Evidence map›Paper›PMID 33415518›Full record

ArticleJournal of molecular modeling2021

Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques.

Keerti Vishwakarma, Hardik Bhatt

Abstract read
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Article in Journal of molecular modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Keerti VishwakarmaDepartment of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, Ahmedabad, 382481, India.
Hardik BhattDepartment of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, Ahmedabad, 382481, India. hardikbhatt23@hotmail.com.ORCID http://orcid.org/0000-0002-6431-0695

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r

Indexed as

Molecular Dynamics SimulationQuantitative Structure-Activity RelationshipClinical Trials as TopicDrug DesignEnzyme InhibitorsHumansInhibitory Concentration 50LigandsMolecular Docking SimulationQuinolinesTelomeraseEnzyme InhibitorsLigandsQuinolinesTelomeraseCoMFACoMSIAMDSMolecular dockingTelomerase

Identifiers

What OpenQuestion holds

Textmetadata
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.