Depressive disorders (DDs) are one of the most widespread forms of psychiatric pathology. According to the World Health Organization, about 350 million people in the world are affected by this condition. Family and twin studies have demonstrated that the contribution of genetic factors to the risk of the onset of DDs is quite large. Various methodological approaches (analysis of candidate genes, genome-wide association analysis, genome-wide sequencing) have been used, and a large number of the associations between genes and different clinical DD variants and DD subphenotypes have been published. However, in most cases, these associations have not been confirmed in replication studies, and only a small number of genes have been proven to be associated with DD development risk. To ascertain the role of genetic factors in DD pathogenesis, further investigations of the relevant conditions are required. Special consideration should be given to the polygenic characteristics noted in whole-genome studies of the heritability of the disorder without a pronounced effect of the major gene. These observations accentuate the relevance of the analysis of gene-interaction roles in DD development and progression. It is important that association studies of the inherited variants of the genome should be supported by analysis of dynamic changes during DD progression. Epigenetic changes that cause modifications of a gene's functional state without changing its coding sequence are of primary interest. However, the opportunities for studying changes in the epigenome, transcriptome, and proteome during DD are limited by the nature of the disease and the need for brain tissue analysis, which is possible only postmortem. Therefore, any association studies between DD pathogenesis and epigenetic factors must be supplemented through the use of different animal models of depression. A threefold approach comprising the combination of gene association studies, assessment of the epigenetic state in DD patients, and analysis of different “omic” changes in animal depression models will make it possible to evaluate the contribution of genetic, epigenetic, and environmental factors to the development of different forms of depression and to help develop ways to decrease the risk of depression and improve the treatment of DD.

The diffusion of small gases to special binding sites within polypeptide matrices pivotally defines the biochemical specificity and reactivity of proteins. We investigate here explicit O(2) diffusion in adult human hemoglobin (HbA) as a case study employing the recently developed temperature-controlled locally enhanced sampling (TLES) method and vary the parameters to greatly increase the simulation efficiency. The method is carefully validated against standard molecular dynamics (MD) simulations and available experimental structural and kinetic data on ligand diffusion in T-state deoxyHbA. The methodology provides a viable alternative approach to traditional MD simulations and/or potential of mean force calculations for: (i) characterizing kinetically accessible diffusion tunnels and escape routes for light ligands in porous proteins; (ii) very large systems when realistic simulations require the inclusion of multiple subunits of a protein; and (iii) proteins that access short-lived conformations relative to the simulation time. In the case of T-state deoxyHbA, we find distinct ligand diffusion tunnels consistent with the experimentally observed disparate Xe cavities in the α- and β-subunits. We identify two distal barriers including the distal histidine (E7) that control access to the heme. The multiple escape routes uncovered by our simulations call for a review of the current popular hypothesis on ligand escape from hemoglobin. Larger deviations from the crystal structure during simulated diffusion in isolated α- and β-subunits highlight the dampening effects of subunit interactions and the importance of including all subunits of multisubunit proteins to map realistic kinetically accessible diffusion tunnels and escape routes.

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