have differentiated the interactions in to HfQ binding and non-binding sRNAs, based on Atomic Contact Energy and area. This methodology may be applied generically for functional grouping of small RNAs in any organism.

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Sharp, Kumar. "Alternatives to Remdesivir: Drug repurposing for inhibition of SARS-CoV2 RNA dependent RNA polymerase." Journal of Pharmacological and Pharmaceutical Research 1, no. 1 (2024): 32. http://dx.doi.org/10.5455/jppr.20240402024133.

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Background & Objectives: Even after more than a year of the beginning of COVID-19 pandemic, a specific treatment for the disease has not been discovered. Vaccination programmes are being rolled out as the fastest pace possible but achievement of herd immunity will take time. Many drugs like favipiravir, remdesivir and tocilizumab are being used for the treatment of this disease but reports published by the World Health Organization and the New England Journal of Medicine shows that they do not produce any significant clinical results. In this study, by molecular docking a large set of drugs has been used to replace remdesivir in RdRp protein so that they can produce the same action and therefore provide suitable alternatives for clinical trials and emergency use. Materials & Methods: The receptor i.e. the RdRp protein was first processed in Drug Discovery studio by removal of heterogenous atoms, water molecules, prime and template RNA strands and remdesivir. This gave us the clean RdRp molecule. Using PyRx docking software, it was converted automatically into an Autodock macromolecule. Around 750 drug molecules were loaded into PyRx using Open Babel plugin which were then converted into Autodock ligands by minimization of their energies, addition of hydrogen atoms and addition of partial charges. Using Autodock Vina ligands were docked into the restricted search space containing the target amino acids. Results: The drugs identified in the study are saquinavir, cefoperazone, gliquidone, nelfinavir, 5-methyltetrahyrofolate among various others. Conclusion: The drugs obtained above have also been identified in other in-silico studies as potential inhibitors of SARS-CoV2 by different mechanisms. They must be tried in-vitro because of the limitations of in-silico docking.

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Abdelaal Ahmed Mahmoud M. Alkhatip, Ahmed, Michail Georgakis, Lucio R. Montero Valenzuela, Mohamed Hamza, Ehab Farag, Jaqui Hodgkinson, Hisham Hosny, et al. "Metal-Bound Methisazone; Novel Drugs Targeting Prophylaxis and Treatment of SARS-CoV-2, a Molecular Docking Study." International Journal of Molecular Sciences 22, no. 6 (March 15, 2021): 2977. http://dx.doi.org/10.3390/ijms22062977.

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SARS-CoV-2 currently lacks effective first-line drug treatment. We present promising data from in silico docking studies of new Methisazone compounds (modified with calcium, Ca; iron, Fe; magnesium, Mg; manganese, Mn; or zinc, Zn) designed to bind more strongly to key proteins involved in replication of SARS-CoV-2. In this in silico molecular docking study, we investigated the inhibiting role of Methisazone and the modified drugs against SARS-CoV-2 proteins: ribonucleic acid (RNA)-dependent RNA polymerase (RdRp), spike protein, papain-like protease (PlPr), and main protease (MPro). We found that the highest binding interactions were found with the spike protein (6VYB), with the highest overall binding being observed with Mn-bound Methisazone at −8.3 kcal/mol, followed by Zn and Ca at −8.0 kcal/mol, and Fe and Mg at −7.9 kcal/mol. We also found that the metal-modified Methisazone had higher affinity for PlPr and MPro. In addition, we identified multiple binding pockets that could be singly or multiply occupied on all proteins tested. The best binding energy was with Mn–Methisazone versus spike protein, and the largest cumulative increases in binding energies were found with PlPr. We suggest that further studies are warranted to identify whether these compounds may be effective for treatment and/or prophylaxis.

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Ivan, Jeremias, Rizky Nurdiansyah, and Arli Aditya Parikesit. "Computational modeling of AGO-mediated molecular inhibition of ARF6 by miR-145." Indonesian Journal of Biotechnology 25, no. 2 (December 2, 2020): 102. http://dx.doi.org/10.22146/ijbiotech.55631.

