What are the molecular determinants of protein–protein binding affinity and whether they are similar to those regulating fold stability are two major questions of molecular biology, whose answers bring important implications both from a theoretical and applicative point of view. Here, we analyze chemical and physical features on a large dataset of protein–protein complexes with reliable experimental binding affinity data and compare them with a set of monomeric proteins for which melting temperature data was available. In particular, we probed the spatial organization of protein (1) intramolecular and intermolecular interaction energies among residues, (2) amino acidic composition, and (3) their hydropathy features. Analyzing the interaction energies, we found that strong Coulombic interactions are preferentially associated with a high protein thermal stability, while strong intermolecular van der Waals energies correlate with stronger protein–protein binding affinity. Statistical analysis of amino acids abundances, exposed to the molecular surface and/or in interaction with the molecular partner, confirmed that hydrophobic residues present on the protein surfaces are preferentially located in the binding regions, while charged residues behave oppositely. Leveraging on the important role of van der Waals interface interactions in binding affinity, we focused on the molecular surfaces in the binding regions and evaluated their shape complementarity, decomposing the molecular patches in the 2D Zernike basis. For the first time, we quantified the correlation between local shape complementarity and binding affinity via the Zernike formalism. In addition, considering the solvent interactions via the residue hydropathy, we found that the hydrophobicity of the binding regions dictates their shape complementary as much as the correlation between van der Waals energy and binding affinity. In turn, these relationships pave the way to the fast and accurate prediction and design of optimal binding regions as the 2D Zernike formalism allows a rapid and superposition-free comparison between possible binding surfaces.

The continuous emergence of novel variants represents one of the major problems in dealing with the SARS-CoV-2 virus. Indeed, also due to its prolonged circulation, more than ten variants of concern emerged, each time rapidly overgrowing the current viral version due to improved spreading features. As, up to now, all variants carry at least one mutation on the spike Receptor Binding Domain, the stability of the binding between the SARS-CoV-2 spike protein and the human ACE2 receptor seems one of the molecular determinants behind the viral spreading potential. In this framework, a better understanding of the interplay between spike mutations and complex stability can help to assess the impact of novel variants. Here, we characterize the peculiarities of the most representative variants of concern in terms of the molecular interactions taking place between the residues of the spike RBD and those of the ACE2 receptor. To do so, we performed molecular dynamics simulations of the RBD-ACE2 complexes of the seven variants of concern in comparison with a large set of complexes with different single mutations taking place on the RBD solvent-exposed residues and for which the experimental binding affinity was available. Analyzing the strength and spatial organization of the intermolecular interactions of the binding region residues, we found that (i) mutations producing an increase of the complex stability mainly rely on instaurating more favorable van der Waals optimization at the cost of Coulombic ones. In particular, (ii) an anti-correlation is observed between the shape and electrostatic complementarities of the binding regions. Finally, (iii) we showed that combining a set of dynamical descriptors is possible to estimate the outcome of point mutations on the complex binding region with a performance of 0.7. Overall, our results introduce a set of dynamical observables that can be rapidly evaluated to probe the effects of novel isolated variants or different molecular systems.

The prolonged circulation of the SARS-CoV-2 virus resulted in the emergence of several viral variants, with different spreading features. Moreover, the increased number of recovered and/or vaccinated people introduced a selective pressure toward variants able to evade the immune system, developed against the former viral versions. This process results in reinfections. Aiming to study the latter process, we first collected a large structural dataset of antibodies in complex with the original version of SARS-CoV-2 Spike protein. We characterized the peculiarities of such antibodies population with respect to a control dataset of antibody-protein complexes, highlighting some statistically significant differences between these two sets of antibodies. Thus, moving our attention to the Spike side of the complexes, we identify the Spike region most prone to interaction with antibodies, describing in detail also the energetic mechanisms used by antibodies to recognize different epitopes. In this framework, fast protocols able to assess the effect of novel mutations on the cohort of developed antibodies would help establish the impact of the variants on the population. Performing a molecular dynamics simulation of the trimeric form of the SARS-CoV-2 Spike protein for the wild type and two variants of concern, that is, the Delta and Omicron variants, we described the physicochemical features and the conformational changes experienced locally by the variants with respect to the original version.Hence, combining the dynamical information with the structural study on the antibody-spike dataset, we quantitatively explain why the Omicron variant has a higher capability of escaping the immune system than the Delta variant, due to the higher conformational variability of the most immunogenic regions. Overall, our results shed light on the molecular mechanism behind the different responses the SARS-CoV-2 variants display against the immune response induced by either vaccines or previous infections. Moreover, our analysis proposes an approach that can be easily extended to both other SARS-CoV-2 variants or different molecular systems.