Parallel multi-objective algorithms for the molecular docking problem

2008/11/04 by Jean-Charles Boisson, Laëtitia Jourdan, Boisson, Jean-Charles +5
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #Computational Drug Discovery Methods #FOS: Biological sciences #Gene Regulatory Network Analysis #Process Optimization and Integration #Quantitative Methods (q-bio.QM)

paper · pdf · doi:10.48550/arxiv.0811.0514

openalex publication_date 2008/11/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Molecular docking is an essential tool for drug design. It helps the scientist to rapidly know if two molecules, respectively called ligand and receptor, can be combined together to obtain a stable complex. We propose a new multi-objective model combining an energy term and a surface term to gain such complexes. The aim of our model is to provide complexes with a low energy and low surface. This model has been validated with two multi-objective genetic algorithms on instances from the literature dedicated to the docking benchmarking.

Citations

• Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function

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