Concepts and Applications of “Natural Computing” Techniques in De Novo Drug and Peptide Design

Title: Concepts and Applications of “Natural Computing” Techniques in De Novo Drug and Peptide Design

Volume: 16 Issue: 15

Author(s): Jan A. Hiss, Markus Hartenfeller and Gisbert Schneider

Affiliation:

Keywords: De novo design, evolutionary algorithm, particle swarm optimization, ant colony optimization, peptide design, scaffold-hopping, bioisosteric replacement, MHC

Abstract: Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.

Cite this article as:

A. Hiss Jan, Hartenfeller Markus and Schneider Gisbert, Concepts and Applications of “Natural Computing” Techniques in De Novo Drug and Peptide Design, Current Pharmaceutical Design 2010; 16 (15) . https://dx.doi.org/10.2174/138161210791164009