Substrate specificity of plant UDP-dependent glycosyltransferases predicted from crystal structures and homology modeling

Plant family 1 UDP-dependent glycosyltransferases (UGTs) catalyze the glycosylation of a plethora of bioactive natural products. In Arabidopsis thaliana, 120 UGT encoding genes have been identified. The crystal-based 3D structures of four plant UGTs have recently been published. Despite low sequence conservation, the UGTs show a highly conserved secondary and tertiary structure. The sugar acceptor and sugar donor substrates of UGTs are accommodated in the cleft formed between the N- and C-terminal domains. Several regions of the primary sequence contribute to the formation of the substrate binding pocket including structurally conserved domains as well as loop regions differing both with respect to their amino acid sequence and sequence length. In this review we provide a detailed analysis of the available plant UGT crystal structures to reveal structural features determining substrate specificity. The high 3D structural conservation of the plant UGTs render homology modeling an attractive tool for structure elucidation. The accuracy and utility of UGT structures obtained by homology modeling are discussed and quantitative assessments of model quality are performed by modeling of a plant UGT for which the 3D crystal structure is known. We conclude that homology modeling offers a high degree of accuracy. Shortcomings in homology modeling are also apparent with modeling of loop regions remaining as a particularly difficult task.     

A novel protocol of energy optimisation for predicted protein structures built by homology modelling

Homology modelling was applied to predict the three-dimensional (3D) structures of six sets of lipase proteins. Sequence identities between the target and template were 34.6, 44.9, 57.4, 69.9, 79.0 and 86.2%, respectively. Then, eight different protocols including three optimising factors [periodically bounded cell (PBC) water, molecular dynamics (MD) simulation, ‘grade-unpacking’ strategy or ‘combinatorial’ strategy] were used to refine the initial model of each system. By comparing the energy-optimised models with the true 3D structure of the target protein in terms of all backbone atoms' root mean square deviation, we determined a novel but all-purpose protocol for model refinement. The protocol refined a homology model by adopting the ‘grade-unpacking’ strategy for energy minimisation while the model was solvated in PBC water. Furthermore, by comparing the influence of each single optimising factor on the accuracy of the refined structure, we found that introducing the MD simulation into the model refinement method would decrease the accuracy of the final protein structure while methods with either PBC water or the ‘grade-unpacking’ strategy would increase the accuracy of the final model.     

Topological testing of the mechanism of homology search promoted by RecA protein

To initiate homologous recombination, sequence similarity between two DNA molecules must be searched for and homology recognized. How the search for and recognition of homology occurs remains unproven. We have examined the influences of DNA topology and the polarity of RecA–single-stranded (ss)DNA filaments on the formation of synaptic complexes promoted by RecA. Using two complementary methods and various ssDNA and duplex DNA molecules as substrates, we demonstrate that topological constraints on a small circular RecA–ssDNA filament prevent it from interwinding with its duplex DNA target at the homologous region. We were unable to detect homologous pairing between a circular RecA–ssDNA filament and its relaxed or supercoiled circular duplex DNA targets. However, the formation of synaptic complexes between an invading linear RecA–ssDNA filament and covalently closed circular duplex DNAs is promoted by supercoiling of the duplex DNA. The results imply that a triplex structure formed by non-Watson–Crick hydrogen bonding is unlikely to be an intermediate in homology searching promoted by RecA. Rather, a model in which RecA-mediated homology searching requires unwinding of the duplex DNA coupled with local strand exchange is the likely mechanism. Furthermore, we show that polarity of the invading RecA–ssDNA does not affect its ability to pair and interwind with its circular target duplex DNA.     

ORFeus: Detection of distant homology using sequence profiles and predicted secondary structure

ORFeus is a fully automated, sensitive protein sequence similarity search server available to the academic community via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/). The goal of the development of ORFeus was to increase the sensitivity of the detection of distantly related protein families. Predicted secondary structure information was added to the information about sequence conservation and variability, a technique known from hybrid threading approaches. The accuracy of the meta profiles created this way is compared with profiles containing only sequence information and with the standard approach of aligning a single sequence with a profile. Additionally, the alignment of meta profiles is more sensitive in detecting remote homology between protein families than if aligning two sequence-only profiles or if aligning a profile with a sequence. The specificity of the alignment score is improved in the lower specificity range compared with the robust sequence-only profiles.     

