SAM-T04: what is new in protein-structure prediction for CASP6

Solution structure of the type I polyketide synthase Pks13 from Mycobacterium tuberculosis

BACKGROUND

Type I polyketide synthases (PKSs) are multifunctional enzymes responsible for the biosynthesis of a group of diverse natural compounds with biotechnological and pharmaceutical interest called polyketides. The diversity of polyketides is impressive despite the limited set of catalytic domains used by PKSs for biosynthesis, leading to considerable interest in deciphering their structure-function relationships, which is challenging due to high intrinsic flexibility. Among nineteen polyketide synthases encoded by the genome of Mycobacterium tuberculosis, Pks13 is the condensase required for the final condensation step of two long acyl chains in the biosynthetic pathway of mycolic acids, essential components of the cell envelope of Corynebacterineae species. It has been validated as a promising druggable target and knowledge of its structure is essential to speed up drug discovery to fight against tuberculosis.

RESULTS

We report here a quasi-atomic model of Pks13 obtained using small-angle X-ray scattering of the entire protein and various molecular subspecies combined with known high-resolution structures of Pks13 domains or structural homologues. As a comparison, the low-resolution structures of two other mycobacterial polyketide synthases, Mas and PpsA from Mycobacterium bovis BCG, are also presented. This study highlights a monomeric and elongated state of the enzyme with the apo- and holo-forms being identical at the resolution probed. Catalytic domains are segregated into two parts, which correspond to the condensation reaction per se and to the release of the product, a pivot for the enzyme flexibility being at the interface. The two acyl carrier protein domains are found at opposite sides of the ketosynthase domain and display distinct characteristics in terms of flexibility.

CONCLUSIONS

The Pks13 model reported here provides the first structural information on the molecular mechanism of this complex enzyme and opens up new perspectives to develop inhibitors that target the interactions with its enzymatic partners or between catalytic domains within Pks13 itself.

Genome-scale investigation of phenotypically distinct but nearly clonal Trichoderma strains

Biological control agents (BCA) are beneficial organisms that are applied to protect plants from pests. Many fungi of the genus Trichoderma are successful BCAs but the underlying mechanisms are not yet fully understood. Trichoderma cf. atroviride strain LU132 is a remarkably effective BCA compared to T. cf. atroviride strain LU140 but these strains were found to be highly similar at the DNA sequence level. This unusual combination of phenotypic variability and high DNA sequence similarity between separately isolated strains prompted us to undertake a genome comparison study in order to identify DNA polymorphisms. We further investigated if the polymorphisms had functional effects on the phenotypes. The two strains were clearly identified as individuals, exhibiting different growth rates, conidiation and metabolism. Superior pathogen control demonstrated by LU132 depended on its faster growth, which is a prerequisite for successful distribution and competition. Genome sequencing identified only one non-synonymous single nucleotide polymorphism (SNP) between the strains. Based on this SNP, we successfully designed and validated an RFLP protocol that can be used to differentiate LU132 from LU140 and other Trichoderma strains. This SNP changed the amino acid sequence of SERF, encoded by the previously undescribed single copy gene “small EDRK-rich factor” (serf). A deletion of serf in the two strains did not lead to identical phenotypes, suggesting that, in addition to the single functional SNP between the nearly clonal Trichoderma cf. atroviride strains, other non-genomic factors contribute to their phenotypic variation. This finding is significant as it shows that genomics is an extremely useful but not exhaustive tool for the study of biocontrol complexity and for strain typing.

DNA damaging, cell cytotoxicity and serum albumin binding efficacy of the rutin–Cu(ii) complex

The rutin–Cu(ii) complex causes DNA damage and is also able to inhibit the growth of human HeLa cells. This complex binds with serum albuminsviahydrophobic forces.

Enhancement of E. coli acyl-CoA synthetase FadD activity on medium chain fatty acids

FadD catalyses the first step in E. coli beta-oxidation, the activation of free fatty acids into acyl-CoA thioesters. This activation makes fatty acids competent for catabolism and reduction into derivatives like alcohols and alkanes. Alcohols and alkanes derived from medium chain fatty acids (MCFAs, 6-12 carbons) are potential biofuels; however, FadD has low activity on MCFAs. Herein, we generate mutations in fadD that enhance its acyl-CoA synthetase activity on MCFAs. Homology modeling reveals that these mutations cluster on a face of FadD from which the co-product, AMP, is expected to exit. Using FadD homology models, we design additional FadD mutations that enhance E. coli growth rate on octanoate and provide evidence for a model wherein FadD activity on octanoate can be enhanced by aiding product exit. These studies provide FadD mutants useful for producing MCFA derivatives and a rationale to alter the substrate specificity of adenylating enzymes.

Insights into the coiled-coil organization of the Hendra virus phosphoprotein from combined biochemical and SAXS studies

Nipah and Hendra viruses are recently emerged paramyxoviruses belonging to the Henipavirus genus. The Henipavirus phosphoprotein (P) consists of a large intrinsically disordered domain and a C-terminal domain (PCT) containing alternating disordered and ordered regions. Among these latter is the P multimerization domain (PMD). Using biochemical, analytical ultracentrifugation and small-angle X-ray scattering (SAXS) studies, we show that Hendra virus (HeV) PMD forms an elongated coiled-coil homotrimer in solution, in agreement with our previous findings on Nipah virus (NiV) PMD. However, the orientation of the N-terminal region differs from that observed in solution for NiV PMD, consistent with the ability of this region to adopt different conformations. SAXS studies provided evidence for a trimeric organization also in the case of PCT, thus extending and strengthening our findings on PMD. The present results are discussed in light of conflicting reports in the literature pointing to a tetrameric organization of paramyxoviral P proteins.

Small auxin upregulated RNA (SAUR) gene family in maize: identification, evolution, and its phylogenetic comparison with Arabidopsis, rice, and sorghum

Small auxin-up RNAs (SAURs) are the early auxin-responsive genes represented by a large multigene family in plants. Here, we identified 79 SAUR gene family members from maize (Zea mays subsp. mays) by a reiterative database search and manual annotation. Phylogenetic analysis indicated that the SAUR proteins from Arabidopsis, rice, sorghum, and maize had divided into 16 groups. These genes were non-randomly distributed across the maize chromosomes, and segmental duplication and tandem duplication contributed to the expansion of the maize SAUR gene family. Synteny analysis established orthology relationships and functional linkages between SAUR genes in maize and sorghum genomes. We also found that the auxin-responsive elements were conserved in the upstream sequences of maize SAUR members. Selection analyses identified some significant site-specific constraints acted on most SAUR paralogs. Expression profiles based on microarray data have provided insights into the possible functional divergence among members of the SAUR gene family. Quantitative real-time PCR analysis indicated that some of the 10 randomly selected ZmSAUR genes could be induced at least in maize shoot or root tissue tested. The results reveal a comprehensive overview of the maize SAUR gene family and may pave the way for deciphering their function during plant development.

