Deleterious nonsynonymous single nucleotide polymorphisms in human solute carriers: The first comparison of three prediction methods
School of Environment, Biotechnology Institute, Dalian Jiaotong University, Dalian, 116028, China, .European Journal of Drug Metabolism and Pharmacokinetics (Impact Factor: 1.56). 05/2012; 38(1). DOI: 10.1007/s13318-012-0095-8
Abundant nsSNPs have been found in genes coding for human solute carrier (SLC) transporters, but there is little known about the relationship between the genotype and phenotype of nsSNPs in these membrane proteins. It is unknown which prediction method is better suited for the prediction of nonneutral nsSNPs of SLC transporters. We have identified 2,958 validated nsSNPs in human SLC family members 1-47 from the Ensembl genome database and the NCBI SNP database. Using three different algorithms, 37-45 % of nsSNPs in SLC genes were predicted to have functional impacts on transporter function. Predictions largely agreed with the available experimental annotations. Overall, 76.5, 74.4, and 73.5 % of nonneutral nsSNPs were predicted correctly as damaging by SNAP, SIFT, and PolyPhen, respectively, while 67.4, 66.3, and 76.7 % of neutral nsSNPs were predicted correctly as nondamaging by the three methods, respectively. This study identified many amino acids that were likely to be functionally critical but have not yet been studied experimentally. There was a significant concordance between the predicted results of different methods. Evolutionarily nonneutral (destabilizing) amino acid substitutions are predicted to be the basis for the pathogenic alteration of SLC transporter activity that is associated with disease susceptibility and altered drug/xenobiotic response.
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ABSTRACT: Preclinical Research Network pharmacology, based on the theory of systems biology, is a new discipline that analyzes the biological network and screens out the nodes of particular interest, with the aim of designing poly-target drug molecule. It emphasizes maximizing drug efficacy and minimizing adverse effect via the multiple regulation of the signaling pathway. Coincidentally, almost all traditional Chinese medicine (TCM) and worldwide ethnomedicine exert therapeutic effect by targeting multiple molecules of the human body. In this overview, we offer a critique on the present perception of TCM and network pharmacology; illustrate the utility of network pharmacology in the study of single herb, medicine pair, and TCM formula; and summarize the recent progress of TCM-based drug discovery inspired by network pharmacology. Network pharmacology could be of great help in decreasing drug attrition rate and thus is essential in rational and cost-effective drug development. We also pinpoint the current TCM issues that could be tackled by the flexible combined use of network pharmacology and relevant disciplines.Drug Development Research 08/2014; 75(5):299-312. DOI:10.1002/ddr.21214 · 0.77 Impact Factor
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