Analysis of six protein structures predicted by comparative modeling techniques

The protein structures of six comparative modeling targets were predicted in a procedure that relied on improved energy minimization, without empirical rules, to position all new atoms. The structures of human nucleoside diphosphate kinase NM23-H2, HPr from Mycoplasma capricolum, 2Fe-2S ferredoxin from Haloarcula marismortui, eosinophil-derived neurotoxin (EDN), mouse cellular retinoic acid protein I (CRABP1), and P450eryf were predicted with root mean square deviations on Cα atoms of 0.69, 0.73, 1.11, 1.48, 1.69, and 1.73 Å, respectively, compared to the target crystal structures. These differences increased as the sequence similarity between the target and parent proteins decreased from about 60 to 20% identity. More residues were predicted than form the common region shared by the two crystal structures. In most cases insertions or deletions between the target and the related protein of known structure were not correctly positioned. One two residue insertion in CRABP1 was predicted in the correct conformation, while a nine residue insertion in EDN was predicted in the correct spatial region, although not in the correct conformation. The positions of common cofactors and their binding sites were predicted correctly, even when overall sequence similarity was low. © 1995 Wiley-Liss, Inc.     

Detection of unrelated proteins in sequences multiple alignments by using predicted secondary structures

MOTIVATION: Multiple sequence alignments are essential tools for establishing the homology relations between proteins. Essential amino acids for the function and/or the structure are generally conserved, thus providing key arguments to help in protein characterization. However for distant proteins, it is more difficult to establish, in a reliable way, the homology relations that may exist between them. In this article, we show that secondary structure prediction is a valuable way to validate protein families at low identity rate. RESULTS: We show that the analysis of the secondary structures compatibility is a reliable way to discard non-related proteins in low identity multiple alignment. AVAILABILITY: This validation is possible through our NPS@ server (http://npsa-pbil.ibcp.fr)     

The predicted secondary structures of class I fructose-bisphosphate aldolases.

The results of several secondary-structure prediction programs were combined to produce an estimate of the regions of alpha-helix, beta-sheet and reverse turns for fructose-bisphosphate aldolases from human and rat muscle and liver, from Trypanosoma brucei and from Drosophila melanogaster. All the aldolase sequences gave essentially the same pattern of secondary-structure predictions despite having sequences up to 50% different. One exception to this pattern was an additional strongly predicted helix in the rat liver and Drosophila enzymes. Regions of relatively high sequence variation generally were predicted as reverse turns, and probably occur as surface loops. Most of the positions corresponding to exon boundaries are located between regions predicted to have secondary-structural elements consistent with a compact structure. The predominantly alternating alpha/beta structure predicted is consistent with the alpha/beta-barrel structure indicated by preliminary high-resolution X-ray diffraction studies on rabbit muscle aldolase [Sygusch, Beaudry & Allaire (1986) Biophys. J. 49, 287a].     

Automated functional classification of experimental and predicted protein structures

Background  

Proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural similarity.     

Chemically accurate protein structures: Validation of protein NMR structures by comparison of measured and predicted pK a values

A new method is presented for evaluating the quality of protein structures obtained by NMR. This method exploits the dependence between measurable chemical properties of a protein, namely pK _a values of acidic residues, and protein structure. The accurate and fast empirical computational method employed by the PROPKA program () allows the user to test the ability of a given structure to reproduce known pK _a values, which in turn can be used as a criterion for the selection of more accurate structures. We demonstrate the feasibility of this novel idea for a series of proteins for which both␣NMR and X-ray structures, as well as pK _a values of all ionizable residues, have been determined. For the 17 NMR ensembles used in this study, this criterion is shown effective in the elimination of a large number of NMR structure ensemble members.     

