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MolOpt: A Web Server for Drug Design using Bioisosteric Transformation.

Jinwen Shan1, Changge Ji1

  • 1NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China.

Current Computer-Aided Drug Design
|July 6, 2019
PubMed
Summary

MolOpt is a web server that aids drug design by suggesting bioisosteric replacements for lead optimization. It generates molecular analogues and evaluates their properties, streamlining the search for new drug candidates.

Keywords:
Bioisosteric replacementdata miningin silico drug designlead optimizationmachine learningweb server

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Design
  • Pharmacology

Background:

  • Bioisosteric replacement is a key strategy in drug design for optimizing lead compounds.
  • Identifying effective bioisosteric groups remains a significant challenge in medicinal chemistry.

Purpose of the Study:

  • To introduce MolOpt, a novel web server designed for in silico drug design.
  • To facilitate the identification of suitable bioisosteric transformations for lead optimization.

Main Methods:

  • Development of a web server (MolOpt) for bioisosteric transformation in drug design.
  • Derivation of bioisosteric transformation rules using data mining, deep generative machine learning, and similarity comparisons.
  • Integration of pharmacokinetic and toxicological property evaluation for generated analogues.

Main Results:

  • MolOpt automatically generates lists of molecular analogues by replacing substructures with chemically similar groups.
  • The server evaluates forty critical pharmacokinetic and toxicological properties for each designed molecule.
  • Generated analogues are suitable for assessment in potential future drug development studies.

Conclusions:

  • MolOpt provides valuable assistance to medicinal chemists in identifying lead optimization strategies.
  • The MolOpt server is accessible online for free use, supporting drug discovery efforts.