Evidence map›Paper›PMID 35163234›Full record

ArticleInternational journal of molecular sciences2022

Identification of New KRAS G12D Inhibitors through Computer-Aided Drug Discovery Methods.

Apoorva M Kulkarni, Vikas Kumar, Shraddha Parate, Gihwan Lee, Sanghwa Yoon, Keun Woo Lee

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Direct GDP-KRASTherapeutic advances in medical oncology · 2023
    Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
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

6 authors.

Apoorva M KulkarniDepartment of Bio and Medical Big Data (BK4 Program), Division of Life Science, Research Institute of Natural Science, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.
Vikas KumarDepartment of Bio and Medical Big Data (BK4 Program), Division of Life Science, Research Institute of Natural Science, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.ORCID 0000-0003-4468-3459
Shraddha ParateDivision of Applied Life Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.ORCID 0000-0001-6566-7496
Gihwan LeeDivision of Applied Life Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.
Sanghwa YoonDepartment of Bio and Medical Big Data (BK4 Program), Division of Life Science, Research Institute of Natural Science, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.
Keun Woo LeeDepartment of Bio and Medical Big Data (BK4 Program), Division of Life Science, Research Institute of Natural Science, Gyeongsang National University, 501 Jinju-daero, Jinju 52828, Korea.

Funding

This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) and funded by the Korean Government (MSIT) NRF-2018M3A9A7057263
6 · The paper itself

Abstract

Owing to several mutations, the oncogene Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is activated in the majority of cancers, and targeting it has been pharmacologically challenging. In this study, using an in silico approach comprised of pharmacophore modeling, molecular docking, and molecular dynamics simulations, potential KRAS G12D inhibitors were investigated. A ligand-based common feature pharmacophore model was generated to identify the framework necessary for effective KRAS inhibition. The chemical features in the selected pharmacophore model comprised two hydrogen bond donors, one hydrogen bond acceptor, two aromatic rings and one hydrophobic feature. This model was used for screening in excess of 214,000 compounds from InterBioScreen (IBS) and ZINC databases. Eighteen compounds from the IBS and ten from the ZINC database mapped onto the pharmacophore model and were subjected to molecular docking. Molecular docking results highlighted a higher affinity of four hit compounds towards KRAS G12D in comparison to the reference inhibitor, BI-2852. Sequential molecular dynamics (MD) simulation studies revealed all four hit compounds them possess higher KRAS G12D binding free energy and demonstrate stable polar interaction with key residues. Further, Principal Component Analysis (PCA) analysis of the hit compounds in complex with KRAS G12D also indicated stability. Overall, the research undertaken provides strong support for further in vitro testing of these newly identified KRAS G12D inhibitors, particularly Hit1 and Hit2.

Indexed as

Computer SimulationDrug DesignDrug DiscoveryHumansHydrogen BondingLigandsMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingProto-Oncogene Proteins p21(ras)Quantitative Structure-Activity RelationshipSmall Molecule LibrariesKRAS protein, humanLigandsProto-Oncogene Proteins p21(ras)Small Molecule Librariesin silicoKRASmolecular dockingmolecular dynamics simulationspharmacophorevirtual screening

Identifiers

PMID35163234
PMCPMC8836163

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.