TMCrys

Predict propensity of success for transmembrane protein crystallization

Julia K. Varga, G. Tusnády

Research output: Contribution to journalArticle

Abstract

Motivation: Transmembrane proteins (TMPs) are crucial in the life of the cells. As they have special properties, their structure is hard to determine––the PDB database consists of 2% TMPs, despite the fact that they are predicted to make up to 25% of the human proteome. Crystallization prediction methods were developed to aid the target selection for structure determination, however, there is a need for a TMP specific service. Results: Here, we present TMCrys, a crystallization prediction method that surpasses existing prediction methods in performance thanks to its specialization for TMPs. We expect TMCrys to improve target selection of TMPs.

Original languageEnglish
Pages (from-to)3126-3130
Number of pages5
JournalBioinformatics
Volume34
Issue number18
DOIs
Publication statusPublished - Jan 1 2018

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Crystallization
Proteins
Protein
Predict
Prediction
Target
Proteome
Specialization
Databases
Cell

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

TMCrys : Predict propensity of success for transmembrane protein crystallization. / Varga, Julia K.; Tusnády, G.

In: Bioinformatics, Vol. 34, No. 18, 01.01.2018, p. 3126-3130.

Research output: Contribution to journalArticle

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