Improving protein structural class prediction using novel combined sequence information and predicted secondary structural features

Protein structural class prediction solely from protein sequences is a challenging problem in bioinformatics. Numerous efficient methods have been proposed for protein structural class prediction, but challenges remain. Using novel combined sequence information coupled with predicted secondary structural features (PSSF), we proposed a novel scheme to improve prediction of protein structural classes. Given an amino acid sequence, we first transformed it into a reduced amino acid sequence and calculated its word frequencies and word position features to combine novel sequence information. Then we added the PSSF to the combine sequence information to predict protein structural classes. The proposed method was tested on four benchmark datasets in low homology and achieved the overall prediction accuracies of 83.1%, 87.0%, 94.5%, and 85.2%, respectively. The comparison with existing methods demonstrates that the overall improvements range from 2.3% to 27.5%, which indicates that the proposed method is more efficient, especially for low-homology amino acid sequences.     

Predicting lysine‐malonylation sites of proteins using sequence and predicted structural features

Malonylation is a recently discovered post‐translational modification (PTM) in which a malonyl group attaches to a lysine (K) amino acid residue of a protein. In this work, a novel machine learning model, SPRINT‐Mal, is developed to predict malonylation sites by employing sequence and predicted structural features. Evolutionary information and physicochemical properties are found to be the two most discriminative features whereas a structural feature called half‐sphere exposure provides additional improvement to the prediction performance. SPRINT‐Mal trained on mouse data yields robust performance for 10‐fold cross validation and independent test set with Area Under the Curve (AUC) values of 0.74 and 0.76 and Matthews’ Correlation Coefficient (MCC) of 0.213 and 0.20, respectively. Moreover, SPRINT‐Mal achieved comparable performance when testing on H. sapiens proteins without species‐specific training but not in bacterium S. erythraea. This suggests similar underlying physicochemical mechanisms between mouse and human but not between mouse and bacterium. SPRINT‐Mal is freely available as an online server at: http://sparks-lab.org/server/SPRINT-Mal/ . © 2018 Wiley Periodicals, Inc.     

Structural analysis of missense mutations causing isolated sulfite oxidase deficiency

The physiologically essential oxidation of sulfite to sulfate is catalyzed by the molybdoheme enzyme, sulfite oxidase. Deficiencies of this enzyme in human patients lead to severe neurological symptoms, which usually result in death in early childhood. Up to date eleven missense mutations in the gene encoding sulfite oxidase have been identified from sulfite oxidase deficient patients. The structural characterization of these mutants is now possible after the chicken sulfite oxidase gene has been synthesized chemically and due to the high homology to the human enzyme it provides a good model of human sulfite oxidase. This review focuses on the possible effects of the sulfite oxidase deficiency causing mutations based on our new structures of recombinant chicken sulfite oxidase.     

Virtual screening for R-groups, including predicted pIC50 contributions, within large structural databases, using Topomer CoMFA

Multiple R-groups (monovalent fragments) are implicitly accessible within most of the molecular structures that populate large structural databases. R-group searching would desirably consider pIC50 contribution forecasts as well as ligand similarities or docking scores. However, R-group searching, with or without pIC50 forecasts, is currently not practical. The most prevalent and reliable source of pIC50 predictions, existing 3D-QSAR approaches, is also difficult and somewhat subjective. Yet in 25 of 25 trials on data sets on which a field-based 3D-QSAR treatment had already succeeded, substitution of objective (canonically generated) topomer poses for the original structure-guided manual alignments produced acceptable 3D-QSAR models, on average having almost equivalent statistical quality to the published models, and with negligible effort. Their overall pIC50 prediction error is 0.805, calculated as the average over these 25 topomer CoMFA models in the standard deviations of pIC50 predictions, derived from the 1109 possible "leave-out-one-R-group" (LOORG) pIC50 contributions. (This novel LOORG protocol provides a more realistic and stringent test of prediction accuracy than the customary "leave-out-one-compound" LOO approach.) The associated average predictive r(2) of 0.495 indicates a pIC50 prediction accuracy roughly halfway between perfect and useless. To assess the ability of topomer-CoMFA based virtual screening to identify "highly active" R-groups, a Receiver Operating Curve (ROC) approach was adopted. Using, as the binary criterion for a "highly active" R-group, a predicted pIC50 greater than the top 25% of the observed pIC50 range, the ROC area averaged across the 25 topomer CoMFA models is 0.729. Conventionally interpreted, the odds that a "highly active" R-group will indeed confer such a high pIC50 are 0.729/(1-0.729) or almost 3 to 1. To confirm that virtual screening within large collections of realized structures would provide a useful quantity and variety of R-group suggestions, combining shape similarity with the "highly active" pIC50, the 50 searches provided by these 25 models were applied to 2.2 million structurally distinct R-group candidates among 2.0 million structures within a ZINC database, identifying an average of 5705 R-groups per search, with the highest predicted pIC50 combination averaging 1.6 log units greater than the highest reported pIC50s.     

