Local conformational changes in the DNA interfaces of proteins

Evaluation of DNA-protein complex structures using the deep learning method

Biological processes such as transcription, repair, and regulation require interactions between DNA and proteins. To unravel their functions, it is imperative to determine the high-resolution structures of DNA-protein complexes. However, experimental methods for this purpose are costly and technically demanding. Consequently, there is an urgent need for computational techniques to identify the structures of DNA-protein complexes. Despite technological advancements, accurately identifying DNA-protein complexes through computational methods still poses a challenge. Our team has developed a cutting-edge deep-learning approach called DDPScore that assesses DNA-protein complex structures. DDPScore utilizes a 4D convolutional neural network to overcome limited training data. This approach effectively captures local and global features while comprehensively considering the conformational changes arising from the flexibility during the DNA-protein docking process. DDPScore consistently outperformed the available methods in comprehensive DNA-protein complex docking evaluations, even for the flexible docking challenges. DDPScore has a wide range of applications in predicting and designing structures of DNA-protein complexes.

Flanking regions, amyloid cores, and polymorphism: the potential interplay underlying structural diversity

The β-sheet-rich amyloid core is the defining feature of protein aggregates associated with neurodegenerative disorders. Recent investigations have revealed that there exist multiple examples of the same protein, with the same sequence, forming a variety of amyloid cores with distinct structural characteristics. These structural variants, termed as polymorphs, are hypothesized to influence the pathological profile and the progression of different neurodegenerative diseases, giving rise to unique phenotypic differences. Thus, identifying the origin and properties of these structural variants remain a focus of studies, as a preliminary step in the development of therapeutic strategies. Here, we review the potential role of the flanking regions of amyloid cores in inducing polymorphism. These regions, adjacent to the amyloid cores, show a preponderance for being structurally disordered, imbuing them with functional promiscuity. The dynamic nature of the flanking regions can then manifest in the form of conformational polymorphism of the aggregates. We take a closer look at the sequences flanking the amyloid cores, followed by a review of the polymorphic aggregates of the well-characterized proteins amyloid-β, α-synuclein, Tau, and TDP-43. We also consider different factors that can potentially influence aggregate structure and how these regions can be viewed as novel targets for therapeutic strategies by utilizing their unique structural properties.

Functional Layer-by-Layer Thin Films of Inducible Nitric Oxide (NO) Synthase Oxygenase and Polyethylenimine: Modulation of Enzyme Loading and NO-Release Activity

Nitric oxide (NO) release counteracts platelet aggregation and prevents the thrombosis cascade in the inner walls of blood vessels. NO-release coatings also prevent thrombus formation on the surface of blood-contacting medical devices. Our previous work has shown that inducible nitric oxide synthase (iNOS) films release NO fluxes upon enzymatic conversion of the substrate l-arginine. In this work, we report on the modulation of enzyme loading in layer-by-layer (LbL) thin films of inducible nitric oxide synthase oxygenase (iNOSoxy) on polyethylenimine (PEI). The layer of iNOSoxy is electrostatically adsorbed onto the PEI layer. The pH of the iNOSoxy solution affects the amount of enzyme adsorbed. The overall negative surface charge of iNOSoxy in solution depends on the pH and hence determines the density of adsorbed protein on the positively charged PEI layer. We used buffered iNOSoxy solutions adjusted to pHs 8.6 and 7.0, while saline PEI solution was used at pH 7.0. Atomic force microscopy imaging of the outermost layer shows higher protein adsorption with iNOSoxy at pH 8.6 than with a solution of iNOSoxy at pH 7.0. Graphite electrodes with PEI/iNOSoxy films show higher catalytic currents for nitric oxide reduction mediated by iNOSoxy. The higher enzyme loading translates into higher NO flux when the enzyme-modified surface is exposed to a solution containing the substrate and a source of electrons. Spectrophotometric assays showed higher NO fluxes with iNOSoxy/PEI films built at pH 8.6 than with films built at pH 7.0. Fourier transform infrared analysis of iNOSoxy adsorbed on PEI at pH 8.6 and 7.0 shows structural differences of iNOSoxy in films, which explains the observed changes in enzymatic activity. Our findings show that pH provides a strategy to optimize the NOS loading and enzyme activity in NOS-based LbL thin films, which enables improved NO release with minimum layers of PEI/NOS.

