Evidence map›Paper›PMID 34888727›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Creating Maps of the Ligand Binding Landscape for Kinetics-Based Drug Discovery.

Tom Dixon, Samuel D Lotz, Alex Dickson

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. 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
–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

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.

  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.

Tom DixonDepartment of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, USA.
Samuel D LotzDepartment of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, USA.
Alex DicksonDepartment of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI, USA. alexrd@msu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulations of ligand-protein interactions can be very useful for drug design and to gain biological insight. Full pathways of ligand-protein binding can be used to get information about ligand binding transition states, which form the rate-limiting step of the binding and release processes. However, these simulations are typically limited by the presence of large energy barriers that separate stable poses of interest. Here we describe a simulation protocol for exploring and analyzing landscapes of ligand-protein interactions that makes use of molecular docking, enhanced molecular simulation with the weighted ensemble algorithm, and network analysis. It can be accomplished using a modest cluster of graphics processing units and freely accessible software. This protocol focuses on the construction and analysis of a network model of ligand binding poses and provides links to resources that describe the other steps in more detail. The end result of this protocol is a map of the ligand-protein binding landscape that identifies transition states of the ligand binding pathway, as well as alternative bound poses that could be stabilized with modifications to the ligand.

Indexed as

Drug DiscoveryBinding SitesKineticsLigandsMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingProteinsLigandsProteinsKineticsLigand bindingMolecular dynamicsNetwork analysisTransition pathsWeighted ensemble

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.