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European Conference on Genetic Programming

EuroGP 2013: Genetic Programming pp 181–192Cite as

A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7831))

Abstract

This work proposes a multi-objective algorithmic method for modelling the prediction of the conformation and configuration of ligands in receptor-ligand complexes by considering energy contributions of molecular interactions. The proposed approach is an improvement over others in the field, where the principle insight is that a Pareto front helps to understand the tradeoffs in the actual problem. The method is based on three main features: (i) Representation of molecular data using a trigonometric model; (ii) Modelling of molecular interactions with all-atoms force field energy functions and (iii) Exploration of the conformational space through a multi-objective evolutionary algorithm. The performance of the proposed model was evaluated and validated over a set of well known complexes. The method showed a promising performance when predicting ligands with high number of rotatable bonds.

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Author information

Authors and Affiliations

  1. Bioinformatics and Intelligent Systems Research Laboratory, Universidad Nacional de Colombia, Bogota, Colombia

    Angelica Sandoval-Perez, David Becerra, Diana Vanegas, Daniel Restrepo-Montoya & Fernando Nino

  2. Computational Biology, Department Biologie, Universität Erlangen-Nürnber, Erlangen, Germany

    Angelica Sandoval-Perez

  3. McGill Centre for Bioinformatics, McGill University, Montreal, Canada

    David Becerra

Authors
  1. Angelica Sandoval-Perez
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  2. David Becerra
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  3. Diana Vanegas
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  4. Daniel Restrepo-Montoya
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  5. Fernando Nino
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Editor information

Editors and Affiliations

  1. Institute of Computing Science, Poznan University of Technology, Piotowo 2, 60-965, Poznań, Poland

    Krzysztof Krawiec

  2. School of Computer Science, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK

    Alberto Moraglio

  3. Geisel School of Medicine, Dartmouth College, 03755, Hanover, NH, USA

    Ting Hu

  4. Department of Computer Engineering, Istanbul Technical University, 34469, Masla, Istanbul, Turkey

    A. Şima Etaner-Uyar

  5. Institute of Computer Graphics and Algorithms, Vienna University of Technology, 1040, Vienna, Austria

    Bin Hu

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© 2013 Springer-Verlag Berlin Heidelberg

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Sandoval-Perez, A., Becerra, D., Vanegas, D., Restrepo-Montoya, D., Nino, F. (2013). A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process. In: Krawiec, K., Moraglio, A., Hu, T., Etaner-Uyar, A.Ş., Hu, B. (eds) Genetic Programming. EuroGP 2013. Lecture Notes in Computer Science, vol 7831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37207-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-37207-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37206-3

  • Online ISBN: 978-3-642-37207-0

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