PFRES: protein fold classification by using evolutionary information and predicted secondary structure

MOTIVATION: The number of protein families has been estimated to be as small as 1000. Recent study shows that the growth in discovery of novel structures that are deposited into PDB and the related rate of increase of SCOP categories are slowing down. This indicates that the protein structure space will be soon covered and thus we may be able to derive most of remaining structures by using the known folding patterns. Present tertiary structure prediction methods behave well when a homologous structure is predicted, but give poorer results when no homologous templates are available. At the same time, some proteins that share twilight-zone sequence identity can form similar folds. Therefore, determination of structural similarity without sequence similarity would be beneficial for prediction of tertiary structures. RESULTS: The proposed PFRES method for automated protein fold classification from low identity (<35%) sequences obtains 66.4% and 68.4% accuracy for two test sets, respectively. PFRES obtains 6.3-12.4% higher accuracy than the existing methods. The prediction accuracy of PFRES is shown to be statistically significantly better than the accuracy of competing methods. Our method adopts a carefully designed, ensemble-based classifier, and a novel, compact and custom-designed feature representation that includes nearly 90% less features than the representation of the most accurate competing method (36 versus 283). The proposed representation combines evolutionary information by using the PSI-BLAST profile-based composition vector and information extracted from the secondary structure predicted with PSI-PRED. AVAILABILITY: The method is freely available from the authors upon request.     

A comparison of optimal and suboptimal RNA secondary structures predicted by free energy minimization with structures determined by phylogenetic comparison.

This article describes the latest version of an RNA folding algorithm that predicts both optimal and suboptimal solutions based on free energy minimization. A number of RNA's with known structures deduced from comparative sequence analysis are folded to test program performance. The group of solutions obtained for each molecule is analysed to determine how many of the known helixes occur in the optimal solution and in the best suboptimal solution. In most cases, a structure about 80% correct is found with a free energy within 2% of the predicted lowest free energy structure.     

Primary and predicted secondary structures of the caseins in relation to their biological functions

In free solution, the caseins behave as non-compact and largely flexible molecules with a high proportion of residues accessible to solvent. Historically, they have been described as random coil-type proteins with only a nutritional function. Nevertheless, secondary structure prediction algorithms indicate that many parts of the (unphosphorylated, unglycosylated) polypeptide chains can form regular structures. In particular, a recurrent motif of the Ca2+-sensitive caseins in man, rat, mouse, guinea pig and ruminant species is an alpha-helix--loop--alpha-helix conformation in which the loop region typically contains a cluster of sites of phosphorylation. The biological function of the caseins is considered and it is suggested that the potential or actual conformations of the group of Ca2+-sensitive caseins are suited to the function of modulating the precipitation of calcium phosphate from solution. Either they can act as sites for nucleation or they can bind rapidly to calcium phosphate nuclei as they form spontaneously from supersaturated solution.     

Sensitive and label-free biosensing of RNA with predicted secondary structures by a triplex affinity capture method

A novel biosensing approach for the label-free detection of nucleic acid sequences of short and large lengths has been implemented, with special emphasis on targeting RNA sequences with secondary structures. The approach is based on selecting 8-aminoadenine-modified parallel-stranded DNA tail-clamps as affinity bioreceptors. These receptors have the ability of creating a stable triplex-stranded helix at neutral pH upon hybridization with the nucleic acid target. A surface plasmon resonance biosensor has been used for the detection. With this strategy, we have detected short DNA sequences (32-mer) and purified RNA (103-mer) at the femtomol level in a few minutes in an easy and level-free way. This approach is particularly suitable for the detection of RNA molecules with predicted secondary structures, reaching a limit of detection of 50 fmol without any label or amplification steps. Our methodology has shown a marked enhancement for the detection (18% for short DNA and 54% for RNA), when compared with the conventional duplex approach, highlighting the large difficulty of the duplex approach to detect nucleic acid sequences, especially those exhibiting stable secondary structures. We believe that our strategy could be of great interest to the RNA field.     

The primary and higher order structures of sea urchin ovoperoxidase as determined by cDNA cloning and predicted by homology modeling.

