Evidence map›Paper›PMID 35337101›Full record

ArticlePharmaceuticals (Basel, Switzerland)2022

Exploring the Prominent and Concealed Inhibitory Features for Cytoplasmic Isoforms of Hsp90 Using QSAR Analysis.

Magdi E A Zaki, Sami A Al-Hussain, Syed Nasir Abbas Bukhari, Vijay H Masand, Mithilesh M Rathore, Sumer D Thakur, Vaishali M Patil

Open access · goldAbstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2022. 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
0.9field-weighted citation impact, top 24% 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, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B.International journal of molecular sciences · 2022
    Article
  4. 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 at 3 institutions in 2 countries.

Magdi E A ZakiDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia.
Sami A Al-HussainDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia.
Syed Nasir Abbas BukhariDepartment of Pharmaceutical Chemistry, College of Pharmacy, Jouf University, Al Jouf 72388, Saudi Arabia.ORCID 0000-0001-8125-7972
Vijay H MasandDepartment of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India.
Mithilesh M RathoreDepartment of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 602, Maharashtra, India.
Sumer D ThakurDepartment of Chemistry, RDIK and NKD College, Badnera-Amravati 444 701, Maharashtra, India.
Vaishali M PatilDepartment of Pharmaceutical Chemistry, KIET School of Pharmacy, KIET Group of Institutions, Delhi-NCR, Ghaziabad 201206, Uttar Pradesh, India.
Imam Mohammad ibn Saud Islamic University · SAJouf University · SASant Gadge Baba Amravati University · IN

Funding

Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia RG-21-09-77
6 · The paper itself

Abstract

Cancer is a major life-threatening disease with a high mortality rate in many countries. Even though different therapies and options are available, patients generally prefer chemotherapy. However, serious side effects of anti-cancer drugs compel us to search for a safer drug. To achieve this target, Hsp90 (heat shock protein 90), which is responsible for stabilization of many oncoproteins in cancer cells, is a promising target for developing an anti-cancer drug. The QSAR (Quantitative Structure-Activity Relationship) could be useful to identify crucial pharmacophoric features to develop a Hsp90 inhibitor. Therefore, in the present work, a larger dataset encompassing 1141 diverse compounds was used to develop a multi-linear QSAR model with a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The new developed six-parameter model satisfies the recommended values for a good number of validation parameters such as R2tr = 0.78, Q2LMO = 0.77, R2ex = 0.78, and CCCex = 0.88. The present analysis reveals that the Hsp90 inhibitory activity is correlated with different types of nitrogen atoms and other hidden structural features such as the presence of hydrophobic ring/aromatic carbon atoms within a specific distance from the center of mass of the molecule, etc. Thus, the model successfully identified a variety of reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with Hsp90.

Indexed as

cancerHsp90machine learningpharmacophoresQSAR

Identifiers

PMID35337101
PMCPMC8953649
OpenAlexW4214928575

What OpenQuestion holds

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LicenceCC BY
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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.