The specific applications of the TSR-based method in identifying Zn

Titli Sarkar, Camille R Reaux, Jianxiong Li, Vijay V Raghavan, Wu Xu

Abstract read

In one paragraph

Article in Data in brief, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it

0cells of the map it votes in

4citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

Quantification of Conformational Changes of Kinase Regulators, Kinases, and Regulator-Kinase Complexes Using the TSR Algorithm.Methods in molecular biology (Clifton, N.J.) · 2026
Article
Development of the TSR-based computational method to investigate spike and monoclonal antibody interactions.Frontiers in chemistry · 2025
Article
Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions.Computational biology and chemistry · 2024
Article
Introducing mirror-image discrimination capability to the TSR-based method for capturing stereo geometry and understanding hierarchical structure relationships of protein receptor family.Computational biology and chemistry · 2023
Article

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Titli SarkarThe Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA 70504, USA.

Camille R ReauxDepartment of Chemistry, University of Louisiana at Lafayette, PO Box 44370, Lafayette, LA 70504, USA.

Jianxiong LiHigh Performance Computing, Frey Computing Services Center, Louisiana State University, Baton Rouge, LA 70803, USA.

Vijay V RaghavanThe Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA 70504, USA.

Wu XuDepartment of Chemistry, University of Louisiana at Lafayette, PO Box 44370, Lafayette, LA 70504, USA.

Funding

Development of a new TSR algorithm to represent sequences of proteins and 3D structures of nucleotides and molecular complexes for mechanistic understanding of protein sequence and structure relationsR15GM144944 · NIGMS · UNIVERSITY OF LOUISIANA AT LAFAYETTE · PI Wu Xu · 2021 to 2026

$963k

NIGMS NIH HHS R15 GM144944

6 · The paper itself

Abstract

We have developed an alignment-free TSR (Triangular Spatial Relationship)-based computational method for protein structural comparison and motif identification and discovery. To demonstrate the potential applications of the method, we have generated two datasets. One dataset contains five classes: Actin/Hsp70, serine protease (chymotrypsin/trypsin/elastase), ArsC/Prdx2, PKA/PKB/PKC, and AChE/BChE at the hierarchical level 1 and twelve groups at the level 2. The other dataset includes representative proteases and ACE/ACE2. The x,y, z coordinates of the structures were obtained from PDB. We calculated the keys (or features) that represent each structure using the TSR-based method. The dataset and data presented here include additional information that help the readers become aware of specific applications of the TSR-based method in protein clustering, identification and discovery of metal ion binding sites as well as to understand the effect of amino acid grouping on protein 3D structural relationships at both global and local levels.

Indexed as

3D structureAlignment-freeAmino acid groupingMetal ion binding siteProtein similarityStructural motifStructure comparisonTSR

Identifiers

PMID36426009

DOI10.1016/j.dib.2022.108629

PMCPMC9679521

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.