Biochemical and structural studies of the oligomerization domain of the Nipah virus phosphoprotein: evidence for an elongated coiled-coil homotrimer

Nipah virus (NiV) is a recently emerged severe human pathogen that belongs to the Henipavirus genus within the Paramyxoviridae family. The NiV genome is encapsidated by the nucleoprotein (N) within a helical nucleocapsid that is the substrate used by the polymerase for transcription and replication. The polymerase is recruited onto the nucleocapsid via its cofactor, the phosphoprotein (P). The NiV P protein has a modular organization, with alternating disordered and ordered domains. Among these latter, is the P multimerization domain (PMD) that was predicted to adopt a coiled-coil conformation. Using both biochemical and biophysical approaches, we show that NiV PMD forms a highly stable and elongated coiled-coil trimer, a finding in striking contrast with respect to the PMDs of Paramyxoviridae members investigated so far that were all found to tetramerize. The present results therefore represent the first report of a paramyxoviral P protein forming trimers.

The influence of common metal ions on the interactions of the isoflavone genistein with bovine serum albumin

The interaction of genistein with bovine serum albumin (BSA) has been characterized via UV-vis, fluorescence spectroscopy and Circular Dichroism (CD) measurements under physiological conditions. In this study, we have investigated the effect of some common metal ions on the binding of genistein with BSA using fluorescence studies. The fluorescence data reveal that the binding affinity of genistein to BSA increases in presence of certain metal ions. The possibility of non-radiative energy transition from the donor tryptophan to the acceptor genistein has been observed in absence and presence of metal ions. The observed similarities in the values of efficiency of energy transfer (E) and the separation between the donor and acceptor (r) in both the cases may be correlated with the complexation between the genistein and metal ions, which is also observed from the UV-vis studies. The changes in enthalpy (ΔH°) and entropy (ΔS°) of the interaction were found to be -14.64 kJ mol(-1) and +42.75 J mol(-1)K(-1) respectively. These values indicate the involvement of electrostatic interactions along with a hydrophobic association that results in a positive entropy change. CD analysis shows that there is a slight increase in the% α-helical content of BSA on binding with genistein at lower molar ratios. Warfarin and ibuprofen displacement studies in accordance with the molecular docking show that genistein binds to site I (subdomain IIA) of BSA.

Computational design of glutamate dehydrogenase in Bacillus subtilis natto

Bacillus subtilis natto is widely used in industry to produce natto, a traditional and popular Japanese soybean food. However, during its secondary fermentation, high amounts of ammonia are released to give a negative influence on the flavor of natto. Glutamate dehydrogenase (GDH) is a key enzyme for the ammonia produced and released, because it catalyzes the oxidative deamination of glutamate to alpha-ketoglutarate using NAD(+) or NADP(+) as co-factor during carbon and nitrogen metabolism processes. To solve this problem, we employed multiple computational methods model and re-design GDH from Bacillus subtilis natto. Firstly, a structure model of GDH with cofactor NADP(+) was constructed by threading and ab initio modeling. Then the substrate glutamate were flexibly docked into the structure model to form the substrate-binding mode. According to the structural analysis of the substrate-binding mode, Lys80, Lys116, Arg196, Thr200, and Ser351 in the active site were found could form a significant hydrogen bonding network with the substrate, which was thought to play a crucial role in the substrate recognition and position. Thus, these residues were then mutated into other amino acids, and the substrate binding affinities for each mutant were calculated. Finally, three single mutants (K80A, K116Q, and S351A) were found to have significant decrease in the substrate binding affinities, which was further supported by our biochemical experiments.

The association of a La module with the PABP-interacting motif PAM2 is a recurrent evolutionary process that led to the neofunctionalization of La-related proteins

La-related proteins (LARPs) are largely uncharacterized factors, well conserved throughout evolution. Recent reports on the function of human LARP4 and LARP6 suggest that these proteins fulfill key functions in mRNA metabolism and/or translation. We report here a detailed evolutionary history of the LARP4 and 6 families in eukaryotes. Genes coding for LARP4 and 6 were duplicated in the common ancestor of the vertebrate lineage, but one LARP6 gene was subsequently lost in the common ancestor of the eutherian lineage. The LARP6 gene was also independently duplicated several times in the vascular plant lineage. We observed that vertebrate LARP4 and plant LARP6 duplication events were correlated with the acquisition of a PABP-interacting motif 2 (PAM2) and with a significant reorganization of their RNA-binding modules. Using isothermal titration calorimetry (ITC) and immunoprecipitation methods, we show that the two plant PAM2-containing LARP6s (LARP6b and c) can, indeed, interact with the major plant poly(A)-binding protein (PAB2), while the third plant LARP6 (LARP6a) is unable to do so. We also analyzed the RNA-binding properties and the subcellular localizations of the two types of plant LARP6 proteins and found that they display nonredundant characteristics. As a whole, our results support a model in which the acquisition by LARP4 and LARP6 of a PAM2 allowed their targeting to mRNA 3' UTRs and led to their neofunctionalization.

Identifying and characterizing the most significant β-glucosidase of the novel species Aspergillus saccharolyticus

The newly discovered fungal species Aspergillus saccharolyticus was found to produce a culture broth rich in β-glucosidase activity. In this present work, the main β-glucosidase of A. saccharolyticus responsible for the efficient hydrolytic activity was identified, isolated, and characterized. Ion exchange chromatography was used to fractionate the culture broth, yielding fractions with high β-glucosidase activity and only 1 visible band on an SDS–PAGE gel. Mass spectrometry analysis of this band gave peptide matches to β-glucosidases from aspergilli. Through a polymerase chain reaction approach using degenerate primers and genome walking, a 2919 bp sequence encoding the 860 amino acid BGL1 polypeptide was determined. BGL1 of A. saccharolyticus has 91% and 82% identity with BGL1 from Aspergillus aculeatus and BGL1 from Aspergillus niger , respectively, both belonging to Glycoside Hydrolase family 3. Homology modeling studies suggested β-glucosidase activity with preserved retaining mechanism and a wider catalytic pocket compared with other β-glucosidases. The bgl1 gene was heterologously expressed in Trichoderma reesei QM6a, purified, and characterized by enzyme kinetics studies. The enzyme can hydrolyze cellobiose, p-nitrophenyl-β-d-glucoside, and cellodextrins. The enzyme showed good thermostability, was stable at 50 °C, and at 60 °C it had a half-life of approximately 6 h.

