Alchemical Free Energy Calculations to Investigate Protein–Protein Interactions: the Case of the CDC42/PAK1 Complex

Abstract

Here, we show that alchemical free energy calculations can quantitatively compute the effect of mutations at the protein–protein interface. As a test case, we have used the protein complex formed by the small Rho-GTPase CDC42 and its downstream effector PAK1, a serine/threonine kinase. Notably, the CDC42/PAK1 complex offers a wealth of structural, mutagenesis, and binding affinity data because of its central role in cellular signaling and cancer progression. In this context, we have considered 16 mutations in the CDC42/PAK1 complex and obtained excellent agreement between computed and experimental data on binding affinity. Importantly, we also show that a careful analysis of the side-chain conformations in the mutated amino acids can considerably improve the computed estimates, solving issues related to sampling limitations. Overall, this study demonstrates that alchemical free energy calculations can conveniently be integrated into the design of experimental mutagenesis studies.

Exploring PROTAC cooperativity with coarse-grained alchemical methods

“…In protein-protein binding, recent applications and development focus on quantifying the relative free energy changes from mutations of single residues. [56][57][58][59][60] To our knowledge, the only case that alchemically estimates PPIs in a three-body setting compares how analogs of inhibitors change aberrant multimerization of the HIV-1 integrase. 61 Their proposed thermodynamic framework involves calculating the relative free energy difference by perturbing small molecules that directly participate at a particular PPI interface.…”

Alchemical Free-Energy Calculations of Watson–Crick and Hoogsteen Base Pairing Interconversion in DNA

“…One such alchemical approach is the restrain–free-energy perturbation–release (R-FEP-R) method that was developed by Levy et al to calculate conformational free-energy differences. The R-FEP-R method is based on the dual-topology FEP method − for calculating the relative binding free energy of two ligands: atoms involved in the conformational change are removed from the initial conformational state and simultaneously grown back in the final conformational state in a series of steps controlled by the coupling parameter λ. Restraints are imposed on these atoms during the FEP calculation to maintain the initial or final conformational state and accelerate convergence, and the free-energy change due to the addition of these restraints is also calculated. The R-FEP-R method performed well against benchmarks of commonly used model systems, including alanine dipeptide, T4 lysozyme, and β-turn flip in ubiquitin. , …”

Free energy perturbation calculations of mutation effects on SARS-CoV-2 RBD::ACE2 binding affinity

“…Here we explore the ability of FEP calculations to reproduce the effects of mutations on the binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein with the human angiotensin converting enzyme 2 (ACE2) using the FEP+ implementation (see Methods). A number of different FEP implementations have been used to study the effects of mutations on protein stability (14), protein-protein binding (15) and protein-ligand binding (16). FEP+ has been employed previously to calculate mutational free energy changes at the protein-protein interfaces obtaining very good correlations with experimental data in these cases (8, 9).…”

“…Free-energy perturbation (FEP) methods have the potential to impact the field as physics-based force fields are, in principle, agnostic to the system being studied. Most current applications have involved the optimization of ligand-protein interaction in the context of small molecule drug design (reviewed in (14)) but recent publications have begun to explore the use of FEP methods to the study of protein-protein interactions (PPIs); specifically, to the effects of interfacial mutations on protein-protein binding free energies (8,9,(15)(16)(17)(18)(19). This is an inherently complex problem since, as opposed to relatively rigid ligand binding pockets, protein-protein interfaces are often quite large and less constrained so that they can more easily undergo conformational change as a result of a mutation.…”

“…Moreover, FEP calculations involve a complex computational infrastructure and are extremely time consuming. However, fast graphical processing units (GPUs) made such calculations feasible and a number of recent publications, involving different software packages, suggest that the methodology has reached the point that good correlation with experiment is to be expected (8,9,(15)(16)(17)(18)(19). Clearly, if FEP methods are capable of providing meaningful results, then in many applications, the computational cost will be worthwhile.…”