Improved membrane protein topology prediction by domain assignments

Topology predictions for integral membrane proteins can be substantially improved if parts of the protein can be constrained to a given in/out location relative to the membrane using experimental data or other information. Here, we have identified a set of 367 domains in the SMART database that, when found in soluble proteins, have compartment-specific localization of a kind relevant for membrane protein topology prediction. Using these domains as prediction constraints, we are able to provide high-quality topology models for 11% of the membrane proteins extracted from 38 eukaryotic genomes. Two-thirds of these proteins are single spanning, a group of proteins for which current topology prediction methods perform particularly poorly.     

Prediction of distant residue contacts with the use of evolutionary information

In this work we present a novel correlated mutations analysis (CMA) method that is significantly more accurate than previously reported CMA methods. Calculation of correlation coefficients is based on physicochemical properties of residues (predictors) and not on substitution matrices. This results in reliable prediction of pairs of residues that are distant in protein sequence but proximal in its three dimensional tertiary structure. Multiple sequence alignments (MSA) containing a sequence of known structure for 127 families from PFAM database have been selected so that all major protein architectures described in CATH classification database are represented. Protein sequences in the selected families were filtered so that only those evolutionarily close to the target protein remain in the MSA. The average accuracy obtained for the alpha beta class of proteins was 26.8% of predicted proximal pairs with average improvement over random accuracy (IOR) of 6.41. Average accuracy is 20.6% for the mainly beta class and 14.4% for the mainly alpha class. The optimum correlation coefficient cutoff (cc cutoff) was found to be around 0.65. The first predictor, which correlates to hydrophobicity, provides the most reliable results. The other two predictors give good predictions which can be used in conjunction to those of the first one. When stricter cc cutoff is chosen, the average accuracy increases significantly (38.76% for alpha beta class), but the trade off is a smaller number of predictions. The use of solvent accessible area estimations for filtering false positives out of the predictions is promising.     

Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure

The present study is an attempt to develop a neural network-based method for predicting the real value of solvent accessibility from the sequence using evolutionary information in the form of multiple sequence alignment. In this method, two feed-forward networks with a single hidden layer have been trained with standard back-propagation as a learning algorithm. The Pearson's correlation coefficient increases from 0.53 to 0.63, and mean absolute error decreases from 18.2 to 16% when multiple-sequence alignment obtained from PSI-BLAST is used as input instead of a single sequence. The performance of the method further improves from a correlation coefficient of 0.63 to 0.67 when secondary structure information predicted by PSIPRED is incorporated in the prediction. The final network yields a mean absolute error value of 15.2% between the experimental and predicted values, when tested on two different nonhomologous and nonredundant datasets of varying sizes. The method consists of two steps: (1) in the first step, a sequence-to-structure network is trained with the multiple alignment profiles in the form of PSI-BLAST-generated position-specific scoring matrices, and (2) in the second step, the output obtained from the first network and PSIPRED-predicted secondary structure information is used as an input to the second structure-to-structure network. Based on the present study, a server SARpred (http://www.imtech.res.in/raghava/sarpred/) has been developed that predicts the real value of solvent accessibility of residues for a given protein sequence. We have also evaluated the performance of SARpred on 47 proteins used in CASP6 and achieved a correlation coefficient of 0.68 and a MAE of 15.9% between predicted and observed values.     

Birds of prey as limiting factors of gamebird populations in Europe: a review

Whether predators can limit their prey has been a topic of scientific debate for decades. Traditionally it was believed that predators take only wounded, sick, old or otherwise low-quality individuals, and thus have little impact on prey populations. However, there is increasing evidence that, at least under certain circumstances, vertebrate predators may indeed limit prey numbers. This potential role of predators as limiting factors of prey populations has created conflicts between predators and human hunters, because the hunters may see predators as competitors for the same resources. A particularly acute conflict has emerged over the past few decades between gamebird hunters and birds of prey in Europe. As a part of a European-wide research project, we reviewed literature on the relationships between birds of prey and gamebirds. We start by analysing available data on the diets of 52 European raptor and owl species. There are some 32 species, mostly specialist predators feeding on small mammals, small passerine birds or insects, which never or very rarely include game animals (e.g. hares, rabbits, gamebirds) in their diet. A second group (20 species) consists of medium-sized and large raptors which prey on game, but for which the proportion in the diet varies temporally and spatially. Only three raptor species can have rather large proportions of gamebirds in their diet, and another seven species may utilise gamebirds locally to a great extent. We point out that the percentage of a given prey species in the diet of an avian predator does not necessarily reflect the impact of that predator on densities of prey populations. Next, we summarise available data on the numerical responses of avian predators to changing gamebird numbers. In half of these studies, no numerical response was found, while in the remainder a response was detected such that either raptor density or breeding success increased with density of gamebirds. Data on the functional responses of raptors were scarce. Most studies of the interaction between raptors and gamebird populations give some estimate of the predation rate (per cent of prey population taken by predator), but less often do they evaluate the subsequent reduction in the pre-harvest population or the potential limiting effect on breeding numbers. The few existing studies indicate that, under certain conditions, raptor predation may limit gamebird populations and reduce gamebird harvests. However, the number and extent of such studies are too modest to draw firm conclusions. Furthermore, their geographical bias to northern Europe, where predator-prey communities are typically simpler than in the south, precludes extrapolation to more diverse southern European ecosystems. There is an urgent need to develop further studies, particularly in southern Europe, to determine the functional and numerical responses of raptors to gamebird populations in species and environments other than those already evaluated in existing studies. Furthermore, additional field experiments are needed in which raptor and possibly also mammalian predator numbers are manipulated on a sufficiently large spatial and temporal scale. Other aspects that have been little studied are the role of predation by the non-breeding part of the raptor population, or floaters, on the breeding success and survival of gamebirds, as well as the effect of intra-guild predation. Finally there is a need for further research on practical methods to reduce raptor predation on gamebirds and thus reduce conflict between raptor conservation and gamebird management.     

