Prediction of modulators of pyruvate kinase in smiles text using aprori methods

Jason Caronna, Rojita Sharma, Jonathan Marra, Virginia L. Iuorno, Katherine G. Herbert, Jeffrey H. Toney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Pyruvate kinase is an enzyme that catalyzes the formation of pyruvate from phosphenolpyruvate in glycolysis. There is a wealth of data on the activity of certain molecules and their effects on pyruvate kinase. This project aims to create an application that uses a pyruvate kinase dataset to determine the nature of unidentified molecules; whether or not they would be activators or inhibitors of this enzyme. This application uses an Apriori algorithm to identify or predict modulators of pyruvate kinase. This initial study focuses on simplified molecular input line entry specification (SMILES) text as target data to be mined. The three dimensional structure of pyruvate kinase is known and accessible though the Protein Data Bank (e.g., PDB code IA3W).

Original languageEnglish
Title of host publicationITiCSE 2007
Subtitle of host publication12th Annual Conference on Innovation and Technology in Computer Science Education - Inclusive Education in Computer Science
Pages348
Number of pages1
DOIs
StatePublished - 2007
EventITiCSE 2007: 12th Annual Conference on Innovation and Technology in Computer Science Education - Inclusive Education in Computer Science - Dundee, Scotland, United Kingdom
Duration: 25 Jun 200727 Jun 2007

Publication series

NameITiCSE 2007: 12th Annual Conference on Innovation and Technology in Computer Science Education - Inclusive Education in Computer Science

Other

OtherITiCSE 2007: 12th Annual Conference on Innovation and Technology in Computer Science Education - Inclusive Education in Computer Science
Country/TerritoryUnited Kingdom
CityDundee, Scotland
Period25/06/0727/06/07

Keywords

  • Apriori
  • Confidence & support
  • Data mining
  • Enzymes

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