The Experts below are selected from a list of 12459 Experts worldwide ranked by ideXlab platform
Didier Rognan - One of the best experts on this subject based on the ideXlab platform.
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Ranking docking poses by graph matching of protein–ligand Interactions: lessons learned from the D3R Grand Challenge 2
Journal of Computer-Aided Molecular Design, 2018Co-Authors: Priscila Silva Figueiredo Celestino Gomes, Franck Silva, Guillaume Bret, Didier RognanAbstract:A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein–ligand Interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing Interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM–HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.
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Predicting Ligand Binding Modes from Neural Networks Trained on Protein–Ligand Interaction Fingerprints
Journal of Chemical Information and Modeling, 2013Co-Authors: Vladimir I. Chupakhin, Gilles Marcou, Igor I. Baskin, Alexandre Varnek, Didier RognanAbstract:We herewith present a novel approach to predict protein–ligand binding modes from the single two-dimensional structure of the ligand. Known protein–ligand X-ray structures were converted into binary bit strings encoding protein–ligand Interactions. An artificial neural network was then set up to first learn and then predict protein–ligand Interaction fingerprints from simple ligand descriptors. Specific models were constructed for three targets (CDK2, p38-α, HSP90-α) and 146 ligands for which protein–ligand X-ray structures are available. These models were able to predict protein–ligand Interaction fingerprints and to discriminate important features from minor Interactions. Predicted Interaction fingerprints were successfully used as descriptors to discriminate true ligands from decoys by virtual screening. In some but not all cases, the predicted Interaction fingerprints furthermore enable to efficiently rerank cross-docking poses and prioritize the best possible docking solutions.
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Structure-Based Discovery of Allosteric Modulators of Two Related Class B G-Protein-Coupled Receptors
ChemMedChem, 2011Co-Authors: Chris De Graaf, Chantal Rein, Fabrizio Giordanetto, David Piwnica, Didier RognanAbstract:Despite the availability of X-ray crystal structure data for several members of the G-protein-coupled receptor (GPCR) superfamily, structure-based discovery of GPCR ligands has been exclusively restricted to classA (rhodopsin-like) receptors. Herein we report the identification, by a docking-based virtual screening approach, of noncompetitive ligands for two related classB (secretin-like) GPCRs: the glucagon receptor (GLR) and the glucagon-like peptide1 receptor (GLP-1R). Starting from a knowledge-based three-dimensional model of the GLR, a database of 1.9 million commercially available drug-like compounds was screened for chemical similarity to existing GLR noncompetitive antagonists and docked to the transmembrane cavity of the GLR; 23 compounds were then selected based on Protein-Ligand Interaction fingerprints, and were then purchased and evaluated for invitro binding to GLR and modulation of glucagon-induced cAMP release. Two of the 23 compounds inhibited the effect of glucagon in a dose-dependent manner, with one inhibitor exhibiting the same potency as L-168049, a reference noncompetitive GLR antagonist, in a whole-cell-based functional assay. Interestingly, one virtual hit that was inactive at the GLR was shown to bind to GLP-1R and potentiate the response to the endogenous GLP-1 ligand. Virtual reality: Although crystallographic structure data and related information have been reported for classA GPCRs, herein we report the first use of structure-based virtual screening to identify new allosteric modulators of classB GPCRs. Despite the modest activities of the identified compounds, this study provides a novel insilico approach for the discovery of future classB GPCR modulators. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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optimizing fragment and scaffold docking by use of molecular Interaction fingerprints
Journal of Chemical Information and Modeling, 2007Co-Authors: G Marcou, Didier RognanAbstract:Protein−ligand Interaction fingerprints have been used to postprocess docking poses of three ligand data sets: a set of 40 low-molecular-weight compounds from the Protein Data Bank, a collection of 40 scaffolds from pharmaceutically relevant protein ligands, and a database of 19 scaffolds extracted from true cdk2 inhibitors seeded in 2230 scaffold decoys. Four popular docking tools (FlexX, Glide, Gold, and Surflex) were used to generate poses for ligands of the three data sets. In all cases, scoring by the similarity of Interaction fingerprints to a given reference was statistically superior to conventional scoring functions in posing low-molecular-weight fragments, predicting protein-bound scaffold coordinates according to the known binding mode of related ligands, and screening a scaffold library to enrich a hit list in true cdk2-targeted scaffolds.
Yuhwa Lo - One of the best experts on this subject based on the ideXlab platform.
