Mapping of the Binding Landscape for a Picomolar Protein-Protein Complex through Computation and Experiment

Abstract

Our understanding of protein evolution would greatly benefit from mapping of binding landscapes, i.e., changes in protein-protein binding affinity due to all single mutations. However, experimental generation of such landscapes is a tedious task due to a large number of possible mutations. Here, we use a simple computational protocol to map the binding landscape for two homologous high-affinity complexes, involving a snake toxin fasciculin and acetylcholinesterase from two different species. To verify our computational predictions, we experimentally measure binding between 25 Fas mutants and the 2 enzymes. Both computational and experimental results demonstrate that the Fas sequence is close to the optimum when interacting with its targets, yet a few mutations could further improve Kd, kon, and koff. Our computational predictions agree well with experimental results and generate distributions similar to those observed in other high-affinity PPIs, demonstrating the potential of simple computational protocols in capturing realistic binding landscapes.

The role of protein “Stability patches” in molecular recognition: A case study of the human growth hormone‐receptor complex

“…A). Moreover, residues that exhibited a negative contribution to the free binding energy, the so‐called “cold spots,” were also static. With the exception of the residues located in the mini‐helix, all the residues that were mutated in the hGH V were static and clustered in the middle of the interfacial SP (Fig.…”

Rapid Fine Conformational Epitope Mapping Using Comprehensive Mutagenesis and Deep Sequencing

“…Additionally, the ability to comprehensively map sequence determinants to binding may help elucidate potential escape mutants and be used to predict whether the antibody will maintain affinity for antigen homologs from model organisms. The sequence-function maps may also be integrated into computational prediction software to improve the predictions of specific antibody-antigen structural contacts at the atomic level or improve computational predictions of individual mutations on protein-protein interactions (28).…”

Saturation scanning of ubiquitin variants reveals a common hot spot for binding to USP2 and USP21

“…To further validate and understand the saturation scanning data, we used an in silico saturation mutagenesis protocol (20,21) to predict the tolerance of each Ub position to mutation. In this protocol, we substituted all Ub residues randomized in this study with the 19 other amino acids and calculated changes in free energy of Ub binding (ΔΔG bind ) to USP2 or USP21 (Fig.…”

“…Such binding landscapes can be obtained by introducing all possible single mutations in the binding site and assessing the consequent effects on affinities (16)(17)(18)(19)(20)(21). However, the low affinities of typical Ub-protein interactions (11) make it difficult to accurately measure the effects of mutations, and thus detailed empirical binding landscapes of Ub-protein interactions have not been reported.…”