Evidence map›Paper›PMID 34572515›Full record

ArticleBiomolecules2021

Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling.

Jingxuan Qiu, Xinxin Tian, Jiangru Liu, Yulong Qin, Junjie Zhu, Dongpo Xu, Tianyi Qiu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. 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

7 authors.

Jingxuan QiuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Xinxin TianSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Jiangru LiuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Yulong QinSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Junjie ZhuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Dongpo XuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.ORCID 0000-0002-9311-9152
Tianyi QiuShanghai Public Health Clinical Center, Fudan University, Shanghai 200032, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-resistant cases of human immunodeficiency virus (HIV) nucleoside reverse transcriptase inhibitors (NRTI) are constantly accumulating due to the frequent mutations of the reverse transcriptase (RT). Predicting the potential drug resistance of HIV-1 NRTIs could provide instructions for the proper clinical use of available drugs. In this study, a novel proteochemometric (PCM) model was constructed to predict the drug resistance between six NRTIs against different variants of RT. Forty-seven dominant mutation sites were screened using the whole protein of HIV-1 RT. Thereafter, the physicochemical properties of the dominant mutation sites can be derived to generate the protein descriptors of RT. Furthermore, by combining the molecular descriptors of NRTIs, PCM modeling can be constructed to predict the inhibition ability between RT variants and NRTIs. The results indicated that our PCM model could achieve a mean AUC value of 0.946 and a mean accuracy of 0.873 on the external validation set. Finally, based on PCM modeling, the importance of features was calculated to reveal the dominant amino acid distribution and mutation patterns on RT, to reflect the characteristics of drug-resistant sequences.

Indexed as

ChemometricsProteomicsAmino AcidsAmino Acid SequenceDrug Resistance, ViralHIV Reverse TranscriptaseHumansMachine LearningMolecular Docking SimulationMutant ProteinsMutationPeptidesROC CurveAmino AcidsHIV Reverse TranscriptaseMutant ProteinsPeptidesreverse transcriptase, Human immunodeficiency virus 1computational modeldrug resistanceHIVreverse transcriptase

Identifiers

PMID34572515
PMCPMC8467226

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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.