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Inhibition of ADP-ribosylation factor 6 messenger RNA (ARF6 mRNA) by microRNA-145 (miR-145), mediated by Argonaute (AGO) protein, has been found to play essential roles in several types of cancer and cellular processes. This study aimed to model the molecular interaction between miR-145 and ARF6 mRNA with AGO protein. The sequences of miR-145 and the 3’ untranslated region (UTR) of ARF6 mRNA were retrieved from miRTarBase, followed by miRNA target-site and structure predictions were done using RNAhybrid, RNAfold, and simRNAweb, respectively. The interaction between the miRNA-mRNA duplex and AGO was further assessed via molecular docking, interaction analysis, and dynamics, using PatchDock Server, PLIP, and VMD/NAMD, respectively. The models between miR-145, predicted target site of ARF6 mRNA, and AGO protein returned stable thermodynamic variables with negative free energy. Specifically, the RNA duplex had an energy of -19.80 kcal/mol, while the docking had -84.58 atomic contact energy supported by 70 hydrogen bonds and 14 hydrophobic interactions. However, the stability of the RMSD plot was still unclear due to limited computational resources. Nevertheless, these results computationally confirm favorable interaction of the three molecules, which can be utilized for further transcriptomics-based drugs or treatments.

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Rehman, Muhammad Fayyaz ur, Shahzaib Akhter, Aima Iram Batool, Zeliha Selamoglu, Mustafa Sevindik, Rida Eman, Muhammad Mustaqeem, et al. "Effectiveness of Natural Antioxidants against SARS-CoV-2? Insights from the In-Silico World." Antibiotics 10, no. 8 (August 20, 2021): 1011. http://dx.doi.org/10.3390/antibiotics10081011.

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The SARS CoV-2 pandemic has affected millions of people around the globe. Despite many efforts to find some effective medicines against SARS CoV-2, no established therapeutics are available yet. The use of phytochemicals as antiviral agents provides hope against the proliferation of SARS-CoV-2. Several natural compounds were analyzed by virtual screening against six SARS CoV-2 protein targets using molecular docking simulations in the present study. More than a hundred plant-derived secondary metabolites have been docked, including alkaloids, flavonoids, coumarins, and steroids. SARS CoV-2 protein targets include Main protease (MPro), Papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), Spike glycoprotein (S), Helicase (Nsp13), and E-Channel protein. Phytochemicals were evaluated by molecular docking, and MD simulations were performed using the YASARA structure using a modified genetic algorithm and AMBER03 force field. Binding energies and dissociation constants allowed the identification of potentially active compounds. Ligand-protein interactions provide an insight into the mechanism and potential of identified compounds. Glycyrrhizin and its metabolite 18-β-glycyrrhetinic acid have shown a strong binding affinity for MPro, helicase, RdRp, spike, and E-channel proteins, while a flavonoid Baicalin also strongly binds against PLpro and RdRp. The use of identified phytochemicals may help to speed up the drug development and provide natural protection against SARS-CoV-2.

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Santiago-Frangos, Andrew, Kathrin S. Fröhlich, Jeliazko R. Jeliazkov, Ewelina M. Małecka, Giada Marino, Jeffrey J. Gray, Ben F. Luisi, Sarah A. Woodson, and Steven W. Hardwick. "Caulobacter crescentus Hfq structure reveals a conserved mechanism of RNA annealing regulation." Proceedings of the National Academy of Sciences 116, no. 22 (May 10, 2019): 10978–87. http://dx.doi.org/10.1073/pnas.1814428116.

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We have solved the X-ray crystal structure of the RNA chaperone protein Hfq from the alpha-proteobacterium Caulobacter crescentus to 2.15-Å resolution, resolving the conserved core of the protein and the entire C-terminal domain (CTD). The structure reveals that the CTD of neighboring hexamers pack in crystal contacts, and that the acidic residues at the C-terminal tip of the protein interact with positive residues on the rim of Hfq, as has been recently proposed for a mechanism of modulating RNA binding. De novo computational models predict a similar docking of the acidic tip residues against the core of Hfq. We also show that C. crescentus Hfq has sRNA binding and RNA annealing activities and is capable of facilitating the annealing of certain Escherichia coli sRNA:mRNA pairs in vivo. Finally, we describe how the Hfq CTD and its acidic tip residues provide a mechanism to modulate annealing activity and substrate specificity in various bacteria.

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Prabahar, Archana, Subashini Swaminathan, Arul Loganathan, and Ramalingam Jegadeesan. "Identification of Novel Inhibitors for Tobacco Mosaic Virus Infection in Solanaceae Plants." Advances in Bioinformatics 2015 (October 18, 2015): 1–9. http://dx.doi.org/10.1155/2015/198214.

