Retrieving backbone string neighbors provides insights into structural modeling of membrane proteins

Identification of protein structural neighbors to a query is fundamental in structure and function prediction. Here we present BS-align, a systematic method to retrieve backbone string neighbors from primary sequences as templates for protein modeling. The backbone conformation of a protein is represented by the backbone string, as defined in Ramachandran space. The backbone string of a query can be accurately predicted by two innovative technologies: a knowledge-driven sequence alignment and encoding of a backbone string element profile. Then, the predicted backbone string is employed to align against a backbone string database and retrieve a set of backbone string neighbors. The backbone string neighbors were shown to be close to native structures of query proteins. BS-align was successfully employed to predict models of 10 membrane proteins with lengths ranging between 229 and 595 residues, and whose high-resolution structural determinations were difficult to elucidate both by experiment and prediction. The obtained TM-scores and root mean square deviations of the models confirmed that the models based on the backbone string neighbors retrieved by the BS-align were very close to the native membrane structures although the query and the neighbor shared a very low sequence identity. The backbone string system represents a new road for the prediction of protein structure from sequence, and suggests that the similarity of the backbone string would be more informative than describing a protein as belonging to a fold.     

Active site binding modes of curcumin in HIV-1 protease and integrase

Structure models for the interaction of curcumin with HIV-1 integrase (IN) and protease (PR) were investigated using computational docking. Curcumin was found to bind preferentially in similar ways to the active sites of both IN and PR. For IN, the binding site is formed by residues Asp64, His67, Thr66, Glu92, Thr93, Asp116, Ser119, Asn120, and Lys159. Docked curcumin contacts the catalytic residues adjacent to Asp116 and Asp64, and near the divalent metal (Mg2+). In the PR docking, the curcumin structure fitted well to the active site, interacting with residues Asp25, Asp29, Asp30, Gly27', Asp29', and Asp30'. The results suggest that o-hydroxyl and/or keto-enol structures are important for both IN and PR inhibitory actions. The symmetrical structure of curcumin seems to play an important role for binding to the PR protein, whereas the keto-enol and only one side of the terminal o-hydroxyl showed tight binding to the IN active site.     

A distant evolutionary relationship between bacterial sphingomyelinase and mammalian DNase I.

The three-dimensional structure of bacterial sphingomyelinase (SMase) was predicted using a protein fold recognition method; the search of a library of known structures showed that the SMase sequence is highly compatible with the mammalian DNase I structure, which suggested that SMase adopts a structure similar to that of DNase I. The amino acid sequence alignment based on the prediction revealed that, despite the lack of overall sequence similarity (less than 10% identity), those residues of DNase I that are involved in the hydrolysis of the phosphodiester bond, including two histidine residues (His 134 and His 252) of the active center, are conserved in SMase. In addition, a conserved pentapeptide sequence motif was found, which includes two catalytically critical residues, Asp 251 and His 252. A sequence database search showed that the motif is highly specific to mammalian DNase I and bacterial SMase. The functional roles of SMase residues identified by the sequence comparison were consistent with the results from mutant studies. Two Bacillus cereus SMase mutants (H134A and H252A) were constructed by site-directed mutagenesis. They completely abolished their catalytic activity. A model for the SMase-sphingomyelin complex structure was built to investigate how the SMase specifically recognizes its substrate. The model suggested that a set of residues conserved among bacterial SMases, including Trp 28 and Phe 55, might be important in the substrate recognition. The predicted structural similarity and the conservation of the functionally important residues strongly suggest a distant evolutionary relationship between bacterial SMase and mammalian DNase I. These two phosphodiesterases must have acquired the specificity for different substrates in the course of evolution.     

SQUARE--determining reliable regions in sequence alignments

The Server for Quick Alignment Reliability Evaluation (SQUARE) is a Web-based version of the method we developed to predict regions of reliably aligned residues in sequence alignments. Given an alignment between a query sequence and a sequence of known structure, SQUARE is able to predict which residues are reliably aligned. The server accesses a database of profiles of sequences of known three-dimensional structures in order to calculate the scores for each residue in the alignment. SQUARE produces a graphical output of the residue profile-derived alignment scores along with an indication of the reliability of the alignment. In addition, the scores can be compared against template secondary structure, conserved residues and important sites.     

