iGPCR-drug

'iGPCR-drug' is a software tool that has been developed to predict drug interactions with G-protein-coupled receptors (GPCRs) in cellular networking. GPCRs involve many diseases like cancer, diabetes, neurodegenerative, inflammatory, and respiratory disorders. GPCRs are among the most frequent targets of therapeutic drugs. However, determining whether a drug and a GPCR are to interact with each other in a cellular network is time-consuming and expensive purely by means of experimental techniques.
To overcome this situation, a sequence-based classifier called "iGPCR-drug" was developed to predict the interactions between GPCRs and drugs in cellular networking. The predictor uses a 2D fingerprint to formulate the drug compound, a PseAAC (pseudo amino acid composition) generated with the grey model theory to generate GPCR, and the prediction engine is operated by the fuzzy K-nearest neighbor algorithm.

Topic

Networks;Pharmacology;Protein interactions;Compound libraries and screening

Detail

  • Operation: Protein interaction network analysis

  • Software interface: Web user interface

  • Language: -

  • License: -

  • Cost: Free

  • Version name: -

  • Credit: The National Natural Science Foundation of China, the Key Project of Chinese Ministry of Education, the Province National Natural Science Foundation of JiangXi, the Department of Education of JiangXi Province, the Jiangxi Provincial Foreign Scientific and Technological Cooperation Project.

  • Input: -

  • Output: -

  • Contact: jdzxiaoxuan@163.com

  • Collection: -

  • Maturity: -

Publications

  • iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking.
  • Xiao X, et al. iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking. iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking. 2013; 8:e72234. doi: 10.1371/journal.pone.0072234
  • https://doi.org/10.1371/journal.pone.0072234
  • PMID: 24015221
  • PMC: PMC3754978

Download and documentation

    Currently not available or not maintained.

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