Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures

Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models. Results: Several probabilistic models not only successfully estimate the continuum secondary structure, but also provide a categorical output on par with models directly trained on categorical data. Importantly, models trained on the continuum secondary structure are also better than their categorical counterparts at identifying the conformational state for structurally ambivalent residues. Conclusion: Cascaded probabilistic neural networks trained on the continuum secondary structure exhibit better accuracy in structurally ambivalent regions of proteins, while sustaining an overall classification accuracy on par with standard, categorical prediction methods.

The use of protein structure/activity relationships in the rational design of stable particulate delivery systems

The recombinant heat shock protein (18 kDa-hsp) from Mycobacterium leprae was studied as a T-epitope model for vaccine development. We present a structural analysis of the stability of recombinant 18 kDa-hsp during different processing steps. Circular dichroism and ELISA were used to monitor protein structure after thermal stress, lyophilization and chemical modification. We observed that the 18 kDa-hsp is extremely resistant to a wide range of temperatures (60% of activity is retained at 80ºC for 20 min). N-Acylation increased its ordered structure by 4% and decreased its ß-T1 structure by 2%. ELISA demonstrated that the native conformation of the 18 kDa-hsp was preserved after hydrophobic modification by acylation. The recombinant 18 kDa-hsp resists to a wide range of temperatures and chemical modifications without loss of its main characteristic, which is to be a source of T epitopes. This resistance is probably directly related to its lack of organization at the level of tertiary and secondary structures.

Protein structure prediction servers at University College London

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction.

The PSIPRED protein structure prediction server

The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

A link between protein structure and enzyme catalyzed hydrogen tunneling

We present evidence that the size of an active site side chain may modulate the degree of hydrogen tunneling in an enzyme-catalyzed reaction. Primary and secondary kH/kT and kD/kT kinetic isotope effects have been measured for the oxidation of benzyl alcohol catalyzed by horse liver alcohol dehydrogenase at 25°C. As reported in earlier studies, the relationship between secondary kH/kT and kD/kT isotope effects provides a sensitive probe for deviations from classical behavior. In the present work, catalytic efficiency and the extent of hydrogen tunneling have been correlated for the alcohol dehydrogenase-catalyzed hydride transfer among a group of site-directed mutants at position 203. Val-203 interacts with the opposite face of the cofactor NAD+ from the alcohol substrate. The reduction in size of this residue is correlated with diminished tunneling and a two orders of magnitude decrease in catalytic efficiency. Comparison of the x-ray crystal structures of a ternary complex of a high-tunneling (Phe-93 → Trp) and a low-tunneling (Val-203 → Ala) mutant provides a structural basis for the observed effects, demonstrating an increase in the hydrogen transfer distance for the low-tunneling mutant. The Val-203 → Ala ternary complex crystal structure also shows a hyperclosed interdomain geometry relative to the wild-type and the Phe-93 → Trp mutant ternary complex structures. This demonstrates a flexibility in interdomain movement that could potentially narrow the distance between the donor and acceptor carbons in the native enzyme and may enhance the role of tunneling in the hydride transfer reaction.

The accuracy of protein structure alignment servers

Background: Protein structural alignment is one of the most fundamental and crucial areas of research in the domain of computational structural biology. Comparison of a protein structure with known structures helps to classify it as a new or belonging to a known group of proteins. This, in turn, is useful to determine the function of protein, its evolutionary relationship with other protein molecules and grasping principles underlying protein architecture and folding. Results: A large number of protein structure alignment methods are available. Each protein structure alignment tool has its own strengths andweaknesses that need to be highlighted.We compared and presented results of six most popular and publically available servers for protein structure comparison. These web-based servers were compared with the respect to functionality (features provided by these servers) and accuracy (how well the structural comparison is performed). The CATH was used as a reference. The results showed that overall CE was top performer. DALI and PhyreStorm showed similar results whereas PDBeFold showed the lowest performance. In case of few secondary structural elements, CE, DALI and PhyreStorm gave 100% success rate. Conclusion: Overall none of the structural alignment servers showed 100% success rate. Studies of overall performance, effect of mainly alpha and effect of mainly beta showed consistent performance. CE, DALI, FatCat and PhyreStorm showed more than 90% success rate.

