Trypanosome RNA Polymerases and Transcription Factors: Sensible Trypanocidal Drug Targets?

2008 ◽  
Vol 9 (11) ◽  
pp. 979-996 ◽  
Author(s):  
Luc Vanhamme
Keyword(s):  
Transcription Factors ◽  
Drug Targets ◽  
Rna Polymerases

A chromomeric model for nuclear and chromosome structure

1995 ◽  
Vol 108 (9) ◽  
pp. 2927-2935 ◽  
Author(s):  
P.R. Cook
Keyword(s):  
Transcription Factors ◽  
Chromosome Structure ◽  
Rna Polymerases ◽  
Stable Structure ◽  
Structural Elements ◽  
Transcription Factories ◽  
Chromatin Loops ◽  
Sticky End

The basic structural elements of chromatin and chromosomes are reviewed. Then a model involving only three architectural motifs, nucleosomes, chromatin loops and transcription factories/chromomeres, is presented. Loops are tied through transcription factors and RNA polymerases to factories during interphase and to the remnants of those factories, chromomeres, during mitosis. On entry into mitosis, increased adhesiveness between nucleosomes and between factories drives a ‘sticky-end’ aggregation to the most compact and stable structure, a cylinder of nucleosomes around an axial chromomeric core.

ETS transcription factors as emerging drug targets in cancer

2019 ◽  
Vol 40 (1) ◽  
pp. 413-430 ◽  
Author(s):  
Michael Hsing ◽  
Yuzhuo Wang ◽  
Paul S. Rennie ◽  
Michael E. Cox ◽  
Artem Cherkasov
Keyword(s):  
Transcription Factors ◽  
Drug Targets ◽  
Ets Transcription Factors

scholarly journals Core regulatory circuitries in defining cancer cell identity across the malignant spectrum

Open Biology ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 200121
Author(s):  
Leila Jahangiri ◽  
Loukia Tsaprouni ◽  
Ricky M. Trigg ◽  
John A. Williams ◽  
Georgios V. Gkoutos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Rna Polymerase ◽  
Chromatin Structure ◽  
Drug Targets ◽  
Genetic Alterations ◽  
Specific Gene ◽  
Molecular Dissection ◽  
Cell Identity ◽  
Lineage Specific Gene

Gene expression programmes driving cell identity are established by tightly regulated transcription factors that auto- and cross-regulate in a feed-forward manner, forming core regulatory circuitries (CRCs). CRC transcription factors create and engage super-enhancers by recruiting acetylation writers depositing permissive H3K27ac chromatin marks. These super-enhancers are largely associated with BET proteins, including BRD4, that influence higher-order chromatin structure. The orchestration of these events triggers accessibility of RNA polymerase machinery and the imposition of lineage-specific gene expression. In cancers, CRCs drive cell identity by superimposing developmental programmes on a background of genetic alterations. Further, the establishment and maintenance of oncogenic states are reliant on CRCs that drive factors involved in tumour development. Hence, the molecular dissection of CRC components driving cell identity and cancer state can contribute to elucidating mechanisms of diversion from pre-determined developmental programmes and highlight cancer dependencies. These insights can provide valuable opportunities for identifying and re-purposing drug targets. In this article, we review the current understanding of CRCs across solid and liquid malignancies and avenues of investigation for drug development efforts. We also review techniques used to understand CRCs and elaborate the indication of discussed CRC transcription factors in the wider context of cancer CRC models.

scholarly journals Drugging Fuzzy Complexes in Transcription

2021 ◽  
Vol 8 ◽  
Author(s):  
Bonnie G. Su ◽  
Matthew J. Henley
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Drug Discovery ◽  
Drug Design ◽  
Drug Targets ◽  
Chemical Biology ◽  
Intrinsic Disorder ◽  
High Degree ◽  
Screening Approaches

Transcription factors (TFs) are one of the most promising but underutilized classes of drug targets. The high degree of intrinsic disorder in both the structure and the interactions (i.e., “fuzziness”) of TFs is one of the most important challenges to be addressed in this context. Here, we discuss the impacts of fuzziness on transcription factor drug discovery, describing how disorder poses fundamental problems to the typical drug design, and screening approaches used for other classes of proteins such as receptors or enzymes. We then speculate on ways modern biophysical and chemical biology approaches could synergize to overcome many of these challenges by directly addressing the challenges imposed by TF disorder and fuzziness.

