Correction: Cserzo et al. The First Quarter Century of the Dense Alignment Surface Transmembrane Prediction Method. Int. J. Mol. Sci. 2023, 24, 14016.

There was an error in the original publication [...].

The First Quarter Century of the Dense Alignment Surface Transmembrane Prediction Method.

The dense alignment surface (DAS) transmembrane (TM) prediction method was first published more than 25 years ago. DAS was the one of the earliest tools to discriminate TM proteins from globular ones and to predict the sequence positions of TM helices in proteins with high accuracy from their amino acid sequence alone. The algorithmic improvements that followed in 2002 (DAS-TMfilter) made it one of the best performing tools among those relying on local sequence information for TM prediction. Since then, many more experimental data about membrane proteins (including thousands of 3D structures of membrane proteins) have accumulated but there has been no significant improvement concerning performance in the area of TM helix prediction tools. Here, we report a new implementation of the DAS-TMfilter prediction web server. We reevaluated the performance of the method using a five-times-larger, updated test dataset. We found that the method performs at essentially the same accuracy as the original even without any change to the parametrization of the program despite the much larger dataset. Thus, the approach captures the physico-chemistry of TM helices well, essentially solving this scientific problem.

Molecular Dynamics Simulation as a Tool to Identify Mutual Synergistic Folding Proteins.

Mutual synergistic folding (MSF) proteins belong to a recently emerged subclass of disordered proteins, which are disordered in their monomeric forms but become ordered in their oligomeric forms. They can be identified by experimental methods following their unfolding, which happens in a single-step cooperative process, without the presence of stable monomeric intermediates. Only a limited number of experimentally validated MSF proteins are accessible. The amino acid composition of MSF proteins shows high similarity to globular ordered proteins, rather than to disordered ones. However, they have some special structural features, which makes it possible to distinguish them from globular proteins. Even in the possession of their oligomeric three-dimensional structure, classification can only be performed based on unfolding experiments, which are frequently absent. In this work, we demonstrate a simple protocol using molecular dynamics simulations, which is able to indicate that a protein structure belongs to the MSF subclass. The presumption of the known atomic resolution quaternary structure is an obvious limitation of the method, and because of its high computational time requirements, it is not suitable for screening large databases; still, it is a valuable in silico tool for identification of MSF proteins.

Origin of Increased Solvent Accessibility of Peptide Bonds in Mutual Synergetic Folding Proteins.

Mutual Synergetic Folding (MSF) proteins belong to a recently discovered class of proteins. These proteins are disordered in their monomeric but ordered in their oligomeric forms. Their amino acid composition is more similar to globular proteins than to disordered ones. Our preceding work shed light on important structural aspects of the structural organization of these proteins, but the background of this behavior is still unknown. We suggest that solvent accessibility is an important factor, especially solvent accessibility of the peptide bonds can be accounted for this phenomenon. The side chains of the amino acids which form a peptide bond have a high local contribution to the shielding of the peptide bond from the solvent. During the oligomerization step, other non-local residues contribute to the shielding. We investigated these local and non-local effects of shielding based on Shannon information entropy calculations. We found that MSF and globular homodimeric proteins have different local contributions resulting from different amino acid pair frequencies. Their non-local distribution is also different because of distinctive inter-subunit contacts.

Biased Coupling to ß-Arrestin of Two Common Variants of the CB2 Cannabinoid Receptor.

ß-arrestins are partners of the G protein-coupled receptors (GPCRs), regulating their intracellular trafficking and signaling. Development of biased GPCR agonists, selectively targeting either G protein or ß-arrestin pathways, are in the focus of interest due to their therapeutic potential in different pathological conditions. The CB2 cannabinoid receptor (CB2R) is a GPCR involved in various functions in the periphery and the central nervous system. Two common occurring variants of CB2R, harboring Q63R or L133I missense mutations, have been implicated in the development of a diverse set of disorders. To evaluate the effect of these mutations, we characterized the binding profile of these mutant CB2 receptors to G proteins and ß-arrestin2. Although their ability to inhibit cAMP signaling was similar, the Q63R mutant had increased, whereas the L133I mutant receptor had decreased ß-arrestin2 binding. In line with these observations, the variants also had altered intracellular trafficking. Our results show that two common variants of the CB2 receptor have biased signaling properties, which may contribute to the pathogenesis of the associated disorders and may offer CB2R as a target for further development of biased receptor activation strategies.

Physical Background of the Disordered Nature of "Mutual Synergetic Folding" Proteins.

