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Structure-based protein-protein interaction networks and drug design

Frontiers of Electrical and Electronic Engineering in China 2013年第3期8卷 183-191页

作者： hammad naveed Jingdong J. Han Chinese Academy of Sciences Key Laboratory of Computational Biology Chinese Academy of Sciences-Max Planck PartnerInstitute for Computational Biology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai200031 China

Proteins carry out their functions by interacting with other proteins and small molecules, forming a complex interaction network. In this review, we briefly introduce classical graph theory based protein-protein interaction networks. We also describe the commonly used experimental methods to construct these networks, and the insights that can be gained from these networks. We then discuss the recent transition from graph theory based networks to structure based protein-protein interaction networks and the advantages of the latter over the former, using two networks as examples. We further discuss the usefulness of structure based protein-protein interaction networks for drug discovery, with a special emphasis on drug repositioning.

关键词： protein-protein interaction network structure-based drug design drug reposition

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Identifying Novel Drug Targets by iDTPnd:A Case Study of Kinase Inhibitors

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Genomics, Proteomics & Bioinformatics 2021年第6期19卷 986-997页

作者： hammad naveed Corinna Reglin Thomas Schubert Xin Gao Stefan T.Arold Michael L.Maitland Toyota Technological Institute at Chicago ChicagoIL 60637USA Department of Computer Science National University of Computer and Emerging SciencesIslamabad 44000Pakistan 2bind GmbH D-93053 RegensburgGermany King Abdullah University of Science and Technology(KAUST) Computational Bioscience Research Center(CBRC)ComputerElectrical and Mathematical Sciences and Engineering(CEMSE)DivisionThuwal 23955Saudi Arabia King Abdullah University of Science and Technology(KAUST) Computational Bioscience Research Center(CBRC)Biological and Environmental Sciences and Engineering(BESE)DivisionThuwal 23955Saudi Arabia Inova Center for Personalized Health and Schar Cancer Institute Falls ChurchVA 22042USA University of Virginia Cancer Center AnnandaleVA 22003USA

Current FDA-approved kinase inhibitors cause diverse adverse effects,some of which are due to the me-chanism-independent effects of these *** these mechanism-independent interactions could improve drug safety and support drug ***,we develop iDTPnd(integrated Drug Target Predictor with negative dataset),a computational approach for large-scale discovery of novel targets for known *** a given drug,we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding *** facilitate assessment of unintended targets,iDTPnd also provides a docking-based interaction score and its statistical *** confirm the interactions of sorafenib,imatinib,dasatinib,sunitinib,and pazopanib with their known targets at a sensitivity of 52%and a specificity of 55%.We also validate 10 predicted novel targets by using in vitro *** results suggest that proteins other than kinases,such as nuclear receptors,cytochrome P450,and MHC class I molecules,can also be physiologically relevant targets of kinase *** method is general and broadly applicable for the identification of protein–small molecule interactions,when sufficient drug–target 3D data are *** code for constructing the structural signatures is available at https://***/Documents/***.

关键词： Protein-drug interaction iDTPnd Kinase inhibitor Drug-binding site signature Drug repurposing

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