Evidence map›Paper›PMID 30861030›Full record

ArticlePloS one2019

Effect of set up protocols on the accuracy of alchemical free energy calculation over a set of ACK1 inhibitors.

José M Granadino-Roldán, Antonia S J S Mey, Juan J Pérez González, Stefano Bosisio, Jaime Rubio-Martinez, Julien Michel

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Perturbation Free-Energy Toolkit: An Automated Alchemical Topology Builder.Journal of chemical information and modeling · 2021
    Article
  5. Review
  6. 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

6 authors.

José M Granadino-RoldánDepartamento de Química Física, Facultad de Ciencias Experimentales, Universidad de Jaén, Campus "Las Lagunillas" s/n, Jaén, Spain.ORCID 0000-0002-9527-1158
Antonia S J S MeyEaStCHEM School of Chemistry, Joseph Black Building, Edinburgh, United Kingdom.
Juan J Pérez GonzálezDepartment of Chemical Engineering, Universitat Politecnica de Catalunya, Barcelona, Spain.
Stefano BosisioEaStCHEM School of Chemistry, Joseph Black Building, Edinburgh, United Kingdom.
Jaime Rubio-MartinezDepartament de Química Física, Universitat de Barcelona (UB) and the Institut de Recerca en Quimica Teorica i Computacional (IQTCUB), Martí i Franqués 1, Barcelona, Spain.
Julien MichelEaStCHEM School of Chemistry, Joseph Black Building, Edinburgh, United Kingdom.

Funding

European Research Council 336289
6 · The paper itself

Abstract

Hit-to-lead virtual screening frequently relies on a cascade of computational methods that starts with rapid calculations applied to a large number of compounds and ends with more expensive computations restricted to a subset of compounds that passed initial filters. This work focuses on set up protocols for alchemical free energy (AFE) scoring in the context of a Docking-MM/PBSA-AFE cascade. A dataset of 15 congeneric inhibitors of the ACK1 protein was used to evaluate the performance of AFE set up protocols that varied in the steps taken to prepare input files (using previously docked and best scored poses, manual selection of poses, manual placement of binding site water molecules). The main finding is that use of knowledge derived from X-ray structures to model binding modes, together with the manual placement of a bridging water molecule, improves the R2 from 0.45 ± 0.06 to 0.76 ± 0.02 and decreases the mean unsigned error from 2.11 ± 0.08 to 1.24 ± 0.04 kcal mol-1. By contrast a brute force automated protocol that increased the sampling time ten-fold lead to little improvements in accuracy. Besides, it is shown that for the present dataset hysteresis can be used to flag poses that need further attention even without prior knowledge of experimental binding affinities.

Indexed as

Binding SitesDrug DesignHumansLigandsMolecular Docking SimulationProtein Kinase InhibitorsProtein Structure, TertiaryProtein-Tyrosine KinasesThermodynamicsLigandsProtein Kinase InhibitorsProtein-Tyrosine KinasesTNK2 protein, human

Identifiers

PMID30861030
PMCPMC6413950

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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.