Motivation: Current techniques of protein engineering focus mostly on re-designing small targeted regions or defined structural scaffolds rather than constructing combinatorial libraries of versatile compositions and lengths. This is a missed opportunity because combinatorial libraries are emerging as a vital source of novel functional proteins and are of interest in diverse research areas.
Results: Here, we present a computational tool for Combinatorial Library Design (CoLiDe) offering precise control over protein sequence composition, length and diversity. The algorithm uses evolutionary approach to provide solutions to combinatorial libraries of degenerate DNA templates. We demonstrate its performance and precision using four different input alphabet distribution on different sequence lengths. In addition, a model design and experimental pipeline for protein library expression and purification is presented, providing a proof-of-concept that our protocol can be used to prepare purified protein library samples of up to 1011-1012 unique sequences. CoLiDe presents a composition-centric approach to protein design towards different functional phenomena.
Availabilityand implementation: CoLiDe is implemented in Python and freely available at https://github.com/voracva1/CoLiDe.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2020. Published by Oxford University Press.