ArticleJournal of cheminformatics2019
Bayesian optimization for conformer generation.
Article in Journal of cheminformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Bayesian Optimization in Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences.Journal of chemical information and modeling · 2023Article
- Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory.Journal of computer-aided molecular design · 2023Review
- Conformer Generation for Structure-Based Drug Design: How Many and How Good?Journal of chemical information and modeling · 2023Article
- Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization.Journal of chemical information and modeling · 2023Article
- GEOM, energy-annotated molecular conformations for property prediction and molecular generation.Scientific data · 2022Article
- Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis.Topics in catalysis · 2022Article
- TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids.Journal of cheminformatics · 2021Article
- NMR-Based Configurational Assignments of Natural Products: Gibbs Sampling and Bayesian Inference Using Floating Chirality Distance Geometry Calculations.Marine drugs · 2021Article
- Efficient Amino Acid Conformer Search with Bayesian Optimization.Journal of chemical theory and computation · 2021Article
- Efficient Closed-loop Maximization of Carbon Nanotube Growth Rate using Bayesian Optimization.Scientific reports · 2020Article
- Detecting stable adsorbates of (1Beilstein journal of nanotechnology · 2020Article
- Fast, efficient fragment-based coordinate generation for Open Babel.Journal of cheminformatics · 2019Article
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Authors and funding
3 authors.
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Abstract
Generating low-energy molecular conformers is a key task for many areas of computational chemistry, molecular modeling and cheminformatics. Most current conformer generation methods primarily focus on generating geometrically diverse conformers rather than finding the most probable or energetically lowest minima. Here, we present a new stochastic search method called the Bayesian optimization algorithm (BOA) for finding the lowest energy conformation of a given molecule. We compare BOA with uniform random search, and systematic search as implemented in Confab, to determine which method finds the lowest energy. Energetic difference, root-mean-square deviation, and torsion fingerprint deviation are used to quantify the performance of the conformer search algorithms. In general, we find BOA requires far fewer evaluations than systematic or uniform random search to find low-energy minima. For molecules with four or more rotatable bonds, Confab typically evaluates [Formula: see text] (median) conformers in its search, while BOA only requires [Formula: see text] energy evaluations to find top candidates. Despite using evaluating fewer conformers, 20-40% of the time BOA finds lower-energy conformations than a systematic Confab search for molecules with four or more rotatable bonds.
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