Insights into the mutation-induced HHH syndrome from modeling human mitochondrial ornithine transporter-1

Human mitochondrial ornithine transporter-1 is reported in coupling with the hyperornithinemia-hyperammonemia-homocitrullinuria (HHH) syndrome, which is a rare autosomal recessive disorder. For in-depth understanding of the molecular mechanism of the disease, it is crucially important to acquire the 3D structure of human mitochondrial ornithine transporter-1. Since no such structure is available in the current protein structure database, we have developed it via computational approaches based on the recent NMR structure of human mitochondrial uncoupling protein (Berardi MJ, Chou JJ, et al. Nature 2011, 476:109–113). Subsequently, we docked the ligand L-ornithine into the computational structure to search for the favorable binding mode. It was observed that the binding interaction for the most favorable binding mode is featured by six remarkable hydrogen bonds between the receptor and ligand, and that the most favorable binding mode shared the same ligand-binding site with most of the homologous mitochondrial carriers from different organisms, implying that the ligand-binding sites are quite conservative in the mitochondrial carriers family although their sequences similarity is very low with 20% or so. Moreover, according to our structural analysis, the relationship between the disease-causing mutations of human mitochondrial ornithine transporter-1 and the HHH syndrome can be classified into the following three categories: (i) the mutation occurs in the pseudo-repeat regions so as to change the region of the protein closer to the mitochondrial matrix; (ii) the mutation is directly affecting the substrate binding pocket so as to reduce the substrate binding affinity; (iii) the mutation is located in the structural region closer to the intermembrane space that can significantly break the salt bridge networks of the protein. These findings may provide useful insights for in-depth understanding of the molecular mechanism of the HHH syndrome and developing effective drugs against the disease.

Computational prediction of secondary and supersecondary structures

The sequence-based prediction of the secondary and supersecondary structures enjoys strong interest and finds applications in numerous areas related to the characterization and prediction of protein structure and function. Substantial efforts in these areas over the last three decades resulted in the development of accurate predictors, which take advantage of modern machine learning models and availability of evolutionary information extracted from multiple sequence alignment. In this chapter, we first introduce and motivate both prediction areas and introduce basic concepts related to the annotation and prediction of the secondary and supersecondary structures, focusing on the β hairpin, coiled coil, and α-turn-α motifs. Next, we overview state-of-the-art prediction methods, and we provide details for 12 modern secondary structure predictors and 4 representative supersecondary structure predictors. Finally, we provide several practical notes for the users of these prediction tools.

Identification of a chemoreceptor zinc-binding domain common to cytoplasmic bacterial chemoreceptors

We report the identification and characterization of a previously unidentified protein domain found in bacterial chemoreceptors and other bacterial signal transduction proteins. This domain contains a motif of three noncontiguous histidines and one cysteine, arranged as Hxx[WFYL]x(21-28)Cx[LFMVI]Gx[WFLVI]x(18-27)HxxxH(boldface type indicates residues that are nearly 100% conserved). This domain was first identified in the soluble Helicobacter pylori chemoreceptor TlpD. Using inductively coupled plasma mass spectrometry on heterologously and natively expressed TlpD, we determined that this domain binds zinc with a subfemtomolar dissociation constant. We thus named the domain CZB, for chemoreceptor zinc binding. Further analysis showed that many bacterial signaling proteins contain the CZB domain, most commonly proteins that participate in chemotaxis but also those that participate in c-di-GMP signaling and nitrate/nitrite sensing, among others. Proteins bearing the CZB domain are found in several bacterial phyla. The variety of signaling proteins using the CZB domain suggests that it plays a critical role in several signal transduction pathways.

Predicting protein folds with fold-specific PSSM libraries

Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies. Herein, we outline an effective method for fold recognition using sets of PSSMs, each of which is constructed for different protein folds. Our analyses demonstrate that FSL (Fold-specific Position Specific Scoring Matrix Libraries) can predict/relate structures given only their amino acid sequences of highly divergent proteins. This ability to detect distant relationships is dependent on low-identity sequence alignments obtained from FSL. Results from our experiments demonstrate that FSL perform well in recognizing folds from the "twilight-zone" SABmark dataset. Further, this method is capable of accurate fold prediction in newly determined structures. We suggest that by building complete PSSM libraries for all unique folds within the Protein Database (PDB), FSL can be used to rapidly and reliably annotate a large subset of protein folds at proteomic level. The related programs and fold-specific PSSMs for our FSL are publicly available at: http://ccp.psu.edu/download/FSLv1.0/.

Characterization of the interactions between the nucleoprotein and the phosphoprotein of Henipavirus

The Henipavirus genome is encapsidated by the nucleoprotein (N) within a helical nucleocapsid that recruits the polymerase complex via the phosphoprotein (P). In a previous study, we reported that in henipaviruses, the N-terminal domain of the phosphoprotein and the C-terminal domain of the nucleoprotein (N(TAIL)) are both intrinsically disordered. Here we show that Henipavirus N(TAIL) domains are also disordered in the context of full-length nucleoproteins. We also report the cloning, purification, and characterization of the C-terminal X domains (P(XD)) of Henipavirus phosphoproteins. Using isothermal titration calorimetry, we show that N(TAIL) and P(XD) form a 1:1 stoichiometric complex that is stable under NaCl concentrations as high as 1 M and has a K(D) in the μM range. Using far-UV circular dichroism and nuclear magnetic resonance, we show that P(XD) triggers an increase in the α-helical content of N(TAIL). Using fluorescence spectroscopy, we show that P(XD) has no impact on the chemical environment of a Trp residue introduced at position 527 of the Henipavirus N(TAIL) domain, thus arguing for the lack of stable contacts between the C termini of N(TAIL) and P(XD). Finally, we present a tentative structural model of the N(TAIL)-P(XD) interaction in which a short, order-prone region of N(TAIL) (α-MoRE; amino acids 473-493) adopts an α-helical conformation and is embedded between helices α2 and α3 of P(XD), leading to a relatively small interface dominated by hydrophobic contacts. The present results provide the first detailed experimental characterization of the N-P interaction in henipaviruses and designate the N(TAIL)-P(XD) interaction as a valuable target for rational antiviral approaches.

