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 |
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