Nucleos: a web server for the identification of nucleotide-binding sites in protein structures

Phosphorylation within Intrinsic Disordered Region Discriminates Histone Variant macroH2A1 Splicing Isoforms-macroH2A1.1 and macroH2A1.2

Simple Summary

MacroH2A1, a histone H2A variant, is present as two alternative splicing isoforms, macroH2A1.1 and macroH2A1.2, which are finely regulated through several mechanisms, including post-translational modifications (PTM). In this article, the authors provide the PTM pattern of macroH2A1.1 and macroH2A1.2 in the same experimental setting through mass spec analysis. They report a different phosphorylation level in their intrinsically disordered linker region, which can be responsible for their different biological role, as computational analysis shows.

Abstract

Background: Gene expression in eukaryotic cells can be governed by histone variants, which replace replication-coupled histones, conferring unique chromatin properties. MacroH2A1 is a histone H2A variant containing a domain highly similar to H2A and a large non-histone (macro) domain. MacroH2A1, in turn, is present in two alternatively exon-spliced isoforms: macroH2A1.1 and macroH2A1.2, which regulate cell plasticity and proliferation in a remarkably distinct manner. The N-terminal and the C-terminal tails of H2A histones stem from the nucleosome core structure and can be target sites for several post-translational modifications (PTMs). MacroH2A1.1 and macroH2A1.2 isoforms differ only in a few amino acids and their ability to bind NAD-derived metabolites, a property allegedly conferring their different functions in vivo. Some of the modifications on the macroH2A1 variant have been identified, such as phosphorylation (T129, S138) and methylation (K18, K123, K239). However, no study to our knowledge has analyzed extensively, and in parallel, the PTM pattern of macroH2A1.1 and macroH2A1.2 in the same experimental setting, which could facilitate the understanding of their distinct biological functions in health and disease. Methods: We used a mass spectrometry-based approach to identify the sites for phosphorylation, acetylation, and methylation in green fluorescent protein (GFP)-tagged macroH2A1.1 and macroH2A1.2 expressed in human hepatoma cells. The impact of selected PTMs on macroH2A1.1 and macroH2A1.2 structure and function are demonstrated using computational analyses. Results: We identified K7 as a new acetylation site in both macroH2A1 isoforms. Quantitative comparison of histone marks between the two isoforms revealed significant differences in the levels of phosphorylated T129 and S170. Our computational analysis provided evidence that the phosphorylation status in the intrinsically disordered linker region in macroH2A1 isoforms might represent a key regulatory element contributing to their distinct biological responses. Conclusions: Taken together, our results report different PTMs on the two macroH2A1 splicing isoforms as responsible for their distinct features and distribution in the cell.

Structural and mechanistic insights into the bifunctional HISN2 enzyme catalyzing the second and third steps of histidine biosynthesis in plants

The second and third steps of the histidine biosynthetic pathway (HBP) in plants are catalyzed by a bifunctional enzyme–HISN2. The enzyme consists of two distinct domains, active respectively as a phosphoribosyl-AMP cyclohydrolase (PRA-CH) and phosphoribosyl-ATP pyrophosphatase (PRA-PH). The domains are analogous to single-domain enzymes encoded by bacterial hisI and hisE genes, respectively. The calculated sequence similarity networks between HISN2 analogs from prokaryotes and eukaryotes suggest that the plant enzymes are closest relatives of those in the class of Deltaproteobacteria. In this work, we obtained crystal structures of HISN2 enzyme from Medicago truncatula (MtHISN2) and described its architecture and interactions with AMP. The AMP molecule bound to the PRA-PH domain shows positioning of the N1-phosphoribosyl relevant to catalysis. AMP bound to the PRA-CH domain mimics a part of the substrate, giving insights into the reaction mechanism. The latter interaction also arises as a possible second-tier regulatory mechanism of the HBP flux, as indicated by inhibition assays and isothermal titration calorimetry.

