Literature DB >> 8595137

Genetic algorithms in molecular recognition and design.

P Willett1.   

Abstract

Genetic algorithms provide a novel tool for the investigation of combinatorial optimization problems. A genetic algorithm takes an initial set of possible starting solutions, and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. This approach is illustrated by reference to applications in molecular modelling, the docking of flexible ligands into protein active sites and de novo ligand design.

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Year:  1995        PMID： 8595137     DOI： 10.1016/S0167-7799(00)89015-0

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN： 0167-7799            Impact factor:   19.536


  18 in total

1.  De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

Authors:  G Schneider; M L Lee; M Stahl; P Schneider
Journal:  J Comput Aided Mol Des       Date:  2000-07       Impact factor: 3.686

2.  Bond-based global and local (bond, group and bond-type) quadratic indices and their applications to computer-aided molecular design. 1. QSPR studies of diverse sets of organic chemicals.

Authors:  Yovani Marrero-Ponce; Francisco Torrens; Ysaias J Alvarado; Richard Rotondo
Journal:  J Comput Aided Mol Des       Date:  2006-11-25       Impact factor: 3.686

3.  In silico evolution of functional morphology: A test on bone tissue biomechanics.

Authors:  Emmanuel de Margerie; Paul Tafforeau; Lalaonirina Rakotomanana
Journal:  J R Soc Interface       Date:  2006-10-22       Impact factor: 4.118

Review 4.  A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection.

Authors:  Mark Sale; Eric A Sherer
Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

5.  Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm.

Authors:  P Chacón; F Morán; J F Díaz; E Pantos; J M Andreu
Journal:  Biophys J       Date:  1998-06       Impact factor: 4.033

Review 6.  Evolutionary algorithms in computer-aided molecular design.

Authors:  D E Clark; D R Westhead
Journal:  J Comput Aided Mol Des       Date:  1996-08       Impact factor: 3.686

7.  Role of genetic algorithms and artificial neural networks in predicting the phase behavior of colloidal delivery systems.

Authors:  S Agatonovic-Kustrin; R G Alany
Journal:  Pharm Res       Date:  2001-07       Impact factor: 4.200

8.  Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.

Authors:  Yovani Marrero-Ponce; Eugenio R Martínez-Albelo; Gerardo M Casañola-Martín; Juan A Castillo-Garit; Yunaimy Echevería-Díaz; Vicente Romero Zaldivar; Jan Tygat; José E Rodriguez Borges; Ramón García-Domenech; Francisco Torrens; Facundo Pérez-Giménez
Journal:  Mol Divers       Date:  2010-01-10       Impact factor: 2.943

Review 9.  De novo protein design, a retrospective.

Authors:  Ivan V Korendovych; William F DeGrado
Journal:  Q Rev Biophys       Date:  2020-02-11       Impact factor: 5.318

10.  Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes.

Authors:  Valerie A Walshe; Channa K Hattotuwagama; Irini A Doytchinova; Mailee Wong; Isabel K Macdonald; Arend Mulder; Frans H J Claas; Pierre Pellegrino; Jo Turner; Ian Williams; Emma L Turnbull; Persephone Borrow; Darren R Flower
Journal:  PLoS One       Date:  2009-11-30       Impact factor: 3.240
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