Evidence map›Paper›PMID 36745307›Full record

ArticleMolecular diversity2024

Integrated use of ligand and structure-based virtual screening, molecular dynamics, free energy calculation and ADME prediction for the identification of potential PTP1B inhibitors.

Bharti Devi, Sumukh Satyanarayana Vasishta, Bhanuranjan Das, Anurag T K Baidya, Rahul Salmon Rampa, Manoj Kumar Mahapatra, Rajnish Kumar

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular diversity, 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
2.2field-weighted citation impact, top 13% 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, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 1 institution in 1 country.

Bharti DeviDepartment of Pharmaceutical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India.
Sumukh Satyanarayana VasishtaDepartment of Chemical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India.
Bhanuranjan DasDepartment of Pharmaceutical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India.
Anurag T K BaidyaDepartment of Pharmaceutical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India.
Rahul Salmon RampaDepartment of Pharmaceutical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India.
Manoj Kumar MahapatraKanak Manjari Institute of Pharmaceutical Sciences, Rourkela, Odisha, 769015, India.
Rajnish KumarDepartment of Pharmaceutical Engineering & Technology, Indian Institute of Technology (B.H.U.), Varanasi, UP, 221005, India. rajnish.phe@iitbhu.ac.in.ORCID http://orcid.org/0000-0002-7021-6996
Indian Institute of Technology BHU · IN

Funding

Science and Engineering Research Board SRG/2021/000415
6 · The paper itself

Abstract

Protein tyrosine phosphatases (PTPs) are the group of enzymes that control both cellular activity and the dephosphorylation of tyrosine (Tyr)-phosphorylated proteins. Dysregulation of PTP1B has contributed to numerous diseases including Diabetes Mellitus, Alzheimer's disease, and obesity rendering PTP1B as a legitimate target for therapeutic applications. It is highly challenging to target this enzyme because of its highly conserved and positively charged active-site pocket motivating researchers to find novel lead compounds against it. The present work makes use of an integrated approach combining ligand-based and structure-based virtual screening to find hit compounds targeting PTP1B. Initially, pharmacophore modeling was performed to find common features like two hydrogen bond acceptors, an aromatic ring and one hydrogen bond donor from the potent PTP1B inhibitors. The dataset of compounds matching with the common pharmacophoric features was filtered to remove Pan-Assay Interference substructure and to match the Lipinski criteria. Then, compounds were further prioritized using molecular docking and top fifty compounds with good binding affinity were selected for absorption, distribution, metabolism, and excretion (ADME) predictions. The top five compounds with high solubility, absorption and permeability holding score of - 10 to - 9.3 kcal/mol along with Ertiprotafib were submitted to all-atom molecular dynamic (MD) studies. The MD studies and binding free energy calculations showed that compound M4, M5 and M8 were having better binding affinity for PTP1B enzyme with ∆G

Indexed as

Enzyme InhibitorsMolecular Docking SimulationMolecular Dynamics SimulationProtein Tyrosine Phosphatase, Non-Receptor Type 1Drug Evaluation, PreclinicalHumansLigandsProtein BindingStructure-Activity RelationshipThermodynamicsEnzyme InhibitorsLigandsProtein Tyrosine Phosphatase, Non-Receptor Type 1PTPN1 protein, humanMD simulationMM_PBSAPharmacophore modelingPTP1B inhibitorsVirtual screening

Identifiers

PMID36745307
OpenAlexW4319295032

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.