A PDZ tandem repeat folds and unfolds via different pathways

The folding and misfolding of multidomain proteins

Protein folding represents a vital process for any living organism. While significant insights have been gained from studying single-domain proteins, our current knowledge on the folding mechanisms of multidomain proteins remains relatively limited, primarily due to their inherent complexity. The principal aim of this review lies in summarizing the emerging view pertaining multi-domain folding, emphasizing their modular nature, which minimizes misfolding and facilitates evolutionary innovation. We discuss the energetic interplay between domains, highlighting particularly the cases where domain interactions lead to transient misfolded intermediates. These interactions can result in diverse effects, including cooperative folding and domain-specific perturbations, which are particularly relevant to the pathogenesis of neurodegenerative diseases like polyglutamine disorders. The review underscores the critical need to understand multidomain folding, to better comprehend and potentially mitigate the molecular underpinnings of protein misfolding diseases.

Estimation of Ligand Binding Free Energy Using Multi-eGO

The computational study of ligand binding to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of in silico drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by thermodynamic integration, and to probe binding mechanisms, including the description of protein conformational dynamics. The advantages of MD come at a high computational cost, which limits its use. Such cost could be reduced by using coarse-grained models, but their use is generally associated with an undesirable loss of resolution and accuracy. To address the trade-off between speed and accuracy of MD simulations, we describe the use of the recently introduced multi-eGO atomic model for the estimation of binding free energies. We illustrate this approach in the case of the binding of benzene to lysozyme by both thermodynamic integration and metadynamics, showing multiple binding/unbinding pathways of benzene. We then provide equally accurate results for the binding free energy of dasatinib and PP1 to Src kinase by thermodynamic integration. Finally, we show how we can describe the binding of the small molecule 10074-G5 to Aβ42 by single molecule simulations and by explicit titration of the ligand as a function of concentration. These results demonstrate that multi-eGO has the potential to significantly reduce the cost of accurate binding free energy calculations and can be used to develop and benchmark in silico ligand binding techniques.