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PUBLICATIONS · PEER-REVIEWED RESEARCH
Translating molecular insights into public venues.
A comprehensive collection of peer-reviewed journal articles, conference proceedings, and scientific presentations advancing the frontiers of biomolecular machine learning, structural simulations, and precision drug discovery.
01 —— RESEARCH ARTICLES & PROCEEDINGS
Peer-Reviewed Articles & Proceedings
Filter and explore original publications across computational chemistry, structural bioinformatics, and biomolecular AI categorized by 3 fundamental research pillars.
11 TOTAL WORKS
Total Works
11
Peer-Reviewed Works
Journal Articles
6
International Journals
Proceedings
3
Symposia & Conferences
Landmark Award
1st
Best Oral Presentation (ANSCSE27)
Filter by Research Pillar:
REPRESENT & INTERPRET
3 WorksExplore in Research
PILLAR 01
Molecular Representation Learning & Computations
Designs and develops computational frameworks and models to represent and interpret complex molecular and biological data.
Key Methodologies & Focus:
Graph Convolutional Networks (GCN)Graph Attention Networks (GAT)Spatial Graph EmbeddingsTransfer & Multi-task LearningSelf-Supervised Pretraining
2025Journal ArticleFeatured
SynProtX: a large-scale proteomics-based deep learning model for predicting synergistic anticancer drug combinations
Boonyarit B, Kositchutima M, Phattalung TN, Yamprasert N, Thuwajit C, Rungrotmongkol T, et al.
GigaScience· 2025; 14: giaf080
Cancer Drug CombinationDeep LearningDrug DiscoveryGraph Neural Networks+2 more
2024Journal ArticleFeatured
GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity
Boonyarit B, Yamprasert N, Kaewnuratchadasorn P, Kinchagawat J, Prommin C, Rungrotmongkol T, et al.
Journal of Computational Chemistry· 2024; 45(23): 2001–2023
Drug DiscoveryEGFRGraph Attention MechanismMulti-task Learning+1 more
2024Conference PresentationAward Winner
SynProtX: Artificial Intelligence Toward Enhanced Prediction of Synergistic Cancer Drug Combinations Using Large-Scale Protein Expression Profiling
Boonyarit B, et al.
The 27th International Annual Symposium on Computational Science and Engineering (ANSCSE27)· Best Oral Presentation in Computational Biology Session (Aug 1, 2024)
Best Oral PresentationCancer TherapeuticsSynProtXProteomics
| Year | Publication & Citation Details | Category | Actions |
|---|---|---|---|
| 2025 | Featured SynProtX: a large-scale proteomics-based deep learning model for predicting synergistic anticancer drug combinationsBoonyarit B, Kositchutima M, Phattalung TN, Yamprasert N, Thuwajit C, Rungrotmongkol T, et al. GigaScience· 2025; 14: giaf080 Cancer Drug CombinationDeep LearningDrug DiscoveryGraph Neural NetworksMulti-omics+1 more | Journal Article | |
| 2024 | Featured GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcityBoonyarit B, Yamprasert N, Kaewnuratchadasorn P, Kinchagawat J, Prommin C, Rungrotmongkol T, et al. Journal of Computational Chemistry· 2024; 45(23): 2001–2023 Drug DiscoveryEGFRGraph Attention MechanismMulti-task LearningTransfer Learning | Journal Article | |
| 2024 | Award Winner SynProtX: Artificial Intelligence Toward Enhanced Prediction of Synergistic Cancer Drug Combinations Using Large-Scale Protein Expression ProfilingBoonyarit B, et al. The 27th International Annual Symposium on Computational Science and Engineering (ANSCSE27)· Best Oral Presentation in Computational Biology Session (Aug 1, 2024) Best Oral PresentationCancer TherapeuticsSynProtXProteomics | Conference Presentation |
DISCOVER & DESIGN
5 WorksExplore in Research
PILLAR 02
Molecular Discovery & Design
Discovers and designs novel therapeutic and biological molecules to specific biological activities and targets.
Key Methodologies & Focus:
Synergistic Cancer Drug CombinationsKinase Inhibitor Discovery (EGFR/HER2)Multi-omics & Proteomics IntegrationHigh-Throughput Hit Compound Classification
2023Journal Article
Structure-based virtual screening for potent inhibitors of GH-20 β-N-acetylglucosaminidase: classical and machine learning scoring functions, and molecular dynamics simulations
Phengsakun G, Boonyarit B, Rungrotmongkol T, Suginta W.
Computational Biology and Chemistry· 2023; 107856
GH-20 Beta-N-acetylglucosaminidasesInhibitorsMachine LearningMD Simulations+1 more
2020Journal Article
Potential tripeptides against the tyrosine kinase domain of human epidermal growth factor receptor (HER) 2 through computational and kinase assay approaches
Seetaha S, Boonyarit B, Tongsima S, Songtawee N, Choowongkomon K.
Journal of Molecular Graphics and Modelling· 2020; 97: 107564
Molecular DockingMD SimulationsHER2 Receptor Tyrosine KinaseTripeptides
2021International Proceeding
Docking-based virtual screening and pharmacophore analysis of novel GH-20 β-N-acetylglucosaminidase inhibitors
Phengsakun G, Boonyarit B, Suginta W.
Proceedings of the 7th International Conference on Biochemistry and Molecular Biology (BMB2021)· 2021
Molecular DockingGH-20 GlcNAcasesPharmacophore Analysis
2016International Proceeding
Computational screening of tripeptides against kinase-domain for human epidermal growth factor receptor 2 (HER2)
Boonyarit B, Mokmak W, Tongsima S, Choowongkomon K.