The C-terminal Region Of The Human P23 Chaperone Modulates Its Structure And Function.

The p23 protein is a chaperone widely involved in protein homeostasis, well known as an Hsp90 co-chaperone since it also controls the Hsp90 chaperone cycle. Human p23 includes a β-sheet domain, responsible for interacting with Hsp90; and a charged C-terminal region whose function is not clear, but seems to be natively unfolded. p23 can undergo caspase-dependent proteolytic cleavage to form p19 (p231-142), which is involved in apoptosis, while p23 has anti-apoptotic activity. To better elucidate the function of the human p23 C-terminal region, we studied comparatively the full-length human p23 and three C-terminal truncation mutants: p23₁₋₁₁₇; p23₁₋₁₃₁ and p23₁₋₁₄₂. Our data indicate that p23 and p19 have distinct characteristics, whereas the other two truncations behave similarly, with some differences to p23 and p19. We found that part of the C-terminal region can fold in an α-helix conformation and slightly contributes to p23 thermal-stability, suggesting that the C-terminal interacts with the β-sheet domain. As a whole, our results suggest that the C-terminal region of p23 is critical for its structure-function relationship. A mechanism where the human p23 C-terminal region behaves as an activation/inhibition module for different p23 activities is proposed.

Mining protein structure data

The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.

Identification of a novel determinant for membrane association in hepatitis C virus nonstructural protein 4B.

Nonstructural protein 4B (NS4B) plays an essential role in the formation of the hepatitis C virus (HCV) replication complex. It is a relatively poorly characterized integral membrane protein predicted to comprise four transmembrane segments in its central portion. Here, we describe a novel determinant for membrane association represented by amino acids (aa) 40 to 69 in the N-terminal portion of NS4B. This segment was sufficient to target and tightly anchor the green fluorescent protein to cellular membranes, as assessed by fluorescence microscopy as well as membrane extraction and flotation analyses. Circular dichroism and nuclear magnetic resonance structural analyses showed that this segment comprises an amphipathic alpha-helix extending from aa 42 to 66. Attenuated total reflection infrared spectroscopy and glycosylation acceptor site tagging revealed that this amphipathic alpha-helix has the potential to traverse the phospholipid bilayer as a transmembrane segment, likely upon oligomerization. Alanine substitution of the fully conserved aromatic residues on the hydrophobic helix side abrogated membrane association of the segment comprising aa 40 to 69 and disrupted the formation of a functional replication complex. These results provide the first atomic resolution structure of an essential membrane-associated determinant of HCV NS4B.

Protein-protein interaction investigated by steered molecular dynamics: the TCR-pMHC complex.

We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism.

Crystal structure of NLRC4 reveals its autoinhibition mechanism.

Nucleotide-binding and oligomerization domain-like receptor (NLR) proteins oligomerize into multiprotein complexes termed inflammasomes when activated. Their autoinhibition mechanism remains poorly defined. Here, we report the crystal structure of mouse NLRC4 in a closed form. The adenosine diphosphate-mediated interaction between the central nucleotide-binding domain (NBD) and the winged-helix domain (WHD) was critical for stabilizing the closed conformation of NLRC4. The helical domain HD2 repressively contacted a conserved and functionally important α-helix of the NBD. The C-terminal leucine-rich repeat (LRR) domain is positioned to sterically occlude one side of the NBD domain and consequently sequester NLRC4 in a monomeric state. Disruption of ADP-mediated NBD-WHD or NBD-HD2/NBD-LRR interactions resulted in constitutive activation of NLRC4. Together, our data reveal the NBD-organized cooperative autoinhibition mechanism of NLRC4 and provide insight into its activation.

ParA2, a Vibrio cholerae chromosome partitioning protein, forms left-handed helical filaments on DNA.

