Molecular Modeling Studies on 2,4-Disubstituted Imidazopyridines as Anti-Malarials: Atom-Based 3D-QSAR, Molecular Docking, Virtual Screening, In-Silico ADMET and Theoretical Analysis

2021 ◽  
pp. 2150012
Author(s):  
Suraj N. Mali ◽  
Anima Pandey
Keyword(s):  
Molecular Docking ◽  
Molecular Modeling ◽  
Virtual Screening ◽  
In Silico ◽  
Energy Gap ◽  
3D Qsar ◽  
Modeling Studies ◽  
In Vitro Investigation ◽  
In Silico Admet ◽  
Molecular Modeling Studies

Malarial parasites have been reported for moderate-high resistance towards classical antimalarial agents and henceforth development of newer novel chemical entities targeting multiple targets rather than targeting single target will be a highly promising strategy in antimalarial drug discovery. Herein, we carried out molecular modeling studies on 2,4-disubstituted imidazopyridines as anti-hemozoin formation inhibitors by using Schrödinger’s molecular modeling package (2020_4). We have developed statistically robust atom-based 3D-QSAR model (training set, [Formula: see text]; test set, [Formula: see text]; [Formula: see text] [Formula: see text]; root-mean-square error, [Formula: see text]; standard deviation, [Formula: see text]). Our molecular docking, in-silico ADMET analysis showed that dataset molecule 37, has highly promising results. Our ligand-based virtual screening resulted in top five ZINC hits, among them ZINC73737443 hit was observed with lesser energy gap, i.e. 7.85[Formula: see text]eV, higher softness value (0.127[Formula: see text]eV), and comparatively good docking score of [Formula: see text]10.2[Formula: see text]kcal/mol. Our in-silico analysis for a proposed hit, ZINC73737443 showed that this molecule has good ADMET, in-silico nonames toxic as well as noncarcinogenic profile. We believe that further experimental as well as the in-vitro investigation will throw more lights on the identification of ZINC73737443 as a potential antimalarial agent.

Virtual Screening, Molecular docking and in-silico ADME-Tox analysis for identification of potential main protease (Mpro) enzyme inhibitors

2020 ◽  
Vol 18 ◽  
Author(s):  
Debadash Panigrahi ◽  
Ganesh Prasad Mishra
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Data Bank ◽  
Future Research ◽  
Reference Compound ◽  
Unexpected Death ◽  
Main Protease ◽  
In Silico Admet

Objective:: Recent pandemic caused by SARS-CoV-2 described in Wuhan China in December-2019 spread widely almost all the countries of the world. Corona virus (COVID-19) is causing the unexpected death of many peoples and severe economic loss in several countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET study has become an effective tool for the identification of small molecules as novel antiviral drugs to treat diseases. Methods:: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of COVID-19 pandemic. Interestingly, some compounds are identified as possible anti-covid-19 agents for future research. 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result:: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and found to be excellent results. All the 10 screened compounds showed significant binding pose with the target enzyme main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion:: Based on results we can suggest that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can be further evaluated for in vitro activity, preclinical, clinical studies and formulated in a suitable dosage form to maximize their bioavailability.

3D-QSAR, molecular docking and in silico ADMET studies of propiophenone derivatives with anti-HIV-1 protease activity

2021 ◽  
Author(s):  
Milan Jovanović ◽  
Nemanja Turković ◽  
Branka Ivković ◽  
Zorica Vujić ◽  
Katarina Nikolić ◽  
...  
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Protease Activity ◽  
3D Qsar ◽  
In Silico Admet ◽  
Anti Hiv ◽  
Hiv 1
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