Evidence map›Paper›PMID 40195161›Full record

ReviewCancer chemotherapy and pharmacology2025

Evolution of computational techniques against various KRAS mutants in search for therapeutic drugs: a review article.

Ayesha Mehmood, Mohammed Ageeli Hakami, Hanan A Ogaly, Vetriselvan Subramaniyan, Asaad Khalid, Abdul Wadood

Abstract readReview
PubMed Publisher
In one paragraph

Review in Cancer chemotherapy and pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Ayesha MehmoodDepartment of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan.
Mohammed Ageeli HakamiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Al- Quwayiyah, Riyadh, Saudi Arabia.
Hanan A OgalyChemistry Department, College of Science, King Khalid University, Abha, 61421, Saudi Arabia.
Vetriselvan SubramaniyanDivision of Pharmacology, School of Medical and Life Sciences, Sunway University No. 5, Jalan Universiti, Bandar Sunway, Selangor Darul Ehsan, 47500, Malaysia.
Asaad KhalidHealth Research Center, Jazan University, 114, Jazan, 45142, Saudi Arabia.
Abdul WadoodDepartment of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan. awadood@awkum.edu.pk.

Funding

Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia through Large Research Project under grant number RGP2/152/45. RGP2/152/45
6 · The paper itself

Abstract

KRAS was (Kirsten rat sarcoma viral oncogene homolog) revealed as an important target in current therapeutic cancer research because alteration of RAS (rat sarcoma viral oncogene homolog) protein has a critical role in malignant modification, tumor angiogenesis, and metastasis. For cancer treatment, designing competitive inhibitors for this attractive target was difficult. Nevertheless, computational investigations of the protein's dynamic behavior displayed the existence of temporary pockets that could be used to design allosteric inhibitors. The last decade witnessed intensive efforts to discover KRAS inhibitors. In 2021, the first KRAS G12C covalent inhibitor, AMG 510, received FDA (Food and drug administration) approval as an anticancer medication that paved the path for future treatment strategies against this target. Computer-aided drug designing discovery has long been used in drug development research targeting different KRAS mutants. In this review, the major breakthroughs in computational methods adapted to discover novel compounds for different mutations have been discussed. Undoubtedly, virtual screening and molecular dynamic (MD) simulation and molecular docking are the most considered approach, producing hits that can be employed in subsequent refinements. After comprehensive analysis, Afatinib and Quercetin were computationally identified as hits in different publications. Several authors conducted covalent docking studies with acryl amide warheads groups containing inhibitors. Future studies are needed to demonstrate their true potential. In-depth studies focusing on various allosteric pockets demonstrate that the switch I/II pocket is a suitable site for drug designing. In addition, machine learning and deep learning based approaches provide new insights for developing anti-KRAS drugs. We believe that this review provides extensive information to researchers globally and encourages further development in this particular area of research.

Indexed as

Antineoplastic AgentsNeoplasmsProto-Oncogene Proteins p21(ras)AnimalsDrug DesignDrug DiscoveryHumansMolecular Docking SimulationMolecular Dynamics SimulationMutationAntineoplastic AgentsKRAS protein, humanProto-Oncogene Proteins p21(ras)Allosteric siteCancerDrug designKRASMutation

Identifiers

What Socratic 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 Socratic graph.