Accurately predicting how mutations alter protein–peptide binding remains challenging for molecular simulations because both conformational sampling and binding kinetics are computationally demanding. Here, we investigate whether multi-eGO, a hybrid transferable/structure-based atomistic-resolution model previously developed and validated for protein–small molecule interactions, can be transferred to protein–peptide binding without peptide-specific retraining. Using the PDZ2 domain of protein tyrosine phosphatase basophil-like in complex with the peptide EQVTAV as a benchmark, we first show that multi-eGO reproduces the structural dynamics of PDZ2 and the equilibrium binding thermodynamics of the wild-type complex. The model substantially accelerates both binding and unbinding relative to experiment but accurately preserves the resulting equilibrium dissociation constant. We then introduce conservative mutations in PDZ2 and in the peptide and evaluate their effects on binding without repeating the computationally expensive training procedure. Multi-eGO reproduces the experimentally observed changes in equilibrium dissociation constants, with strong agreement across PDZ2 mutants and moderate agreement when the peptide is also mutated. In contrast, the individual association and dissociation rate constants show substantially weaker agreement with experiment. The results indicate that the simplified energy landscape of multi-eGO limits the quantitative prediction of absolute kinetics while preserving thermodynamic information relevant to relative binding affinity. These findings establish multi-eGO as a computationally efficient approach for protein–peptide recognition and for predicting and rank-ordering the effects of conservative mutations on binding affinity.
Camilla Ardizzone, Bruno Stegani, Fran Bačić Toplek et al.· bioRxiv· 0 citations
Biomolecular condensates formed by intrinsically disordered proteins require molecular models that accurately describe proteins in both dilute solution and condensed phases. Explicit-solvent coarse-grained models offer an attractive balance between chemical resolution and computational efficiency. Yet, it remains unclear whether improving dilute-state properties is sufficient to obtain an accurate description of condensates. Here, we address this question by introducing minimal modifications to the Martini 3 force field that combine recent advances in bonded interactions with refined protein–water interactions and strengthened glycine self-interactions, while preserving the underlying chemical transferability of the model. The resulting model substantially improves the description of single-chain conformations across a diverse benchmark of disordered proteins. We then investigate phase separation of the well-characterized low-complexity domain of heterogeneous nuclear ribonucleoprotein A1 and its sequence variants. The model reproduces several key physicochemical properties of biomolecular condensates, including chain expansion in the dense phase, sequence-dependent intermolecular contacts, protein diffusion and its relation to single-chain dimensions, and hydration, while revealing quantitative limitations in condensate density, phase equilibria, and ion partitioning. Our results show that improving dilute-state behaviour translates into a better description of condensed-phase properties, including condensate density, but is not sufficient to quantitatively reproduce the equilibrium between the dilute and dense phases.
Fran Bačić Toplek, Luís Borges-Araújo, Kresten Lindorff-Larsen et al.· bioRxiv· 0 citations
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