Structural basis for dimer formation of the CRISPR-associated protein Csm2 of Thermotoga maritima

The clusters of regularly interspaced short palindromic repeats (CRISPR) and the Cas (CRISPR-associated) proteins form an adaptive immune system in bacteria and archaea that evolved as an RNA-guided interference mechanism to target and degrade foreign genetic elements. In the so-called type IIIA CRISPR-Cas systems, Cas proteins from the Csm family form a complex of RNPs that are involved in surveillance and targeting tasks. In the present study, we report the crystal structure of Thermotoga maritima Csm2. This protein is considered to assemble into the helically shaped Csm RNP complex in a site opposite to the CRISPR RNA binding backbone. Csm2 was solved via cadmium single wavelength anomalous diffraction phasing at 2.4 Å resolution. The structure reveals that Csm2 is composed of a large 42 amino-acid long α-helix flanked by three shorter α-helices. The structure also shows that the protein is capable of forming dimers mainly via an extensive contact surface conferred by its long α-helix. This interaction is further stabilized by the N-terminal helix, which is inserted into the C-terminal helical portion of the adjacent subunit. The dimerization of Csm2 was additionally confirmed by size exclusion chromatography of the pure recombinant protein followed by MS analysis of the eluted fractions. Because of its role in the assembly and functioning of the Csm CRISPR RNP complex, the crystal structure of Csm2 is of great importance for clarifying the mechanism of action of the subtype IIIA CRISPR-Cas system, as well as the similarities and diversities between the different CRISPR-Cas system.

DATABASE

The structure of Thermotoga maritima Csm2 has been deposited in the Protein Data Bank under accession code 5AN6.

Protein flexibility in the light of structural alphabets

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

Structure-based modeling of protein: DNA specificity

Protein:DNA interactions are essential to a range of processes that maintain and express the information encoded in the genome. Structural modeling is an approach that aims to understand these interactions at the physicochemical level. It has been proposed that structural modeling can lead to deeper understanding of the mechanisms of protein:DNA interactions, and that progress in this field can not only help to rationalize the observed specificities of DNA-binding proteins but also to allow researchers to engineer novel DNA site specificities. In this review we discuss recent developments in the structural description of protein:DNA interactions and specificity, as well as the challenges facing the field in the future.

Geometry of the nucleus: a perspective on gene expression regulation

Gene expression control results from the combined interactions of the nearly hundred proteins forming the pre-initiation complex, thousands of transcription regulators, and genomic DNA. In the recent years, new technologies have revealed several key aspects of nuclear spatial organization that showed a fine interplay between the function of nuclear proteins, their 3D organization, and their dynamics. Here we review several concepts that link biochemical reactivity in the nucleus to its 3D spatial organization. We present the analogies between the emerging understanding of nuclear organization in the field of cell biology, and the more established disciplines of heterogeneous catalysis and the physics of random walks. We provide several recent examples showing how nuclear geometry affects protein reactivity in the nucleus.

Evolutionarily conserved and conformationally constrained short peptides might serve as DNA recognition elements in intrinsically disordered regions

Despite recent advances, it is yet not clear how intrinsically disordered regions in proteins recognize their targets without any defined structures. Short linear motifs had been proposed to mediate molecular recognition by disordered regions; however, the underlying structural prerequisite remains elusive. Moreover, the role of short linear motifs in DNA recognition has not been studied. We report a repertoire of short evolutionarily Conserved Recognition Elements (CoREs) in long intrinsically disordered regions, which have very distinct amino-acid propensities from those of known motifs, and exhibit a strong tendency to retain their three-dimensional conformations compared to adjacent regions. The majority of CoREs directly interact with the DNA in the available 3D structures, which is further supported by literature evidence, analyses of ΔΔG values of DNA-binding energies and threading-based prediction of DNA binding potential. CoREs were enriched in cancer-associated missense mutations, further strengthening their functional nature. Significant enrichment of glycines in CoREs and the preference of glycyl ϕ-Ψ values within the left-handed bridge range in the l-disallowed region of the Ramachandran plot suggest that Gly-to-nonGly mutations within CoREs might alter the backbone conformation and consequently the function, a hypothesis that we reconciled using available mutation data. We conclude that CoREs might serve as bait for DNA recognition by long disordered regions and that certain mutations in these peptides can disrupt their DNA binding potential and consequently the protein function. We further hypothesize that the preferred conformations of CoREs and of glycyl residues therein might play an important role in DNA binding. The highly ordered nature of CoREs hints at a therapeutic strategy to inhibit malicious molecular interactions using small molecules mimicking CoRE conformations.

Bioinformatic analysis of the protein/DNA interface

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.