A score of the ability of a three-dimensional protein model to retrieve its own sequence as a quantitative measure of its quality and appropriateness

BACKGROUND

Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel.

PRINCIPAL FINDINGS

The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449-460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function.

CONCLUSION

Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models' backbone.

BCL::contact-low confidence fold recognition hits boost protein contact prediction and de novo structure determination

Knowledge of all residue-residue contacts within a protein allows determination of the protein fold. Accurate prediction of even a subset of long-range contacts (contacts between amino acids far apart in sequence) can be instrumental for determining tertiary structure. Here we present BCL::Contact, a novel contact prediction method that utilizes artificial neural networks (ANNs) and specializes in the prediction of medium to long-range contacts. BCL::Contact comes in two modes: sequence-based and structure-based. The sequence-based mode uses only sequence information and has individual ANNs specialized for helix-helix, helix-strand, strand-helix, strand-strand, and sheet-sheet contacts. The structure-based mode combines results from 32-fold recognition methods with sequence information to a consensus prediction. The two methods were presented in the 6(th) and 7(th) Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiments. The present work focuses on elucidating the impact of fold recognition results onto contact prediction via a direct comparison of both methods on a joined benchmark set of proteins. The sequence-based mode predicted contacts with 42% accuracy (7% false positive rate), while the structure-based mode achieved 45% accuracy (2% false positive rate). Predictions by both modes of BCL::Contact were supplied as input to the protein tertiary structure prediction program Rosetta for a benchmark of 17 proteins with no close sequence homologs in the protein data bank (PDB). Rosetta created higher accuracy models, signified by an improvement of 1.3 A on average root mean square deviation (RMSD), when driven by the predicted contacts. Further, filtering Rosetta models by agreement with the predicted contacts enriches for native-like fold topologies.

BuildBeta--a system for automatically constructing beta sheets

We describe a method that can thoroughly sample a protein conformational space given the protein primary sequence of amino acids and secondary structure predictions. Specifically, we target proteins with beta-sheets because they are particularly challenging for ab initio protein structure prediction because of the complexity of sampling long-range strand pairings. Using some basic packing principles, inverse kinematics (IK), and beta-pairing scores, this method creates all possible beta-sheet arrangements including those that have the correct packing of beta-strands. It uses the IK algorithms of ProteinShop to move alpha-helices and beta-strands as rigid bodies by rotating the dihedral angles in the coil regions. Our results show that our approach produces structures that are within 4-6 A RMSD of the native one regardless of the protein size and beta-sheet topology although this number may increase if the protein has long loops or complex alpha-helical regions.

Comparative molecular evolution of trichoderma chitinases in response to mycoparasitic interactions

Certain species of the fungal genus Trichoderma are potent mycoparasites and are used for biological control of fungal diseases on agricultural crops. In Trichoderma, whole-genome sequencing reveal between 20 and 36 different genes encoding chitinases, hydrolytic enzymes that are involved in the mycoparasitic attack. Sequences of Trichoderma chitinase genes chi18-5, chi18-13, chi18-15 and chi18-17, which all exhibit specific expression during mycoparasitism-related conditions, were determined from up to 13 different taxa and studied with regard to their evolutionary patterns. Two of them, chi18-13 and chi18-17, are members of the B1/B2 chitinase subgroup that have expanded significantly in paralog number in mycoparasitic Hypocrea atroviridis and H. virens. Chi18-13 contains two codons that evolve under positive selection and seven groups of co-evolving sites. Chi18-15 displays a unique codon-usage and contains five codons that evolve under positive selection and three groups of co-evolving sites. Regions of high amino acid variability are preferentially localized to substrate- or product side of the catalytic clefts. Differences in amino acid diversity/conservation patterns between different Trichoderma clades are observed. These observations show that Trichoderma chitinases chi18-13 and chi18-15 evolve in a manner consistent with rapid co-evolutionary interactions and identifies putative target regions involved in determining substrate-specificity.

Structure prediction-driven genetics in Saccharomyces cerevisiae identifies an interface between the t-RPA proteins Stn1 and Ten1

In Saccharomyces cerevisiae, Cdc13, Stn1, and Ten1 are essential for both chromosome capping and telomere length homeostasis. These three proteins have been proposed to perform their roles at chromosome termini as a telomere-dedicated t-RPA complex, on the basis of several parallels with the conventional RPA complex. In this study, we have used several approaches to test whether a predicted alpha-helix in the N-terminal domain of the S. cerevisiae Stn1 protein is required for formation of the proposed t-RPA complex, in a manner analogous to the comparable helix in Rpa2. Analysis of a panel of Rpa2-OB(Stn1) chimeras indicates that whether a chimeric protein contains the Rpa2 or Stn1 version of this alpha-helix dictates its ability to function in place of Rpa2 or Stn1, respectively. In addition, mutations introduced into a hydrophobic surface of the predicted Stn1 alpha-helix eliminated association with Ten1. Strikingly, allele-specific suppression of a stn1 mutation in this helix (stn1-L164D) by a ten1 mutation (ten1-D138Y) resulted in a restored Stn1-Ten1 interaction, supporting the identification of a Stn1-Ten1 interface. We conclude that Stn1 interacts with Ten1 through an alpha-helix, in a manner analogous to the interaction between the comparable subunits of the RPA complex.

Template-based protein structure modeling

Functional characterization of a protein is often facilitated by its 3D structure. However, the fraction of experimentally known 3D models is currently less than 1% due to the inherently time-consuming and complicated nature of structure determination techniques. Computational approaches are employed to bridge the gap between the number of known sequences and that of 3D models. Template-based protein structure modeling techniques rely on the study of principles that dictate the 3D structure of natural proteins from the theory of evolution viewpoint. Strategies for template-based structure modeling will be discussed with a focus on comparative modeling, by reviewing techniques available for all the major steps involved in the comparative modeling pipeline.