Proceedings of the 42nd Congress on Science and Technology of Thailand (STT42)· 2016; pp. 495 – 504
Molecular DockingHER2TripeptidesTyrosine Kinase
2016Conference Presentation
Computational Screening of Tripeptides Against Kinase-Domain for Human Epidermal Growth Factor Receptor 2 (HER2)
Boonyarit B, et al.
The 42nd Congress on Science and Technology of Thailand (STT42)· Poster Presentation (Nov 30 – Dec 2, 2016)
Poster PresentationHER2Tripeptides
| Year | Publication & Citation Details | Category | Actions |
|---|---|---|---|
| 2023 | Structure-based virtual screening for potent inhibitors of GH-20 β-N-acetylglucosaminidase: classical and machine learning scoring functions, and molecular dynamics simulationsPhengsakun G, Boonyarit B, Rungrotmongkol T, Suginta W. Computational Biology and Chemistry· 2023; 107856 GH-20 Beta-N-acetylglucosaminidasesInhibitorsMachine LearningMD SimulationsVirtual Screening | Journal Article | |
| 2020 | Potential tripeptides against the tyrosine kinase domain of human epidermal growth factor receptor (HER) 2 through computational and kinase assay approachesSeetaha S, Boonyarit B, Tongsima S, Songtawee N, Choowongkomon K. Journal of Molecular Graphics and Modelling· 2020; 97: 107564 Molecular DockingMD SimulationsHER2 Receptor Tyrosine KinaseTripeptides | Journal Article | |
| 2021 | Docking-based virtual screening and pharmacophore analysis of novel GH-20 β-N-acetylglucosaminidase inhibitorsPhengsakun G, Boonyarit B, Suginta W. Proceedings of the 7th International Conference on Biochemistry and Molecular Biology (BMB2021)· 2021 Molecular DockingGH-20 GlcNAcasesPharmacophore Analysis | International Proceeding | |
| 2016 | Computational screening of tripeptides against kinase-domain for human epidermal growth factor receptor 2 (HER2)Boonyarit B, Mokmak W, Tongsima S, Choowongkomon K. Proceedings of the 42nd Congress on Science and Technology of Thailand (STT42)· 2016; pp. 495 – 504 Molecular DockingHER2TripeptidesTyrosine Kinase | International Proceeding | |
| 2016 | Computational Screening of Tripeptides Against Kinase-Domain for Human Epidermal Growth Factor Receptor 2 (HER2)Boonyarit B, et al. The 42nd Congress on Science and Technology of Thailand (STT42)· Poster Presentation (Nov 30 – Dec 2, 2016) Poster PresentationHER2Tripeptides | Conference Presentation |
UNDERSTAND & SIMULATE
3 WorksExplore in Research
PILLAR 03
Molecular Modeling & Simulation
Simulates and models the structure, dynamics, and interactions of biomolecules to uncover molecular mechanisms and functions.
Key Methodologies & Focus:
Molecular Dynamics (MD) SimulationsStructure-Based Virtual Screening (SBVS)Protein-Ligand DockingEnzyme Kinetics & Catalysis
2026Journal ArticleFeatured
Structural and Functional Characterization of a Novel Broad-Spectrum Oligosaccharide Uptake Channel OmpV25 in Vibrio campbellii
Meesrikaew P, Soysa HSM, Boonyarit B, Schulte A, Robinson RC, Suginta W.
Journal of Biological Chemistry· 2026 : Accepted
Vibrio campbelliiPorin StructureMolecular DockingStructural Biology+1 more
2025Journal ArticleFeatured
The structure of an actin nucleus stabilized by villin
Robinson RC, Chongrungreang T, Ponlachantra K, Boonyarit B, Dilly GF, Li YI, et al.
Science Advances· 2025; 11(49): eadw6915
ActinAsgard archaeaGelsolinMolecular Dynamics+3 more
2025International ProceedingFeatured
Enhanced DeHa2 for PFACs Degradation Efficiency through Deep Learning and Molecular Dynamics Simulation Approaches
Tantisuphakornsakul P, Pobsirikasem P, Thirach A, Sirisakwisut P, Uttamapinant C, Boonyarit B.
Proceedings of the 19th International Symposium of the Protein Society of Thailand (PST2025)· 2025; pp. 113 – 125
DeHa2Deep LearningEnzymeMolecular Docking+2 more
| Year | Publication & Citation Details | Category | Actions |
|---|---|---|---|
| 2026 | Featured Structural and Functional Characterization of a Novel Broad-Spectrum Oligosaccharide Uptake Channel OmpV25 in Vibrio campbelliiMeesrikaew P, Soysa HSM, Boonyarit B, Schulte A, Robinson RC, Suginta W. Journal of Biological Chemistry· 2026 : Accepted Vibrio campbelliiPorin StructureMolecular DockingStructural BiologyX-ray Crystallography | Journal Article | |
| 2025 | Featured The structure of an actin nucleus stabilized by villinRobinson RC, Chongrungreang T, Ponlachantra K, Boonyarit B, Dilly GF, Li YI, et al. Science Advances· 2025; 11(49): eadw6915 ActinAsgard archaeaGelsolinMolecular DynamicsStructural Biology+2 more | Journal Article | |
| 2025 | Featured Enhanced DeHa2 for PFACs Degradation Efficiency through Deep Learning and Molecular Dynamics Simulation ApproachesTantisuphakornsakul P, Pobsirikasem P, Thirach A, Sirisakwisut P, Uttamapinant C, Boonyarit B. Proceedings of the 19th International Symposium of the Protein Society of Thailand (PST2025)· 2025; pp. 113 – 125 DeHa2Deep LearningEnzymeMolecular DockingMD Simulation+1 more | International Proceeding |