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detecting protein ligand Interaction from integrated transient induced molecular electronic signal i times
Analytical Chemistry, 2020Co-Authors: Pingwei Chen, Chiyang Tseng, Bo Bi, Yuhwa LoAbstract:Quantitative information about protein–ligand Interactions is central to drug discovery. To obtain the quintessential reaction dissociation constant, ideally measurements of reactions should be per...
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Transient Induced Molecular Electronic Spectroscopy (TIMES) for study of Protein-Ligand Interactions.
Scientific Reports, 2016Co-Authors: Tiantian Zhang, Ti-hsuan Ku, Ramkumar Subramanian, Iftikhar Ahmad Niaz, Derrick Chang, Jian-jang Huang, Yuhwa LoAbstract:We present a method, Transient Induced Molecular Electronic Spectroscopy (TIMES), to detect Protein-Ligand Interactions without any protein engineering or chemical modification. We developed a physics model for the TIMES signal and mathematically formulated the problem to attain physical insight of Protein-Ligand Interactions without any disturbances by molecular probes, fluorescent labels, or immobilization of molecules. To demonstrate the functionality of this method, we have used the TIMES signals to find the dissociation constants for the affinity of reactions, the shear-stress dependent adsorption time of molecules on surface, and other interesting features of Protein-Ligand Interaction in native conditions. As a unique tool, TIMES offers a simple and effective method to investigate fundamental protein chemistry and drug discoveries.
Calvin Yuchian Chen - One of the best experts on this subject based on the ideXlab platform.
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lead screening for chronic obstructive pulmonary disease of ikk2 inhibited by traditional chinese medicine
Evidence-based Complementary and Alternative Medicine, 2014Co-Authors: Yung An Tsou, Hungjin Huang, Calvin Yuchian ChenAbstract:Chronic obstructive pulmonary disease (COPD) is a chronic obstructive lung disease and is frequently found in well-developed countries due to the issue of aging populations. Not all forms of medical treatment are unable to return a patient's limited pulmonary function back to normal and eventually they could require a lung transplant. At this time, COPD is the leading cause of death in the world. Studies surveying I-kappa-B-kinase beta (IKK2) are very relevant to the occurrence and deterioration of the condition COPD. The sinapic acid-4-O-sulfate, kaempferol, and alpha-terpineol were found to be IKK2 inhibitors and helped prevent COPD occurrence and worsening according to a screening of the traditional Chinese medicine (TCM) database. The Protein-Ligand Interaction of these three compounds with regard to IKK2 was also done by molecular dynamics. The docking poses, hydrogen bond variation, and hydrophobic Interactions found Asp103 and Lys106 are crucial to IKK2 binding areas for IKK2 inhibition. Finally, we found the three compounds that have an equally strong effect in terms of IKK2 binding proven by the TCM database and perhaps these may be an alternative treatment for COPD in the future.
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stroke prevention by traditional chinese medicine a genetic algorithm support vector machine and molecular dynamics approach
Soft Matter, 2011Co-Authors: Kuanchung Chen, Calvin Yuchian ChenAbstract:Phosphodiesterase 4D (PDE4D) has been identified be a promising target which associate with stroke, which is one of the top 3 leading of death and main leading cause of adult disability in US. In this study, we applied virtual screening on the world's largest traditional Chinese medicine (TCM) database (http://tcm.cmu.edu.tw;1 C. Y. C. Chen, PLoS One, 2011, 6, e15939) for natural compounds that inhibit PDE4D functions. Molecular docking and dynamics simulation were employed to investigate the protein–ligand Interactions of compounds with top two dock scores. During the simulation, the divalent metal cations in PDE4D formed stable hydrogen bonds and electrostatic Interactions between ligand and binding site residues. Furthermore, the two top TCM candidates, 2-O-caffeoyl tartaric acid and mumefural, formed additional steady hydrogen bond with binding site residue and active site residue respectively. The additional hydrogen bonds further stabilize Protein-Ligand Interaction at the PDE4D binding site. To predict the bioactivity of the top TCM candidates, we built two prediction models using multiple linear regression (MLR) and support vector machine (SVM). The predicted pIC50 values suggest that 2-O-caffeoyl tartaric acid and mumefural are potential PDE4D inhibitors.
Divya Bhanu - One of the best experts on this subject based on the ideXlab platform.
