Evidence map›Paper›PMID 39519786›Full record

ArticleMolecules (Basel, Switzerland)2024

Discovery of Cyclic Peptide Inhibitors Targeted on TNFα-TNFR1 from Computational Design and Bioactivity Verification.

Jiangnan Zhang, Huijian Zhao, Qianqian Zhou, Xiaoyue Yang, Haoran Qi, Yongxing Zhao, Longhua Yang

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Jiangnan ZhangKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
Huijian ZhaoKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
Qianqian ZhouKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
Xiaoyue YangKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
Haoran QiKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
Yongxing ZhaoKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.ORCID 0000-0002-4128-4543
Longhua YangKey Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.ORCID 0000-0002-3583-8255

Funding

Innovation and Entrepreneurship Training Program for College Students 202310459225Key Scientific and Technological Projects of Henan Province No. 232102311174National Natural Science Foundation of China NSFC No.21803058
6 · The paper itself

Abstract

Activating tumor necrosis factor receptor 1 (TNFR1) with tumor necrosis factor alpha (TNFα) is one of the key pathological mechanisms resulting in the exacerbation of rheumatoid arthritis (RA) immune response. Despite various types of drugs being available for the treatment of RA, a series of shortcomings still limits their application. Therefore, developing novel peptide drugs that target TNFα-TNFR1 interaction is expected to expand therapeutic drug options. In this study, the detailed interaction mechanism between TNFα and TNFR1 was elucidated, based on which, a series of linear peptides were initially designed. To overcome its large conformational flexibility, two different head-to-tail cyclization strategies were adopted by adding a proline-glycine (GP) or cysteine-cysteine (CC) to form an amide or disulfide bond between the N-C terminal. The results indicate that two cyclic peptides, R1_CC4 and α_CC8, exhibit the strongest binding free energies. α_CC8 was selected for further optimization using virtual mutations through in vitro activity and toxicity experiments due to its optimal biological activity. The L16R mutant was screened, and its binding affinity to TNFR1 was validated using ELISA assays. This study designed a novel cyclic peptide structure with potential anti-inflammatory properties, possibly bringing an additional choice for the treatment of RA in the future.

Indexed as

Peptides, CyclicReceptors, Tumor Necrosis Factor, Type ITumor Necrosis Factor-alphaAnti-Inflammatory AgentsArthritis, RheumatoidDrug DesignHumansMolecular Docking SimulationProtein BindingAnti-Inflammatory AgentsPeptides, CyclicReceptors, Tumor Necrosis Factor, Type ITNFRSF1A protein, humanTumor Necrosis Factor-alphacomputational drug designcyclic peptidemolecular dynamics simulationTNFR1TNFα

Identifiers

PMID39519786
PMCPMC11547827

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Registered trials

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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.