An integrated methodology for mining promiscuous proteins: a case study of an integrative bioinformatics approach for hepatitis C virus non-structural 5A protein

A methodology for elucidation of structural, functional, and mechanistic knowledge on promiscuous proteins is proposed that constitutes a workflow of integrated bioinformatics analysis. Sequence alignments with closely related homologues can reveal conserved regions which are functionally important. Scanning protein motif databases, along with secondary and surface accessibility predictions integrated with post-translational modification sites (PTMs) prediction reveal functional and protein-binding motifs. Integrating this information about the protein with the GO, SCOP, and CATH annotations of the templates can help to formulate a 3D model with reasonable accuracy even in the case of distant sequence homology. A novel integrative model of the non-structural protein 5A of Hepatitis C virus: a hub promiscuous protein with roles in virus replication and host interactions is proposed. The 3D structure for domain II was predicted based on, the Homo sapiens Replication factor-A protein-1 (RPA1), as a template using consensus meta-servers results. Domain III is an intrinsically unstructured domain with a fold from the retroviral matrix protein, which conducts diverse protein interactions and is involved in viral replication and protein interactions. It also has a single-stranded DNA-binding protein motif (SSDP) signature for pyrimidine binding during viral replication. Two protein-binding motifs with high sequence conservation and disordered regions are proposed; the first corresponds to an Interleukin-8B receptor signature (IL-8R-B), while the second has a lymphotoxin beta receptor (LTβR) high local similarity. A mechanism is proposed to their contribution to NS5A Interferon signaling pathway interception. Lastly, the overlapping between LTβR and SSDP is considered as a sign for NS5A date hubs.

Natural genetic engineering of hepatitis C virus NS5A for immune system counterattack

The Hepatitis C virus nonstructural 5A (NS5A) protein is a hydrophilic phosphoprotein with diverse functions. The domain assignment of NS5A had been refined using a systematic in silico bioinformatics approach using DOMAC, the protein is divided into three domains and domain III is subdivided into two subdomains using ProDom and SSEP servers. The fold structure for domains II and III were predicted using the meta-server 3D-Jury. Scanning motif databases (SMART, BLOCKS, and PROSITE) gave new motifs. Two important motifs, the interleukins 1 and 8 interaction motifs, relating to NS5A function in inducing the interleukin 8 promoter, were discovered from the BLOCKS scan. Protein-protein interaction motifs were predicted as hot loops and disordered regions, corresponding to binding regions with the ds-protein kinase R, viral polymerase, and Src homology 3 signaling proteins binding motif. Other hot loops were predicted in the V3 region and in the single-stranded DNA-binding protein motif. The different mechanisms by which the NS5A protein leads to immune system signaling dysfunction points to the natural genetic engineering of this protein.

Model quality assessment using distance constraints from alignments

Given a set of alternative models for a specific protein sequence, the model quality assessment (MQA) problem asks for an assignment of scores to each model in the set. A good MQA program assigns these scores such that they correlate well with real quality of the models, ideally scoring best that model which is closest to the true structure. In this article, we present a new approach for addressing the MQA problem. It is based on distance constraints extracted from alignments to templates of known structure, and is implemented in the Undertaker program for protein structure prediction. One novel feature is that we extract noncontact constraints as well as contact constraints. We describe how the distance constraint extraction is done and we show how they can be used to address the MQA problem. We have compared our method on CASP7 targets and the results show that our method is at least comparable with the best MQA methods that were assessed at CASP7. We also propose a new evaluation measure, Kendall's tau, that is more interpretable than conventional measures used for evaluating MQA methods (Pearson's r and Spearman's rho). We show clear examples where Kendall's tau agrees much more with our intuition of a correct MQA, and we therefore propose that Kendall's tau be used for future CASP MQA assessments.

Evaluating the absolute quality of a single protein model using structural features and support vector machines

Knowing the quality of a protein structure model is important for its appropriate usage. We developed a model evaluation method to assess the absolute quality of a single protein model using only structural features with support vector machine regression. The method assigns an absolute quantitative score (i.e. GDT-TS) to a model by comparing its secondary structure, relative solvent accessibility, contact map, and beta sheet structure with their counterparts predicted from its primary sequence. We trained and tested the method on the CASP6 dataset using cross-validation. The correlation between predicted and true scores is 0.82. On the independent CASP7 dataset, the correlation averaged over 95 protein targets is 0.76; the average correlation for template-based and ab initio targets is 0.82 and 0.50, respectively. Furthermore, the predicted absolute quality scores can be used to rank models effectively. The average difference (or loss) between the scores of the top-ranked models and the best models is 5.70 on the CASP7 targets. This method performs favorably when compared with the other methods used on the same dataset. Moreover, the predicted absolute quality scores are comparable across models for different proteins. These features make the method a valuable tool for model quality assurance and ranking.

A conserved unfoldase activity for the p97 AAA-ATPase in proteasomal degradation

The multifunctional AAA-ATPase p97 is one of the most abundant and conserved proteins in eukaryotic cells. The p97/Npl4/Ufd1 complex dislocates proteins that fail the protein quality control in the endoplasmic reticulum to the cytosol where they are subject to degradation by the ubiquitin/proteasome system. Substrate dislocation depends on the unfoldase activity of p97. Interestingly, p97 is also involved in the degradation of specific soluble proteasome substrates but the exact mode of action of p97 in this process is unclear. Here, we show that both the central pore and ATPase activity of p97 are necessary for the degradation of cytosolic ubiquitin-fusion substrates. Addition of a flexible extended C-terminal peptide to the substrate relieves the requirement for p97. Deletion mapping reveals a conserved length dependency of 20 residues for the peptide, which allows p97-independent degradation to occur. Our results suggest that initiation of unfolding may be more complex than previously anticipated and that the 19S regulatory complex of the proteasome can require preprocessing of highly folded, ubiquitylated substrates by the p97(Ufd1/Npl4) complex. Our data provide an explanation for the observation that p97 is only essential for a subpopulation of soluble substrates and predict that a common characteristic of soluble p97-dependent substrates is the lack of an initiation site to facilitate unfolding by the 26S proteasome.