scholarly journals ApicoTFdb: the comprehensive web repository of apicomplexan transcription factors and transcription-associated co-factors

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Rahila Sardar ◽  
Abhinav Kaushik ◽  
Rajan Pandey ◽  
Asif Mohmmed ◽  
Shakir Ali ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Protein Interactions ◽  
Drug Targets ◽  
Complex Life Cycle ◽  
Protein Protein Interactions ◽  
Apicomplexan Parasites ◽  
Reference Protein ◽  
Ap2 Family ◽  
Novel Drug ◽  
Novel Drug Targets

Abstract Despite significant progress in apicomplexan genome sequencing and genomics, the current list of experimentally validated transcription factors (TFs) in these genomes is incomplete and mainly consists of AP2 family of proteins, with only a limited number of non-AP2 family TFs and transcription-associated co-factors (TcoFs). We have performed a systematic bioinformatics-aided prediction of TFs and TcoFs in apicomplexan genomes and developed the ApicoTFdb database which consists of experimentally validated as well as computationally predicted TFs and TcoFs in 14 apicomplexan species. The predicted TFs are manually curated to complement the existing annotations. The current version of the database includes 1292 TFs which includes experimentally validated and computationally predicted TFs, representing 20 distinct families across 14 apicomplexan species. The predictions include TFs of TUB, NAC, BSD, HTH, Cupin/Jumonji, winged helix and FHA family proteins, not reported earlier as TFs in the genomes. Apart from TFs, ApicoTFdb also classifies TcoFs into three main subclasses: TRs, CRRs and RNARs, representing 2491 TcoFs in 14 apicomplexan species, are analyzed in this study. The database is designed to integrate different tools for comparative analysis. All entries in the database are dynamically linked with other databases, literature reference, protein–protein interactions, pathways and annotations associated with each protein. ApicoTFdb will be useful to the researchers interested in less-studied gene regulatory mechanisms mediating the complex life cycle of the apicomplexan parasites. The database will aid in the discovery of novel drug targets to much needed combat the growing drug resistance in the parasites.

scholarly journals Forkhead Domains of FOXO Transcription Factors Differ in both Overall Conformation and Dynamics

Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 966 ◽  
Author(s):  
Katarina Psenakova ◽  
Klara Kohoutova ◽  
Veronika Obsilova ◽  
Michael Ausserlechner ◽  
Vaclav Veverka ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Dna Binding ◽  
Drug Targets ◽  
Hepatic Glucose Production ◽  
Glucose Production ◽  
Hydrophobic Core ◽  
Dna Binding Domains ◽  
Binding Domains ◽  
Hepatic Glucose ◽  
Foxo Transcription Factors

FOXO transcription factors regulate cellular homeostasis, longevity and response to stress. FOXO1 (also known as FKHR) is a key regulator of hepatic glucose production and lipid metabolism, and its specific inhibition may have beneficial effects on diabetic hyperglycemia by reducing hepatic glucose production. Moreover, all FOXO proteins are considered potential drug targets for drug resistance prevention in cancer therapy. However, the development of specific FOXO inhibitors requires a detailed understanding of structural differences between individual FOXO DNA-binding domains. The high-resolution structure of the DNA-binding domain of FOXO1 reported in this study and its comparison with structures of other FOXO proteins revealed differences in both their conformation and flexibility. These differences are encoded by variations in protein sequences and account for the distinct functions of FOXO proteins. In particular, the positions of the helices H1, H2 and H3, whose interface form the hydrophobic core of the Forkhead domain, and the interactions between hydrophobic residues located on the interface between the N-terminal segment, the H2-H3 loop, and the recognition helix H3 differ among apo FOXO1, FOXO3 and FOXO4 proteins. Therefore, the availability of apo structures of DNA-binding domains of all three major FOXO proteins will support the development of FOXO-type-specific inhibitors.

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