Evidence map›Paper›PMID 37517604›Full record

ReviewDrug discovery today2023

Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism.

Jingchen Zhai, Viet Hoang Man, Beihong Ji, Lianjin Cai, Junmei Wang

Open access · greenAbstract readReview
In one paragraph

Review in Drug discovery today, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.7field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Soft drugs: design principles and topical applications.Nature reviews. Drug discovery · 2026
    Review
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  7. Frontiers in bioinformatics · 2026
    Review
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  17. Investigation ofComputational and structural biotechnology journal · 2024
    Review
  18. Article
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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

5 authors at 1 institution in 1 country.

Jingchen ZhaiDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Viet Hoang ManDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Beihong JiDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Lianjin CaiDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Junmei WangDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA. Electronic address: junmei.wang@pitt.edu.
University of Pittsburgh · US

Funding

New Generation of General AMBER Force Field for Biomedical ResearchR01GM147673 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WANG, JUNMEI, YANG, WEI · 2022 to 2025
$1.5M
AI-Powered Biased Ligand DesignR01GM149705 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Junmei Wang · 2023 to 2026
$1.3M
Development of novel computational protocols to study amyloid oligomerizationK25AG070277 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MAN, VIET HOANG · 2021 to 2025
$736k
NIA NIH HHS K25 AG070277NIGMS NIH HHS R01 GM147673NIGMS NIH HHS R01 GM149705
6 · The paper itself

Abstract

The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme-drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery.

Indexed as

Cytochrome P-450 Enzyme SystemDrug DiscoveryDrug InteractionsCytochrome P-450 Enzyme SystemCYP450 inhibitorCYP450 metabolismCYP450 predictioncytochrome P450drug discoverydrug research and development

Identifiers

PMID37517604
PMCPMC10543639
OpenAlexW4385336636

What OpenQuestion holds

Textmetadata
LicenceTDM
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.