PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions

T Sun, Y Chen, Y Wen, Z Zhu, M Li - Communications biology, 2021 - nature.com
Resistance to small-molecule drugs is the main cause of the failure of therapeutic drugs in
clinical practice. Missense mutations altering the binding of ligands to proteins are one of the …

[HTML][HTML] Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods

DD Wang, L Ou-Yang, H Xie, M Zhu, H Yan - Computational and structural …, 2020 - Elsevier
Purpose Mutation-induced variation of protein-ligand binding affinity is the key to many
genetic diseases and the emergence of drug resistance, and therefore predicting such …

iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations

C Geng, A Vangone, GE Folkers… - Proteins: Structure …, 2019 - Wiley Online Library
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein
engineering and drug design. Machine learning‐based methods are gaining increasing …

mCSM-PPI2: predicting the effects of mutations on protein–protein interactions

CHM Rodrigues, Y Myung, DEV Pires… - Nucleic acids …, 2019 - academic.oup.com
Protein–protein Interactions are involved in most fundamental biological processes, with
disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a …

Quantification of biases in predictions of protein–protein binding affinity changes upon mutations

M Tsishyn, F Pucci, M Rooman - Briefings in bioinformatics, 2024 - academic.oup.com
Understanding the impact of mutations on protein–protein binding affinity is a key objective
for a wide range of biotechnological applications and for shedding light on disease-causing …

mmCSM-PPI: predicting the effects of multiple point mutations on protein–protein interactions

CHM Rodrigues, DEV Pires… - Nucleic Acids Research, 2021 - academic.oup.com
Protein–protein interactions play a crucial role in all cellular functions and biological
processes and mutations leading to their disruption are enriched in many diseases. While a …

Predicting the impact of missense mutations on protein–protein binding affinity

M Li, M Petukh, E Alexov… - Journal of chemical …, 2014 - ACS Publications
The crucial prerequisite for proper biological function is the protein's ability to establish
highly selective interactions with macromolecular partners. A missense mutation that alters …

[PDF][PDF] MutaBind2: predicting the impacts of single and multiple mutations on protein-protein interactions

N Zhang, Y Chen, H Lu, F Zhao, RV Alvarez… - Iscience, 2020 - cell.com
Missense mutations may affect proteostasis by destabilizing or over-stabilizing protein
complexes and changing the pathway flux. Predicting the effects of stabilizing mutations on …

Deep geometric representations for modeling effects of mutations on protein-protein binding affinity

X Liu, Y Luo, P Li, S Song, J Peng - PLoS computational biology, 2021 - journals.plos.org
Modeling the impact of amino acid mutations on protein-protein interaction plays a crucial
role in protein engineering and drug design. In this study, we develop GeoPPI, a novel …

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

S Jemimah, M Sekijima, MM Gromiha - Bioinformatics, 2020 - academic.oup.com
Motivation Protein–protein interactions are essential for the cell and mediate various
functions. However, mutations can disrupt these interactions and may cause diseases …