Analysis of AlphaFold and molecular dynamics structure predictions of mutations in serpins
Pedro GarridoiD, Miguel Carmena‐BargueñoiD, María Eugenia de la Morena‐BarrioiD, Carlos Bravo‐PéreziD, Belén de la Morena‐BarrioiD, Rosa Cifuentes‐Riquelme, Marı́a Luisa LozanoiD, Horacio Pérez‐SáncheziD, Javier CorraliD
Abstract
Serine protease inhibitors (serpins) include thousands of structurally conserved proteins playing key roles in many organisms. Mutations affecting serpins may disturb their conformation, leading to inactive forms. Unfortunately, conformational consequences of mutations affecting serpins are difficult to predict. In this study we integrate experimental data of patients with mutations affecting one serpin with the predictions obtained by AlphaFold and molecular dynamics. Five SERPINC1 mutations causing antithrombin deficiency, the strongest congenital thrombophilia, (p.Arg79Cys; p.Pro112Ser, p.Met283Val; p.Pro352insValPheLeuPro, and p.Glu241_Leu242delinsValLeuValLeuValAsnThrArgThr-Ser) were selected from a cohort of 350 unrelated patients based on functional, biochemical, and crystallographic evidence supporting a folding defect. AlphaFold gave an accurate prediction for the wild-type antithrombin structure. However, it only produced native structures for all variants, regardless of its complexity and in-vivo conformational consequences. Similarly, molecular dynamics of up to 1000 ns at temperatures that caused conformational transitions did not show significant changes in the native structure of wild-type or variants. In conclusion, one predictive tool of protein folding, AlphaFold, and a simulation method for analyzing the physical movements of atoms and molecules, molecular dynamics, force predictions into the native stressed conformation at conditions with experimental evidence supporting a conformational change to relaxed structures. It is necessary to improve predictive strategies for serpins that consider the conformational sensitivity of these molecules.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 22
- FWCI
- 2.99
- Field percentile
- top 7%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins
Gia G. Maisuradze, Abhishek Thakur, … Ronald M. Levy·bioRxiv·Feb 10, 2025
- Adversarial Sequence Mutations in AlphaFold andESMFold Reveal Nonphysical StructuralInvariance, Confidence Failures, and Concerns forProtein Design
Jonathan Feldman, Maximilian Brogi, Jeffrey Skolnick·Computational and Structural Biotechnology JournalPeer-reviewed·Mar 1, 2026
- Using AlphaFold to predict the impact of single mutations on protein stability and function
Marina A. Pak, Karina A. Markhieva, … Dmitry N. Ivankov·PLoS ONEPeer-reviewed·Mar 16, 2023
- Rosetta Energy Analysis of AlphaFold2 models: Point Mutations and Conformational Ensembles
R. A. Stein, H. S. Mchaourab·bioRxiv·Sep 5, 2023
- AlphaFold2's training set powers its predictions of fold-switched conformations
Joseph W. Schafer, Lauren L. Porter·bioRxiv·Oct 11, 2024
- AlphaFold2 can predict single-mutation effects
J. M. Mcbride, V. Reinharz, … T. Tlusty·Physical Review LettersPeer-reviewed·Nov 20, 2023