Evidence map›Paper›PMID 39280611›Full record

ArticleiScience2024

Computational modeling of mast cell tryptase family informs selective inhibitor development.

Ying Ma, Bole Li, Xiangqin Zhao, Yi Lu, Xuesong Li, Jin Zhang, Yifei Wang, Jie Zhang, Lulu Wang, Shuai Meng and 1 more

Abstract read
In one paragraph

Article in iScience, 2024. 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

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

11 authors.

Ying MaDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
Bole LiDepartment of Pharmacy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Xiangqin ZhaoDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
Yi LuDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
Xuesong LiDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
Jin ZhangDepartment of Bone and Soft Tissue Tumors, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Yifei WangDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
Jie ZhangDepartment of Pharmacy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Lulu WangTianjin Key Laboratory of Technologies Enabling Development of Clinical Therapeutics and Diagnostics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Pharmacy, Tianjin Medical University, Tianjin 300070, China.
Shuai MengDepartment of Pharmacy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Jihui HaoDepartment of Pancreatic Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mast cell tryptases, a family of serine proteases involved in inflammatory responses and cancer development, present challenges in structural characterization and inhibitor development. We employed state-of-the-art protein structure prediction algorithms to model the three-dimensional structures of tryptases α, β, δ, γ, and ε with high accuracy. Computational docking identified potential substrates and inhibitors, suggesting overlapping yet distinct activities. Tryptases β, δ, and ε were predicted to act on phenolic compounds, with β and ε additionally hydrolyzing cyanides. Tryptase δ may possess unique formyl-CoA dehydrogenase activity. Virtual screening revealed 63 compounds exhibiting strong binding to tryptase β (TPSB2), 12 exceeding the affinity of the known inhibitor. Notably, the top hit (3-chloro-4-methylbenzimidamide) displayed over 10-fold selectivity for tryptase β over other isoforms. Our integrative approach combining protein modeling, functional annotation, and molecular docking provides a framework for characterizing tryptase isoforms and developing selective inhibitors of therapeutic potential in inflammatory and cancer conditions.

Indexed as

BioinformaticsCancerImmunology

Identifiers

PMID39280611
PMCPMC11396024

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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.