scholarly journals Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening

2021 ◽  
Author(s):  
Abdulrahim R Hakami ◽  
Ahmed H Bakheit ◽  
Abdulrahman A Almehizia ◽  
Mohammed Y Ghazwani
Keyword(s):  
Virtual Screening ◽  
Experimental Studies ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Nonstructural Proteins ◽  
Sars Coronavirus ◽  
Main Protease ◽  
Zinc Database ◽  
Simulation Results ◽  
Selection Of

Background: Conserved domains within SARS coronavirus 2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS coronavirus 2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three compounds were selected as coronavirus NSP5 inhibitors after passing absorption, distribution, metabolism, excretion and toxicity study; root and mean square deviation; and radius of gyration calculations. Conclusion: ZINC000049899562, ZINC000169336666 and ZINC000095542577 are potential NSP5 protease inhibitors that warrant further experimental studies.

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

scholarly journals Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4829
Author(s):  
Sajjad Haider ◽  
Assem Barakat ◽  
Zaheer Ul-Haq
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Root Mean Square ◽  
Cancer Metastasis ◽  
Pharmacophore Model ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dynamic Simulations

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

scholarly journals Structure-Based Discovery and Synthesis of Potential Transketolase Inhibitors

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2116 ◽  
Author(s):  
Jingqian Huo ◽  
Bin Zhao ◽  
Zhe Zhang ◽  
Jihong Xing ◽  
Jinlin Zhang ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Structural Similarity ◽  
Biological Evaluation ◽  
Dynamics Simulation ◽  
Antifungal Activities ◽  
Protein Model ◽  
Zinc Database ◽  
Amide Derivatives ◽  
Plant Photosynthesis ◽  
New Compounds

Transketolase (TKL) plays a key role in plant photosynthesis and has been predicted to be a potent herbicide target. Homology modeling and molecular dynamics simulation were used to construct a target protein model. A target-based virtual screening was developed to discover novel potential transketolase inhibitors. Based on the receptor transketolase 1 and a target-based virtual screening combined with structural similarity, six new compounds were selected from the ZINC database. Among the structural leads, a new compound ZINC12007063 was identified as a novel inhibitor of weeds. Two novel series of carboxylic amide derivatives were synthesized, and their structures were rationally identified by NMR and HRMS. Biological evaluation of the herbicidal and antifungal activities indicated that the compounds 4u and 8h were the most potent herbicidal agents, and they also showed potent fungicidal activity with a relatively broad-spectrum. ZINC12007063 was identified as a lead compound of potential transketolase inhibitors, 4u and 8h which has the herbicidal and antifungal activities were synthesized based on ZINC12007063. This study lays a foundation for the discovery of new pesticides.

In Silico Discovery of Novel Inhibitors Against Main Protease (Mpro) of SARS-CoV-2 Using Pharmacophore and Molecular Docking Based Virtual Screening from ZINC Database

2020 ◽  
Author(s):  
Zeshan Haider ◽  
Muhammad Muneeb Subhani ◽  
Muhammad Ansar Farooq ◽  
Maryum Ishaq ◽  
Maryam Khalid ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Effective Vaccine ◽  
Ligand Complex ◽  
Online Tool ◽  
Public Health Emergencies ◽  
Main Protease ◽  
Zinc Database ◽  
Recent Outbreak ◽  
Selection Of

Recent outbreak of Coronavirus Disease 2019 (COVID-19) caused by a novel ‘SARS-CoV-2’ virus resulted public health emergencies across the world. An effective vaccine to cure this virus is not yet available, thus requires concerted efforts at various scales. In this study, we employed Computer Aided Drug Design (CADD) based approach to identify the drug-like compounds - inhibiting the replication of main protease (Mpro) of SARS-CoV-2. Our database search using online tool “ZINC pharmer” retrieved ~1500 compounds based on pharmacophore features. Lipinski’s rule was applied to further evaluate the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with Mpro based on S-score (higher than reference inhibitor) and root-mean-square deviation (RMSD) value (less than reference inhibitor) using Molecular Operating Environment (MOE) system. Resultantly, ~200 compounds were identified having strong interaction with Mpro of SARS-CoV-2. After evaluating their binding energy using the MOE LigX algorithm, three compounds (ZINC20291569, ZINC90403206, ZINC95480156) were identified that showed highest binding energy with Mpro of SARS-CoV-2 and strong inhibition effect than the reference inhibitor. It is suggested that these candidate “drug-like compounds” have greater potential to stop the replication of SARS-CoV-2, hence might lead to the cure of COVID-19.

scholarly journals Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach

2021 ◽  
Vol 1 ◽  
Author(s):  
Shafi Mahmud ◽  
Md. Robiul Hasan ◽  
Suvro Biswas ◽  
Gobindo Kumar Paul ◽  
Shamima Afrose ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Economy ◽  
Transmission Rate ◽  
Accessible Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Protease Inhibition ◽  
Main Protease

Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of −8.3, −8.6, and −8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.

scholarly journals Phytochemicals from Leucas zeylanica Targeting Main Protease of SARS-CoV-2: Chemical Profiles, Molecular Docking, and Molecular Dynamics Simulations

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 789
Author(s):  
Mycal Dutta ◽  
Abu Montakim Tareq ◽  
Ahmed Rakib ◽  
Shafi Mahmud ◽  
Saad Ahmed Sami ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Surface Area ◽  
Dynamics Simulation ◽  
Solvent Accessible Surface Area ◽  
Gas Chromatography Mass Spectrometry ◽  
Radius Of Gyration ◽  
Hydrogen Bond Formation ◽  
Main Protease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus’s severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography–mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics–generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (−5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (−5.39 kcal/mol), and lorazepam, 2TMS derivative (−5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand–Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.