A spectroscopic investigation into the interactions of 3'-O-carboxy esters of thymidine with bovine serum albumin

Binding studies of 3'-O-carboxy esters of thymidine, reported inhibitors of ribonucleases, with bovine serum albumin (BSA) have been explored in this report. Fluorescence spectroscopy in combination with Fourier transform infrared (FTIR) and circular dichroism (CD) spectroscopy have been used to determine the nature and mode of binding. The binding and quenching parameters were determined from tryptophan fluorescence quenching by Scatchard plots and modified Stern-Volmer plots. The association constants are of the order of 10(4) M(-1) for both the ligands. Thermodynamic parameters suggest that apart from an initial hydrophobic association, hydrogen bonding and van der Waals interactions play a decisive role during protein-ligand complex formation. Minor changes were observed in the secondary structures of human serum albumin (HSA) as revealed by FTIR and CD. Docking studies suggest that the ligands are close to Trp 213, which causes fluorescence quenching.

Characterization and comparative sequence analysis of the DNA mismatch repair MSH2 and MSH7 genes from tomato

DNA mismatch repair proteins play an essential role in maintaining genomic integrity during replication and genetic recombination. We successfully isolated a full length MSH2 and partial MSH7 cDNAs from tomato, based on sequence similarity between MutS and plant MSH homologues. Semi-quantitative RT-PCR reveals higher levels of mRNA expression of both genes in young leaves and floral buds. Genetic mapping placed MSH2 and MSH7 on chromosomes 6 and 7, respectively, and indicates that these genes exist as single copies in the tomato genome. Analysis of protein sequences and phylogeny of the plant MSH gene family show that these proteins are evolutionarily conserved, and follow the classical model of asymmetric protein evolution. Genetic manipulation of the expression of these MSH genes in tomato will provide a potentially useful tool for modifying genetic recombination and hybrid fertility between wide crosses.

Structural modeling identified the tRNA-binding domain of Utp8p, an essential nucleolar component of the nuclear tRNA export machinery of Saccharomyces cerevisiae

Utp8p is an essential 80 kDa intranuclear tRNA chaperone that transports tRNAs from the nucleolus to the nuclear tRNA export receptors in Saccharomyces cerevisiae. To help understand the mechanism of Utp8p function, predictive tools were used to derive a partial model of the tertiary structure of Utp8p. Secondary structure prediction, supported by circular dichroism measurements, indicated that Utp8p is divided into 2 domains: the N-terminal beta sheet and the C-terminal alpha helical domain. Tertiary structure prediction was more challenging, because the amino acid sequence of Utp8p is not directly homologous to any known protein structure. The tertiary structures predicted by threading and fold recognition had generally modest scores, but for the C-terminal domain, threading and fold recognition consistently pointed to an alpha-alpha superhelix. Because of the sequence diversity of this fold type, no single structural template was an ideal fit to the Utp8p sequence. Instead, a composite template was constructed from 3 different alpha-alpha superhelix structures that gave the best matches to different portions of the C-terminal domain sequence. In the resulting model, the most conserved sequences grouped in a tight cluster of positive charges on a protein that is otherwise predominantly negative, suggesting that the positive-charge cleft may be the tRNA-binding site. Mutations of conserved positive residues in the proposed binding site resulted in a reduction in the affinity of Utp8p for tRNA both in vivo and in vitro. Models were also derived for the 10 fungal homologues of Utp8p, and the localization of the positive charges on the conserved surface was found in all cases. Taken together, these data suggest that the positive-charge cleft of the C-terminal domain of Utp8p is involved in tRNA-binding.

Pokefind: a novel topological filter for use with protein structure prediction

MOTIVATION

Our focus has been on detecting topological properties that are rare in real proteins, but occur more frequently in models generated by protein structure prediction methods such as Rosetta. We previously created the Knotfind algorithm, successfully decreasing the frequency of knotted Rosetta models during CASP6. We observed an additional class of knot-like loops that appeared to be equally un-protein-like and yet do not contain a mathematical knot. These topological features are commonly referred to as slip-knots and are caused by the same mechanisms that result in knotted models. Slip-knots are undetectable by the original Knotfind algorithm. We have generalized our algorithm to detect them, and analyzed CASP6 models built using the Rosetta loop modeling method.

RESULTS

After analyzing known protein structures in the PDB, we found that slip-knots do occur in certain proteins, but are rare and fall into a small number of specific classes. Our group used this new Pokefind algorithm to distinguish between these rare real slip-knots and the numerous classes of slip-knots that we discovered in Rosetta models and models submitted by the various CASP7 servers. The goal of this work is to improve future models created by protein structure prediction methods. Both algorithms are able to detect un-protein-like features that current metrics such as GDT are unable to identify, so these topological filters can also be used as additional assessment tools.

SAM-T08, HMM-based protein structure prediction

The SAM-T08 web server is a protein structure prediction server that provides several useful intermediate results in addition to the final predicted 3D structure: three multiple sequence alignments of putative homologs using different iterated search procedures, prediction of local structure features including various backbone and burial properties, calibrated E-values for the significance of template searches of PDB and residue–residue contact predictions. The server has been validated as part of the CASP8 assessment of structure prediction as having good performance across all classes of predictions. The SAM-T08 server is available at http://compbio.soe.ucsc.edu/SAM_T08/T08-query.html

Fold prediction of VP24 protein of Ebola and Marburg viruses using de novo fragment assembly

Virus particle 24 (VP24) is the smallest protein of the Ebola and Marburg virus genomes. Recent experiments show that Ebola VP24 blocks binding of tyrosine-phosphorylated STAT-1 homodimer (PY-STAT1) to the NPI-1 subfamily of importin alpha, thereby preventing nuclear accumulation of this interferon-promoting transcription factor which, in turn, reduces the innate immune response of the host target. Lacking an experimental structure for VP24, we applied de novo protein structure prediction using the fragment assembly-based Rosetta method to classify its fold topology and better understand its biological function. Filtering and ranking of models were performed with the DFIRE all-atom statistical potential and the CHARMM22 force field with a generalized Born solvent model. From 40,000 Rosetta-generated structures and selective comparisons with the SCOP database, a structural match to two of our top 10-ranking models was the Armadillo repeat fold topology. Specific members of this fold family include importin alpha, importin beta, and exportin. We propose that, unlike the nuclear import of host cargo, VP24 lacks a classical nuclear localization signal (NLS) and targets importin alpha in a similar manner to the observed heterodimeric complex with exportin, thereby interfering with the auto-inhibitory NLS on importin alpha and blocking peripheral docking sites for PY-STAT1 assembly.

