Evidence map›Paper›PMID 34170848›Full record

ArticleAging2021

Computational study on new natural compound agonists of dopamine receptor.

Hui Li, Wenzhuo Yang, Jianxin Xi, Zhenhua Wang, Han Lu, Zhishan Du, Weihang Li, Bo Wu, Shanshan Jiang, Yida Peng and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2021. 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
0.5field-weighted citation impact, top 33% of its field
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, 4 citations in OpenAlex.

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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

14 authors at 6 institutions in 2 countries.

Hui LiDepartment of Neurology, The First Hospital of Jilin University, Changchun, China.
Wenzhuo YangClinical College, Jilin University, Changchun, China.
Jianxin XiClinical College, Jilin University, Changchun, China.
Zhenhua WangClinical College, Jilin University, Changchun, China.
Han LuClinical College, Jilin University, Changchun, China.
Zhishan DuClinical College, Jilin University, Changchun, China.
Weihang LiDepartment of Orthopaedic Surgery, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Bo WuDepartment of Orthopaedic Surgery, The First Hospital of Jilin University, Changchun, China.
Shanshan JiangChinese Academy of Sciences, Research Group of Evolution and Population Genomics, Institute of Zoology, Beijing, China.
Yida PengCollege of Computer Science and Technology, Jilin University, Changchun, China.
Jingyi LiuDepartment of Biomedical Informatics, Harvard Medical School, Cambridge, MA 02115, USA.
Luwei LiuDepartment of Biomedical Informatics, Harvard Medical School, Cambridge, MA 02115, USA.
Xiangheng ZhangDepartment of Neurosurgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Jiachun FengDepartment of Neurology, The First Hospital of Jilin University, Changchun, China.
Jilin University · CNFirst Hospital of Jilin University · CNHarvard University · USAir Force Medical University · CNInstitute of Zoology · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dopamine receptor, a polypeptide chain composed of 7 hydrophobic transmembrane regions, is a new and vital drug target, especially Dopamine receptor 2(D2). Targeting dopamine receptors, Dopamine receptor agonists are a class of drugs similar in function and structure to dopamine and can directly act on dopamine receptors and activate it. Clinically, Dopamine receptor agonist drugs have achieved significant therapeutic effects on prolactinoma and Parkinson's Disease. In the study, we virtually screened a series of potential effective agonists of Dopamine receptor by computer techniques. Firstly, we used the Molecular Docking (LibDock) step to screen out some molecules that can dock well with the protein. Then, analysis of toxicity prediction and ADME (adsorption, distribution, metabolism and excretion) were carried out. More precise molecular docking (CDOCKER) and 3-Dimensional Quantitative Structure-Activity Relationship Modeling Study(3D-QSAR) pharmacophore generation were implemented to research and explore these compounds' binding mechanism with Dopamine receptor. Last but not least, to assess compound's binding stabilities, we carried out a molecular dynamic analysis. As the results show, two compounds (ZINC000008860530 and ZINC000004096987) from the small molecule database (ZINC database) were potential effective agonists of Dopamine receptor. These two compounds can combine with Dopamine receptor with higher affinity and proved to be no toxic. The cell experiment showed that two compounds could inhibit the proliferation and PRL secretion of MMQ cells (pituitary tumor cells). Thus, this study provided valuable information about Dopamine receptor agonist-based drug discovery. So, this study will benefit patients with prolactinoma and Parkinson's disease a lot.

Indexed as

Molecular Docking SimulationBiological ProductsBromocriptineCell Line, TumorCell SurvivalDopamine AgonistsDrug Evaluation, PreclinicalHumansHydrogen BondingLigandsMolecular Dynamics SimulationProlactinReceptors, DopamineBiological ProductsBromocriptineDopamine AgonistsLigandsProlactinReceptors, Dopamineagonistdopamine receptor (DAR)Parkinson's diseaseprolactinomavirtual screening

Identifiers

PMID34170848
PMCPMC8266345
OpenAlexW3175673349

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.