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

Abstract

Protein design algorithms must search an enormous conformational space to identify favorable conformations. As a result, those that perform this search with guarantees of accuracy generally start with a conformational pruning step, such as dead‐end elimination (DEE). However, the mathematical assumptions of DEE‐based pruning algorithms have up to now severely restricted the biophysical model that can feasibly be used in protein design. To lift these restrictions, I propose to prune local unrealistic geometries (PLUG) using a linear programming‐based method. PLUG's biophysical model consists only of well‐known lower bounds on interatomic distances. PLUG is intended as preprocessing for energy‐based protein design calculations, whose biophysical model need not support DEE pruning. Based on 96 test cases, PLUG is at least as effective at pruning as DEE for larger protein designs—the type that most require pruning. When combined with the LUTE protein design algorithm, PLUG greatly facilitates designs that account for continuous entropy, large multistate designs with continuous flexibility, and designs with extensive continuous backbone flexibility and advanced nonpairwise energy functions. Many of these designs are tractable only with PLUG, either for empirical reasons (LUTE's machine learning step achieves an accurate fit only after PLUG pruning), or for theoretical reasons (many energy functions are fundamentally incompatible with DEE).

Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering

“…Owing to persistent optimization efforts [125][126][127][128], provable algorithms can nowadays be applied for protein design while simultaneously employing both the continuous flexibility of side-chains and enhanced backbone flexibility efficiently at similar computational costs to more rigid approaches. These methods are available in OSPREY 3.0 [129], in which the analysis speed has been further promoted by the newly supported use of GPUs and multicore CPUs for some of the modeling tasks, which were prohibitively complicated for the previous version of the software.…”