OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design

Abstract

Summary Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (1), we used our OSPREY (Open Source Protein REdesign for You) suite of CSPD algorithms to prospectively predict resistance mutations that arise in the active site of the dihydrofolate reductase enzyme from methicillin-resistant Staphylococcus aureus (SaDHFR) in response to selective pressure from an experimental competitive inhibitor. We demonstrated that our top predicted candidates are indeed viable resistant mutants. Since that study, we have significantly enhanced the capabilities of OSPREY with not only improved modeling of backbone flexibility, but also efficient multi-state design, fast sparse approximations, partitioned rotamers for more accurate energy bounds, and a computationally efficient representation of molecular-mechanics and quantum-mechanical energy functions. Here, using SaDHFR as an example, we present a protocol for resistance prediction using the latest version of OSPREY. Specifically, we show how to use a combination of positive and negative design to predict active site escape mutations that maintain the enzyme’s catalytic function but selectively ablate binding of an inhibitor.

PLUG (Pruning of Local Unrealistic Geometries) removes restrictions on biophysical modeling for protein design

“…By presenting PLUG, this paper makes the following contributions: A method for pruning portions of protein (or other polymer) conformational space based on geometry and a model of steric clashes. A method to apply this pruning method in protein designs using the LUTE algorithm, greatly facilitating its use with extensive backbone flexibility, nonpairwise energy functions, and continuous sidechain entropy and in multistate designs. Many of these designs would not be practical without PLUG, as shown empirically here. Empirical results on 96 design test cases using 36 protein structures, demonstrating that PLUG's pruning power is comparable to the previous state of the art, while it allows the use of a wider range of biophysical models in protein design. An implementation of PLUG in the open‐source OSPREY protein design software package, available at www.github.com/markhallen369/OSPREY_refactor …”

“…PLUG is implemented in the OSPREY 10,[34][35][36] open-source protein design package. OSPREY has yielded many designs that performed well experimentally-in vitro 29,[37][38][39][40][41][42] and in vivo 29,38,40,41 as well as in non-human primates 41 -and contains a wide array of flexibility modeling options and provably accurate design algorithms.…”

PLUG (Pruning of Local Unrealistic Geometries) removes restrictions on biophysical modeling for protein design

“…PLUG is implemented in the osprey 11,13,14,35 open-source protein design package. osprey has yielded many designs that performed well experimentally-in vitro 1,8,12,16,38,43,45 and in vivo 8,16,38,43 as well as in non-human primates 43 -and contains a wide array of flexibility modeling options and provably accurate design algorithms 11,14 .…”

CATS (Coordinates of Atoms by Taylor Series): protein design with backbone flexibility in all locally feasible directions

“…We have implemented CATS in the OSPREY ( Gainza et al , 2013 ; Georgiev et al , 2008b , 2009 ; Ojewole et al , 2017 ) open-source protein design package. OSPREY has yielded many designs that performed well experimentally— in vitro ( Chen et al , 2009 ; Frey et al , 2010 ; Georgiev et al , 2012 ; Gorczynski et al , 2007 ; Roberts et al , 2012 ; Rudicell et al , 2014 ; Stevens et al , 2006 ) and in vivo ( Frey et al , 2010 ; Gorczynski et al , 2007 ; Roberts et al , 2012 ; Rudicell et al , 2014 ) as well as in non-human primates ( Rudicell et al , 2014 )—and contains a wide array of flexibility modeling options and provably accurate design algorithms ( Gainza et al , 2013 ; Georgiev et al , 2009 ).…”