Publications
Peer-reviewed work on the Triangular Spatial Relationship method and its applications, newest first. Each entry links to the publisher's record through its DOI.
2026
SSE-TSR: An Approach to Integrate Secondary Structure Elements into Triangular Spatial Relationships for Protein Classification
IEEE Transactions on Computational Biology and Bioinformatics, 2026, 23(2), 694–703
Abstract
The proposed method integrates secondary structure elements (SSEs) into TSR-based protein representations, allowing an enriched representation of protein structures by considering 18 different combinations of helix, strand, and coil arrangements.
Application of the TSR-Based Method in Detecting and Quantifying Ligand-Induced Conformational Changes of 14-3-3 Proteins
Challenges and Advances in Computational Chemistry and Physics: Computational Approaches in Drug Design, 2026, 77–98
Quantification of Conformational Changes of Kinase Regulators, Kinases, and Regulator–Kinase Complexes Using the TSR Algorithm
Methods in Molecular Biology: Protein Evolution, 2026, 189–212
Investigation of 3D structural specificities between neurotransmitters and receptors using the TSR-based computational method
Journal of Biomolecular Structure and Dynamics, 2026, 44(12), 5666–5696
2025
A Parallel Implementation for Large-Scale TSR-based 3D Structural Comparisons of Protein and Amino Acid
Current Bioinformatics, 2025, 20(6), 564–579
Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I
BMC Bioinformatics, 2025, 26(1), 15
Application of the Triangular Spatial Relationship Algorithm in Representing and Quantifying Conformational Changes in Chlorophylls and Protein Local Environments
Photochem, 2025, 5(1), 8
Development of the TSR-based computational method to investigate spike and monoclonal antibody interactions
Frontiers in Chemistry, 2025, 13, 1395374
Development of a Novel Method for Representing 3D Structures of Nucleotides Using the Concept of the TSR Algorithm and Evaluation of the Method Through Studying Specific Interactions Between DNAs and p53
Proteins: Structure, Function, and Bioinformatics, 2025, 93(11), 1988–2004
Design of a TSR-based project learning strategy for biochemistry undergraduate teaching and research labs: a case study
Frontiers in Education, 2025, 9, 1455173
2024
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, 112, 108117
Abstract
A new approach to representing ligand and drug 3D structures is introduced and evaluated. A novel algorithm calculating cross TSR keys is developed for enabling comparisons of drug/ligand–target complexes. The results demonstrate the capability of the TSR-based method to interpret hierarchical relationships of drugs and drug–target complexes.
Representing and Quantifying Conformational Changes of Kinases and Phosphatases Using the TSR-Based Algorithm
Kinases and Phosphatases, 2024, 2(4), 315–339
Abstract
The main objective of this study is to provide structural insight into conformational changes. We also aim to link TSR-based structural descriptors to their functions. The 3D structures of 2527 kinases and 505 phosphatases are studied.
2023
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, 103, 107824
Abstract
Mirror-image discrimination capability is introduced into the Triangular Spatial Relationship (TSR)-based key generation formula to capture stereo geometry. Applying mirror images decreases structural similarity, which can be partially explained by the observation of a decrease in common keys. For a hierarchically organized structure dataset, applying mirror images enhances the opportunity to discover specific keys that exclusively belong to certain types of proteins.
2022
A study of a hierarchical structure of proteins and ligand binding sites of receptors using the triangular spatial relationship-based structure comparison method and development of a size-filtering feature designed for comparing different sizes of protein structures
Proteins: Structure, Function, and Bioinformatics, 2022, 90(1), 239–257
Abstract
We propose amino-acid scoring matrices that capture “evolutionary closeness” information based on the BLOSUM62 matrix, and present the development of a new visualization method where keys are organized according to evolutionary closeness and shown in a 2D image.
The specific applications of the TSR-based method in identifying Zn2+ binding sites of proteases and ACE/ACE2
Data in Brief, 2022, 45, 108629
Abstract
We have developed an alignment-free TSR (Triangular Spatial Relationship)-based computational method for protein structural comparison and motif identification and discovery. The dataset and data presented here include additional information that help readers become aware of specific applications of the TSR-based method in protein clustering.
2021
Development of a TSR-Based Method for Protein 3-D Structural Comparison With Its Applications to Protein Classification and Motif Discovery
Frontiers in Chemistry, 2021, 8, 602291
Abstract
We have developed a novel method where the 3-D structure of a protein is modeled using the concept of Triangular Spatial Relationship (TSR), where triangles are constructed with the Cα atoms of a protein as vertices.
Exploring the effectiveness of the TSR-based protein 3-D structural comparison method for protein clustering, and structural motif identification and discovery of protein kinases, hydrolases, and SARS-CoV-2’s protein via the application of amino acid grouping
Computational Biology and Chemistry, 2021, 92, 107479
Abstract
Exploring the effectiveness of the TSR-based method for protein clustering and structural motif identification via amino acid grouping. We have classified the keys into different categories for a better understanding of protein structure relations. Applying amino acid grouping to the TSR-based method modestly improves the accuracy of protein clustering in certain cases.
2017
Descriptor based protein structure representation using triangular spatial relationships in 3-D
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017, 1114–1118