scholarly journals In Silico Study of Pubchem Compounds for Solanum torvum as Antiviral Agent against SARS-CoV-2

2021 ◽  
Vol 1 (1) ◽  
pp. 235-242
Author(s):  
Subramaniyan Vaithilingam ◽  
Lakshmipathy Vivekanandan ◽  
Moorthy S. Krishna
Keyword(s):  
In Silico ◽  
Active Sites ◽  
Treatment Options ◽  
3D Structure ◽  
Antiviral Agent ◽  
Ligand Docking ◽  
Solanum Torvum ◽  
Ligand Interaction ◽  
Pubchem Database ◽  
Novel Coronavirus

Background: The recent epidemic outbreak of a novel coronavirus called SARS-CoV-2 has caused suffering among many people in the form of respiratory tract infection. Currently, there are no targeted drugs, and effective treatment options remain limited. Objective: In order to rapidly discover new compounds for clinical purposes, in silico drug design and virtual drug screening have been initiated to identify new drug leads that target the main protease of the COVID-19 virus. Mpro is a key CoV enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus. Methods: The present study was done to investigate the PubChem compounds of an ayurvedic herb Solanum torvum as an effective antiviral agent against COVID-19. The PubChem compounds like Torvoside H, Torvoside A, Torvoside E, Torvoside F, Torvonin A, 2,3,4-trimethyltriacontane, Torvanol A Q27134802, 5-hexatriacontanone, Jurubine, Tritriacontan-3-one, Torvanol A, Chlorogenone Spirostane-3,6-dione of Solanum torvum were downloaded from NCBI PubChem database acting as ligands for protein ligand docking. The 3D structure of the viral MPro (PDB ID: 6yb7) was retrieved from the RCSB PDB database. The active sites and binding sites were analyzed, and Docking molecular simulations were realized among a total of 12 ligands against COVID-19. Results: The PubChem compounds from the fruits of Solanum torvum showed good docking score and protein-ligand interaction, indicating that the PubChem compounds can cure the COVID-19 disease and act as an effective antiviral agent. Conclusion: Most of the PubChem compounds in the fruits of Solanum torvum showed better paramagnetic parameters.

scholarly journals Elucidating Binding Sites and Affinities of ERα Agonist and Antagonist to Human Alpha-Fetoprotein by in silico Modeling and Point Mutagenesis

2019 ◽  
Author(s):  
Nurbubu T. Moldogazieva ◽  
Daria S. Ostroverkhova ◽  
Nikolai N. Kuzmich ◽  
Vladimir V. Kadochnikov ◽  
Alexander A. Terentiev ◽  
...  
Keyword(s):  
Binding Sites ◽  
In Silico ◽  
Disulfide Bonds ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Scoring Function ◽  
Alpha Fetoprotein ◽  
Ligand Interaction ◽  
Ligand Interactions

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔGbind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

In Silico Approaches for Novel Drug Discovery Against Coronavirus by Employing the Hybrid Molecular Technique: A Review

2021 ◽  
pp. 1-8
Author(s):  
Noor ul Amin Mohsin ◽  
Muhammad Irfan ◽  
Muhammad Naeem Aamir
Keyword(s):  
In Silico ◽  
Antiviral Agent ◽  
Molecular Technique ◽  
The Novel ◽  
Hybrid Molecules ◽  
The World ◽  
Being There ◽  
Novel Coronavirus ◽  
Novel Drug ◽  
Day By Day

The coronavirus disease (COVID-19) is causing havoc all around the world. The number of active cases and deaths is increasing day by day. The novel coronavirus (CoV) is the causative agent of this disease. For the time being, there is no specific antiviral agent for the cure of COVID-19. A variety of drugs are being repurposed to counteract this disease. Scientists all over the world are striving to get some ideal molecules against this pandemic. Some hybrid molecules have been designed by coupling the privileged scaffolds of known antiviral and antimalarial drugs. This review deals with the hybrid molecules that have been designed and evaluated against the known targets of CoV by in silico techniques.

scholarly journals Elucidating Binding Sites and Affinities of ERα Agonists and Antagonists to Human Alpha-Fetoprotein by In Silico Modeling and Point Mutagenesis

2020 ◽  
Vol 21 (3) ◽  
pp. 893 ◽  
Author(s):  
Nurbubu T. Moldogazieva ◽  
Daria S. Ostroverkhova ◽  
Nikolai N. Kuzmich ◽  
Vladimir V. Kadochnikov ◽  
Alexander A. Terentiev ◽  
...  
Keyword(s):  
Binding Sites ◽  
In Silico ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Alpha Fetoprotein ◽  
Affinity Binding ◽  
Scoring Functions ◽  
Ligand Interaction ◽  
Ligand Interactions

