Algorithm-supported, mass and sequence diversity-oriented random peptide library design

Daniela Kalafatovic,Toni Todorovski,Goran Mauša,Ernest Giralt

doi:10.1186/s13321-019-0347-6

Abstract

Random peptide libraries that cover large search spaces are often used for the discovery of new binders, even when the target is unknown. To ensure an accurate population representation, there is a tendency to use large libraries. However, parameters such as the synthesis scale, the number of library members, the sequence deconvolution and peptide structure elucidation, are challenging when increasing the library size. To tackle these challenges, we propose an algorithm-supported approach to peptide library design based on molecular mass and amino acid diversity. The aim is to simplify the tedious permutation identification in complex mixtures, when mass spectrometry is used, by avoiding mass redundancy. For this purpose, we applied multi (two- and three-)-objective genetic algorithms to discriminate between library members based on defined parameters. The optimizations led to diverse random libraries by maximizing the number of amino acid permutations and minimizing the mass and/or sequence overlapping. The algorithm-suggested designs offer to the user a choice of appropriate compromise solutions depending on the experimental needs. This implies that diversity rather than library size is the key element when designing peptide libraries for the discovery of potential novel biologically active peptides.

Highlights

Small-molecule libraries are widely used in drug discovery to identify biologically active molecules [1]
A high chemical and structural diversity can be achieved by designing libraries composed of sequences of amino acids which total number is calculated using the formula R = mr, where r is the number of positions where the variability can be introduced and m the number of amino acids per position [22]
The introduction of complexity of the system refers to the molecular weight ( MW ) diversity of Scheme 1 Towards the algorithm-supported design of random peptide libraries. a Amino acid toolbox of L- and D-stereoisomers of 20 proteinogenic amino acids color-coded to represent a specific property: hydrophobic-aromatic, hydrophobic-aliphatic, hydrophilic-uncharged, hydrophilic-positively charged, and hydrophilic-negatively charged. b Graphical representation of building an OBOC peptide library, based on dipeptides (r = 2), using the representative amino acids from the toolbox (m = 5), depicting the advantage of working with sequences having unique masses

Summary

Introduction

Small-molecule libraries are widely used in drug discovery to identify biologically active molecules [1]. Small molecule library design is based on a known target structure or on known ligands. Molecular docking is the main approach in the structure-based peptidyl-drug design studies, even though peptide based drugs are less explored than the small molecule ones. There is a need to develop combinatorial approaches to identify new peptide therapeutics [5]. In this context, phage display was the main approach to obtain a variety of random peptide sequences [8, 9]. The phage display technology is well established in the peptide-based drug discovery process [10, 11].

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Conclusion