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Related Experiment Video

Updated: Nov 3, 2025

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EXPRORER: Rational Cosolvent Set Construction Method for Cosolvent Molecular Dynamics Using Large-Scale Computation.

Keisuke Yanagisawa1,2, Yoshitaka Moriwaki3, Tohru Terada2,4,3

  • 1Department of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.

Journal of Chemical Information and Modeling
|June 1, 2021
PubMed
Summary
This summary is machine-generated.

We developed EXPRORER, a systematic method to create diverse cosolvent sets for drug discovery. This approach enhances hotspot detection and binding site identification in protein-ligand interactions.

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Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Drug discovery and development

Background:

  • Cosolvent molecular dynamics (CMD) simulations aid in protein-ligand interaction analysis.
  • Existing methods use limited cosolvent selections, hindering comprehensive binding site exploration.

Purpose of the Study:

  • To introduce EXPRORER (EXtended PRObes set construction by REpresentative Retrieval), a systematic method for constructing diverse cosolvent sets for drug discovery.
  • To improve hotspot detection, binding site identification, and binding energy estimation in computational drug discovery.

Main Methods:

  • Extraction of typical substructures from FDA-approved drugs to generate 138 cosolvent candidates.
  • Conducting CMD simulations for each cosolvent to generate spatial probability distribution maps (PMAPs).
  • Analyzing PMAP similarity to identify structurally similar cosolvents and constructing optimized cosolvent subsets based on a similarity threshold.

Main Results:

  • Established a quantitative measure of cosolvent structural similarity using PMAP analysis (similarity > 0.70-0.75 indicates shared features).
  • Successfully constructed and tested cosolvent subsets for four different proteins.
  • Demonstrated the systematic approach for building comprehensive cosolvent libraries.

Conclusions:

  • EXPRORER provides a novel, systematic strategy for cosolvent set construction in drug discovery.
  • The developed cosolvent sets offer deeper insights into ligand binding sites.
  • This method advances the application of CMD simulations for identifying potential drug targets.