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Conformational searching methods for small molecules. II. Genetic algorithm approach
Author(s) -
Judson R.S.,
Jaeger E.P.,
Treasurywala A.M.,
Peterson M.L.
Publication year - 1993
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.540141117
Subject(s) - algorithm , computer science , genetic algorithm , computational chemistry , chemistry , machine learning
Abstract We demonstrate the use of a genetic algorithm (GA) search procedure for finding low‐energy conformations of small to medium organic molecules (1–12 rotatable bonds). GAS are in a class of biologically motivated optimization methods that evolve a population of individuals where individuals who are more “fit” have a higher probability of surviving into subsequent generations. Here, an individual is a conformation of a given molecule and the fitness is the molecule's conformational energy. In the course of a simulated evolution, the population produces conformations having increasingly lower energy. We test the GA method on a suite of 72 molecules and compare the performance against the CSEARCH algorithm in Sybyl. For molecules with more than eight rotatable bonds, the GA method is more efficient computationally and as the number of rotatable bonds increases the relative efficiency of the GA method grows. The GA method also found energies equal to or lower than the energy of the relaxed crystal structure in the large majority of cases. © John Wiley & Sons, Inc.