An adaptive geometric search algorithm for macromolecular scaffold selection.

Tian Jiang,Den Nis Shasha,P Douglas Renfrew,Noah Youngs,Glenn L Butterfoss,Richard Bonneau,Kevin Drew,Brian Kuhlman

doi:10.1093/protein/gzy028

Abstract

A wide variety of protein and peptidomimetic design tasks require matching functional 3D motifs to potential oligomeric scaffolds. For example, during enzyme design, one aims to graft active-site patterns—typically consisting of 3–15 residues—onto new protein surfaces. Identifying protein scaffolds suitable for such active-site engraftment requires costly searches for protein folds that provide the correct side chain positioning to host the desired active site. Other examples of biodesign tasks that require similar fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications, the speed and scaling of geometric searches limits the scope of downstream design to small patterns. Here, we present an adaptive algorithm capable of searching for side chain take-off angles, which is compatible with an arbitrarily specified functional pattern and which enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided. Our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

Highlights

In the past 15 years, protein design has advanced considerably in scale, accuracy and the variety of design tasks carried out by practitioners
We recapitulate an OOP foldamer designed by Drew and coworkers that mimics P53 and can disrupt the P53/MDM2 interaction (Fig. 3), which relies on three hotspot residues on P53 that constitute the majority of the binding affinity for MDM2 (Fig. 3A)
We have presented an adaptive method for finding matches between target geometric patterns and scaffolds

Summary

Introduction

In the past 15 years, protein design has advanced considerably in scale, accuracy and the variety of design tasks carried out by practitioners. Protein engineers have turned toward the redesign of protein active sites and smaller functional patterns that demand sub-angstrom accuracy in the positioning of key side chains. Such works include both the engraftment of known active sites onto new scaffolds (Jiang et al, 2008) as well as the engraftment of novel active sites Reactions) (Röthlisberger et al, 2008) onto new scaffold proteins In these enzyme design applications, active site patterns can become quite large—as residues involved in substrate binding, reaction mechanism and the surrounding environment may be considered. Enzyme design and related design tasks involving functional site or hotspot transplantation depend, in part, upon methods for matching a spatial pattern of chemical functional groups onto large libraries of potential scaffolds (proteins, nucleic acids or synthetic peptidomimetics, for example)

Objectives

Methods

Results

Conclusion