Evidence map›Paper›PMID 27085751›Full record

ArticleJournal of molecular graphics & modelling2016

Fragment oriented molecular shapes.

Ethan Hain, Carlos J Camacho, David Ryan Koes

Abstract read
In one paragraph

Article in Journal of molecular graphics & modelling, 2016. 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

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

2 citing papers in PubMed.

  1. Review
  2. 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.

Ethan HainDepartment of Chemistry, St. Mary's College of Maryland, United States.
Carlos J CamachoDepartment of Computational and Systems Biology, University of Pittsburgh, United States.
David Ryan KoesDepartment of Computational and Systems Biology, University of Pittsburgh, United States. Electronic address: dkoes@pitt.edu.

Funding

Real-time discovery of inhibitors among billion compounds for preview and downloadR01GM097082 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CAMACHO, CARLOS J. · 2011 to 2020
$2.5M
Methods, Tools and Resources for Interactive Online Virtual Screening and Lead OptimizationR01GM108340 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KOES, DAVID RYAN · 2013 to 2020
$1.8M
NIGMS NIH HHS R01 GM097082NIGMS NIH HHS R01 GM108340
6 · The paper itself

Abstract

Molecular shape is an important concept in drug design and virtual screening. Shape similarity typically uses either alignment methods, which dynamically optimize molecular poses with respect to the query molecular shape, or feature vector methods, which are computationally less demanding but less accurate. The computational cost of alignment can be reduced by pre-aligning shapes, as is done with the Volumetric-Aligned Molecular Shapes (VAMS) method. Here, we introduce and evaluate fragment oriented molecular shapes (FOMS), where shapes are aligned based on molecular fragments. FOMS enables the use of shape constraints, a novel method for precisely specifying molecular shape queries that provides the ability to perform partial shape matching and supports search algorithms that function on an interactive time scale. When evaluated using the challenging Maximum Unbiased Validation dataset, shape constraints were able to extract significantly enriched subsets of compounds for the majority of targets, and FOMS matched or exceeded the performance of both VAMS and an optimizing alignment method of shape similarity search.

Indexed as

Drug DesignModels, MolecularMolecular StructureAlgorithmsComputational BiologyDrug Evaluation, PreclinicalMolecular shapeMolecular similarityVirtual screening

Identifiers

PMID27085751
PMCPMC4862882

What OpenQuestion holds

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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.