Quantitative analysis of film coating in a pan coater based on in-line sensor measurements

A method was developed that enables in-line analysis of film coating thickness on tablets during a pan coating operation. Real-time measurements were made using a diffusereflectance near-infrared (NIR) probe positioned inside the pan during the coating operation. Real-time spectra of replicate batches were used for modeling film growth. Univariate analysis provided a simple method for in-line monitoring of the coating process using NIR data. An empirical geometric 2-vector volumetric growth model was developed, which accounts for differential growth on the face and band regions of biconvex tablets. The thickness of the film coat was determined by monitoring the decrease of absorption bands characteristic of a component of the tablet core and monitoring the increase of bands characteristic of a component in the coating material. There was good correlation between values estimated from the NIR data and the measured tablet volumetric growth. In-line measurements allow the coating process to be stopped when a predetermined tablet coating thickness is achieved. Published: September 20, 2005     

Prediction of coordination number and relative solvent accessibility in proteins

Knowing the coordination number and relative solvent accessibility of all the residues in a protein is crucial for deriving constraints useful in modeling protein folding and protein structure and in scoring remote homology searches. We develop ensembles of bidirectional recurrent neural network architectures to improve the state of the art in both contact and accessibility prediction, leveraging a large corpus of curated data together with evolutionary information. The ensembles are used to discriminate between two different states of residue contacts or relative solvent accessibility, higher or lower than a threshold determined by the average value of the residue distribution or the accessibility cutoff. For coordination numbers, the ensemble achieves performances ranging within 70.6-73.9% depending on the radius adopted to discriminate contacts (6A-12A). These performances represent gains of 16-20% over the baseline statistical predictor, always assigning an amino acid to the largest class, and are 4-7% better than any previous method. A combination of different radius predictors further improves performance. For accessibility thresholds in the relevant 15-30% range, the ensemble consistently achieves a performance above 77%, which is 10-16% above the baseline prediction and better than other existing predictors, by up to several percentage points. For both problems, we quantify the improvement due to evolutionary information in the form of PSI-BLAST-generated profiles over BLAST profiles. The prediction programs are implemented in the form of two web servers, CONpro and ACCpro, available at http://promoter.ics.uci.edu/BRNN-PRED/.     

N-terminal N-myristoylation of proteins: refinement of the sequence motif and its taxon-specific differences

N-terminal N-myristoylation is a lipid anchor modification of eukaryotic and viral proteins targeting them to membrane locations, thus changing the cellular function of modified proteins. Protein myristoylation is critical in many pathways; e.g. in signal transduction, apoptosis, or alternative extracellular protein export. The myristoyl-CoA:protein N-myristoyltransferase (NMT) recognizes the sequence motif of appropriate substrate proteins at the N terminus and attaches the lipid moiety to the absolutely required N-terminal glycine residue. Reliable recognition of capacity for N-terminal myristoylation from the substrate protein sequence alone is desirable for proteome-wide function annotation projects but the existing PROSITE motif is not practical, since it produces huge numbers of false positive and even some false negative predictions.As a first step towards a new prediction method, it is necessary to refine the sequence motif coding for N-terminal N-myristoylation. Relying on the in-depth study of the amino acid sequence variability of substrate proteins, on binding site analyses in X-ray structures or 3D homology models for NMTs from various taxa, and on consideration of biochemical data extracted from the scientific literature, we found indications that, at least within a complete substrate protein, the N-terminal 17 protein residues experience different types of variability restrictions. We identified three motif regions: region 1 (positions 1-6) fitting the binding pocket; region 2 (positions 7-10) interacting with the NMT's surface at the mouth of the catalytic cavity; and region 3 (positions 11-17) comprising a hydrophilic linker. Each region was characterized by physical requirements to single sequence positions or groups of positions regarding volume, polarity, backbone flexibility and other typical properties of amino acids (http://mendel.imp.univie.ac.at/myristate/). These specificity differences are confined partly to taxonomic ranges and are proposed for the design of NMT inhibitors in pathogenic fungal and protozoan systems including Aspergillus fumigatus, Leishmania major, Trypanosoma cruzi, Trypanosoma brucei, Giardia intestinalis, Entamoeba histolytica, Pneumocystis carinii, Strongyloides stercoralis and Schistosoma mansoni. An exhaustive search for NMT-homologues led to the discovery of two putative entomopoxviral NMTs.     

SnapDRAGON: a method to delineate protein structural domains from sequence data

We describe a method to identify protein domain boundaries from sequence information alone based on the assumption that hydrophobic residues cluster together in space. SnapDRAGON is a suite of programs developed to predict domain boundaries based on the consistency observed in a set of alternative ab initio three-dimensional (3D) models generated for a given protein multiple sequence alignment. This is achieved by running a distance geometry-based folding technique in conjunction with a 3D-domain assignment algorithm. The overall accuracy of our method in predicting the number of domains for a non-redundant data set of 414 multiple alignments, representing 185 single and 231 multiple-domain proteins, is 72.4 %. Using domain linker regions observed in the tertiary structures associated with each query alignment as the standard of truth, inter-domain boundary positions are delineated with an accuracy of 63.9 % for proteins comprising continuous domains only, and 35.4 % for proteins with discontinuous domains. Overall, domain boundaries are delineated with an accuracy of 51.8 %. The prediction accuracy values are independent of the pair-wise sequence similarities within each of the alignments. These results demonstrate the capability of our method to delineate domains in protein sequences associated with a wide variety of structural domain organisation.