TMQuery: a database of precomputed template modeling scores for assessment of protein structural similarity

Author:

Price Stephen1ORCID,Tombeur Stéphane2,Hudson Alexander3,Sathiyamoorthy Nanda Kumar4ORCID,Smyth Paul5,Singh Anjana4,Peccianti Mara3,Baroncelli Elisa3,Essaghir Ahmed5,Ferlenghi Ilaria3,Phogat Sanjay Kumar3,Singh Gurpreet6ORCID

Affiliation:

1. Computational Biology Department, Carnegie Mellon University , Pittsburgh, PA, USA

2. RADIX , Bruxelles, Belgium

3. GSK , Siena, Italy

4. Cognizant Technology Solutions , Pune, Maharashtra, India

5. GSK , Rixensart, Belgium

6. GSK , Philadelphia, PA, USA

Abstract

Abstract Summary Comparisons of protein structures are critical for developing novel protein designs, annotating protein functions and predicting protein structure. The template modeling score (TM-score) is a widely used but computationally expensive measure of protein similarity that is applicable to a wide variety of structural biology problems. We introduce TMQuery—a continuously updated database containing over eight billion pre-computed TM-score values for every pair of proteins in the Protein Data Bank, allowing researchers to quickly query and download TM-scores via a web interface. Availability and implementation Publicly available at https://tmquery.gsk.com/.

Funder

GlaxoSmithKline Biologicals SA

Publisher

Oxford University Press (OUP)

Subject

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

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