A comprehensive analysis of the La-motif protein superfamily

The extremely well-conserved La motif (LAM), in synergy with the immediately following RNA recognition motif (RRM), allows direct binding of the (genuine) La autoantigen to RNA polymerase III primary transcripts. This motif is not only found on La homologs, but also on La-related proteins (LARPs) of unrelated function. LARPs are widely found amongst eukaryotes and, although poorly characterized, appear to be RNA-binding proteins fulfilling crucial cellular functions. We searched the fully sequenced genomes of 83 eukaryotic species scattered along the tree of life for the presence of LAM-containing proteins. We observed that these proteins are absent from archaea and present in all eukaryotes (except protists from the Plasmodium genus), strongly suggesting that the LAM is an ancestral motif that emerged early after the archaea-eukarya radiation. A complete evolutionary and structural analysis of these proteins resulted in their classification into five families: the genuine La homologs and four LARP families. Unexpectedly, in each family a conserved domain representing either a classical RRM or an RRM-like motif immediately follows the LAM of most proteins. An evolutionary analysis of the LAM-RRM/RRM-L regions shows that these motifs co-evolved and should be used as a single entity to define the functional region of interaction of LARPs with their substrates. We also found two extremely well conserved motifs, named LSA and DM15, shared by LARP6 and LARP1 family members, respectively. We suggest that members of the same family are functional homologs and/or share a common molecular mode of action on different RNA baits.

Candidate effector gene identification in the ascomycete fungal phytopathogen Venturia inaequalis by expressed sequence tag analysis

The hemi-biotrophic fungus Venturia inaequalis infects members of the Maloideae, causing the economically important apple disease, scab. The plant-pathogen interaction of Malus and V. inaequalis follows the gene-for-gene model. cDNA libraries were constructed, and bioinformatic analysis of the resulting expressed sequence tags (ESTs) was used to characterize potential effector genes. Effectors are small proteins, secreted in planta, that are assumed to facilitate infection. Therefore, a cDNA library was constructed from a compatible interaction. To distinguish pathogen from plant sequences, the library was probed with genomic DNA from V. inaequalis to enrich for pathogen genes, and cDNA libraries were constructed from in vitro-grown material. A suppression subtractive hybridization library enriched for cellophane-induced genes was included, as growth on cellophane may mimic that in planta, with the differentiation of structures resembling those formed during plant colonization. Clustering of ESTs from the in planta and in vitro libraries indicated a fungal origin of the resulting non-redundant sequence. A total of 937 ESTs was classified as putatively fungal, which could be assembled into 633 non-redundant sequences. Sixteen new candidate effector genes were identified from V. inaequalis based on features common to characterized effector genes from filamentous fungi, i.e. they encode a small, novel, cysteine-rich protein, with a putative signal peptide. Three of the 16 candidates, in particular, conformed to most of the protein structural characteristics expected of fungal effectors and showed significant levels of transcriptional up-regulation during in planta growth. In addition to candidate effector genes, this collection of ESTs represents a valuable genomic resource for V. inaequalis.

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB) might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R₁ (Deira), resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP) and the Protein Structural Interactome (PSI)-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

Proteomic tools for the analysis of cytoskeleton proteins

Proteomic tools have become an essential part of the tool kit of the molecular biologist, and provide techniques for detecting homologous sequences, recognizing functional domains, modeling, and analyzing the three-dimensional structure for any given protein sequence. Although a wealth of structural and functional information is available for a large number of members of the various classes of cytoskeletal proteins, many more members remain uncharacterized. These computational tools that are freely and easily accessible to the scientific community provide an excellent starting point to predict the structural and functional properties of such partially or fully uncharacterized protein sequences, and can lead to elegantly designed experiments to probe the hypothesized function. This chapter discusses various proteomic analysis tools with a focus on protein structure and function predictions.

Evolutionary and structural analyses of alpha-papillomavirus capsid proteins yields novel insights into L2 structure and interaction with L1

Background

PVs (PV) are small, non-enveloped, double-stranded DNA viruses that have been identified as the primary etiological agent for cervical cancer and their potential for malignant transformation in mucosal tissue has a large impact on public health. The PV family Papillomaviridae is organized into multiple genus based on sequential parsimony, host range, tissue tropism, and histology. We focused this analysis on the late gene products, major (L1) and minor (L2) capsid proteins from the family Papillomaviridae genus Alpha-papillomavirus. Alpha-PVs preferentially infect oral and anogenital mucosa of humans and primates with varied risk of oncogenic transformation. Development of evolutionary associations between PVs will likely provide novel information to assist in clarifying the currently elusive relationship between PV and its microenvironment (i.e., the single infected cell) and macro environment (i.e., the skin tissue). We attempt to identify the regions of the major capsid proteins as well as minor capsid proteins of alpha-papillomavirus that have been evolutionarily conserved, and define regions that are under constant selective pressure with respect to the entire family of viruses.

Results

This analysis shows the loops of L1 are in fact the most variable regions among the alpha-PVs. We also identify regions of L2, involved in interaction with L1, as evolutionarily conserved among the members of alpha- PVs. Finally, a predicted three-dimensional model was generated to further elucidate probable aspects of the L1 and L2 interaction.

Modeling of Escherichia coli Endonuclease V structure in complex with DNA

Endonuclease V (EndoV) is a metal-dependent DNA repair enzyme involved in removal of deaminated bases (e.g., deoxyuridine, deoxyinosine, and deoxyxanthosine), with pairing specificities different from the original bases. Homologs of EndoV are present in all major phyla from bacteria to humans and their function is quite well analyzed. EndoV has been combined with DNA ligase to develop an enzymatic method for mutation scanning and has been engineered to obtain variants with different substrate specificities that serve as improved tools in mutation recognition and cancer mutation scanning. However, little is known about the structure and mechanism of substrate DNA binding by EndoV. Here, we present the results of a bioinformatic analysis and a structural model of EndoV from Escherichia coli in complex with DNA. The structure was obtained by a combination of fold-recognition, comparative modeling, de novo modeling and docking methods. The modeled structure provides a convenient tool to study protein sequence-structure-function relationships in EndoV and to engineer its further variants.

