DNA and RNA binding proteins (DRBPs) are a broad class of molecules that regulate numerous cellular processes across all living organisms, creating intricate dynamic multilevel networks to control nucleotide metabolism and gene expression. These interactions are highly regulated, and dysregulation contributes to the development of a variety of diseases, including cancer. An increasing number of proteins with DNA and/or RNA binding activities have been identified in recent years, and it is important to understand how their activities are related to the molecular mechanisms of cancer. In addition, many of these proteins have overlapping functions, and it is therefore essential to analyze not only the loss of function of individual factors, but also to group abnormalities into specific types of activities in regard to particular cancer types. In this review, we summarize the classes of DNA-binding, RNA-binding, and DRBPs, drawing particular attention to the similarities and differences between these protein classes. We also perform a cross-search analysis of relevant protein databases, together with our own pipeline, to identify DRBPs involved in cancer. We discuss the most common DRBPs and how they are related to specific cancers, reviewing their biochemical, molecular biological, and cellular properties to highlight their functions and potential as targets for treatment.

• Klíčová slova
• DNA/RNA binding protein, biomarkers, cancer, mutation, targeted treatment,
• MeSH
• DNA vazebné proteiny metabolismus   MeSH
• DNA MeSH
• lidé MeSH
• nádory * genetika   metabolismus   MeSH
• proteiny vázající RNA * metabolismus   MeSH
• RNA genetika   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH
• Názvy látek
• DNA vazebné proteiny MeSH
• DNA MeSH
• proteiny vázající RNA * MeSH
• RNA MeSH

To investigate the principles driving recognition between proteins and DNA, we analyzed more than thousand crystal structures of protein/DNA complexes. We classified protein and DNA conformations by structural alphabets, protein blocks [de Brevern, Etchebest and Hazout (2000) (Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Prots. Struct. Funct. Genet., 41:271-287)] and dinucleotide conformers [Svozil, Kalina, Omelka and Schneider (2008) (DNA conformations and their sequence preferences. Nucleic Acids Res., 36:3690-3706)], respectively. Assembling the mutually interacting protein blocks and dinucleotide conformers into 'interaction matrices' revealed their correlations and conformer preferences at the interface relative to their occurrence outside the interface. The analyzed data demonstrated important differences between complexes of various types of proteins such as transcription factors and nucleases, distinct interaction patterns for the DNA minor groove relative to the major groove and phosphate and importance of water-mediated contacts. Water molecules mediate proportionally the largest number of contacts in the minor groove and form the largest proportion of contacts in complexes of transcription factors. The generally known induction of A-DNA forms by complexation was more accurately attributed to A-like and intermediate A/B conformers rare in naked DNA molecules.

• MeSH
• DNA vazebné proteiny chemie   MeSH
• DNA chemie   MeSH
• fosfáty MeSH
• interpretace statistických dat MeSH
• konformace nukleové kyseliny MeSH
• konformace proteinů MeSH
• molekulární modely MeSH
• vazba proteinů MeSH
• voda chemie   MeSH
• výpočetní biologie MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• DNA vazebné proteiny MeSH
• DNA MeSH
• fosfáty MeSH
• voda MeSH

We contribute a novel, ball-histogram approach to DNA-binding propensity prediction of proteins. Unlike state-of-the-art methods based on constructing an ad-hoc set of features describing physicochemical properties of the proteins, the ball-histogram technique enables a systematic, Monte-Carlo exploration of the spatial distribution of amino acids complying with automatically selected properties. This exploration yields a model for the prediction of DNA binding propensity. We validate our method in prediction experiments, improving on state-of-the-art accuracies. Moreover, our method also provides interpretable features involving spatial distributions of selected amino acids.

• MeSH
• algoritmy MeSH
• aminokyseliny analýza   MeSH
• DNA analýza   MeSH
• metoda Monte Carlo MeSH
• proteiny analýza   MeSH
• sekundární struktura proteinů MeSH
• teoretické modely MeSH
• vazba proteinů MeSH
• výpočetní biologie metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• aminokyseliny MeSH
• DNA MeSH
• proteiny MeSH

The regulation of gene transcription allows yeast cells to respond properly to changing environmental conditions. Several protein complexes take part in this process. They involve RNA polymerase complexes, chromatin remodeling complexes, mediators, general transcription factors and specific transcriptional regulators. Using Saccharomyces cerevisiae as reference, the genomes of six species (Ashbya gossypii, Kluyveromyces lactis, K. waltii, Candida albicans, C. glabrata and Schizosaccharomyces pombe) that are human pathogens or important for the food industry were analyzed for their complement of genes encoding the homologous transcriptional regulators. The number of orthologs identified in a given species correlated with its phylogenetic distance from S. cerevisiae. Many duplicated genes encoding transcriptional regulators in S. cerevisiae and C. glabrata were reduced to one copy in species diverged before the ancestral whole genome duplication. Some transcriptional regulators appear to be specific for S. cerevisiae and probably reflect the physiological differences among species. Phylogenetic analysis and conserved gene order relationships indicate that a similar set of gene families involved in the control of multidrug resistance and oxidative stress response already existed in the common ancestor of the compared fungal species.

• MeSH
• fungální léková rezistence MeSH
• fungální proteiny chemie   genetika   metabolismus   MeSH
• fylogeneze MeSH
• genetická transkripce * MeSH
• genom fungální * MeSH
• kvasinky chemie   klasifikace   genetika   metabolismus   MeSH
• molekulární sekvence - údaje MeSH
• regulace genové exprese u hub MeSH
• sekvence aminokyselin MeSH
• transkripční faktory chemie   genetika   metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• srovnávací studie MeSH
• Názvy látek
• fungální proteiny MeSH
• transkripční faktory MeSH