MolTaut: A Tool for the Rapid Generation of Favorable Tautomer in Aqueous Solution

Xiaolin Pan, Fanyu Zhao, Yueqing Zhang, Xingyu Wang, Xudong Xiao, John Z.H. Zhang, Changge Ji

Research output: Contribution to journalArticlepeer-review

Abstract

Fast and proper treatment of the tautomeric states for drug-like molecules is critical in computer-aided drug discovery since the major tautomer of a molecule determines its pharmacophore features and physical properties. We present MolTaut, a tool for the rapid generation of favorable states of drug-like molecules in water. MolTaut works by enumerating possible tautomeric states with tautomeric transformation rules, ranking tautomers with their relative internal energies and solvation energies calculated by AI-based models, and generating preferred ionization states according to predicted microscopic pKa. Our test shows that the ranking ability of the AI-based tautomer scoring approach is comparable to the DFT method (wB97X/6-31G*//M062X/6-31G*/SMD) from which the AI models try to learn. We find that the substitution effect on tautomeric equilibrium is well predicted by MolTaut, which is helpful in computer-aided ligand design. The source code of MolTaut is freely available to researchers and can be accessed at https://github.com/xundrug/moltaut. To facilitate the usage of MolTaut by medicinal chemists, we made a free web server, which is available at http://moltaut.xundrug.cn. MolTaut is a handy tool for investigating the tautomerization issue in drug discovery.

Original languageEnglish (US)
Pages (from-to)1833-1840
Number of pages8
JournalJournal of Chemical Information and Modeling
Volume63
Issue number7
DOIs
StatePublished - Apr 10 2023

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Computer Science Applications
  • Library and Information Sciences

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