Literature DB >> 11918076

A genetic algorithm for structure-based de novo design.

S C Pegg1, J J Haresco, I D Kuntz.   

Abstract

Genetic algorithms have properties which make them attractive in de novo drug design. Like other de novo design programs, genetic algorithms require a method to reduce the enormous search space of possible compounds. Most often this is done using information from known ligands. We have developed the ADAPT program, a genetic algorithm which uses molecular interactions evaluated with docking calculations as a fitness function to reduce the search space. ADAPT does not require information about known ligands. The program takes an initial set of compounds and iteratively builds new compounds based on the fitness scores of the previous set of compounds. We describe the particulars of the ADAPT algorithm and its application to three well-studied target systems. We also show that the strategies of enhanced local sampling and re-introducing diversity to the compound population during the design cycle provide better results than conventional genetic algorithm protocols.

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Year:  2001        PMID: 11918076     DOI: 10.1023/a:1014389729000

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  27 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

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5.  CONCERTS: dynamic connection of fragments as an approach to de novo ligand design.

Authors:  D A Pearlman; M A Murcko
Journal:  J Med Chem       Date:  1996-04-12       Impact factor: 7.446

6.  Folate antagonists: toward improving the therapeutic index and development of new analogs.

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Journal:  J Clin Pharmacol       Date:  1990-04       Impact factor: 3.126

Review 7.  Non-nucleoside anti-HIV-1 reverse transcriptase inhibitors (NNRTIs): a chemical survey from lead compounds to selected drugs for clinical trials.

Authors:  M Artico
Journal:  Farmaco       Date:  1996-05

8.  BUILDER v.2: improving the chemistry of a de novo design strategy.

Authors:  D C Roe; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  1995-06       Impact factor: 3.686

9.  HOOK: a program for finding novel molecular architectures that satisfy the chemical and steric requirements of a macromolecule binding site.

Authors:  M B Eisen; D C Wiley; M Karplus; R E Hubbard
Journal:  Proteins       Date:  1994-07

10.  Meeting on binding sites: characterizing and satisfying steric and chemical restraints. University of York, 28-30 March 1993.

Authors:  T Slater; D Timms
Journal:  J Mol Graph       Date:  1993-12
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  18 in total

1.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

2.  ENPDA: an evolutionary structure-based de novo peptide design algorithm.

Authors:  Ignasi Belda; Sergio Madurga; Xavier Llorà; Marc Martinell; Teresa Tarragó; Mireia G Piqueras; Ernesto Nicolás; Ernest Giralt
Journal:  J Comput Aided Mol Des       Date:  2005-11-03       Impact factor: 3.686

3.  Ultrafast de novo docking combining pharmacophores and combinatorics.

Authors:  Marcus Gastreich; Markus Lilienthal; Hans Briem; Holger Claussen
Journal:  J Comput Aided Mol Des       Date:  2007-01-30       Impact factor: 3.686

4.  Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets.

Authors:  William J Allen; Brian C Fochtman; Trent E Balius; Robert C Rizzo
Journal:  J Comput Chem       Date:  2017-09-22       Impact factor: 3.376

Review 5.  Machine Learning and Computational Chemistry for the Endocannabinoid System.

Authors:  Kenneth Atz; Wolfgang Guba; Uwe Grether; Gisbert Schneider
Journal:  Methods Mol Biol       Date:  2023

6.  Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations.

Authors:  Lars Elend; Luise Jacobsen; Tim Cofala; Jonas Prellberg; Thomas Teusch; Oliver Kramer; Ilia A Solov'yov
Journal:  Molecules       Date:  2022-06-22       Impact factor: 4.927

7.  e-LEA3D: a computational-aided drug design web server.

Authors:  Dominique Douguet
Journal:  Nucleic Acids Res       Date:  2010-05-05       Impact factor: 16.971

8.  VitAL: Viterbi algorithm for de novo peptide design.

Authors:  E Besray Unal; Attila Gursoy; Burak Erman
Journal:  PLoS One       Date:  2010-06-02       Impact factor: 3.240

9.  AutoGrow: a novel algorithm for protein inhibitor design.

Authors:  Jacob D Durrant; Rommie E Amaro; J Andrew McCammon
Journal:  Chem Biol Drug Des       Date:  2009-02       Impact factor: 2.817

Review 10.  In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery.

Authors:  Lauro Ribeiro de Souza Neto; José Teófilo Moreira-Filho; Bruno Junior Neves; Rocío Lucía Beatriz Riveros Maidana; Ana Carolina Ramos Guimarães; Nicholas Furnham; Carolina Horta Andrade; Floriano Paes Silva
Journal:  Front Chem       Date:  2020-02-18       Impact factor: 5.221

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