Analysis of a set of missense, frameshift, and in-frame deletion variants of BRCA1

Germline mutations that inactivate BRCA1 are responsible for breast and ovarian cancer susceptibility. One possible outcome of genetic testing for BRCA1 is the finding of a genetic variant of uncertain significance for which there is no information regarding its cancer association. This outcome leads to problems in risk assessment, counseling and preventive care. The purpose of the present study was to functionally evaluate seven unclassified variants of BRCA1 including a genomic deletion that leads to the in-frame loss of exons 16/17 (Delta exons 16/17) in the mRNA, an insertion that leads to a frameshift and an extended carboxy-terminus (5673insC), and five missense variants (K1487R, S1613C, M1652I, Q1826H and V1833M). We analyzed the variants using a functional assay based on the transcription activation property of BRCA1 combined with supervised learning computational models. Functional analysis indicated that variants S1613C, Q1826H, and M1652I are likely to be neutral, whereas variants V1833M, Delta exons 16/17, and 5673insC are likely to represent deleterious variants. In agreement with the functional analysis, the results of the computational analysis also indicated that the latter three variants are likely to be deleterious. Taken together, a combined approach of functional and bioinformatics analysis, plus structural modeling, can be utilized to obtain valuable information pertaining to the effect of a rare variant on the structure and function of BRCA1. Such information can, in turn, aid in the classification of BRCA1 variants for which there is a lack of genetic information needed to provide reliable risk assessment.

PREDICT-2ND: a tool for generalized protein local structure prediction

MOTIVATION

Predictions of protein local structure, derived from sequence alignment information alone, provide visualization tools for biologists to evaluate the importance of amino acid residue positions of interest in the absence of X-ray crystal/NMR structures or homology models. They are also useful as inputs to sequence analysis and modeling tools, such as hidden Markov models (HMMs), which can be used to search for homology in databases of known protein structure. In addition, local structure predictions can be used as a component of cost functions in genetic algorithms that predict protein tertiary structure. We have developed a program (predict-2nd) that trains multilayer neural networks and have applied it to numerous local structure alphabets, tuning network parameters such as the number of layers, the number of units in each layer and the window sizes of each layer. We have had the most success with four-layer networks, with gradually increasing window sizes at each layer.

RESULTS

Because the four-layer neural nets occasionally get trapped in poor local optima, our training protocol now uses many different random starts, with short training runs, followed by more training on the best performing networks from the short runs. One recent addition to the program is the option to add a guide sequence to the profile inputs, increasing the number of inputs per position by 20. We find that use of a guide sequence provides a small but consistent improvement in the predictions for several different local-structure alphabets.

AVAILABILITY

Local structure prediction with the methods described here is available for use online at http://www.soe.ucsc.edu/compbio/SAM_T08/T08-query.html. The source code and example networks for PREDICT-2ND are available at http://www.soe.ucsc.edu/~karplus/predict-2nd/ A required C++ library is available at http://www.soe.ucsc.edu/~karplus/ultimate/

The Est3 protein associates with yeast telomerase through an OB-fold domain

The Est3 protein is a small regulatory subunit of yeast telomerase which is dispensable for enzyme catalysis but essential for telomere replication in vivo. Using structure prediction combined with in vivo characterization, we show here that Est3 consists of a predicted OB (oligo-saccharide/oligo-nucleotide binding) fold. Mutagenesis of predicted surface residues was used to generate a functional map of one surface of Est3, which identified a site that mediates association with the telomerase complex. Surprisingly, the predicted OB-fold of Est3 is structurally similar to the OB-fold of the mammalian TPP1 protein, despite the fact that Est3 and TPP1, as components of telomerase and a telomere capping complex, respectively, perform functionally distinct tasks at chromosome ends. The analysis performed on Est3 may be instructive in generating comparable missense mutations on the surface of the OB-fold domain of TPP1.

Contact prediction in protein modeling: scoring, folding and refinement of coarse-grained models

BACKGROUND

Several different methods for contact prediction succeeded within the Sixth Critical Assessment of Techniques for Protein Structure Prediction (CASP6). The most relevant were non-local contact predictions for targets from the most difficult categories: fold recognition-analogy and new fold. Such contacts could provide valuable structural information in case a template structure cannot be found in the PDB.

RESULTS

We described comprehensive tests of the effectiveness of contact data in various aspects of de novo modeling with CABS, an algorithm which was used successfully in CASP6 by the Kolinski-Bujnicki group. We used the predicted contacts in a simple scoring function for the post-simulation ranking of protein models and as a soft bias in the folding simulations and in the fold-refinement procedure. The latter approach turned out to be the most successful. The CABS force field used in the Replica Exchange Monte Carlo simulations cooperated with the true contacts and discriminated the false ones, which resulted in an improvement of the majority of Kolinski-Bujnicki's protein models. In the modeling we tested different sets of predicted contact data submitted to the CASP6 server. According to our results, the best performing were the contacts with the accuracy balanced with the coverage, obtained either from the best two predictors only or by a consensus from as many predictors as possible.

CONCLUSION

Our tests have shown that theoretically predicted contacts can be very beneficial for protein structure prediction. Depending on the protein modeling method, a contact data set applied should be prepared with differently balanced coverage and accuracy of predicted contacts. Namely, high coverage of contact data is important for the model ranking and high accuracy for the folding simulations.

The PMS2 subunit of human MutLalpha contains a metal ion binding domain of the iron-dependent repressor protein family

DNA mismatch repair (MMR) is responsible for correcting replication errors. MutLalpha, one of the main players in MMR, has been recently shown to harbor an endonuclease/metal-binding activity, which is important for its function in vivo. This endonuclease activity has been confined to the C-terminal domain of the hPMS2 subunit of the MutLalpha heterodimer. In this work, we identify a striking sequence-structure similarity of hPMS2 to the metal-binding/dimerization domain of the iron-dependent repressor protein family and present a structural model of the metal-binding domain of MutLalpha. According to our model, this domain of MutLalpha comprises at least three highly conserved sequence motifs, which are also present in most MutL homologs from bacteria that do not rely on the endonuclease activity of MutH for strand discrimination. Furthermore, based on our structural model, we predict that MutLalpha is a zinc ion binding protein and confirm this prediction by way of biochemical analysis of zinc ion binding using the full-length and C-terminal domain of MutLalpha. Finally, we demonstrate that the conserved residues of the metal ion binding domain are crucial for MMR activity of MutLalpha in vitro.