Molecular docking is a method for structure-based drug design which attempts to predict the position and orientation of a small molecule (ligand) in relation to a protein (receptor) in order to produce a stable complex. The goal of molecular docking techniques is to find states with a minimum biding energy. One of the most widely used software packages for this purpose is AutoDock, which incorporates three metaheuristic techniques for that purpose. We propose the integration of AutoDock with jMetalCpp, an optimization framework thereby providing both single- and multi-objective algorithms that can be used to effectively solve docking problems.

The resulting combination of AutoDock + jMetalCpp allows users of the former to easily use the metaheuristics provided by the latter. In this way, biologists have at their disposal a richer set of optimization techniques than those already provided in AutoDock. Moreover, designers of metaheuristic techniques can use molecular docking for case studies, which can lead to more efficient algorithms oriented to solving the target problems

AutoDock 4

AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure.

jMetal (C++ version)

The jMetalCpp project has the goal of providing a C++ implementation of jMetal, a Java framework for multi-objective optimation with metaheuristics. As with the original jMetal framework, our plan is to develop jMetalCpp according to our needs and then sharing the software to allow interested researchers to use it freely.

  1. Esteban López-Camacho, María Jesús García Godoy, Antonio J. Nebro and José F. Aldana-Montes
    jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework.
    Bioinformatics (2014) 30 (3): 437-438 first published online November 22, 2013 doi:10.1093/bioinformatics/btt679
  2. Esteban López-Camacho, María Jesús García Godoy, José García-Nieto, Antonio J. Nebro and José F. Aldana-Montes
    Solving molecular flexible docking problems with metaheuristics: A comparative study.
    Applied Soft Computing (2015) 28: 379-393 doi:10.1016/j.asoc.2014.10.049
  3. María Jesús García Godoy, Esteban López-Camacho, José García-Nieto, Antonio J. Nebro and José F. Aldana-Montes
    Solving molecular docking problems with multi-objective metaheuristics
    Molecules (2015) 20(6): 10154-10183 doi:10.3390/molecules200610154
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