ArticleMolecules (Basel, Switzerland)2019
MoleGear: A Java-Based Platform for Evolutionary De Novo Molecular Design.
Article in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Ultra-large library screening with an evolutionary algorithm in Rosetta (REvoLd).Communications chemistry · 2025Article
- Crossover operators for molecular graphs with an application to virtual drug screening.Journal of cheminformatics · 2025Article
- The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges.Molecular therapy. Nucleic acids · 2024Review
- Recent Advances in Automated Structure-Based De Novo Drug Design.Journal of chemical information and modeling · 2024Review
- Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: anFrontiers in chemistry · 2024Article
- Development and application of fragment-based de novo inhibitor design approaches against Plasmodium falciparum GST.Journal of molecular modeling · 2023Article
- GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics.Journal of cheminformatics · 2021Article
- Autonomous molecule generation using reinforcement learning and docking to develop potential novel inhibitors.Scientific reports · 2020Article
- AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization.Journal of cheminformatics · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
A Java-based platform, MoleGear, is developed for de novo molecular design based on the chemistry development kit (CDK) and other Java packages. MoleGear uses evolutionary algorithm (EA) to explore chemical space, and a suite of fragment-based operators of growing, crossover, and mutation for assembling novel molecules that can be scored by prediction of binding free energy or a weighted-sum multi-objective fitness function. The EA can be conducted in parallel over multiple nodes to support large-scale molecular optimizations. Some complementary utilities such as fragment library design, chemical space analysis, and graphical user interface are also integrated into MoleGear. The candidate molecules as inhibitors for the human immunodeficiency virus 1 (HIV-1) protease were designed by MoleGear, which validates the potential capability for de novo molecular design.
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Registered trials
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