Computational modeling suggests dimerization of equine infectious anemia virus Rev is required for RNA binding

Background The lentiviral Rev protein mediates nuclear export of intron-containing viral RNAs that encode structural proteins or serve as the viral genome. Following translation, HIV-1 Rev localizes to the nucleus and binds its cognate sequence, termed the Rev-responsive element (RRE), in incompletely spliced viral RNA. Rev subsequently multimerizes along the viral RNA and associates with the cellular Crm1 export machinery to translocate the RNA-protein complex to the cytoplasm. Equine infectious anemia virus (EIAV) Rev is functionally homologous to HIV-1 Rev, but shares very little sequence similarity and differs in domain organization. EIAV Rev also contains a bipartite RNA binding domain comprising two short arginine-rich motifs (designated ARM-1 and ARM-2) spaced 79 residues apart in the amino acid sequence. To gain insight into the topology of the bipartite RNA binding domain, a computational approach was used to model the tertiary structure of EIAV Rev. Results The tertiary structure of EIAV Rev was modeled using several protein structure prediction and model quality assessment servers. Two types of structures were predicted: an elongated structure with an extended central alpha helix, and a globular structure with a central bundle of helices. Assessment of models on the basis of biophysical properties indicated they were of average quality. In almost all models, ARM-1 and ARM-2 were spatially separated by \u3e15 Å, suggesting that they do not form a single RNA binding interface on the monomer. A highly conserved canonical coiled-coil motif was identified in the central region of EIAV Rev, suggesting that an RNA binding interface could be formed through dimerization of Rev and juxtaposition of ARM-1 and ARM-2. In support of this, purified Rev protein migrated as a dimer in Blue native gels, and mutation of a residue predicted to form a key coiled-coil contact disrupted dimerization and abrogated RNA binding. In contrast, mutation of residues outside the predicted coiled-coil interface had no effect on dimerization or RNA binding. Conclusions Our results suggest that EIAV Rev binding to the RRE requires dimerization via a coiled-coil motif to juxtapose two RNA binding motifs, ARM-1 and ARM-2

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications

A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the avoidance of data overfitting. Capturing information from as few as 50 protein sequences spread among the four target classes (6 transmembrane, 10 fibrous, 13 globular, and 17 mixed), PRED-CLASS was able to obtain 371 correct predictions out of a set of 387 proteins (success rate approximately 96%) unambiguously assigned into one of the target classes. The application of PRED-CLASS to several test sets and complete proteomes of several organisms demonstrates that such a method could serve as a valuable tool in the annotation of genomic open reading frames with no functional assignment or as a preliminary step in fold recognition and ab initio structure prediction methods. Detailed results obtained for various data sets and completed genomes, along with a web sever running the PRED-CLASS algorithm, can be accessed over the World Wide Web at http://o2.biol.uoa.gr/PRED-CLAS

Atomic-level structure characterization of an ultrafast folding mini-protein denatured state

Atomic-level analyses of non-native protein ensembles constitute an important aspect of protein folding studies to reach a more complete understanding of how proteins attain their native form exhibiting biological activity. Previously, formation of hydrophobic clusters in the 6 M urea-denatured state of an ultrafast folding mini-protein known as TC5b from both photo-CIDNP NOE transfer studies and FCS measurements was observed. Here, we elucidate the structural properties of this mini-protein denatured in 6 M urea performing 15N NMR relaxation studies together with a thorough NOE analysis. Even though our results demonstrate that no elements of secondary structure persist in the denatured state, the heterogeneous distribution of R2 rate constants together with observing pronounced heteronuclear NOEs along the peptide backbone reveals specific regions of urea-denatured TC5b exhibiting a high degree of structural rigidity more frequently observed for native proteins. The data are complemented with studies on two TC5b point mutants to verify the importance of hydrophobic interactions for fast folding. Our results corroborate earlier findings of a hydrophobic cluster present in urea-denatured TC5b comprising both native and non-native contacts underscoring their importance for ultra rapid folding. The data assist in finding ways of interpreting the effects of pre-existing native and/or non-native interactions on the ultrafast folding of proteins; a fact, which might have to be considered when defining the starting conditions for molecular dynamics simulation studies of protein folding

Molecular models for the core components of the flagellar type-III secretion complex

We show that by using a combination of computational methods, consistent three-dimensional molecular models can be proposed for the core proteins of the type-III secretion system. We employed a variety of approaches to reconcile disparate, and sometimes inconsistent, data sources into a coherent picture that for most of the proteins indicated a unique solution to the constraints. The range of difficulty spanned from the trivial (FliQ) to the difficult (FlhA and FliP). The uncertainties encountered with FlhA were largely the result of the greater number of helix packing possibilities allowed in a large protein, however, for FliP, there remains an uncertainty in how to reconcile the large displacement predicted between its two main helical hairpins and their ability to sit together happily across the bacterial membrane. As there is still no high resolution structural information on any of these proteins, we hope our predicted models may be of some use in aiding the interpretation of electron microscope images and in rationalising mutation data and experiments

