ProAffiMuSeq: sequence-based method to predict the binding free energy change of protein–protein complexes upon mutation using functional classification

Abstract

Abstract Motivation Protein–protein interactions are essential for the cell and mediate various functions. However, mutations can disrupt these interactions and may cause diseases. Currently available computational methods require a complex structure as input for predicting the change in binding affinity. Further, they have not included the functional class information for the protein–protein complex. To address this, we have developed a method, ProAffiMuSeq, which predicts the change in binding free energy using sequence-based features and functional class. Results Our method shows an average correlation between predicted and experimentally determined ΔΔG of 0.73 and mean absolute error (MAE) of 0.86 kcal/mol in 10-fold cross-validation and correlation of 0.75 with MAE of 0.94 kcal/mol in the test dataset. ProAffiMuSeq was also tested on an external validation set and showed results comparable to structure-based methods. Our method can be used for large-scale analysis of disease-causing mutations in protein–protein complexes without structural information. Availability and implementation Users can access the method at https://web.iitm.ac.in/bioinfo2/proaffimuseq/. Supplementary information Supplementary data are available at Bioinformatics online.