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Computational approaches to detect allosteric pathways in transmembrane molecular machines.

ABSTRACT: Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

SUBMITTER: Stolzenberg S

PROVIDER: S-EPMC4877268 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Computational approaches to detect allosteric pathways in transmembrane molecular machines.

Stolzenberg Sebastian S Michino Mayako M LeVine Michael V MV Weinstein Harel H Shi Lei L

Biochimica et biophysica acta 20160122 7 Pt B

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic ...[more]

PMID: 26806157

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Project description:Introduction: Pompe disease (PD) is a disease caused by pathogenic variations in the GAA gene known as glycogen storage disease type II, characterized by heart hypertrophy, respiratory failure, and muscle hypotonia, leading to premature death if not treated early. The only treatment option, enzyme replacement therapy (ERT), significantly improves the prognosis for some patients while failing to help others. In this study, the determination of key genes involved in the response to ERT and potential molecular mechanisms were investigated. Methods: Gene Expression Omnibus (GEO) data, accession number GSE38680, containing samples of biceps and quadriceps muscles was used. Expression array data were analyzed using BRB-Array Tools. Biceps group patients did not receive ERT, while quadriceps received treatment with rhGAA at 0, 12, and 52 weeks. Differentially expressed genes (DEGs) were deeply analyzed by DAVID, GO, KEGG and STRING online analyses, respectively. Results: A total of 1727 genes in the biceps group and 1198 genes in the quadriceps group are expressed differently. It was observed that DEGs were enriched in the group that responded poorly to ERT in the 52nd week. Genes frequently changed in the weak response group; the expression of 530 genes increased and 1245 genes decreased compared to 0 and 12 weeks. The GO analysis demonstrated that the DEGs were mainly involved in vascular smooth muscle contraction, lysosomes, autophagy, regulation of actin cytoskeleton, inflammatory response, and the WNT signaling pathway. We also discovered that the WNT signaling pathway is highly correlated with DEGs. Several DEGs, such as WNT11, WNT5A, CTNNB1, M6PR, MYL12A, VCL, TLN, FYN, YES1, and BCL2, may be important in elucidating the mechanisms underlying poor response to ERT. Conclusion: Early diagnosis and treatment of PD are very important for the clinic of the disease. As a result, it suggests that the enriched genes and new pathways emerging as a result of the analysis may help identify the group that responds poorly to treatment and the outcome of the treatment. Obtained genes and pathways in neonatal screening will guide diagnosis and treatment.

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Computational approaches to detect allosteric pathways in transmembrane molecular machines.

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Computational approaches to detect allosteric pathways in transmembrane molecular machines.

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