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani Alluri, Samriddhi GuptaAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. Docking profile with 9 different conformations of the ligand with the protein model using Autodock Vina showed an affinity of -7.1 Kcal/mol. This region was conserved in 831 genomes of SARS-CoV-2. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. Docking profile with 9 different conformation of the ligand with the protein model using Autodock Vina showed an affinity of -7.9 Kcal/mol. This region was conserved in 831 genomes of SARS-CoV-2. It is possible that these ligands can be antivirals of SARS-CoV-2. </p><p></p><p></p>
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani AlluriAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. The regions studied was conserved in more than 90 genomes of SARS-CoV-2. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Anajani Alluri, Divya BhanuAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Whole Genome Sequences Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Anajani Alluri, Divya BhanuAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Analysis of Whole Genome Sequences and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein of the Novel Coronavirus COVID-19 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Ant
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani AlluriAbstract:The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the Novel COVID-19 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the Novel COVID-19 whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible vaccine development. Our results showed that the tertiary structure of the polyprotein isolate COVID-19 _HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. Our results indicate that a part of the viral genome (residues 254 to 13480 in Frame 2 with 4409 amino acids) of the Novel COVID-19 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the Novel COVID-19.
Arun Shanker - One of the best experts on this subject based on the ideXlab platform.
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani Alluri, Samriddhi GuptaAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. Docking profile with 9 different conformations of the ligand with the protein model using Autodock Vina showed an affinity of -7.1 Kcal/mol. This region was conserved in 831 genomes of SARS-CoV-2. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. Docking profile with 9 different conformation of the ligand with the protein model using Autodock Vina showed an affinity of -7.9 Kcal/mol. This region was conserved in 831 genomes of SARS-CoV-2. It is possible that these ligands can be antivirals of SARS-CoV-2. </p><p></p><p></p>
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani AlluriAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. The regions studied was conserved in more than 90 genomes of SARS-CoV-2. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Whole Genome Sequence Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Anajani Alluri, Divya BhanuAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Whole Genome Sequences Analysis and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein 3 of the SARS-CoV-2 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Antiviral Properties
2020Co-Authors: Arun Shanker, Anajani Alluri, Divya BhanuAbstract:<p></p><p>The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the SARS-CoV-2 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and explore the possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the <a>SARS-CoV-2 </a>whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible binding with ligands that exhibit antiviral properties. Our results showed that the tertiary structure of the polyprotein isolate SARS-CoV-2_HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. <a>Our results indicate that a part of the viral genome </a><a>(residues 3268 -3573 in Frame 2 with 306 amino acids) of the SARS-CoV-2 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) </a>when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome (residues 1568-1882 in Frame 2 with 315 amino acids) when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the SARS-CoV-2.</p><p></p><p></p>
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Analysis of Whole Genome Sequences and Homology Modelling of a 3C Like Peptidase and a Non-Structural Protein of the Novel Coronavirus COVID-19 Shows Protein Ligand Interaction with an Aza-Peptide and a Noncovalent Lead Inhibitor with Possible Ant
2020Co-Authors: Arun Shanker, Divya Bhanu, Anajani AlluriAbstract:The family of viruses belonging to Coronaviridae mainly consist of virulent pathogens that have a zoonotic property, Severe Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) of this family have emerged before and now the Novel COVID-19 has emerged in China. Characterization of spike glycoproteins, polyproteins and other viral proteins from viruses are important for vaccine development. Homology modelling of these proteins with known templates offers the opportunity to discover ligand binding sites and possible antiviral properties of these protein ligand complexes. Any information emerging from these protein models can be used for vaccine development. In this study we did a complete bioinformatic analysis, sequence alignment, comparison of multiple sequences and homology modelling of the Novel COVID-19 whole genome sequences, the spike protein and the polyproteins for homology with known proteins, we also analysed receptor binding sites in these models for possible vaccine development. Our results showed that the tertiary structure of the polyprotein isolate COVID-19 _HKU-SZ-001_2020 had 98.94 percent identity with SARS-Coronavirus NSP12 bound to NSP7 and NSP8 co-factors. Our results indicate that a part of the viral genome (residues 254 to 13480 in Frame 2 with 4409 amino acids) of the Novel COVID-19 virus isolate Wuhan-Hu-1 (Genbank Accession Number MN908947.3) when modelled with template 2a5i of the PDB database had 96 percent identity with a 3C like peptidase of SARS-CoV which has ability to bind with Aza-Peptide Epoxide (APE) which is known for irreversible inhibition of SARS-CoV main peptidase. The part of the genome when modelled with template 3e9s of the PDB database had 82 percent identity with a papain-like protease/deubiquitinase which when complexed with ligand GRL0617 acts as inhibitor which can block SARS-CoV replication. It is possible that these viral inhibiters can be used for vaccine development for the Novel COVID-19.
