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Detalle de: Accurate predictions of protein mutational effects accelerated with a hybrid-topology free energy protocol

Title Accurate predictions of protein mutational effects accelerated with a hybrid-topology free energy protocol
Abstract

Quantifying the effects of point mutations is of utmost interest for pharmaceutical and biotechnological applications. Reliable computational methods range from statistical and AI-based to physics-based approaches, with the optimal balance between accurate and fast predictions remaining a challenge. Free energy perturbation (FEP) simulations, a powerful physics-based approach available for decades, constitutes nowadays a method of common application in protein mutational studies. We present QresFEP-2, a novel hybrid-topology FEP protocol benchmarked on a comprehensive protein stability dataset of 10 protein systems, encompassing almost 600 mutations. QresFEP-2 combines excellent accuracy with the highest computational efficiency among available FEP protocols, and its robustness is further validated through comprehensive domain-wide mutagenesis, assessing the thermodynamic stability of over 400 mutations generated by a systematic mutation scan of the 56-residue B1 domain of streptococcal protein G (Gβ1). We also demonstrate the applicability domain of QresFEP-2 on evaluating site-directed mutagenesis effects on protein-ligand binding, tested on a GPCR, as well as on protein-protein interactions examined on the barnase/barstar complex. QresFEP-2 emerges as an open-source, physics-based alternative for advancing protein engineering, drug design, and elucidating the impact of mutations on human health.

Apa Reference Koenekoop, L., van de Brug, N., Jespers, W., Åqvist, J. & Gutiérrez-de-Terán, H. (2025). Accurate predictions of protein mutational effects accelerated with a hybrid-topology free energy protocol. Communications Chemistry, 8(1). 10.1038/s42004-025-01771-0
Doi 10.1038/s42004-025-01771-0
Publication Date 20 Nov 2025
Publication Type Article
Researcher Hugo Gutiérrez de Terán Castañón
Ontology Computational Methods, Artificial Intelligence, Bioinformatics Software and Tools, Benchmarking, Computational models and simulations, Mutation Analysis and design, Drug Discovery and design, Molecular Interactions/Docking, Protein-Protein Interactions, Protein/Nucleic Acid design
Research Groups
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