Single residue mutation in integrase catalytic core domain affects feline foamy viral DNA integration

DD(35)E motif in catalytic core domain (CCD) of integrase (IN) is extremely involved in retroviral integration step. Here, nine single residue mutants of feline foamy virus (FFV) IN were generated to study their effects on IN activities and on viral replication. As expected, mutations in the highly conserved D107, D164, and E200 residues abolished all IN catalytic activities (3′-end processing, strand transfer, and disintegration) as well as viral infectivity by blocking viral DNA integration into cellular DNA. However, Q165, Y191, and S195 mutants, which are located closely to DDE motif were observed to have diverse levels of enzymatic activities, compared to those of the wild type IN. Their mutant viruses produced by one-cycle transfection showed different infectivity on their natural host cells. Therefore, it is likely that effects of single residue mutation at DDE motif is critical on viral replication depending on the position of the residues.     

Conserved amino acid motifs from the novel Piv/MooV family of transposases and site-specific recombinases are required for catalysis of DNA inversion by Piv

Piv, a site-specific invertase from Moraxella lacunata, exhibits amino acid homology with the transposases of the IS110/IS492 family of insertion elements. The functions of conserved amino acid motifs that define this novel family of both transposases and site-specific recombinases (Piv/MooV family) were examined by mutagenesis of fully conserved amino acids within each motif in Piv. All Piv mutants altered in conserved residues were defective for in vivo inversion of the M. lacunata invertible DNA segment, but competent for in vivo binding to Piv DNA recognition sequences. Although the primary amino acid sequences of the Piv/MooV recombinases do not contain a conserved DDE motif, which defines the retroviral integrase/transposase (IN/Tnps) family, the predicted secondary structural elements of Piv align well with those of the IN/Tnps for which crystal structures have been determined. Molecular modelling of Piv based on these alignments predicts that E59, conserved as either E or D in the Piv/MooV family, forms a catalytic pocket with the conserved D9 and D101 residues. Analysis of Piv E59G confirms a role for E59 in catalysis of inversion. These results suggest that Piv and the related IS110/IS492 transposases mediate DNA recombination by a common mechanism involving a catalytic DED or DDD motif.     

Homology-based modeling of 3D structures of protein-protein complexes using alignments of modified sequence profiles

Customary practice in predicting 3D structures of protein-protein complexes is employment of various docking methods when the structures of separate monomers are known a priori. The alternative approach, i.e. the template-based prediction with pure sequence information as a starting point, is still considered as being inferior mostly due to presumption that the pool of available structures of protein-protein complexes, which can serve as putative templates, is not sufficiently large. Recently, however, several labs have developed databases containing thousands of 3D structures of protein-protein complexes, which enable statistically reliable testing of homology-based algorithms. In this paper we report the results on homology-based modeling of 3D structures of protein complexes using alignments of modified sequence profiles. The method, called HOMology-BAsed COmplex Prediction (HOMBACOP), has two distinctive features: (I) extra weight on aligning interfacial residues in the dynamical programming algorithm, and (II) increased gap penalties for the interfacial segments. The method was tested against our recently developed ProtCom database and against the Boston University protein-protein BENCHMARK. In both cases, models generated were compared to the models built on basis of customarily protein structure initiative (PSI)-BLAST sequence alignments. It was found that existence of homologous (by the means of PSI-BLAST) templates (44% of cases) enables both methods to produce models of good quality, with the profiles method outperforming the PSI-BLAST models (with respect to the percentage of correctly predicted residues on the complex interface and fraction of native interfacial contacts). The models were evaluated according to the CAPRI assessment criteria and about two thirds of the models were found to fall into acceptable and medium-quality categories. The same comparison of a larger set of 463 protein complexes showed again that profiles generate better models. We further demonstrate, using our ProtCom database, the suitability of the profile alignment algorithm in detecting remote homologues between query and template sequences, where the PSI-BLAST method fails.     

