Evidence map›Paper›PMID 31360332›Full record

ArticleComputational and structural biotechnology journal2019

A Web Tool for Ranking Candidate Drugs Against a Selected Disease Based on a Combination of Functional and Structural Criteria.

Evangelos Karatzas, George Minadakis, George Kolios, Alex Delis, George M Spyrou

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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  5. Network-based stage-specific drug repurposing for Alzheimer's disease.Computational and structural biotechnology journal · 2022
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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

5 authors.

Evangelos KaratzasDepartment of Informatics and Telecommunications, University of Athens, 15703 Athens, Greece.
George MinadakisThe Cyprus Institute of Neurology and Genetics, 6 International Airport Avenue, Nicosia, 2370, Cyprus.
George KoliosLaboratory of Pharmacology, Department of Medicine, Democritus University of Thrace, Greece.
Alex DelisDepartment of Informatics and Telecommunications, University of Athens, 15703 Athens, Greece.
George M SpyrouThe Cyprus Institute of Neurology and Genetics, 6 International Airport Avenue, Nicosia, 2370, Cyprus.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug repurposing techniques allow existing drugs to be tested against diseases outside their initial spectrum, resulting in reduced cost and eliminating the long time-frames of new drug development. In silico drug repurposing further speeds up the process either by proposing drugs suitable to invert the transcriptomic profile of a disease or by indicating drugs based on their common targets or structural similarity with other drugs with similar mode of action. Such methods usually return a number of potential repurposed drugs that need to be tested against the disease in in vitro, pre-clinical and clinical studies. Thus, it is crucial to have a more sophisticated candidate drug ranking in order to start testing from the most promising chemical substances. As a means to enhance the above decision process, we present CoDReS (Composite Drug Reranking Scoring), a drug (re-)ranking web-based tool, which combines an initial drug ranking (i.e. repurposing score or hypothesis/potentiality score) with a functional score of each drug considered in conjunction with the disease under study as well as with a structural score derived from potential drugability violations. Furthermore, a structural similarity clustering is applied on the considered drugs and a handful of structural exemplars are suggested for further in vitro and in vivo validation. The user is able to filter the results further, through structural similarity examination of the candidate drugs with drugs that have failed against the queried disease where related clinical trials have been carried out. CoDReS is publicly available online at http://bioinformatics.cing.ac.cy/codres.

Indexed as

CheminformaticsData miningDrug discoveryDrug ranking

Identifiers

PMID31360332
PMCPMC6637175

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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.