Evidence map›Paper›PMID 30721995›Full record

ArticleMolecular biology and evolution2019

Constrained Mutational Sampling of Amino Acids in HIV-1 Protease Evolution.

Jeffrey I Boucher, Troy W Whitfield, Ann Dauphin, Gily Nachum, Carl Hollins, Konstantin B Zeldovich, Ronald Swanstrom, Celia A Schiffer, Jeremy Luban, Daniel N A Bolon

Open access · greenAbstract read
In one paragraph

Article in Molecular biology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  4. Kinetic coevolutionary models predict the temporal emergence of HIV-1 resistance mutations under drug selection pressure.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

10 authors at 2 institutions in 1 country.

Jeffrey I BoucherDepartment of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA.
Troy W WhitfieldDepartment of Medicine, University of Massachusetts Medical School, Worcester, MA.
Ann DauphinProgram in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA.
Gily NachumDepartment of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA.
Carl HollinsDepartment of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA.
Konstantin B ZeldovichProgram in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA.
Ronald SwanstromDepartment of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC.
Celia A SchifferDepartment of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA.
Jeremy LubanDepartment of Medicine, University of Massachusetts Medical School, Worcester, MA.
Daniel N A BolonDepartment of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA.
University of Massachusetts Chan Medical School · USUniversity of North Carolina at Chapel Hill · US

Funding

Tracking the evolution of drug resistance for highly potent HIV protease inhibitoP01GM109767 · NIGMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SHERMAN, BRIAN WOODY · 2014 to 2018
$8.0M
NIGMS NIH HHS P01 GM109767
6 · The paper itself

Abstract

The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.

Indexed as

Evolution, MolecularPoint MutationGenetic CodeHIV-1HIV ProteaseSelection, GeneticHIV Proteasep16 protease, Human immunodeficiency virus 1fitness landscapeHIVmutation

Identifiers

PMID30721995
PMCPMC6804413
OpenAlexW2808794070

What OpenQuestion 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 OpenQuestion graph.