Evidence map›Paper›PMID 25428367›Full record

ArticleNucleic acids research2014

Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes.

Mario Pujato, Fabien Kieken, Amanda A Skiles, Nikos Tapinos, Andras Fiser

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
–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

62 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Therapeutic, Clinicopathological, and Molecular Correlates ofPharmaceuticals (Basel, Switzerland) · 2024
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2 more citing papers are in PubMed but not listed here.

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.

Mario PujatoDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA.
Fabien KiekenDepartment of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA Macromolecular Therapeutics Development, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA.
Amanda A SkilesMolecular Neuroscience Laboratory, Geisinger Clinic, 100 North Academy Avenue, Danville, PA 17822, USA.
Nikos TapinosMolecular Neuroscience Laboratory, Geisinger Clinic, 100 North Academy Avenue, Danville, PA 17822, USA.
Andras FiserDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, NY 10461, USA andras.fiser@einstein.yu.edu.

Funding

WORD PROCESSORP30CA013330 · NCI · YESHIVA UNIVERSITY · PI THOMAS E ROHAN · 1985 to 2026
$111.2M
Consortia for High-Throughput-Enabled Structural Biology Partnerships (U01)U01GM094665 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI CASADEVALL, ARTURO · 2010 to 2014
$5.5M
Role of an alternatively spliced nuclear variant of ErbB3 in the nervous systemR01NS070975 · NINDS · GEISINGER CLINIC · PI TAPINOS, NIKOLAOS · 2010 to 2014
$1.7M
Membrane protein structure modeling with experimental restraintsR01GM096041 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI FISER, ANDRAS · 2011 to 2014
$1.3M
NCI NIH HHS P30 CA013330NIGMS NIH HHS GM094665NIGMS NIH HHS GM096041NINDS NIH HHS R01 NS070975
6 · The paper itself

Abstract

Proper cell functioning depends on the precise spatio-temporal expression of its genetic material. Gene expression is controlled to a great extent by sequence-specific transcription factors (TFs). Our current knowledge on where and how TFs bind and associate to regulate gene expression is incomplete. A structure-based computational algorithm (TF2DNA) is developed to identify binding specificities of TFs. The method constructs homology models of TFs bound to DNA and assesses the relative binding affinity for all possible DNA sequences using a knowledge-based potential, after optimization in a molecular mechanics force field. TF2DNA predictions were benchmarked against experimentally determined binding motifs. Success rates range from 45% to 81% and primarily depend on the sequence identity of aligned target sequences and template structures, TF2DNA was used to predict 1321 motifs for 1825 putative human TF proteins, facilitating the reconstruction of most of the human gene regulatory network. As an illustration, the predicted DNA binding site for the poorly characterized T-cell leukemia homeobox 3 (TLX3) TF was confirmed with gel shift assay experiments. TLX3 motif searches in human promoter regions identified a group of genes enriched in functions relating to hematopoiesis, tissue morphology, endocrine system and connective tissue development and function.

Indexed as

AlgorithmsGene Regulatory NetworksPromoter Regions, GeneticBinding SitesDNAGene Expression RegulationHomeodomain ProteinsHumansModels, MolecularNucleotide MotifsSequence Analysis, DNATranscription FactorsDNAHomeodomain ProteinsTLX3 protein, humanTranscription Factors

Identifiers

PMID25428367
PMCPMC4267649

What OpenQuestion holds

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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.