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Tobacco mosaic virus (TMV) infects several crops of economic importance (e.g., tomato) and remains as one of the major concerns to the farmers. TMV enters the host cell and produces the capping enzyme RNA polymerase. The viral genome replicates further to produce multiple mRNAs which encodes several proteins, including the coat protein and an RNA-dependent RNA polymerase (RdRp), as well as the movement protein. TMV replicase domain was chosen for the virtual screening studies against small molecules derived from ligand databases such as PubChem and ChemBank. Catalytic sites of the RdRp domain were identified and subjected to docking analysis with screened ligands derived from virtual screening LigandFit. Small molecules that interact with the target molecule at the catalytic domain region amino acids, GDD, were chosen as the best inhibitors for controlling the TMV replicase activity.

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Sari, Dewi Ratih Tirto, Heny Yusuf, Laily Sifaiyah, Nur Dina Camelia, and Yohanes Bare. "Kajian Farmakoinformatika Senyawa Brazilin dan 3-O-Methyl Brazilin Caesalpinia sappan Sebagai Terapi Demam Berdarah Dengue." al-Kimiya 9, no. 1 (July 1, 2022): 19–25. http://dx.doi.org/10.15575/ak.v9i1.17613.

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Demam berdarah Dengue (DBD) merupakan penyakit tropis yang diakibatkan oleh gigitan nyamuk yang terinfeksi oleh virus DENV. Beberapa tanaman herbal dapat digunakan untuk mengatasi demam berdarah baik upaya preventif maupun kuratif. Kayu secang merupakan salah satu tanaman herbal kayu yang memiliki berbagai aktivitas biologis, utamanya sebagai immunomodulator dan antivirus. Penelitian ini bertujuan untuk mengidentifikasi aktivitas brazilin dan 3-O-methyl brazilin sebagai obat terapi demam berdarah melalui kajian komputasi. Pendekatan molecular docking digunakan dalam studi penelitian ini. Senyawa brazilin dan 3-O-methyl brazilin diunduh dari database PubChem dan diinteraksikan dengan protein non- structural-5 (NS-5) yang didapatkan dari database PDB. Pemodelan docking dilakukan dengan Molegro virtual Docker versi 5.0 dan dianalisis dengan PyMol 2.2 dan Discovery studio versi 21.1.1. Hasil interaksi menunjukkan bahwa brazilin dan 3-O-methyl brazilin berikatan dengan protein NS-5 di sisi aktif guanosine triphosphate dan daerah RNA dependent RNA polymerase (RdRP). Pengikatan kedua senyawa aktif ini menyebabkan tidak terjadinya replikasi virus DENV pada sel inang dan berpotensi sebagai penghambat infeksi DENV. Berdasarkan analisis in silico, disimpulkan bahwa brazilin dan 3-O-methyl brazilin berpotensi sebagai agen terapi demam berdarah, studi in vitro perlu dilakukan untuk pembuktian lebih lanjut.

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Alhossary, Amr, Yaw Awuni, Chee Keong Kwoh, and Yuguang Mu. "Proposing drug fragments for dengue virus NS5 protein." Journal of Bioinformatics and Computational Biology 16, no. 03 (June 2018): 1840017. http://dx.doi.org/10.1142/s0219720018400176.

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Dengue fever is a febrile illness caused by Dengue Virus, which belongs to the Flaviviridae family. Among its proteome, the nonstructural protein 5 (NS5) is the biggest and most conserved. It has a primer-independent RNA-dependent RNA polymerase (RdRp) domain at its C-Terminus. Zou et al. studied the biological relevance of the two conserved cavities (named A and B) within the NS5 proteins of dengue virus (DENV) and West Nile Virus (WNV) using mutagenesis and revertant analysis and found four mutations located at cavity B having effects on viral replication. They recommended Cavity B, but not Cavity A as a potential target for drugs against flavivirus RdRp. In this study, we virtually screened the MayBridge drug fragments dataset for potential small molecule binders of cavity B using both AutoDock Vina, the standard docking tool, and QuickVina 2, our previously developed tool. We selected 16 fragments that appeared in the top 100 docking results of each of the representative structures of NS5. Visual inspection suggests that they have reasonable binding poses. The 16 predicted fragments are plausible drug candidates and should be considered for further validation, optimization, and linking to come up with a suitable inhibitor of dengue virus.

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Journal articles on the topic 'Protein-RNA docking'

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