Pharmacogenomics of the cytochrome P450 2C family: impacts of amino acid variations on drug metabolism.

Pharmacogenomics investigates DNA and RNA variations in the human genome related to drug responses. Cytochrome P450 (CYP) is a supergene family of drug-metabolizing enzymes responsible for the metabolism of approximately 90% of human drugs. Among the major CYP isoforms, the CYP2C subfamily is of clinical significance because it metabolizes approximately 20% of clinically administrated drugs and represents several variant alleles leading to adverse drug reactions or altering drug efficacy. Here, we review recent progress on understanding the interindividual variability of the CYP2C members and the functional and clinical impact on drug metabolism. We summarize current advances in the molecular modeling of CYP2C polymorphisms and discuss the structural bases and molecular mechanisms of amino acid variants of CYP2C members that affect drug metabolism.

A computational approach to structural properties of glycoside hydrolase family 4 from bacteria.

Structural bioinformatics approaches applied to the alpha- and beta-glycosidases from the GH4 enzyme family reveal that, despite low sequence identity, these enzymes possess quite similar global structural characteristics reflecting a common reaction mechanism. Locally, there are a few distinctive structural characteristics of GH4 alpha- and beta-glycosidases, namely, surface cavities with different geometric characteristics and two regions with highly dissimilar structural organizations and distinct physicochemical properties in the alpha- and beta-glucosidases from Thermotoga maritima. We suggest that these structurally dissimilar regions may be involved in specific protein-protein interactions and this hypothesis is sustained by the predicted distinct functional partners of the investigated proteins. Also, we predict that alpha- and beta-glycosidases from the GH4 enzyme family interact with difenoconazole, a fungicide, but there are different features of these interactions especially concerning the identified structurally distinct regions of the investigated proteins.

Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

BACKGROUND: Protein-Protein Interactions (PPIs) are key for many cellular processes. The characterization of PPI interfaces and the prediction of putative ligand binding sites and hot spot residues are essential to design efficient small-molecule modulators of PPI. Terphenyl and its derivatives are small organic molecules known to mimic one face of protein-binding alpha-helical peptides. In this work we focus on several PPIs mediated by alpha-helical peptides. METHOD: We performed computational sequence- and structure-based analyses in order to evaluate several key physicochemical and surface properties of proteins known to interact with alpha-helical peptides and/or terphenyl and its derivatives. RESULTS: Sequence-based analysis revealed low sequence identity between some of the analyzed proteins binding alpha-helical peptides. Structure-based analysis was performed to calculate the volume, the fractal dimension roughness and the hydrophobicity of the binding regions. Besides the overall hydrophobic character of the binding pockets, some specificities were detected. We showed that the hydrophobicity is not uniformly distributed in different alpha-helix binding pockets that can help to identify key hydrophobic hot spots. CONCLUSIONS: The presence of hydrophobic cavities at the protein surface with a more complex shape than the entire protein surface seems to be an important property related to the ability of proteins to bind alpha-helical peptides and low molecular weight mimetics. Characterization of similarities and specificities of PPI binding sites can be helpful for further development of small molecules targeting alpha-helix binding proteins.