TMCrys
TMCrys predicts crystallization propensity of transmembrane proteins (TMPs) to support target selection for structural studies.
Key Features:
- TMP specialization: Predicts crystallization propensity specifically for transmembrane proteins (TMPs).
- Crystallization propensity prediction: Estimates likelihood of successful crystallization for TMP targets.
- Improved predictive accuracy: Focuses exclusively on TMPs to address limitations of general crystallization prediction methods and enhance prediction accuracy.
- Focus on TMP-specific characteristics: Developed with attention to the unique characteristics of transmembrane proteins.
Scientific Applications:
- Target selection for structural studies: Predicts which TMPs are more likely to yield successful crystallization, supporting prioritization of targets for structure determination.
- Prioritization of experiments and resources: Helps allocate experimental effort and resources toward TMPs with higher predicted crystallization success.
- Support for therapeutic target characterization: Aids selection of TMPs for structural characterization that are potential therapeutic targets.
Methodology:
Leverages specialization for transmembrane proteins to inform prediction of crystallization propensity.
Topics
Details
- License:
- GPL-3.0
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- R, Perl
- Added:
- 6/1/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Varga JK, Tusnády GE. TMCrys: predict propensity of success for transmembrane protein crystallization. Bioinformatics. 2018;34(18):3126-3130. doi:10.1093/bioinformatics/bty342. PMID:29718100. PMCID:PMC6137969.
PMID: 29718100
PMCID: PMC6137969
Funding: - Hungarian Scientific Research Fund: K119287
- Hungarian Academy of Sciences: FIEK_16-1-2016-0005, LP2012/35
- National Research, Development and Innovation Fund: ÚNKP-16-2_VBK-016