New computational protein design methods for de novo small molecule binding sites.

James E Lucas,Tanja Kortemme,Nikolay V Dokholyan

doi:10.1371/journal.pcbi.1008178

James E Lucas, Tanja Kortemme + Show 1 more

Open Access

https://doi.org/10.1371/journal.pcbi.1008178

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Abstract

Protein binding to small molecules is fundamental to many biological processes, yet it remains challenging to predictively design this functionality de novo. Current state-of-the-art computational design methods typically rely on existing small molecule binding sites or protein scaffolds with existing shape complementarity for a target ligand. Here we introduce new methods that utilize pools of discrete contacts between protein side chains and defined small molecule ligand substructures (ligand fragments) observed in the Protein Data Bank. We use the Rosetta Molecular Modeling Suite to recombine protein side chains in these contact pools to generate hundreds of thousands of energetically favorable binding sites for a target ligand. These composite binding sites are built into existing scaffold proteins matching the intended binding site geometry with high accuracy. In addition, we apply pools of side chain rotamers interacting with the target ligand to augment Rosetta’s conventional design machinery and improve key metrics known to be predictive of design success. We demonstrate that our method reliably builds diverse binding sites into different scaffold proteins for a variety of target molecules. Our generalizable de novo ligand binding site design method provides a foundation for versatile design of protein to interface previously unattainable molecules for applications in medical diagnostics and synthetic biology.

Highlights

Despite significant advances in de novo design of protein structures, innovations in algorithms and methodologies for the computational design of protein function have not kept pace [1,2]
Current methods are limited by the availability of structurally characterized protein-ligand complexes and the inability of design methods to incorporate appropriate residues at the protein-ligand interface that predictably yield a functional binding site
In this work we introduce a new set of methods that combines information from the Protein Data Bank (PDB) with the Rosetta Macromolecular Modeling Suite to improve our ability to design new binding sites for arbitrary small molecules

Summary

Introduction

Despite significant advances in de novo design of protein structures, innovations in algorithms and methodologies for the computational design of protein function have not kept pace [1,2]. It remains challenging to design proteins that bind new small molecule ligands [3,4]. On-demand design of proteins with defined small-molecule binding functionality would have many applications in bioremediation, synthetic biology, and medical diagnostics. Various strategies have been developed and successfully applied to the computational design of ligand binding function [5,6]. PocketOptimizer correctly predicted mutations that impart higher affinity in small molecule ligand binding sites in 69% of cases [8]. The BBK algorithm [9] as implemented in the OSPREY protein design software package [10] applies an ensemble-based branch-and-bound approach to efficiently identify highest-affinity sequences for ligand-binding sites in a design problem containing up to 106 sequences. The Erebus web server [11] uses geometric descriptions of atoms positioned in space relative to each other to identify protein structures in the PBD that possess a potential ligand binding site of interest

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