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MolMod: a molecular modification platform for molecular property optimization via fragment-based generation.

Yao Zhou1, Zhipei Sang1, Chao Xu1

  • 1Key Laboratory of Tropical Biological Resources of Ministry of Education and Hainan Engineering Research Center for Drug Screening and Evaluation, School of Pharmaceutical Sciences, Hainan University, Haikou, 570228, China.

Molecular Diversity
|September 4, 2025
PubMed
Summary

MolMod accelerates drug design by enabling site-specific molecular modifications using generative AI. This platform enhances lead compounds efficiently, improving drug-like properties with high accuracy and experimental validation.

Keywords:
ADMET predictionDeep learningFragment-based drug designLead optimizationSite-specific modification

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Design
  • Artificial Intelligence in Drug Discovery

Background:

  • Lead optimization is critical in drug design, but current AI tools often focus on de novo design, not targeted modifications.
  • Existing AI methods have limitations in practical application for medicinal chemists working with validated lead compounds.

Purpose of the Study:

  • To introduce MolMod, a web-based platform for site-specific molecular modifications.
  • To enable targeted optimization of lead compounds by generating property-enhanced fragments.

Main Methods:

  • Developed MolMod, a platform using a transformer model trained on ZINC20 and ChEMBL fragments.
  • Implemented site-specific modification by user-defined marking of molecular positions.
  • Utilized fragment-based optimization to generate improved molecular fragments.

Main Results:

  • MolMod demonstrated high scaffold retention and a >99.99% fragment assembly success rate.
  • Achieved >93% success rate for single-property optimization and 95% accuracy for multi-property constraints.
  • Experimental validation showed significant improvement in aqueous solubility (α-mangostin: <5 μg/mL to 789 μg/mL).

Conclusions:

  • MolMod offers a practical solution for medicinal chemistry by focusing on site-specific modifications.
  • The platform provides ADMET profiles and real-time visualization, aiding both computational and experimental scientists.
  • MolMod effectively enhances drug-like properties of lead compounds through targeted, AI-driven fragment optimization.