Literature DB >> 11924740

MM3 parametrization of four- and five-coordinated rhenium complexes by a genetic algorithm--which factors influence the optimization performance?

Thomas Strassner1, Markus Busold, Wolfgang A Herrmann.   

Abstract

Genetic algorithms (GA) were used to solve one of the multidimensional problems in computational chemistry, the optimization of force field parameters. The correlation between the composition of the GA, its parameters (p(c), p(m)) and the quality of the results were investigated. The composition was studied for all combinations of a Simple GA/Steady State GA with a Roulette Wheel/Tournament Selector using different values each for crossover (0.5, 0.7, 0.9) and mutation rates (0.01, 0.02, 0.05, 0.10, 0.20). The results show that the performance is strongly dependent on the GA scheme, where the Simple GA/Tournament Selector yields the best results. Two new MM3 parameters were introduced for rhenium compounds with coordination number four (204) and coordination number five (205), the formal oxidation states of rhenium ranging from +V to +VII. A manifold of parameters (Re-C, N, O, S) was obtained by using a diverse set of CSD structures. The advantage of the GA vs. UFF calculations is shown by comparison of several examples. The GA optimized parameters were able to reproduce the geometrical data of the X-ray structures.

Entities:  

Year:  2002        PMID: 11924740     DOI: 10.1002/jcc.10000

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  3 in total

1.  QSAR studies of copper azamacrocycles and thiosemicarbazones: MM3 parameter development and prediction of biological properties.

Authors:  Peter Wolohan; Jeongsoo Yoo; Michael J Welch; David E Reichert
Journal:  J Med Chem       Date:  2005-08-25       Impact factor: 7.446

Review 2.  CoMSIA and docking study of rhenium based estrogen receptor ligand analogs.

Authors:  Peter Wolohan; David E Reichert
Journal:  Steroids       Date:  2007-02-05       Impact factor: 2.668

3.  JACOB: an enterprise framework for computational chemistry.

Authors:  Mark P Waller; Thomas Dresselhaus; Jack Yang
Journal:  J Comput Chem       Date:  2013-04-03       Impact factor: 3.376

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.