Intrinsically disordered proteins (IDPs) lack a well-defined 3D structure. Their disordered nature enables them to interact with several other proteins and to fulfil their vital biological roles, in most cases after coupled folding and binding. In this paper, we analyze IDPs involved in a new mechanism, mutual synergistic folding (MSF). These proteins define a new subset of IDPs. Recently we collected information on these complexes and created the Mutual Folding Induced by Binding (MFIB) database. These protein complexes exhibit considerable structural variation, and almost half of them are homodimers, but there is a significant amount of heterodimers and various kinds of oligomers. In order to understand the basic background of the disordered character of the monomers found in MSF complexes, the simplest part of the MFIB database, the homodimers are analyzed here. We conclude that MFIB homodimeric proteins have a larger solvent-accessible main-chain surface area on the contact surface of the subunits, when compared to globular homodimeric proteins. The main driving force of the dimerization is the mutual shielding of the water-accessible backbones and the formation of extra intermolecular interactions.

Prediction of new abiotic stress genes in Arabidopsis thaliana and Oryza sativa according to enumeration-based statistical analysis.

Plants undergo an extensive change in gene regulation during abiotic stress. It is of great agricultural importance to know which genes are affected during stress response. The genome sequence of a number of plant species has been determined, among them Arabidopsis and Oryza sativa, whose genome has been annotated most completely as of yet, and are well-known organisms widely used as experimental systems. This paper applies a statistical algorithm for predicting new stress-induced motifs and genes by analyzing promoter sets co-regulated by abiotic stress in the previously mentioned two species. After identifying characteristic putative regulatory motif sequence pairs (dyads) in the promoters of 125 stress-regulated Arabidopsis genes and 87 O. sativa genes, these dyads were used to screen the entire Arabidopsis and O. sativa promoteromes to find related stress-induced genes whose promoters contained a large number of these dyads found by our algorithm. We were able to predict a number of putative dyads, characteristic of a large number of stress-regulated genes, some of them newly discovered by our algorithm and serve as putative transcription factor binding sites. Our new motif prediction algorithm comes complete with a stand-alone program. This algorithm may be used in motif discovery in the future in other species. The more than 1,200 Arabidopsis and 1,700 Orzya sativa genes found by our algorithm are good candidates for further experimental studies in abiotic stress.

Relating underrepresented genomic DNA patterns and tiRNAs: the rule behind the observation and beyond.

BACKGROUND: One of the central problems of post-genomic biology is the understanding of regulatory network of genes. Traditionally the problem is approached from the protein-DNA interaction perspective. In recent years various types of noncoding RNAs appeared on the scene as new potent players of the game. The exact role of these molecules in gene expression control is mostly unknown at present, while their importance is generally recognized. RESULTS: The Human and Mouse genomes have been screened with a statistical model for sequence patterns underrepresented in these genomes, and a subset of motifs, named spanions, has been identified. The common portion of the motif lists of the two species is 75% indicating evolutionary conservation of this feature. These motifs are arranged in clusters at close proximity of distinct genetic landmarks: 5' ends of genes, exon side of the exon/intron junctions and 5' ends of 3' UTRs. The length of the clusters is typically in the 20 to 25 bases range. The findings are in agreement with the known C/G bias of promoter regions while access much more sequential information than the simple composition based model.In the Human genome the recently reported transcription initiation RNAs (tiRNAs) are typically transcribed from these spanion clusters according to the presented results. The spanion clusters account for 70% of the published tiRNAs. Apparently, the model access the common statistical feature of this new and mostly uncharacterized non-coding RNA class and, in this way, supports the experimental observations with theoretical background. CONCLUSIONS: The presented results seem to support the emerging model of the RNA-driven eukaryotic gene expression control. Beyond that, the model detects spanion clusters at genetic positions where no tiRNA counterpart was considered and reported. The GO-term analysis of genes with high concentration of spanion clusters in their promoter proximal region indicates involvement in gene regulatory processes. The results of the analysis suggest that the gene regulatory potential of the small non-coding RNAs is grossly underestimated at present. REVIEWERS: This article was reviewed by Frank Eisenhaber, Sandor Pongor and Rotem Sorek (nominated by Doron Lancet).

Mechanisms of angiotensin II-mediated regulation of aldosterone synthase expression in H295R human adrenocortical and rat adrenal glomerulosa cells.