Molecular modeling of the dimeric structure of human lipoprotein lipase and functional studies of the carboxyl-terminal domain.

Lipoprotein lipase (LPL) plays a key role in lipid metabolism. Molecular modeling of dimeric LPL was carried out using insight ii based upon the crystal structures of human, porcine, and horse pancreatic lipase. The dimeric model reveals a saddle-shaped structure and the key heparin-binding residues in the amino-terminal domain located on the top of this saddle. The models of two dimeric conformations - a closed, inactive form and an open, active form - differ with respect to how surface-loop positions affect substrate access to the catalytic site. In the closed form, the surface loop covers the catalytic site, which becomes inaccessible to solvent. Large conformational changes in the open form, especially in the loop and carboxyl-terminal domain, allow substrate access to the active site. To dissect the structure-function relationships of the LPL carboxyl-terminal domain, several residues predicted by the model structure to be essential for the functions of heparin binding and substrate recognition were mutagenized. Arg405 plays an important role in heparin binding in the active dimer. Lys413/Lys414 or Lys414 regulates heparin affinity in both monomeric and dimeric forms. To evaluate the prediction that LPL forms a homodimer in a 'head-to-tail' orientation, two inactive LPL mutants - a catalytic site mutant (S132T) and a substrate-recognition mutant (W390A/W393A/W394A) - were cotransfected into COS7 cells. Lipase activity could be recovered only when heterodimerization occurred in a head-to-tail orientation. After cotransfection, 50% of the wild-type lipase activity was recovered, indicating that lipase activity is determined by the interaction between the catalytic site on one subunit and the substrate-recognition site on the other.     

Prediction of substrate specificity in NS3/4A serine protease by biased sequence search threading

Proteases recognize specific substrate sequences and catalyze the hydrolysis of targeted peptide bonds to activate or degrade them. It is particularly important to identify the recognition and binding mechanisms of protease–substrate complex structures in studies of drug development. Cleavage specificity in protease systems is generally determined by the amino acid profile, structural features, and distinct molecular interactions. In this work, substrate variability and substrate specificity of the NS3/4A serine protease encoded by the hepatitis C virus (HCV) was investigated by the biased sequence search threading (BSST) methodology. The available crystal structures of peptide-bound protease were used as templates as well as new complex structures that were generated via docking calculations. Threading various binding and nonbinding sequences as starting sequences over multiple templates, the potential sequence space was efficiently explored by a low-resolution knowledge-based scoring potential. The low-energy substrate sequences generated by the biased search are correlated with the natural substrates with conserved amino acid preferences, although some positions exhibit variability. Specifically, the amino acids which play essential roles in cleavage are mostly preferred. Potential substrate sequences were predicted by statistical probability approaches that consider the pairwise and triplewise interdependencies among residue positions in the low-energy sequences. The predicted substrate sequences also reproduce most of the natural substrate sequences, implying the complex interdependence between the different substrate residues. Consequently, the BSST seems to provide a powerful methodology for predicting the substrate specificity for the NS3/4A protease, which is a target in drug discovery studies for HCV.     

Structural and sequencing analysis of local target DNA recognition by MLV integrase

Target-site selection by retroviral integrase (IN) proteins profoundly affects viral pathogenesis. We describe the solution nuclear magnetic resonance structure of the Moloney murine leukemia virus IN (M-MLV) C-terminal domain (CTD) and a structural homology model of the catalytic core domain (CCD). In solution, the isolated MLV IN CTD adopts an SH3 domain fold flanked by a C-terminal unstructured tail. We generated a concordant MLV IN CCD structural model using SWISS-MODEL, MMM-tree and I-TASSER. Using the X-ray crystal structure of the prototype foamy virus IN target capture complex together with our MLV domain structures, residues within the CCD α2 helical region and the CTD β1-β2 loop were predicted to bind target DNA. The role of these residues was analyzed in vivo through point mutants and motif interchanges. Viable viruses with substitutions at the IN CCD α2 helical region and the CTD β1-β2 loop were tested for effects on integration target site selection. Next-generation sequencing and analysis of integration target sequences indicate that the CCD α2 helical region, in particular P187, interacts with the sequences distal to the scissile bonds whereas the CTD β1-β2 loop binds to residues proximal to it. These findings validate our structural model and disclose IN-DNA interactions relevant to target site selection.     

