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Updated: May 25, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Molecular Modeling of Protein-Peptide Complexes Mimicking Factor Xa-Prothrombin Using AlphaFold-Multimer and
Dejvid Veizaj1, David A Poole2, Ka Lei Cheung1
1Department of Internal Medicine, Division of Thrombosis and Hemostasis, Einthoven Laboratory for Vascular and Regenerative Medicine, Leiden University Medical Center, Leiden 2333 ZA, The Netherlands.
None:
Accurately predicting how point mutations influence protease activity is a major challenge in protein engineering and in the study of coagulation disorders. Factor Xa (FXa) catalyzes the proteolytic activation of prothrombin, a critical step in thrombin generation, yet the molecular details of direct enzyme-substrate recognition and the impact of pathogenic variants remain incompletely defined. Here, we combined AlphaFold-Multimer modeling with explicit-solvent molecular dynamics (MD) simulations to investigate simplified FXa-substrate interactions using prothrombin-derived peptides encompassing the Arg271 and Arg320 cleavage sites in the absence of the full prothrombinase complex. AlphaFold predictions identified catalytically competent peptide orientations, while subsequent MD simulations and free energy analyses identified key contributions of the P1 and P4 cleavage site residues to FXa binding. Distinct stability and affinity differences between the two cleavage sites were highlighted. Active site variants associated with factor X deficiency demonstrated variant-specific disruptions in peptide engagement, implicating key residues within the FXa active site as critical determinants of catalytic activity. Experimental validation with recombinant FXa variants was consistent with the computational predictions, indicating comparable inhibition by the prothrombin peptides. Together, these findings establish an integrative computational-experimental framework for probing local protease-substrate recognition, rationalizing the effects of disease-causing mutations, and guiding the design of therapeutic protease variants.
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