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Related Experiment Video

Updated: Jun 26, 2026

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

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

Published on: June 20, 2025

Managing protein flexibility in docking and its applications.

Chandrika B-Rao¹, Jyothi Subramanian, Somesh D Sharma

¹Discovery Informatics, Piramal Life Sciences Limited, 1 Nirlon Complex, Off Western Express Highway, Goregaon (E), Mumbai 400063, India. chandrika.rao@piramal.com

Drug Discovery Today

|February 3, 2009

Summary

This summary is machine-generated.

Managing receptor flexibility in computational drug discovery remains challenging. Combining multiple computational methods offers the most reliable approach for determining optimal protein conformations for drug targets.

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

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Structure-Guided Design and Development of Novel Cyclophilin A Inhibitors and Ganoderiol-F Derivatives: An In-Silico Approach

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Published on: June 23, 2026

Area of Science:

Computational chemistry
Drug discovery
Structural biology

Background:

Docking, virtual screening, and structure-based drug design are essential in modern drug discovery.
Handling flexible ligands is standard, but receptor flexibility presents a significant computational challenge.

Purpose of the Study:

To review the state-of-the-art computational methods for addressing receptor flexibility in drug design.
To introduce a novel statistical computational approach for managing protein flexibility.

Main Methods:

Review of current computational techniques for receptor flexibility.
Presentation of a new statistical computational method.
Comparative analysis of different approaches.

Main Results:

Current docking methods struggle with receptor flexibility.
A novel statistical computational approach has been recently published.
Different methods show varying degrees of success in handling receptor flexibility.

Conclusions:

A combination of computational methods is most effective for managing receptor flexibility.
This integrated approach enhances the reliability of finding correct protein conformations for drug design.