Evidence map›Paper›PMID 27478367›Full record

ArticleBioinformatics and biology insights2016

Molecular Shape Analysis-Guided Virtual Screening Platform for Adenosine Kinase Inhibitors.

Savita Bhutoria, Ballari Das, Nanda Ghoshal

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics and biology insights, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 92% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Savita BhutoriaStructural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, India.
Ballari DasDepartment of Bioinformatics, West Bengal University of Technology, Kolkata, India.
Nanda GhoshalStructural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata, India.
Indian Institute of Chemical Biology · INMaulana Abul Kalam Azad University of Technology, West Bengal · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a new application of molecular shape descriptors in hierarchical selection during virtual screening (VS). Here, a structure-based pharmacophore and docking-guided VS protocol have been evolved to identify inhibitors against adenosine kinase (AK). The knowledge gained on the shape requirements has been extrapolated in classifying active and inactive molecules against this target. This classification enabled us to pick the appropriate ligand conformation in the binding site. We have suggested a set of hierarchical filters for VS, from a simple molecular shape analysis (MSA) descriptor-based recursive models to docking scores. This approach permits a systematic study to understand the importance of spatial requirements and limitations for inhibitors against AK. Finally, the guidelines on how to select compounds for AK to achieve success have been highlighted. The utility of this approach has been suggested by giving an example of database screening for plausible active compounds.

Indexed as

adenosine kinasedockingmolecular shape analysisstructure-based pharmacophorevirtual screening

Identifiers

PMID27478367
PMCPMC4954751
OpenAlexW2497837971

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.