Most bacterial chromosomes contain homologs of plasmid partitioning (par) loci. These loci encode ATPases called ParA that are thought to contribute to the mechanical force required for chromosome and plasmid segregation. In Vibrio cholerae, the chromosome II (chrII) par locus is essential for chrII segregation. Here, we found that purified ParA2 had ATPase activities comparable to other ParA homologs, but, unlike many other ParA homologs, did not form high molecular weight complexes in the presence of ATP alone. Instead, formation of high molecular weight ParA2 polymers required DNA. Electron microscopy and three-dimensional reconstruction revealed that ParA2 formed bipolar helical filaments on double-stranded DNA in a sequence-independent manner. These filaments had a distinct change in pitch when ParA2 was polymerized in the presence of ATP versus in the absence of a nucleotide cofactor. Fitting a crystal structure of a ParA protein into our filament reconstruction showed how a dimer of ParA2 binds the DNA. The filaments formed with ATP are left-handed, but surprisingly these filaments exert no topological changes on the right-handed B-DNA to which they are bound. The stoichiometry of binding is one dimer for every eight base pairs, and this determines the geometry of the ParA2 filaments with 4.4 dimers per 120 A pitch left-handed turn. Our findings will be critical for understanding how ParA proteins function in plasmid and chromosome segregation.

The C-terminal domain of Plasmodium falciparum merozoite surface protein 3 self-assembles into alpha-helical coiled coil tetramer.

Proteins located on the surface of the pathogenic malaria parasite Plasmodium falciparum are objects of intensive studies due to their important role in the invasion of human cells and the accessibility to host antibodies thus making these proteins attractive vaccine candidates. One of these proteins, merozoite surface protein 3 (MSP3) represents a leading component among vaccine candidates; however, little is known about its structure and function. Our biophysical studies suggest that the 40 residue C-terminal domain of MSP3 protein self-assembles into a four-stranded alpha-helical coiled coil structure where alpha-helices are packed "side-by-side". A bioinformatics analysis provides an extended list of known and putative proteins from different species of Plasmodium which have such MSP3-like C-terminal domains. This finding allowed us to extend some conclusions of our studies to a larger group of the malaria surface proteins. Possible structural and functional roles of these highly conserved oligomerization domains in the intact merozoite surface proteins are discussed.

Characterization of the phosphorylation sites involved in G protein-coupled receptor kinase- and protein kinase C-mediated desensitization of the alpha1B-adrenergic receptor.

Catecholamines as well as phorbol esters can induce the phosphorylation and desensitization of the alpha1B-adrenergic receptor (alpha1BAR). In this study, phosphoamino acid analysis of the phosphorylated alpha1BAR revealed that both epinephrine- and phorbol ester-induced phosphorylation predominantly occurs at serine residues of the receptor. The findings obtained with receptor mutants in which portions of the C-tail were truncated or deleted indicated that a region of 21 amino acids (393-413) of the carboxyl terminus including seven serines contains the main phosphorylation sites involved in agonist- as well as phorbol ester-induced phosphorylation and desensitization of the alpha1BAR. To identify the serines invoved in agonist- versus phorbol ester-dependent regulation of the receptor, two different strategies were adopted, the seven serines were either substituted with alanine or reintroduced into a mutant lacking all of them. Our findings indicate that Ser394 and Ser400 were phosphorylated following phorbol ester-induced activation of protein kinase C, whereas Ser404, Ser408, and Ser410 were phosphorylated upon stimulation of the alpha1BAR with epinephrine. The observation that overexpression of G protein-coupled kinase 2 (GRK2) could increase agonist-induced phosphorylation of Ser404, Ser408, and Ser410, strongly suggests that these serines are the phosphorylation sites of the alpha1BAR for kinases of the GRK family. Phorbol ester-induced phosphorylation of the Ser394 and Ser400 as well as GRK2-mediated phosphorylation of the Ser404, Ser408, and Ser410, resulted in the desensitization of alpha1BAR-mediated inositol phosphate response. This study provides generalities about the biochemical mechanisms underlying homologous and heterologous desensitization of G protein-coupled receptors linked to the activation of phospholipase C.