Target‐template relationships in protein structure prediction and their effect on the accuracy of thermostability calculations

Abstract

Improving protein thermostability has been a labor-and time-consuming process in industrial applications of protein engineering. Advances in computational approaches have facilitated the development of more efficient strategies to allow the prioritization of stabilizing mutants. Among these is FEP+, a free energy perturbation implementation that uses a thoroughly tested physicsbased method to achieve unparalleled accuracy in predicting changes in protein thermostability. To gauge the applicability of FEP+ to situations where crystal structures are unavailable, here we have applied the FEP+ approach to homology models of 12 different proteins covering 316 mutations. By comparing predictions obtained with homology models to those obtained using crystal structures, we have identified that local rather than global sequence conservation between target and template sequence is a determining factor in the accuracy of predictions. By excluding mutation sites with low local sequence identity (<40%) to a template structure, we have obtained predictions with comparable performance to crystal structures (R 2 of 0.67 and 0.63 and an RMSE of 1.20 and 1.16 kcal/mol for crystal structure and homology model predictions, respectively) for identifying stabilizing mutations when incorporating residue scanning into a cascade screening strategy. Additionally, we identify and discuss inherent limitations in sequence alignments and homology modeling protocols that translate into the poor FEP+ performance of a few select examples. Overall, our retrospective study provides detailed guidelines for the application of the FEP+ approach using homology models for protein thermostability predictions, which will greatly extend this approach to studies that were previously limited by structure availability.

Rapid protein stability prediction using deep learning representations

“…Interpreting this observation is, however, complicated by the fact that low pLDDT scores are often found in loop regions that might have naturally lower scores, thus increasing the effects of noise and minor outliers on correlation scores. Overall, these results, together with those using the homology models above, indicate that RaSP can also deliver accurate predictions using computationally generated protein structures; we note that similar results have been obtained using other stability prediction methods ( Akdel et al, 2022 ; Valanciute et al, 2023 ; Lihan et al, 2023 ; Keskin Karakoyun et al, 2023 ).…”

Structural Adaptation of the Single-Stranded DNA-Binding Protein C-Terminal to DNA Metabolizing Partners Guides Inhibitor Design

“…The proteins and peptides were parametrized using the recently developed OPLS4 [45] force field. This force field, together with the SPC water model, has already been successfully applied in several drug design-related studies (e.g., [46][47][48]). The whole system was relaxed according to the default protocol of the Desmond program.…”

Development of A. solani β-tubulin models and comparison of docking results for benzo[d]azoles derivatives as potential antifungal agents

“…The Prime commercial program does not have this limitation. Both software products have been successfully used to construct three-dimensional homologous models of proteins or parts thereof [25][26][27][28].…”