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP–ligand interaction remains obscure. In our study, we constructed a homology-based 3D model of human AFP (HAFP) with the purpose of molecular docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol), and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on the ligand-docked scoring functions, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity binding sites were located (i) in a tunnel formed within HAFP subdomains IB and IIA and (ii) on the opposite side of the molecule in a groove originating from a cavity formed between domains I and III, while (iii) the third low-affinity binding site was found at the bottom of the cavity. Here, 100 ns molecular dynamics (MD) simulation allowed us to study their geometries and showed that HAFP–estrogen interactions were caused by van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP–antiestrogen binding. Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring method exploited for estimation of binding free energies (ΔGbind) showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP–ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues, along with two disulfide bonds (Cys224–Cys270 and Cys269–Cys277), have key roles in both HAFP–estrogen and HAFP–antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein–ligand interactions and anticancer therapy strategies based on ERα-binding ligands.

scholarly journals A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

2020 ◽  
Author(s):  
Christoph Gorgulla ◽  
Krishna PadmanabhaDas ◽  
Kendra E. Leigh ◽  
Marco Cespugli ◽  
Patrick D. Fischer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Active Sites ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
The Face ◽  
Computing Platforms ◽  
Screening Platform ◽  
Novel Coronavirus ◽  
Further Development

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

scholarly journals In silico characterization of the NiRAN domain of RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV2

2020 ◽  
Author(s):  
Abhisek Dwivedy ◽  
Richard Mariadasse ◽  
Mohammed Ahmed ◽  
Deepsikha Kar ◽  
Jeyaraman Jeyakanthan ◽  
...  
Keyword(s):  
Active Site ◽  
In Silico ◽  
3D Structure ◽  
Drug Repurposing ◽  
The Novel ◽  
Lead Compounds ◽  
Nucleotidyl Transferase ◽  
Domain Organisation ◽  
Novel Coronavirus ◽  
In Silico Characterization

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of the RdRp from the novel coronavirus – SARS-CoV2, provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, this study predicts that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds GTP and UTP at its proposed active site. Additionally, using molecular docking this study predicts the binding of five well characterized anti-microbial compounds at the NiRAN domain active site and their drug-likeliness and DFT properties. In line with the current global COVID-19 pandemic urgency, this study provides a new target and potential lead compounds for drug repurposing against SARS-CoV2.

scholarly journals Insilico Identification of Potential Antivirals and Molecular Dynamics Against SARS-CoV2 Main Protease and RBD of Spike Protein

2020 ◽  
Author(s):  
Vijayakumar Rajendran ◽  
Saravanan Kandasamy ◽  
Ankita Gupta ◽  
Jagannathan Selvaraj ◽  
Kukkaler Channappa Shivanandappa
Keyword(s):  
Drug Target ◽  
Antiviral Agent ◽  
Antiviral Drugs ◽  
World Health ◽  
Definitive Treatment ◽  
Potential Drug ◽  
Dynamic Simulations ◽  
Pubchem Database ◽  
Novel Coronavirus ◽  
Health Organization

<p>A coronavirus identified as 2019 novel coronavirus (COVID-19) is the etiological agent responsible for the 2019-2020 viral pneumonia outbreak that commenced in Wuhan has been declared as a pandemic by the World Health Organization. The virus is predominantly spread from person-to-person mainly through airborne, fomite, contact, and droplet from the infected patients. Also, the lack of definitive treatment is another concern that needs consideration. The novel 2019 SARS-CoV-2 enters the host cell by binding of the viral surface spike glycoprotein (S-protein) to angiotensin-converting enzyme 2 (ACE2). Mpro is a key coronavirus enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus. Considering the importance of these two proteins in the viral infection, these were preferred as a potential drug target against Covid19. In this study, we screened potential antiviral drugs from the Pubchem database and natural antiviral agent quercetin for induced fit docking against these two key proteins. The identified top hit was further evaluated through molecular dynamic simulations. Our results suggest that the antiviral drugs Indinavir and Famciclovir could be a potential drug against Covid19. <br></p>

CISSAMPELOS PAREIRA: PROTEIN-LIGAND DOCKING TO IDENTIFY SUITABLE TARGETS FOR HEPATOCELLULAR CARCINOMA (HCC) BY IN-SILICO TECHNIQUES AND TOOLS

2015 ◽  
Vol 77 (2) ◽  
Author(s):  
B. Samuel Thavamani ◽  
Molly Mathew ◽  
Dhanabal S. Palaniswamy
Keyword(s):  
Hepatocellular Carcinoma ◽  
Growth Factor ◽  
In Silico ◽  
B Cell Lymphoma ◽  
Aurora Kinase ◽  
Pharmacological Action ◽  
Ligand Docking ◽  
Ligand Interaction

