Evidence map›Paper›PMID 24936211›Full record

ArticleJournal of cheminformatics2014

Experimental validation of FINDSITE(comb) virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders.

Bharath Srinivasan, Hongyi Zhou, Julia Kubanek, Jeffrey Skolnick

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Review
  3. FINDSITEJournal of chemical information and modeling · 2018
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Modeling enzyme-ligand binding in drug discovery.Journal of cheminformatics · 2015
    Review
  13. Article
  14. Article
  15. Article
  16. Template-based prediction of protein function.Current opinion in structural biology · 2015
    Review
  17. Article
  18. Review
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

4 authors.

Bharath SrinivasanCenter for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250, 14th Street, N.W., Atlanta, GA 30318, USA.
Hongyi ZhouCenter for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250, 14th Street, N.W., Atlanta, GA 30318, USA.
Julia KubanekSchool of Biology, Atlanta, GA 30332, USA ; School of Chemistry and Biochemistry, Aquatic Chemical Ecology Center, Institute of Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Jeffrey SkolnickCenter for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250, 14th Street, N.W., Atlanta, GA 30318, USA.

Funding

Interaction Pattern Based Predictor of Protein StruturesR01GM048835 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI SKOLNICK, JEFFREY · 1994 to 2015
$4.0M
THEORY OF FOLDING TRANSITIONS IN A-HELICAL PROTEINSR01GM037408 · NIGMS · WASHINGTON UNIVERSITY · PI SKOLNICK, JEFFREY · 1987 to 2014
$3.9M
NIGMS NIH HHS R01 GM037408NIGMS NIH HHS R01 GM048835
6 · The paper itself

Abstract

backgroundIdentification of ligand-protein binding interactions is a critical step in drug discovery. Experimental screening of large chemical libraries, in spite of their specific role and importance in drug discovery, suffer from the disadvantages of being random, time-consuming and expensive. To accelerate the process, traditional structure- or ligand-based VLS approaches are combined with experimental high-throughput screening, HTS. Often a single protein or, at most, a protein family is considered. Large scale VLS benchmarking across diverse protein families is rarely done, and the reported success rate is very low. Here, we demonstrate the experimental HTS validation of a novel VLS approach, FINDSITE(comb), across a diverse set of medically-relevant proteins.

resultsFor eight different proteins belonging to different fold-classes and from diverse organisms, the top 1% of FINDSITE(comb)'s VLS predictions were tested, and depending on the protein target, 4%-47% of the predicted ligands were shown to bind with μM or better affinities. In total, 47 small molecule binders were identified. Low nanomolar (nM) binders for dihydrofolate reductase and protein tyrosine phosphatases (PTPs) and micromolar binders for the other proteins were identified. Six novel molecules had cytotoxic activity (<10 μg/ml) against the HCT-116 colon carcinoma cell line and one novel molecule had potent antibacterial activity.

conclusionsWe show that FINDSITE(comb) is a promising new VLS approach that can assist drug discovery.

Indexed as

Differential scanning fluorimetry (DSF)Drug discoveryHigh-throughput screening (HTS)Ligand homology modelingVirtual ligand screening (VLS)

Identifiers

PMID24936211
PMCPMC4038399

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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.