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J Comput Chem. 2017 Sep 15;38(24):2118-2126. doi: 10.1002/jcc.24847. Epub 2017 Jun 12.

GaudiMM: A modular multi-objective platform for molecular modeling.

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1
Departament de Química, Universitat Autónoma de Barcelona, Cerdanyola del Vallès, Barcelona, 08193, Spain.

Abstract

GaudiMM (for Genetic Algorithms with Unrestricted Descriptors for Intuitive Molecular Modeling) is here presented as a modular platform for rapid 3D sketching of molecular systems. It combines a Multi-Objective Genetic Algorithm with diverse molecular descriptors to overcome the difficulty of generating candidate models for systems with scarce structural data. Its grounds consist in transforming any molecular descriptor (i.e. those generally used for analysis of data) as a guiding objective for PES explorations. The platform is written in Python with flexibility in mind: the user can choose which descriptors to use for each problem and is even encouraged to code custom ones. Illustrative cases of its potential applications are included to demonstrate the flexibility of this approach, including metal coordination of multidentate ligands, peptide folding, and protein-ligand docking. GaudiMM is available free of charge from https://github.com/insilichem/gaudi.

KEYWORDS:

genetic algorithms; metallopeptides; molecular modeling; multi-objective optimization; protein-ligand docking

PMID:
28605037
DOI:
10.1002/jcc.24847

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