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Recent studies have identified cyclic GMP-AMP synthase (cGAS) as an important target for treating autoimmune diseases, and several inhibitors of human cGAS (hcGAS) and their structures in complexation with hcGAS have been reported. However, the mechanisms via which these inhibitors interact with hcGAS are not completely understood. Here, we aimed to assess the performance of molecular mechanics/Poisson&ndash, Boltzmann solvent-accessible surface area (MM/PBSA) in evaluating the binding affinity of various hcGAS inhibitors and to elucidate their detailed interactions with hcGAS from an energetic viewpoint. Using molecular dynamics (MD) simulation and MM/PBSA approaches, the estimated free energies were in good agreement with the experimental ones, with a Pearson&rsquo, s correlation coefficient and Spearman&rsquo, s rank coefficient of 0.67 and 0.46, respectively. In per-residue energy decomposition analysis, four residues, K362, R376, Y436, and K439 in hcGAS were found to contribute significantly to the binding with inhibitors via hydrogen bonding, salt bridges, and various &pi, interactions, such as &pi, &middot, &pi, stacking, cation&middot, hydroxyl&middot, and alkyl&middot, interactions. In addition, we discussed other key interactions between specific residues and ligands, in particular, between H363 and JUJ, F379 and 9BY, and H437 and 8ZM. The sandwiched structures of the inhibitor bound to the guanidinium group of R376 and the phenyl ring of Y436 were also consistent with the experimental data. The results indicated that MM/PBSA in combination with other virtual screening methods, could be a reliable approach to discover new hcGAS inhibitors and thus is valuable for potential treatments of cGAS-dependent inflammatory diseases.

Reliable prediction of binding affinities for ligand-receptor complex has been the primary goal of a structure-based drug design process. In this respect, alchemical methods are evolving as a popular choice to predict the binding affinities for biomolecular complexes. However, the highly flexible protein-ligand systems pose a challenge to the accuracy of binding free energy calculations mostly due to insufficient sampling. Herein, integrated computational protocol combining free energy perturbation based absolute binding free energy calculation with free energy landscape method was proposed for improved prediction of binding free energy for flexible protein-ligand complexes. The proposed method is applied to the dataset of various classes of p53-MDM2 (murine double minute 2) inhibitors. The absolute binding free energy calculations for MDMX (murine double minute X) resulted in a mean absolute error value of 0.816 kcal/mol while it is 3.08 kcal/mol for MDM2, a highly flexible protein compared to MDMX. With the integration of the free energy landscape method, the mean absolute error for MDM2 is improved to 1.95 kcal/mol.

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.