Literature DB >> 24981492

Optimization algorithms and natural computing in drug discovery.

Tom Solmajer1, Jure Zupan2.   

Abstract

Recent efforts in structural biology have lead to considerable growth in the number of structures available which are potential drug targets. Considerable progress in docking algorithms has enabled in silico screening as an attractive alternative to traditional screening for drug leads and optimization, because in vitro high-throughput screening of compounds is costly and relatively inefficient. In molecular modeling one is often confronted with hard problems, such as highly complicated energy landscapes in many dimensions and a combinatorial explosion of the number of possible solutions. Recently, however, several algorithms based on situations in nature have appeared and in this review we illustrate their strengths and weaknesses.:
© 2004 Elsevier Ltd . All rights reserved.

Year:  2004        PMID: 24981492     DOI: 10.1016/j.ddtec.2004.11.011

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  3 in total

1.  Thrombin inhibitors with novel P1 binding pocket functionality: free energy of binding analysis.

Authors:  Gregor Mlinsek; Marko Oblak; Milan Hodoscek; Tom Solmajer
Journal:  J Mol Model       Date:  2006-09-30       Impact factor: 1.810

2.  Designing lead optimisation of MMP-12 inhibitors.

Authors:  Matteo Borrotti; Davide De March; Debora Slanzi; Irene Poli
Journal:  Comput Math Methods Med       Date:  2014-01-12       Impact factor: 2.238

3.  Antimicrobial peptides design by evolutionary multiobjective optimization.

Authors:  Giuseppe Maccari; Mariagrazia Di Luca; Riccardo Nifosí; Francesco Cardarelli; Giovanni Signore; Claudia Boccardi; Angelo Bifone
Journal:  PLoS Comput Biol       Date:  2013-09-05       Impact factor: 4.475

  3 in total

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