scholarly journals In silico drug designing for COVID-19: an approach of highthroughput virtual screening, molecular and essential dynamics simulations

2020 ◽  
Author(s):  
Rakesh Kumar ◽  
Rahul Kumar ◽  
Pranay Tanwar
Keyword(s):  
Virtual Screening ◽  
Dynamics Simulation ◽  
Stable Complex ◽  
Binding Affinities ◽  
Essential Dynamics ◽  
Free Energies ◽  
Main Protease ◽  
Drug Designing ◽  
Dynamics Simulations ◽  
Potential Opportunity

Abstract SARS-CoV2, a new coronavirus has emerged in Wuhan city of China, December last year causing pneumonia named COVID-19 which has now spread to entire world. By April 2020, number of confirmed cumulative cases crossed ~2.4 million worldwide, according to WHO. Till date, no effective treatment or drug is available for this virus. Availability of X-ray structures of SARS-CoV2 main protease (Mpro) provided the potential opportunity for structure based drug designing. Here, we have made an attempt to do computational drug design by targeting main protease of SARS-CoV2. Highthroughput virtual screening of million molecules and natural compounds databases was performed followed by docking. Six ligands showed better binding affinities which were further optimized by MD simulation and rescoring of binding energy was calculated through MM/PBSA method. In addition, conformational effect of various ligands on protein was examined through essential dynamics simulation. Three compounds namely ZINC14732869, ZINC19774413 and ZINC19774479 were finally filtered that displayed high binding free energies than N3 inhibitor and form conformationally stable complex. Hence, current study features the discovery of novel inhibitors for main protease of CoV2 which will provide effective therapeutic candidates against COVID19.

scholarly journals Structure-Based Virtual Screening, Insilico Docking, ADME Prediction, and Molecular Dynamics Studies for Identification of Potential NMT Inhibitors Against Malaria

2021 ◽  
Author(s):  
Mohan Anbuselvam ◽  
C Ji Katherine ◽  
Anbuselvam Jeeva ◽  
Hai-Feng Ji
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Virtual Screening ◽  
Plasmodium Species ◽  
Dynamics Simulation ◽  
Therapeutic Drug ◽  
Infected Female ◽  
Adme Prediction ◽  
Zinc Database ◽  
The Stability

Abstract One of the major public health problems globally, malaria, is mainly caused protozoan parasites from the genus Plasmodium, and commonly spreads to people through the bites of infected female mosquitoes of the genus Anopheles. Strategies for treatment, prevention, and control are available for malaria but the eradication of malaria still poses great challenge due to plasmodium’s drug resistance over the past decades. Development of novel antimalarial drugs remains a significant task to protect people from malaria. N-Myristoyl transferase is responsible for the N-Myristoylation catalysis process and the survival of Plasmodium species. Thus, it is considered a therapeutic drug target in protozoans and was recently validated as a significant target for Plasmodium vivax. In this present scenario, we endeavour to identify effective NMT inhibitors to prevent the onset of malaria in the human species. Initially, the structure-based virtual screening was executed against ZINC database and four potential candidates for NMT were identified. Furthermore, the four identified compounds were subjected to ADME prediction and all the four compounds found within adequate range with predicted ADME properties. Eventually, we conducted the molecular dynamics simulation to investigate the binding stability of top three protein-ligand complexes at different time scale by employing the tool Desmond. The molecular dynamics simulation studies revealed the protein-ligand complexes were stable throughout the entire simulation. Besides, we noticed that the residues ASN 365, PHE 103 and HIS 213 of NMT were crucially involved in the formation of various intermolecular interactions, significantly contributing to the stability of protein-ligand complexes. From this computational investigation, we suggest that the three identified potential compounds are extremely useful for further lead optimization and drug development.

scholarly journals A Drug Repurposing Approach to Identify Therapeutics by Screening Medicines for Malaria Ventures Exploiting SARS-CoV-2 Main Protease

2021 ◽  
Author(s):  
Rashmi Tyagi ◽  
Anubrata Paul ◽  
V. Samuel Raj ◽  
Krishna Kumar Ojha ◽  
Manoj Kumar Yadav
Keyword(s):  
Free Energy ◽  
Catalytic Domain ◽  
Binding Free Energy ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Energy Calculation ◽  
High Morbidity ◽  
Molecular Docking Study ◽  
Virus Propagation ◽  
Main Protease

<p>COVID-19 pandemic makes the human-kind standstill and results in high morbidity and mortality cases worldwide. Still, there are no approved antiviral drugs with proven efficacy nor any therapeutic vaccines to combat the disease as per the current date. In the present study, SARS-CoV-2 main protease (Mpro) has been taken as a potential drug target considering its crucial role in virus propagation. We have used 400 diverse bioactive inhibitors with proven antibacterial and antiviral properties for screening against Mpro target. Our screening result identifies ten compounds with higher binding affinity than N3 (used as a reference compound to validate the experiment). All the compounds possess desire physicochemical properties. Later on, in-depth docking and superimposition of selected complexes confirm that only three compounds (MMV1782211, MMV1782220 and MMV1578574) are actively interacting with the catalytic domain of Mpro. </p> <p>Furthermore, the selected three molecules complexed with Mpro and N3-Mpro as control are subjected to molecular dynamics simulation study (root means square deviation, root mean square fluctuation, hydrogen bonding, solvent-accessible area and radius of gyration). MMV1782211-Mpro complex shows a strong and stable interaction as compared to others. The MM/PBSA free energy calculation shows the highest binding free energy of –115.8 kJ/mol for MMV1782211 compound also cross-confirms our molecular docking study. Therefore, our <i>in silico</i> findings become very interesting towards developing alternative medicine against SARS-CoV-2 Mpro target. So, we can expect prompt actions in this direction to combat the COVID-19.</p>

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