DNABind: A hybrid algorithm for structure‐based prediction of DNA‐binding residues by combining machine learning‐ and template‐based approaches

Accurate prediction of DNA‐binding residues has become a problem of increasing importance in structural bioinformatics. Here, we presented DNABind, a novel hybrid algorithm for identifying these crucial residues by exploiting the complementarity between machine learning‐ and template‐based methods. Our machine learning‐based method was based on the probabilistic combination of a structure‐based and a sequence‐based predictor, both of which were implemented using support vector machines algorithms. The former included our well‐designed structural features, such as solvent accessibility, local geometry, topological features, and relative positions, which can effectively quantify the difference between DNA‐binding and nonbinding residues. The latter combined evolutionary conservation features with three other sequence attributes. Our template‐based method depended on structural alignment and utilized the template structure from known protein–DNA complexes to infer DNA‐binding residues. We showed that the template method had excellent performance when reliable templates were found for the query proteins but tended to be strongly influenced by the template quality as well as the conformational changes upon DNA binding. In contrast, the machine learning approach yielded better performance when high‐quality templates were not available (about 1/3 cases in our dataset) or the query protein was subject to intensive transformation changes upon DNA binding. Our extensive experiments indicated that the hybrid approach can distinctly improve the performance of the individual methods for both bound and unbound structures. DNABind also significantly outperformed the state‐of‐art algorithms by around 10% in terms of Matthews's correlation coefficient. The proposed methodology could also have wide application in various protein functional site annotations. DNABind is freely available at http://mleg.cse.sc.edu/DNABind/ . Proteins 2013; 81:1885–1899. © 2013 Wiley Periodicals, Inc.     

Constructing HIV-1 integrase tetramer and exploring influences of metal ions on forming integrase-DNA complex

HIV-1 integrase (IN) is essential for the replication of HIV-1 in human cells. At present, the complete structure of complex IN-DNA has not been resolved. In this paper, a HIV-1 IN tetramer model was built with homology modeling and molecular dynamics simulation approach, in which two Mg2+ ions were reasonably located in each catalytic core domain. Moreover, it was found that the AB and CD chains of HIV-1 IN tetramer were different in the structures and metal ions of HIV-1 IN tetramer might have great influences on DNA locating on IN. These findings may provide a more complete structural basis for guiding drug discovery and revealing integration mechanism.     

Modeling protein loops with knowledge-based prediction of sequence-structure alignment

MOTIVATION: As protein structure database expands, protein loop modeling remains an important and yet challenging problem. Knowledge-based protein loop prediction methods have met with two challenges in methodology development: (1) loop boundaries in protein structures are frequently problematic in constructing length-dependent loop databases for protein loop predictions; (2) knowledge-based modeling of loops of unknown structure requires both aligning a query loop sequence to loop templates and ranking the loop sequence-template matches. RESULTS: We developed a knowledge-based loop prediction method that circumvents the need of constructing hierarchically clustered length-dependent loop libraries. The method first predicts local structural fragments of a query loop sequence and then structurally aligns the predicted structural fragments to a set of non-redundant loop structural templates regardless of the loop length. The sequence-template alignments are then quantitatively evaluated with an artificial neural network model trained on a set of predictions with known outcomes. Prediction accuracy benchmarks indicated that the novel procedure provided an alternative approach overcoming the challenges of knowledge-based loop prediction. AVAILABILITY: http://cmb.genomics.sinica.edu.tw     

Enhanced performance in prediction of protein active sites with THEMATICS and support vector machines