In adrenal zona glomerulosa cells angiotensin II (Ang II) is a key regulator of steroidogenesis. Our purpose was to compare the mechanisms of Ang II-induced changes in the expression level of early transcription factors NR4A1 (NGFIB) and NR4A2 (Nurr1) genes, and the CYP11B2 gene encoding aldosterone synthase in H295R human adrenocortical tumor cells and in primary rat adrenal glomerulosa cells. Real-time PCR studies have demonstrated that Ang II increased the expression levels of NR4A1 and NR4A2 in H295R cells within 1 h after stimulation, which persisted up to 6 h; whereas in rat adrenal glomerulosa cells the kinetics of the expression of these genes were more rapid and transient. Ang II also induced prolonged nuclear translocation of Nurr1 and NGFIB proteins in both cell types. Studies using MEK inhibitor (PD98059, 20 microM), protein kinase C inhibitor (BIM1, 3 microM) and calmodulin kinase (CAMK) inhibitor (KN93, 10 microM) revealed that in rat adrenal glomerulosa cells CAMK-mediated mechanisms play a predominant role in the regulation of CYP11B2. In accordance with earlier findings, in H295R cells MEK inhibition increased the expression of NR4A1, NR4A2 and CYP11B2 genes, however, it decreased the Ang II-induced gene expression levels, suggesting that ERK activation has a role in control of expression of these genes. No such mechanism was detected in rat glomerulosa cells. Sar1-Ile4-Ile8-AngII, which can cause G protein-independent ERK activation, also stimulated the expression of CYP11B2 in H295R cells. These data suggest that the previously reported CAMK-mediated stimulation of early transcription factors NGFIB and Nurr1 has a predominant role in Ang II-induced CYP11B2 activation in rat adrenal glomerulosa cells, whereas in H295R cells ERK activation and G protein-independent mechanisms also contribute to this process.

Dimerization and oligomerization of G-protein-coupled receptors: debated structures with established and emerging functions.

Dimerization or oligomerization of G-protein-coupled receptors (GPCRs) is a novel concept, which may lead to the reevaluation of the actions of pharmacological ligands, hormones, neurotransmitters, and other mediators acting on GPCRs. Although a large number of data obtained using different biophysical, biochemical and structural methods, and functional approaches argue for dimerization or oligomerization of these receptors, several publications criticized the applied methods and challenged the concept. The aim of this paper is to review the data that support the concept of receptor oligomerization, and the most important arguments against it. We conclude that it will require major methodical improvements to obtain decisive proof, whether GPCRs exist in their native membrane environments as homo- or heterodimeric or oligomeric complexes, in which receptor monomers have stable direct interactions. However, overwhelming amounts of data suggest that many GPCRs exhibit functional properties that require direct or indirect interactions between clustered receptors. Although it is difficult to conclude, about the exact nature of these interactions, dimerization or oligomerization of GPCRs is a useful paradigm for pharmacologists to study properties of receptors, which require functionally important clustering of receptors, such as trafficking of newly synthesized receptors to the cell surface, allosteric modulation of ligand binding, signaling specificity, co-internalization, or cross-inhibition of GPCRs.

TM or not TM: transmembrane protein prediction with low false positive rate using DAS-TMfilter.

UNLABELLED: Web-based servers implementing the DAS-TMfilter algorithm have been launched at three mirror sites and their usage is described. The underlying computer program is an upgraded and modified version of the DAS-prediction method. The new server is (approximately 1 among 100 unrelated queries) while the high efficiency of the original algorithm locating TM segments in queries is preserved (sensitivity of approximately 95% among documented proteins with helical TM regions). AVAILABILITY: The server operates at three mirror sites: http://mendel.imp.univie.ac.at/sat/DAS/DAS.html, http://wooster.bip.bham.ac.uk/DAS.html and http://www.enzim.hu/DAS/DAS.html. The program is available on request.

Servers for sequence-structure relationship analysis and prediction.

We describe several algorithms and public servers that were developed to analyze and predict various features of protein structures. These servers provide information about the covalent state of cysteine (CYSREDOX), as well as about residues involved in non-covalent cross links that play an important role in the structural stability of proteins (SCIDE and SCPRED). We also discuss methods and servers developed to identify helical transmembrane proteins from large databases and rough genomic data, including two of the most popular transmembrane prediction methods, DAS and HMMTOP. Several biologically interesting applications of these servers are also presented. The servers are available through http://www.enzim.hu/servers.html.

On filtering false positive transmembrane protein predictions.

While helical transmembrane (TM) region prediction tools achieve high (>90%) success rates for real integral membrane proteins, they produce a considerable number of false positive hits in sequences of known nontransmembrane queries. We propose a modification of the dense alignment surface (DAS) method that achieves a substantial decrease in the false positive error rate. Essentially, a sequence that includes possible transmembrane regions is compared in a second step with TM segments in a sequence library of documented transmembrane proteins. If the performance of the query sequence against the library of documented TM segment-containing sequences in this test is lower than an empirical threshold, it is classified as a non-transmembrane protein. The probability of false positive prediction for trusted TM region hits is expressed in terms of E-values. The modified DAS method, the DAS-TMfilter algorithm, has an unchanged high sensitivity for TM segments ( approximately 95% detected in a learning set of 128 documented transmembrane proteins). At the same time, the selectivity measured over a non-redundant set of 526 soluble proteins with known 3D structure is approximately 99%, mainly because a large number of falsely predicted single membrane-pass proteins are eliminated by the DAS-TMfilter algorithm.