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Understanding the molecular mechanisms that correlate pathologies with missense mutations is of critical importance for disease risk estimations and for devising personalized therapies. Thus, we have performed a bioinformatic survey of ClinVar, a database of human genomic variations, to find signals that can account for missense mutation pathogenicity. Arginine resulted as the most frequently replaced amino acid both in benign and pathogenic mutations. By adding the structural dimension to this investigation to increase its resolution, we found that arginine mutations occurring at the protein–DNA interface increase pathogenicity 6.5 times with respect to benign variants. Glycine is the second amino acid among all the pathological missense mutations. Necessarily replaced by larger amino acids, glycine substitutions perturb the structural stability of proteins and, therefore, their functions, being mostly located in buried protein moieties. Arginine and glycine appear as representative of missense mutations causing respective changes in interaction processes and protein structural features, the two main molecular mechanisms of genome-induced pathologies. [ABSTRACT FROM AUTHOR]

Nowadays, it is well established that most of the human diseases which are not related to pathogen infections have their origin from DNA disorders. Thus, DNA mutations, waiting for the availability of CRISPR-like remedies, will propagate into proteomics, offering the possibility to select natural or synthetic molecules to fight against the effects of malfunctioning proteins. Drug discovery, indeed, is a flourishing field of biotechnological research to improve human health, even though the development of a new drug is increasingly more expensive in spite of the massive use of informatics in Medicinal Chemistry. CRISPR technology adds new alternatives to cure diseases by removing DNA defects responsible of genome-related pathologies. In principle, the same technology, however, could also be exploited to induce protein mutations whose effects are controlled by the presence of suitable ligands. In this paper, a new idea is proposed for the realization of mutated proteins, on the surface of which more spacious transient pockets are formed and, therefore, are more suitable for hosting drugs. In particular, new allosteric sites are obtained by replacing amino-acids with bulky side chains with glycine, Gly, the smallest natural amino-acid. We also present a machine learning approach to evaluate the druggability score of new (or enlarged) pockets. Preliminary experimental results are very promising, showing that 10% of the sites created by the Gly-pipe software are druggable. [ABSTRACT FROM AUTHOR]