Protein–protein interactions form central elements of almost all cellular processes. Knowledge of the structure of protein–protein complexes but also of the binding affinity is of major importance to understand the biological function of protein–protein interactions. Even weak transient protein–protein interactions can be of functional relevance for the cell during signal transduction or regulation of metabolism. The structure of a growing number of protein–protein complexes has been solved in recent years. Combined with docking approaches or template‐based methods, it is possible to generate structural models of many putative protein–protein complexes or to design new protein–protein interactions. In order to evaluate the functional relevance of putative or predicted protein–protein complexes, realistic binding affinity prediction is of increasing importance. Several computational tools ranging from simple force‐field or knowledge‐based scoring of single protein–protein complexes to ensemble‐based approaches and rigorous binding free energy simulations are available to predict relative and absolute binding affinities of complexes. With a focus on molecular mechanics force‐field approaches the present review aims at presenting an overview on available methods and discussing advantages, approximations, and limitations of the various methods. This article is categorized under: Molecular and Statistical Mechanics > Molecular Interactions Molecular and Statistical Mechanics > Free Energy Methods Software > Molecular Modeling

The accurate prediction of protein−protein complex geometries is of major importance to ultimately model the complete interactome of interacting proteins in a cell. A major bottleneck is the realistic free energy evaluation of predicted docked structures. Typically, simple scoring functions applied to single-complex structures are employed that neglect conformational entropy and often solvent effects completely. The binding free energy of a predicted protein− protein complex can, however, be calculated using umbrella sampling (US) along a predefined dissociation/association coordinate of a complex. We employed atomistic USmolecular dynamics simulations including appropriate conformational and axial restraints and an implicit generalized Born solvent model to calculate binding free energies of a large set of docked decoys for 20 different complexes. Free energies associated with the restraints were calculated separately. In principle, the approach includes all energetic and entropic contributions to the binding process. The evaluation of docked complexes based on binding free energy calculation was in better agreement with experiment compared to a simple scoring based on energy minimization or MD refinement using exactly the same force field description. Even calculated absolute binding free energies of structures close to the native binding geometry showed a reasonable correlation to experiment. However, still for a number of complexes docked decoys of lower free energy than near-native geometries were found indicating inaccuracies in the force field or the implicit solvent model. Although time consuming the approach may open up a new route for realistic ranking of predicted geometries based on calculated free energy of binding.

The realistic prediction of protein-protein complex structures is import to ultimately model the interaction of all proteins in a cell and for the design of new proteinprotein interactions. In principle, molecular dynamics (MD) simulations allow one to follow the association process under realistic conditions including full partner flexibility and surrounding solvent. However, due to the many local binding energy minima at the surface of protein partners, MD simulations are frequently trapped for long times in transient association states. We have designed a replica-exchange based scheme employing different levels of a repulsive biasing between partners in each replica simulation. The bias acts only on intermolecular interactions based on an increase in effective pairwise van der Waals radii (repulsive scaling (RS)-REMD) without affecting interactions within each protein or with the solvent. For a set of five protein test cases (out of six) the RS-REMD technique allowed the sampling of near-native complex structures even when starting from the opposide site with respect to the native binding site for one partner. Using the same start structures and same computational demand regular MD simulations sampled near native complex structures only for one case.The method showed also improved results for the refinement of docked structures in the vicinity of the native binding geometry compared to regular MD refinement.

Glycosaminoglycans (GAGs), long linear periodic anionic polysaccharides, are key molecules in the extracellular matrix (ECM). Therefore, deciphering their role in the biologically relevant context is important for fundamental understanding of the processes ongoing in ECM and for establishing new strategies in the regenerative medicine. Although GAGs represent a number of computational challenges, molecular docking is a powerful tool for analysis of their interactions. Despite the recent development of GAG‐specific docking approaches, there is plenty of room for improvement. Here, replica exchange molecular dynamics with repulsive scaling (REMD‐RS) recently proved to be a successful approach for protein–protein complexes, was applied to dock GAGs. In this method, effective pairwise radii are increased in different Hamiltonian replicas. REMD‐RS is shown to be an attractive alternative to classical docking approaches for GAGs. This work contributes to setting up of GAG‐specific computational protocols and provides new insights into the nature of these biological systems.

Telomeric DNA consists of tandem repeats of the sequence d(TTAGGG) that form G-quadruplex structures made of stacked guanines with monovalent cations bound at a central cavity. Although different ions can stabilize a G-quadruplex structure, the preferred bound ions are typically K or Na. Several different strand-folding topologies have been reported for Q-quadruplexes formed from telomeric repeats depending on DNA length and ion solution condition. This suggests a possible dependence of the ion selectivity of the central pore on the folding topology of the quadruplex. Molecular dynamics free energy perturbation has been employed to systematically study the relative affinity of the central quadruplex pore for different cation types and the associated energetic and solvation contributions to ion selectivity. The calculations have been performed on two different common quadruplex folding topologies. For both topologies, the same ion selectivity was found with a preference for K followed by Rb and Na, which agrees with the experimentally determined preference for most investigated quadruplexes. The selectivity is determined by a balance between attractive Coulomb interactions and loss of hydration but also modulated by van der Waals contributions. Specificity is mediated by the central guanines and no significant contribution of the nucleic acid backbone. The simulations indicate that different topologies might be stabilized by ions bound at the surface or alternative sites of the quadruplex because the ion specificity of the central pore does not depend on the strand folding topology.