Protein-ligand interaction plays a major role in identification of the possible mechanism by which a ligand can bind with the target and exerts the pharmacological action. The present study aims to identify new possible candidates for treating Hepatocellular Carcinoma (HCC) by docking the reported phytochemicals present in Cissampelos pareira with the well known HCC targets using in-silico techniques. Although C. pareira demonstrated in vitro and in vivo anti-heptatocellular carcinoma activities, the mechanism remains uncertain. Selected compounds from C. pareira were docked using GLIDE software with known targets of hepatocellular carcinoma viz. Aurora Kinase, c-Kit, Fibroblast Growth Factor (FGF), Nuclear Factor kappa B (NF-kB), B-cell lymphoma-extra large (Bcl-xL) and Vascular Endothelial Growth Factor (VEGF). Among the compounds docked, pareitropone and pareirubrine B exhibited good hydrogen bonding interactions and binding energy with the targets of HCC taken in the study. Hence these compounds deserve consideration for further studies towards HCC.

scholarly journals Structural and functional characterization of allatostatin receptor type-C of Thaumetopoea pityocampa revealed the importance of Q2716.55 residue in G protein-dependent activation pathway

2020 ◽  
Author(s):  
Aida Shahraki ◽  
Ali Isbilir ◽  
Berna Dogan ◽  
Martin J. Lohse ◽  
Serdar Durdagi ◽  
...  
Keyword(s):  
G Protein ◽  
In Silico ◽  
Functional Characterization ◽  
3D Structure ◽  
Receptor Type ◽  
Ligand Docking ◽  
Thaumetopoea Pityocampa ◽  
Type C ◽  
Kinetics Of

AbstractInsect neuropeptide receptors are among the potential targets for designing next-generation pesticides. Activation of allatostatin receptor type C (AstR-C), a G Protein-coupled receptor (GPCR), upon stimulation with its endogenous ligand, allatostatin C (AST-C), leads to the inhibition of juvenile hormone (JH) secretion that consequently regulates physiology of insects. Here we conducted in silico and in vitro approaches to characterize the structure and function of AstR-C of Thaumetopoea pityocampa (T.pit), a well-known pest in Mediterranean countries. The sequence of AstR-C and AST-C were derived from whole genome sequencing (WGS) data. Resonance energy transfer (RET) methods were used to investigate the downstream effectors of the receptor and the temporal kinetics of G protein activation. Three-dimensional (3D) structure of AstR-C constructed via homology modeling methods was subjected to molecular dynamics (MD) simulations and docking studies to identify the orthosteric pocket. Our results showed that T.pit AstR-C couples to Gαi/o subtype of G proteins at sub-nanomolar ranges of the the ligand with the G protein recruitment and activation kinetics of ∼4 and 6 seconds, respectively, when 1 nM AST-C is administered. At the increasing concentration of native ligand, βarrestin was shown to be recruited at nanomolar ranges the ligand. Docking and MD simulation studies revealed the importance of extracellular loop 2 (ECL2) in T.pit AstRC/AST-C interaction, and combination of in silico and in vitro methods supported the accuracy of the built model and the predicted orthosteric pocket. Q2716.55 (Ballesteros-Weinstein generic numbering) was found to have a substantial role in G protein dependent activation of AstR-C possibly via contributing to the flexibility of the structure.

Insilico Identification of Potential Antivirals and Molecular Dynamics Against SARS-CoV2 Main Protease and RBD of Spike Protein

2020 ◽  
Author(s):  
Vijayakumar Rajendran ◽  
Saravanan Kandasamy ◽  
Ankita Gupta ◽  
Jagannathan Selvaraj ◽  
Kukkaler Channappa Shivanandappa
Keyword(s):  
Drug Target ◽  
Antiviral Agent ◽  
Antiviral Drugs ◽  
World Health ◽  
Definitive Treatment ◽  
Potential Drug ◽  
Dynamic Simulations ◽  
Pubchem Database ◽  
Novel Coronavirus ◽  
Health Organization

<p>A coronavirus identified as 2019 novel coronavirus (COVID-19) is the etiological agent responsible for the 2019-2020 viral pneumonia outbreak that commenced in Wuhan has been declared as a pandemic by the World Health Organization. The virus is predominantly spread from person-to-person mainly through airborne, fomite, contact, and droplet from the infected patients. Also, the lack of definitive treatment is another concern that needs consideration. The novel 2019 SARS-CoV-2 enters the host cell by binding of the viral surface spike glycoprotein (S-protein) to angiotensin-converting enzyme 2 (ACE2). Mpro is a key coronavirus enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus. Considering the importance of these two proteins in the viral infection, these were preferred as a potential drug target against Covid19. In this study, we screened potential antiviral drugs from the Pubchem database and natural antiviral agent quercetin for induced fit docking against these two key proteins. The identified top hit was further evaluated through molecular dynamic simulations. Our results suggest that the antiviral drugs Indinavir and Famciclovir could be a potential drug against Covid19. <br></p>

scholarly journals A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

2020 ◽  
Author(s):  
Christoph Gorgulla ◽  
Krishna PadmanabhaDas ◽  
Kendra E. Leigh ◽  
Marco Cespugli ◽  
Patrick D. Fischer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Active Sites ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
The Face ◽  
Computing Platforms ◽  
Screening Platform ◽  
Novel Coronavirus ◽  
Further Development

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

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