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A Review of Evolutionary Algorithms for Computing Functional Conformations of Protein Molecules

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Computer-Aided Drug Discovery

Part of the book series: Methods in Pharmacology and Toxicology ((MIPT))

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Abstract

The ubiquitous presence of proteins in chemical pathways in the cell and their key role in many human disorders motivates a growing body of protein modeling studies to unravel the relationship between protein structure and function. The foundation of such studies is the realization that knowledge of the structures a protein accesses under physiological conditions is key to a detailed understanding of its biological function and the design of therapeutic compounds for the purpose of altering misfunction in aberrant variants of a protein.

Dry laboratory investigations promise a holistic treatment of the relationship between protein sequence, structure, and function. Significant efforts are made in the dry laboratory to map protein conformation spaces and underlying energy landscapes of proteins. The majority of such efforts employ well-studied computational templates, such as Molecular Dynamics and Monte Carlo. The focus of this review is on a third emerging template, stochastic optimization under the umbrella of evolutionary computation. Algorithms based on such a template, also known as evolutionary algorithms, are showing promise in addressing fundamental computational challenges in protein structure modeling and are opening up new avenues in protein modeling research. This review summarizes evolutionary algorithms for novice readers, while highlighting recent developments that showcase current, state-of-the-art capabilities for experts.

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Acknowledgement

Funding for this work is provided in part by the National Science Foundation (Grant No. 1421001 and CAREER Award No. 1144106) and the Thomas F. and Kate Miller Jeffress Memorial Trust Award.

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Authors and Affiliations

  1. Department of Computer Science, George Mason University, Fairfax, VA, USA

    Amarda Shehu

  2. Department of Bioengineering, George Mason University, Fairfax, VA, USA

    Amarda Shehu

  3. School of Systems Biology, George Mason University, Manassas, VA, USA

    Amarda Shehu

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  1. Amarda Shehu
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Correspondence to Amarda Shehu .

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Editors and Affiliations

  1. Chemistry Department, Southern Research Institute, Birmingham, Alabama, USA

    Wei Zhang

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Shehu, A. (2015). A Review of Evolutionary Algorithms for Computing Functional Conformations of Protein Molecules. In: Zhang, W. (eds) Computer-Aided Drug Discovery. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/7653_2015_47

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  • DOI: https://doi.org/10.1007/7653_2015_47

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3519-2

  • Online ISBN: 978-1-4939-3521-5

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