Theoretical microscopic titration curves (THEMATICS) is a computational method for the identification of active sites in proteins through deviations in computed titration behavior of ionizable residues. While the sensitivity to catalytic sites is high, the previously reported sensitivity to catalytic residues was not as high, about 50%. Here THEMATICS is combined with support vector machines (SVM) to improve sensitivity for catalytic residue prediction from protein 3D structure alone. For a test set of 64 proteins taken from the Catalytic Site Atlas (CSA), the average recall rate for annotated catalytic residues is 61%; good precision is maintained selecting only 4% of all residues. The average false positive rate, using the CSA annotations is only 3.2%, far lower than other 3D-structure-based methods. THEMATICS-SVM returns higher precision, lower false positive rate, and better overall performance, compared with other 3D-structure-based methods. Comparison is also made with the latest machine learning methods that are based on both sequence alignments and 3D structures. For annotated sets of well-characterized enzymes, THEMATICS-SVM performance compares very favorably with methods that utilize sequence homology. However, since THEMATICS depends only on the 3D structure of the query protein, no decline in performance is expected when applied to novel folds, proteins with few sequence homologues, or even orphan sequences. An extension of the method to predict non-ionizable catalytic residues is also presented. THEMATICS-SVM predicts a local network of ionizable residues with strong interactions between protonation events; this appears to be a special feature of enzyme active sites.     

Recurrent use of evolutionary importance for functional annotation of proteins based on local structural similarity

The annotation of protein function has not kept pace with the exponential growth of raw sequence and structure data. An emerging solution to this problem is to identify 3D motifs or templates in protein structures that are necessary and sufficient determinants of function. Here, we demonstrate the recurrent use of evolutionary trace information to construct such 3D templates for enzymes, search for them in other structures, and distinguish true from spurious matches. Serine protease templates built from evolutionarily important residues distinguish between proteases and other proteins nearly as well as the classic Ser-His-Asp catalytic triad. In 53 enzymes spanning 33 distinct functions, an automated pipeline identifies functionally related proteins with an average positive predictive power of 62%, including correct matches to proteins with the same function but with low sequence identity (the average identity for some templates is only 17%). Although these template building, searching, and match classification strategies are not yet optimized, their sequential implementation demonstrates a functional annotation pipeline which does not require experimental information, but only local molecular mimicry among a small number of evolutionarily important residues.     

Influence of C Terminus on Monoamine Oxidase A and B Catalytic Activity

Abstract: Monoamine oxidase (MAO) A and B play important roles in the metabolism of neurotransmitters and dietary amines. The domains important for enzyme specificities were studied by construction of chimeric MAOA/B enzymes. Exchange of the N-terminal 45 amino acids of MAOA with the N-terminal 36 residues of MAOB (chimeric enzymes B₃₆A and A₄₅B) resulted in the same substrate and inhibitor sensitivities as the wild-type MAOA or B. Thus, the N terminus may not be responsible for MAOA or B enzyme specificities. When MAOB C-terminal residues 393–520 were replaced with MAOA C-terminal residues 402–527 (chimeric B₃₉₃A) catalytic activity was not detectable. Chimeric B₃₉₃A consists of eight residues with different charges, three less proline residues (458, 476, and 490), and one additional proline at 518 compared with wild-type MAOB. These differences may have induced conformational changes and affected MAOB catalytic activity. Thus, the C terminus of MAOB is critical for maintaining MAOB in an active form. It is interesting that when the C terminus of MAOA was switched with MAOB (chimeric A₄₀₂B), little effect was observed on MAOA catalytic activity. This new information is valuable for further studies of the structure and function relationship of this important enzyme.     