Isolation and structural characterization of capistruin, a lasso peptide predicted from the genome sequence of Burkholderia thailandensis E264

Lasso peptides are a structurally unique class of bioactive peptides characterized by a knotted arrangement, where the C-terminus threads through an N-terminal macrolactam ring. Although ribosomally synthesized, only the gene cluster for the best studied lasso peptide MccJ25 from Escherichia coli consisting of the precursor protein McjA and the processing and immunity proteins McjB, McjC, and McjD is known. Through genome mining studies, we have identified homologues of all four proteins in Burkholderia thailandensis E264 and predicted this strain to produce a lasso peptide. Here we report the successful isolation of the predicted peptide, named capistruin. Upon optimization of the fermentation conditions, mass spectrometric and NMR structural studies proved capistruin to adopt a novel lasso fold. Heterologous production of the lasso peptide in Escherichia coli showed that the identified genes are sufficient for the biosynthesis of capistruin, which exhibits antimicrobial activity against closely related Burkholderia and Pseudomonas strains. In general, our rational approach should be widely applicable for the isolation of new lasso peptides to explore their high structural stability and diverse biological activity.     

Solid phase extraction conditions for the selective isolation of drugs from biological fluids predicted using liquid chromatography

Summary A new method to predict the most suitable conditions for the solid phase extraction of 1,4-benzodiazepines and related compounds using C18 Sep-Pak carridges is proposed. The composition of the washing and elution solvents for the solid phase extraction of a test compound can be obtained from its capacity factor on a C18 HPLC column and an equation which relates capacity factors and solid phase extraction data of other similar compounds. The solid phase extraction data given in this paper can be used by others, there by saving considerable time and effort in the development of sample preparation methods. The suitability of the method was checked with two test compounds, showing good results.     

Synthesis and structural characterisation using Rietveld and pair distribution function analysis of layered mixed titanium-zirconium phosphates

Crystalline metal (IV) phosphates with variable zirconium-to-titanium molar ratios of general formula (Ti_1−xZr_x)(HPO₄)₂·H₂O have been prepared by precipitation of soluble salts of the metals with phosphoric acid and heating the amorphous solids in 12 M H₃PO₄ in an autoclave. The new materials are structurally characterised by Rietveld analysis of synchrotron X-ray powder diffraction data and pair distribution function (PDF) analysis of high energy synchrotron X-ray total scattering data. A broad range of zirconium-titanium phosphate solid solutions were formed showing isomorphous substitution of titanium by zirconium in the α-titanium phosphate lattice and vice versa for titanium substitution into the α-zirconium phosphate lattice. In both cases the solubility is partial with the coexistence of two substituted phases observed in samples with nominal compositions between the solubility limits.     

Assessment of cellulose structural variety from different origins using near infrared spectroscopy

Near infrared (NIR) spectroscopy was tested as a rapid monitor of cellulose features by analyzing structurally distinguishable cellulose from different organisms ranging from Monera to Plantae as well as Animalia. The optimal spectral region was first identified using intra-crystalline deuteration, and then statistically analyzed based on second derivative spectra by principal component analysis. The score plots clearly distributed the samples according to crystalline structure such as relative crystallinity and allomorphism. These characteristics and the corresponding loading factors provided key NIR absorption criteria for identifying structural properties, especially in bands at 6527 and 6383 cm^?1, which correspond to I_α and I_β, respectively. In addition, calibration models were created for relative cellulose crystallinity using partial least square regression and for allomorph ratios using simple absorption band shifts at 6476–6446 cm^?1. NIR spectra of cellulose from various organisms combined with multivariate analysis can be used as a database for simple and rapid assessment of unknown cellulose materials.     

A new economical design of acceptance sampling models using Bayesian inference

In this paper, a new acceptance sampling model is proposed to decide about the received lot based on cost objective function. Bayesian inference is used to update the probability distribution function of the proportion of defectives. Moreover, to determine the optimal decision, the Bayesian inference along with backward induction is utilized to evaluate the expected cost of different decisions. A numerical example is solved, and sensitivity analysis is carried out on the parameters of the proposed methodology in order to analyse the optimal solution in different conditions.     