Identification of coenzyme-binding proteins with machine learning algorithms

The coenzyme-binding proteins play a vital role in the cellular metabolism processes, such as fatty acid biosynthesis, enzyme and gene regulation, lipid synthesis, particular vesicular traffic, and β-oxidation donation of acyl-CoA esters. Based on the theory of Star Graph Topological Indices (SGTIs) of protein primary sequences, we proposed a method to develop a first classification model for predicting protein with coenzyme-binding properties. To simulate the properties of coenzyme-binding proteins, we created a dataset containing 2897 proteins, among 456 proteins functioned as coenzyme-binding activity. The SGTIs of peptide sequence were calculated with Sequence to Star Network (S2SNet) application. We used the SGTIs as inputs to several classification techniques with a machine learning software - Weka. A Random Forest classifier based on 3 features of the embedded and non-embedded graphs was identified as the best predictive model for coenzyme-binding proteins. This model developed was with the true positive (TP) rate of 91.7%, false positive (FP) rate of 7.6%, and Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.971. The prediction of new coenzyme-binding activity proteins using this model could be useful for further drug development or enzyme metabolism researches.

In silico identification and computational analysis of the nucleotide binding site in the C-terminal domain of Hsp90

Hsp90 contains two distinct Nucleotide Binding Sites (NBS), in its N-terminal domain (NTD) and C-terminal domain (CTD), respectively. The NTD site belongs to the GHKL super-family of ATPases and has been the subject of extensive characterization. However, a structure of the nucleotide-bound form of CTD is still unavailable. In this study molecular modeling was employed to incorporate experimental data using partial constructs of the CTD, from work published by many research groups, onto existing structural models of its apo- form. Our attempts to locate potential nucleotide ligand-binding sites or cavities yielded one major candidate-a structurally unconventional site-exhibiting the requisite shape and volume for accommodation of tri-phosphate nucleotides. Its structure was refined by molecular dynamics (MD)-based techniques. We reproducibly docked the Mg²⁺ complexed form of ATP, GTP, CTP, TTP and UTP to this putative NBS. These docking simulations and calculated ligand-binding scores are in general agreement with published data about experimentally measured binding to the CTD. The overall pattern of interactions between residues lining the site and docked nucleotides is conserved and broadly similar to that of other nucleotide-binding sites. Our docking simulations suggest that nucleotide binding stabilizes the only structurally labile region, thereby providing a rationale for the increased resistance to thermal denaturation and proteolysis. The docked nucleotides do not intrude onto the surface of residues involved in dimerization or chaperoning. Our molecular modeling permitted recognition of larger structural changes in the nucleotide-bound CTD dimer, including stabilization of helix-2 in both chains and intra- and inter- chain interactions between three residues (I613, Q617, R620).

Considerations of Protein Subpockets in Fragment-Based Drug Design

While the fragment-based drug design approach continues to gain importance, gaps in the tools and methods available in the identification and accurate utilization of protein subpockets have limited the scope. The importance of these features of small molecule-protein recognition is highlighted with several examples. A generalized solution for the identification of subpockets and corresponding chemical fragments remains elusive, but there are numerous advancements in methods that can be used in combination to address subpockets. Finally, additional examples of approaches that consider the relative importance of small-molecule co-dependence of protein conformations are highlighted to emphasize an increased significance of subpockets, especially at protein interfaces.

Cofactory: sequence-based prediction of cofactor specificity of Rossmann folds

Obtaining optimal cofactor balance to drive production is a challenge in metabolically engineered microbial production strains. To facilitate identification of heterologous enzymes with desirable altered cofactor requirements from native content, we have developed Cofactory, a method for prediction of enzyme cofactor specificity using only primary amino acid sequence information. The algorithm identifies potential cofactor binding Rossmann folds and predicts the specificity for the cofactors FAD(H2), NAD(H), and NADP(H). The Rossmann fold sequence search is carried out using hidden Markov models whereas artificial neural networks are used for specificity prediction. Training was carried out using experimental data from protein-cofactor structure complexes. The overall performance was benchmarked against an independent evaluation set obtaining Matthews correlation coefficients of 0.94, 0.79, and 0.65 for FAD(H2), NAD(H), and NADP(H), respectively. The Cofactory method is made publicly available at http://www.cbs.dtu.dk/services/Cofactory.

Binding site comparison for function prediction and pharmaceutical discovery

While structural genomics resulted in thousands of new protein crystal structures, we still do not know the functions of most of these proteins. One reason for this shortcoming is their unique sequences or folds, which leaves them assigned as proteins of 'unknown function'. Recent advances in and applications of cutting edge binding site comparison algorithms for binding site detection and function prediction have begun to shed light on this problem. Here, we review these algorithms and their use in function prediction and pharmaceutical discovery. Finding common binding sites in weakly related proteins may lead to the discovery of new protein functions and to novel ways of drug discovery.