.png){kind=icon}
Return
Bayesian optimization for conformer generation
.png){kind=icon}
OA
AI
DOI：10.1186/s13321-019-0354-7.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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 104(median) conformers in its search, while BOA only requires 102 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.
Keywords:
Bayesian optimization
Gaussian processes
Conformer generation
Rotatable bond
Torsion angle
Conformational space
Molecular energetics
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.7
Papers:
1.5K
Citations:
1.1W
Organization
Cited Papers
ShareSaveShareSaveMerck molecular force field .1. Basis, form, scope, parameterization, and performance of MMFF94
PREAI
ShareSaveShareSaveEfficient decellularization for tissue engineering of the tendon-bone interface with preservation of biomechanics.png)
PLOS ONEOAAI
PLOS ONEIF0
OAAIShareSaveTaking the Human Out of the Loop: A Review of Bayesian OptimizationPROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
ShareSaveShareSaveShareSave
View more