Classification and Automatic Annotation of Tandem Repeat Proteins in RepeatsDB

Protein tandem repeats are crucial structural elements in various biological processes, playing essential roles in cell adhesion, protein-protein interactions, and molecular recognition. These repetitive regions have sparked considerable interest in structural biology and bioinformatics, leading to the development of specialized resources like RepeatsDB. RepeatsDB is a comprehensive, curated database of annotated tandem repeat protein structures, offering a valuable resource for researchers. In this study, we systematically analyzed protein tandem repeats in RepeatsDB, with a primary focus on Alpha-Solenoids and Beta-Propellers, to enhance the existing classification system and provide a more profound understanding of protein tandem repeats. Our investigation commenced with an initial statistical analysis to elucidate the diversity and population status of distinct repeat groups within the database, as well as their respective degree of annotation. This approach proved instrumental in addressing the challenges associated with numerous entries that had a missing annotation. We conducted a structural analysis using pairwise structural alignment and explored dimensionality reduction and visualization techniques to uncover novel structural relationships. These findings improved our understanding of protein structural comparisons and informed a refined classification system. We utilized the density-based clustering algorithm, DBSCAN, to establish structural similarity ranges for Clan members and provide computational support for defining Clan boundaries. This method proved effective in detecting outlier entries and refining existing clans, leading to the proposal of new repeat groups. Additionally, we implemented a supervised classification experiment using the K-Nearest Neighbors (KNN) algorithm, which facilitated the automatic annotation of previously unannotated entries. This study introduces an automatic annotation methodology that significantly improves the performance of RepeatsDB curators and can be extended to other bioinformatics applications. The findings contribute to a more comprehensive understanding of protein tandem repeats and offer valuable insights for future research in structural biology and bioinformatics.Abstract Protein tandem repeats are crucial structural elements in various biological processes, playing essential roles in cell adhesion, protein-protein interactions, and molecular recognition. These repetitive regions have sparked considerable interest in structural biology and bioinformatics, leading to the development of specialized resources like RepeatsDB. RepeatsDB is a comprehensive, curated database of annotated tandem repeat protein structures, offering a valuable resource for researchers. In this study, we systematically analyzed protein tandem repeats in RepeatsDB, with a primary focus on Alpha-Solenoids and Beta-Propellers, to enhance the existing classification system and provide a more profound understanding of protein tandem repeats. Our investigation commenced with an initial statistical analysis to elucidate the diversity and population status of distinct repeat groups within the database, as well as their respective degree of annotation. This approach proved instrumental in addressing the challenges associated with numerous entries that had a missing annotation. We conducted a structural analysis using pairwise structural alignment and explored dimensionality reduction and visualization techniques to uncover novel structural relationships. These findings improved our understanding of protein structural comparisons and informed a refined classification system. We utilized the density-based clustering algorithm, DBSCAN, to establish structural similarity ranges for Clan members and provide computational support for defining Clan boundaries. This method proved effective in detecting outlier entries and refining existing clans, leading to the proposal of new repeat groups. Additionally, we implemented a supervised classification experiment using the K-Nearest Neighbors (KNN) algorithm, which facilitated the automatic annotation of previously unannotated entries. This study introduces an automatic annotation methodology that significantly improves the performance of RepeatsDB curators and can be extended to other bioinformatics applications. The findings contribute to a more comprehensive understanding of protein tandem repeats and offer valuable insights for future research in structural biology and bioinformatics

Folding and Assembly of Multimeric Proteins: Dimeric HIV-1 Protease and a Trimeric Coiled Coil Component of a Complex Hemoglobin Scaffold: A Dissertation

Knowledge of how a polypeptide folds from a space-filling random coil into a biologically-functional, three-dimensional structure has been the essence of the protein folding problem. Though mechanistic details of DNA transcription and RNA translation are well understood, a specific code by which the primary structure dictates the acquisition of secondary, tertiary, and quarternary structure remains unknown. However, the demonstrated reversibility of in vitroprotein folding allows for a thermodynamic analysis of the folding reaction. By probing both the equilibrium and kinetics of protein folding, a protein folding mechanism can be postulated. Over the past 40 years, folding mechanisms have been determined for many proteins; however, a generalized folding code is far from clear. Furthermore, most protein folding studies have focused on monomeric proteins even though a majority of biological processes function via the association of multiple subunits. Consequently, a complete understanding of the acquisition of quarternary protein structure is essential for applying the basic principles of protein folding to biology. The studies presented in this dissertation examined the folding and assembly of two very different multimeric proteins. Underlying both of these investigations is the need for a combined analysis of a repertoire of approaches to dissect the folding mechanism for multimeric proteins. Chapter II elucidates the detailed folding energy landscape of HIV-1 protease, a dimeric protein containing β-barrel subunits. The folding of this viral enzyme exhibited a sequential three-step pathway, involving the rate-limiting formation of a monomeric intermediate. The energetics determined from this analysis and their applications to HIV-1 function are discussed. In contrast, Chapter III illustrates the association of a coiled coil component of L. terrestriserythrocruorin. This extracellular hemoglobin consists of a complex scaffold of linker chains with a central ring of interdigitating coiled coils. Allostery is maintained by twelve dodecameric hemoglobin subunits that dock upon this scaffold. Modest association was observed for this coiled coil, and the implications of this fragment to linker assembly are addressed. These studies depict the complexity of multimeric folding reactions. Chapter II demonstrates that a detailed energy landscape of a dimeric protein can be determined by combining traditional equilibrium and kinetic approaches with information from a global analysis of kinetics and a monomer construct. Chapter III indicates that fragmentation of large complexes can show the contributions of separate domains to hierarchical organization. As a whole, this dissertation highlights the importance of pursuing mulitmeric protein folding studies and the implications of these folding mechanisms to biological function