Evidence map›Paper›PMID 32525263›Full record

ArticleProteins2020

Ligand-protein interactions in lysozyme investigated through a dual-resolution model.

Raffaele Fiorentini, Kurt Kremer, Raffaello Potestio

Abstract read
In one paragraph

Article in Proteins, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Fast, Accurate, and System-Specific Variable-Resolution Modeling of Proteins.Journal of chemical information and modeling · 2023
    Article
  3. Review
  4. Review
  5. 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.

Raffaele FiorentiniMax Planck Institute for Polymer Research, Mainz, Germany.
Kurt KremerMax Planck Institute for Polymer Research, Mainz, Germany.
Raffaello PotestioPhysics Department, University of Trento, Trento, Italy.ORCID 0000-0001-6408-9380

Funding

European Research Council 340906European Research Council 758588
6 · The paper itself

Abstract

A fully atomistic (AT) modeling of biological macromolecules at relevant length- and time-scales is often cumbersome or not even desirable, both in terms of computational effort required and a posteriori analysis. This difficulty can be overcome with the use of multiresolution models, in which different regions of the same system are concurrently described at different levels of detail. In enzymes, computationally expensive AT detail is crucial in the modeling of the active site in order to capture, for example, the chemically subtle process of ligand binding. In contrast, important yet more collective properties of the remainder of the protein can be reproduced with a coarser description. In the present work, we demonstrate the effectiveness of this approach through the calculation of the binding free energy of hen egg white lysozyme with the inhibitor di-N-acetylchitotriose. Particular attention is payed to the impact of the mapping, that is, the selection of AT and coarse-grained residues, on the binding free energy. It is shown that, in spite of small variations of the binding free energy with respect to the active site resolution, the separate contributions coming from different energetic terms (such as electrostatic and van der Waals interactions) manifest a stronger dependence on the mapping, thus pointing to the existence of an optimal level of intermediate resolution.

Indexed as

AnimalsAvian ProteinsBinding SitesChickensFemaleGlycoside Hydrolase InhibitorsLigandsModels, MolecularMuramidaseProtein BindingProtein ConformationProtein Interaction Domains and MotifsStatic ElectricitySubstrate SpecificityThermodynamicsTrisaccharidesAvian ProteinsGlycoside Hydrolase Inhibitorshen egg lysozymeLigandsMuramidaseN,N',N''-triacetylchitotrioseTrisaccharidescoarse-grainingdual-resolution modelingfree energy calculationmultiscale modelingprotein-ligand binding

Identifiers

PMID32525263
PMCPMC7497117

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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.