At fertilization, sea urchin ovoperoxidase (OPO) is incorporated into a nascent fertilization envelope in association with proteoliaisin and plays an essential role in its hardening. By cDNA cloning based on the previously reported partial amino acid sequences of Hemicentrotus pulcherrimus OPO, the cDNA and deduced amino acid sequences of the enzyme precursor were determined. Its 814-residue sequence consists of 125-residue signal- plus pro-peptides and 689-residue mature enzyme and has 92.2 and 81.4% identity with the OPOs of Strongylocentrotus purpuratus and Lytechinus variegatus, respectively. Compared with human myeloperoxidase, it has 30.3% identity and 9.6% similarity and has an additional C-terminal sequence of about 100 residues, suggesting its possible role as the site for interaction with proteoliaisin, if not for the entire sequence. The linker peptide sequence between L- and H-chains (e.g., ASFVTG and FSFFTG) cleaved off upon activation in mammalian promyeloperoxidases is intrinsically lacking in OPO, uniquely rendering the single 70K polypeptide a basic unit. The positions of distal and proximal histidines, distal arginine, and six disulfide bridges are highly conserved among mammalian and sea urchin peroxidases. The secondary structure was predicted by EMBL-PHD on the Internet for the whole sequence of mature OPO, and both secondary and tertiary structures were predicted by Swiss-Model for the partial sequences residues 18-65 and 123-570 with canine myeloperoxidase as a template. The overall architecture of the OPO molecule is close to that of human myeloperoxidase but its secondary structure has some differences based on the sequence variation, as depicted by RasMol. Another software, Swiss-PdbViewer, produced a slightly but significantly different image of the OPO structure for the same predicted atomic coordinates. A discrepancy was also found between the secondary structures of human myeloperoxidase in the PDB file and in its Swiss-PdbViewer presentation.     

The hydration of protein secondary structures

The hydration of the main-chain carbonyl (CO) groups in proteins have been studied using infra-red spectroscopy, and computer-graphics analysis of high resolution protein crystal structures. The IR measurements indicate that the strength of water binding to the CO groups is lower in beta-sheet proteins compared with alpha-helical ones. Analysis of the protein crystal structures shows that this is due primarily to differences in the geometry of water-CO group interactions in the two types of secondary structure.     

Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologies

Database-searching programs generally identify only a fraction of the spectra acquired in a standard LC/MS/MS study of digested proteins. Subtle variations in database-searching algorithms for assigning peptides to MS/MS spectra have been known to provide different identification results. To leverage this variation, a probabilistic framework is developed for combining the results of multiple search engines. The scores for each search engine are first independently converted into peptide probabilities. These probabilities can then be readily combined across search engines using Bayesian rules and the expectation maximization learning algorithm. A significant gain in the number of peptides identified with high confidence with each additional search engine is demonstrated using several data sets of increasing complexity, from a control protein mixture to a human plasma sample, searched using SEQUEST, Mascot, and X! Tandem database-searching programs. The increased rate of peptide assignments also translates into a substantially larger number of protein identifications in LC/MS/MS studies compared to a typical analysis using a single database-search tool.     

SPEM: improving multiple sequence alignment with sequence profiles and predicted secondary structures

MOTIVATION: Multiple sequence alignment is an essential part of bioinformatics tools for a genome-scale study of genes and their evolution relations. However, making an accurate alignment between remote homologs is challenging. Here, we develop a method, called SPEM, that aligns multiple sequences using pre-processed sequence profiles and predicted secondary structures for pairwise alignment, consistency-based scoring for refinement of the pairwise alignment and a progressive algorithm for final multiple alignment. RESULTS: The alignment accuracy of SPEM is compared with those of established methods such as ClustalW, T-Coffee, MUSCLE, ProbCons and PRALINE(PSI) in easy (homologs) and hard (remote homologs) benchmarks. Results indicate that the average sum of pairwise alignment scores given by SPEM are 7-15% higher than those of the methods compared in aligning remote homologs (sequence identity <30%). Its accuracy for aligning homologs (sequence identity >30%) is statistically indistinguishable from those of the state-of-the-art techniques such as ProbCons or MUSCLE 6.0. AVAILABILITY: The SPEM server and its executables are available on http://theory.med.buffalo.edu.