ArticleJournal of cheminformatics2021
MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES.
Article in Journal of cheminformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- MOZAIC: compound growth via in silico reactions and global optimization using Conformational Space Annealing.Bioinformatics (Oxford, England) · 2026Article
- Molecular Design with Artificial Intelligence: Progress and Perspectives for Small Molecules.Chemical reviews · 2026Review
- Article
- Multi-Objective Drug Molecule Optimization Based on Tanimoto Crowding Distance and Acceptance Probability.Pharmaceuticals (Basel, Switzerland) · 2025Article
- CMOMO: a deep multi-objective optimization framework for constrained molecular multi-property optimization.Briefings in bioinformatics · 2025Article
- Crossover operators for molecular graphs with an application to virtual drug screening.Journal of cheminformatics · 2025Article
- Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations.Journal of cheminformatics · 2025Article
- Artificial Intelligence in Molecular Optimization: Current Paradigms and Future Frontiers.International journal of molecular sciences · 2025Review
- CSearch: chemical space search via virtual synthesis and global optimization.Journal of cheminformatics · 2024Article
- Accurate prediction of protein-ligand interactions by combining physical energy functions and graph-neural networks.Journal of cheminformatics · 2024Article
- Evolutionary Multiobjective Molecule Optimization in an Implicit Chemical Space.Journal of chemical information and modeling · 2024Article
- Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening.Journal of chemical information and modeling · 2024Article
- Combatting over-specialization bias in growing chemical databases.Journal of cheminformatics · 2023Article
- Generative Models as an Emerging Paradigm in the Chemical Sciences.Journal of the American Chemical Society · 2023Review
- Parallel tempered genetic algorithm guided by deep neural networks for inverse molecular design.Digital discovery · 2022Article
- Molecular generation by Fast Assembly of (Deep)SMILES fragments.Journal of cheminformatics · 2021Article
- V-Dock: Fast Generation of Novel Drug-like Molecules Using Machine-Learning-Based Docking Score and Molecular Optimization.International journal of molecular sciences · 2021Article
- Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization.Journal of cheminformatics · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
Here, we introduce a new molecule optimization method, MolFinder, based on an efficient global optimization algorithm, the conformational space annealing algorithm, and the SMILES representation. MolFinder finds diverse molecules with desired properties efficiently without any training and a large molecular database. Compared with recently proposed reinforcement-learning-based molecule optimization algorithms, MolFinder consistently outperforms in terms of both the optimization of a given target property and the generation of a set of diverse and novel molecules. The efficiency of MolFinder demonstrates that combinatorial optimization using the SMILES representation is a promising approach for molecule optimization, which has not been well investigated despite its simplicity. We believe that our results shed light on new possibilities for advances in molecule optimization methods.
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