Evidence map›Paper›PMID 29633047›Full record

ArticleJournal of cheminformatics2018

KRDS: a web server for evaluating drug resistance mutations in kinases by molecular docking.

Aeri Lee, Seungpyo Hong, Dongsup Kim

Open access · goldAbstract read
In one paragraph

Article in Journal of cheminformatics, 2018. 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
0.6field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Aeri LeeDepartment of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea.
Seungpyo HongDivision of Nutrition and Metabolism Research, Korea Food Research Institute, Wanju-gun, Jeollabuk-do, Republic of Korea.
Dongsup KimDepartment of Bio and Brain Engineering, KAIST, Daejeon, 34141, Republic of Korea. kds@kaist.ac.kr.
Korea Advanced Institute of Science and Technology · KRKorea Food Research Institute · KR

Funding

Bio-Synergy Research Project NRF-2017M3A9C4065952Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea HI12C0014
6 · The paper itself

Abstract

Kinases are major targets of anti-cancer therapies owing to their importance in signaling processes that regulate cell growth and proliferation. However, drug resistance has emerged as a major obstacle to cancer therapy. Resistance to drugs has various underlying mechanisms, including the acquisition of mutations at drug binding sites and the resulting reduction in drug binding affinity. Therefore, the identification of mutations that are relevant to drug resistance may be useful to overcome this issue. We hypothesized that these mutations can be identified by combining recent advances in computational methods for protein structure modeling and ligand docking simulation. Hence, we developed a web-based tool named the Kinase Resistance Docking System (KRDS) that enables the assessment of the effects of mutations on kinase-ligand interactions. KRDS receives a list of mutations in kinases, generates structural models of the mutants, performs docking simulations, and reports the results to users. The changes in docking scores and docking conformations can be analyzed to infer the effects of mutations on drug binding and drug resistance. We expect our tool to improve our understanding of drug binding mechanisms and facilitate the development of effective new drugs to overcome resistance related to kinases; it may be particularly useful for biomedical researchers who are not familiar with computational environments. Our tool is available at http://bcbl.kaist.ac.kr/KRDS/ .

Indexed as

DockingDrug resistanceEnsembleKinasePoint mutation

Identifiers

PMID29633047
PMCPMC5891443
OpenAlexW2798338906

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.