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Related Concept Videos

Drug Discovery: Overview01:26

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Related Experiment Video

Updated: Nov 30, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

A Acharya1, R Agarwal2,3,4, M Baker5

  • 1School of Physics, Georgia Institute of Technology, Atlanta, GA 30332.

Chemrxiv : the Preprint Server for Chemistry
|November 17, 2020
PubMed
Summary

We developed a supercomputer pipeline for in-silico drug discovery targeting SARS-CoV-2 proteins. This method uses enhanced sampling molecular dynamics (MD) and ensemble docking for rapid identification of potential drug candidates.

Keywords:
AutodockCOVID-19Drug RepurposingEnsemble DockingHigh-Throughput ScreeningMProNSP10NSP15NSP16NSP3NSP9Nucelocapsid (N) ProteinPLProSARS CoV-2Spike (S) ProteinSupercomputingT-REMD

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Virology

Background:

  • SARS-CoV-2 poses a significant global health threat.
  • Efficient in-silico methods are crucial for rapid drug discovery.
  • Protein targets within the SARS-CoV-2 proteome require extensive investigation.

Conclusions:

  • The developed pipeline offers a powerful and efficient approach for in-silico drug discovery.
  • Preliminary results show promise for identifying SARS-CoV-2 drug candidates.
  • Future work will integrate quantum mechanical, machine learning, and AI methods for pipeline enhancement.