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Related Experiment Video

Updated: Nov 2, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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Finding Druggable Sites in Proteins Using TACTICS.

Daniel J Evans1, Remy A Yovanno1, Sanim Rahman1

  • 1Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States.

Journal of Chemical Information and Modeling
|June 7, 2021
PubMed
Summary
This summary is machine-generated.

We developed TACTICS, a machine-learning tool that analyzes protein dynamics to find drug-binding sites. This method identifies known and novel druggable pockets, advancing structure-based drug discovery.

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Area of Science:

  • Computational biology
  • Structural biology
  • Drug discovery

Background:

  • Structure-based drug discovery relies on identifying drug-binding sites on target proteins.
  • Locating all potential druggable sites, especially transient or 'cryptic' ones, remains a significant challenge.

Purpose of the Study:

  • To introduce TACTICS (trajectory-based analysis of conformations to identify cryptic sites), a novel machine-learning algorithm for predicting druggable protein sites.
  • To demonstrate TACTICS's capability in identifying both known and previously unobserved binding pockets.

Main Methods:

  • TACTICS utilizes molecular dynamics simulation data, employing k-means clustering to capture conformational heterogeneity.
  • A random forest model analyzes protein motion and geometry to identify potential binding residues.
  • Fragment docking scores residues within predicted binding pockets.

Main Results:

  • TACTICS successfully recapitulated known small-molecule binding sites in SARS-CoV-2 protease and methyltransferase, and *Yersinia pestis* aryl carrier protein.
  • The algorithm predicted novel potential binding sites not evident in existing experimental structures.
  • The TACTICS code is publicly available for broader research application.

Conclusions:

  • TACTICS offers a robust computational approach for identifying druggable protein sites from molecular dynamics data.
  • This method enhances the discovery of novel binding pockets, crucial for advancing drug development.
  • TACTICS provides a valuable tool for structure-based drug discovery and medicinal chemistry research.