Functional Non-Synonymous Polymorphisms Prediction Methods: Current Approaches and Future Developments

M.      Gonzalez-Castejon; F.      Marin; C.      Soler-Rivas; G.      Reglero; F.      Visioli; A.      Rodriguez-Casado

Abstract

Non-synonymous single nucleotide polymorphisms (nsSNPs) are genetic variations that affect the encoded protein by an amino acid change. In humans, many naturally-occurring nsSNPs cause protein dysfunction and increase vulnerability to disease. Identification of such nsSNPs provides an important opportunity to develop drugs/nutrients with precise therapeutic targets. Therefore, current biomedical research and medicinal chemistry look for targets and functional nsSNPs, to establish correlation with disease susceptibility and foster rational drug design. We review the molecular bases of missense mutation effects at the protein level, namely on sequence conservation, including stability, conformation, biophysical parameters, and protein-protein interaction. Further, we summarize some computational methods, available information resources, and the current approaches used to predict nsSNPs functionality in human genome, most of which based on protein structures and/or evolutionary conservation. Finally, using an approach paradigmatic of the nsSNPs-gene interactions, we evaluate the functional consequences and phenotypic effects of nsSNPs on two genes associated with cholesterol response. Biophysical changes produced by exchanged amino acids I638V (rs5908) from the 3-hydroxy-3-methylglutaryl- coenzyme A reductase gene, and A370T (rs11669576) from the low density lipoprotein receptor gene have been analyzed with an emphasis on stability, activity, and structure of their related proteins. Based on available data and the results of our study, we propose that, even though the extent and precise nature of nsSNPs role in health and disease is yet to be fully elucidated, targeted investigations are warranted and will – in the future – provide useful tools to develop targeted drugs.

Keywords: Cholesterol, disease, gene, HMGCR, LDLR, non-synonymous single nucleotide polymorphisms, protein structure, protein sequence, structural genomics, functional genomics