The geometry of interactions between catalytic residues and their substrates

The process of deducing the catalytic mechanism of an enzyme from its structure is highly complex and requires extensive experimental work to validate a proposed mechanism. As one step towards improving the reliability of this process, we have gathered statistics describing the typical geometry of catalytic residues with regard to the substrate and one another. In order to analyse residue-substrate interactions, we have assembled a dataset of structures of enzymes of known mechanism bound to substrate, product, or a substrate analogue. Despite the challenges presented in obtaining such experimental data, we were able to include 42 enzyme structures. We have also assembled a separate dataset of catalytic residues which act upon other catalytic residues, using a set of 60 enzyme structures. For both datasets, we have extracted the distances between residues with a given catalytic function and their target moieties. The geometry of residues whose function involves the transfer or sharing of hydrogens (either with substrate or another residue) was analysed more closely. The results showed that the geometry for such productive interactions (prior to the transition state) closely resembles that seen in non-catalytic hydrogen bonds, with distances and angles in the normal expected range. Such statistics provide limits on "expected geometries" for catalytic residues, which will help to identify these residues and elucidate enzyme mechanisms.     

Prediction of catalytic residues in enzymes based on known tertiary structure,stability profile,and sequence conservation

The catalytic or functionally important residues of a protein are known to exist in evolutionarily constrained regions. However, the patterns of residue conservation alone are sometimes not very informative, depending on the homologous sequences available for a given query protein. Here, we present an integrated method to locate the catalytic residues in an enzyme from its sequence and structure. Mutations of functional residues usually decrease the activity, but concurrently often increase stability. Also, catalytic residues tend to occupy partially buried sites in holes or clefts on the molecular surface. After confirming these general tendencies by carrying out statistical analyses on 49 representative enzymes, these data together with amino acid conservation were evaluated. This novel method exhibited better sensitivity in the prediction accuracy than traditional methods that consider only the residue conservation. We applied it to some so-called "hypothetical" proteins, with known structures but undefined functions. The relationships among the catalytic, conserved, and destabilizing residues in enzymatic proteins are discussed.     

亚洲玉米螟幼虫酚氧化酶原基因序列的生物信息学分析

酚氧化酶原PPO是昆虫免疫的关键酶, 本文从生物信息学角度对亚洲玉米螟Ostrinia furnacalis Guenée幼虫PPO进行分析, 为进一步研究其高级结构与功能的关系提供理论依据。利用我们已提交到GenBank的数据, 采用在线分析及MEGA4和RasMol软件对亚洲玉米螟酚氧化酶原（Of-PPO）的核苷酸和氨基酸序列、系统发生关系和蛋白质三级结构进行分析。结果表明: Of-PPO全长cDNA序列有2 686 bp, 包含一个2 079 bp的开放阅读框, 其推导的693个氨基酸序列中包含6个组氨酸残基构成的2个铜离子结合位点, 以及保守的硫羟酸酯区域。Of-PPO属于PPO2类群, 其N端不含信号肽, 无跨膜结构域区域, 无糖基化位点, 44个磷酸化位点均匀分布于整个多肽链中, 有2段序列可能形成卷曲螺旋, 有5个区域的氨基酸具较强疏水性, 其二级结构中α-螺旋占22.54%, 随机卷曲占56.79%。同源建模显示其三级结构为“α/β型”中的“滚筒结构”, 存在一个明显的空位, 可能与该酶催化活性有关。本文可为Of-PPO的实验研究和应用开发提供有价值的信息。     

Effect of probiotic-fermented milk administration on gastrointestinal survival of Lactobacillus casei ATCC 393 and modulation of intestinal microbial flora

The aim of the present study was to assess the survival of free and immobilized Lactobacillus casei ATCC 393 on apple pieces, contained in probiotic-fermented milk, after gastrointestinal (GI) transit and to investigate the potential regulation of intestinal microbial flora in a rat model. In in vitro GI stress tolerance tests, immobilized L. casei ATCC 393 exhibited significantly higher survival rates compared to free cells. At a second stage, probiotic-fermented milk produced by either free or immobilized cells was administered orally at a single dose or daily for 9 days in Wistar rats. By 12 h after single-dose administration, both free and immobilized cells were detected by microbiological and molecular analysis at levels ≥6 logCFU/g of feces. Moreover, daily administration led to significant reduction of staphylococci, enterobacteria, coliforms and streptococci counts. In conclusion, L. casei ATCC 393 contained in fermented milk survived GI transit and modulated intestinal microbiota.