Enthalpies of mixing predicted using molecular dynamics simulations and OPLS force field

Enthalpy of mixing (EOM) is one of the most basic thermodynamic properties of mixtures. To assess feasibility of predicting EOM using force field simulation methods, fifteen (15) representative binary mixtures were investigated using MD simulations based on OPLS and TIP4P force fields. The simulation conditions and errors were carefully examined. The precision level of 0.04 kJ/mol was obtained for calculated EOM data. However, the predictions, measured by deviations from experimental data, were only qualitatively correct. Among various factors influencing the accuracy of predictions, force field quality representing interactions among different molecules plays the most significant role. Using methanol/benzene and ethanol/benzene as examples, we demonstrated that non-additive interaction terms between polarizable atoms can be used to significantly improve the quality of predictions. In addition, it appears that charge-dependent LJ parameters are required in order to represent the polarization effects accurately.     

De novo glycan structural identification from mass spectra using tree merging strategy

MotivationGlycans are large molecules with specific tree structures. Glycans play important roles in a great variety of biological processes. These roles are primarily determined by the fine details of their structures, making glycan structural identification highly desirable. Mass spectrometry (MS) has become the major technology for elucidation of glycan structures. Most de novo approaches to glycan structural identification from mass spectra fall into three categories: enumerating followed by filtering approaches, heuristic and dynamic programming-based approaches. The former suffers from its low efficiency while the latter two suffer from the possibility of missing the actual glycan structures. Thus, how to reliably and efficiently identify glycan structures from mass spectra still remains challenging.ResultsIn this study we propose an efficient and reliable approach to glycan structure identification using tree merging strategy. Briefly, for each MS peak, our approach first calculated monosaccharide composition of its corresponding fragment ion, and then built a constraint that forces these monosaccharides to be directly connected in the underlying glycan tree structure. According to these connecting constraints, we next merged constituting monosaccharides of the glycan into a complete structure step by step. During this process, the intermediate structures were represented as subtrees, which were merged iteratively until a complete tree structure was generated. Finally the generated complete structures were ranked according to their compatibility to the input mass spectra. Unlike the traditional enumerating followed by filtering strategy, our approach performed deisomorphism to remove isomorphic subtrees, and ruled out invalid structures that violates the connection constraints at each tree merging step, thus significantly increasing efficiency. In addition, all complete structures satisfying the connection constraints were enumerated without any missing structure. Over a test set of 10 N-glycan standards, our approach accomplished structural identification in minutes and gave the manually-validated structure first three highest score. We further successfully applied our approach to profiling and subsequent structure assignment of glycans released from glycoprotein mAb, which was in perfect agreement with previous studies and CE analysis.     

A model of the oxygen-evolving center of photosystem II predicted by structural refinement based on EXAFS simulations

A refined computational structural model of the oxygen-evolving complex (OEC) of photosystem II (PSII) is introduced. The model shows that the cuboidal core Mn3CaO4 with a "dangler" Mn ligated to a corner mu4-oxide ion is maximally consistent with the positioning of the amino acids around the metal cluster as characterized by XRD models and high-resolution spectroscopic data, including polarized EXAFS of oriented single crystals and isotropic EXAFS. It is, therefore, natural to expect that the proposed structural model should be particularly useful to establish the structure of the OEC, consistently with high-resolution spectroscopic data, and for elucidating the mechanism of water-splitting in PSII as described by the intermediate oxidation states of the EC along the catalytic cycle.     

Detection of point mutations using pyrene-labeled DNA probes

Pyrene-labeled oligodeoxyribonucleotide probes were shown to be suitable for the detection of point mutations. Reagents based on homochiral 2,4-dihydroxybutyramides were used to introduce pyrene residues at the 3"- and 5"- ends of oligonucleotide pairs. The oligonucleotide pair forms a tandem complex with a complementary target, giving rise to an excimer signal (_max 470—490 nm) in the fluorescence spectra when the pyrene residues come into close proximity. The maximum ratio of the intensity of the excimer signal to the monomer signal (_max 380—400 nm) is attained when (S)-N-(1-pyrenylmethyl)-3,3-dimethyl-2,4-dihydroxybutyramide is used to introduce the pyrene residue. The excimer fluorescence completely disappears with an increase in the distance between the pyrene residues (upon the introduction of an additional nucleotide in the target) or in the presence of a mismatch near the contact site of the probes.     

Solubilization of itraconazole as a function of cyclodextrin structural space

Cyclodextrins are functional pharmaceutical excipients, which can dynamically include poorly water-soluble drugs and drug candidates resulting in improved solubility, stability and oral bioavailability. A number of formulations containing “natural” and chemically modified cyclodextrins have reached the market and are enjoying widespread attention and use. One such example is itraconazole, a broad-spectrum antifungal agent which is available in an aqueous hydroxypropyl-β-cyclodextrin (HPβCD) vehicle for both oral and parenteral use (Sporanox Oral Solution and Sporanox Intravenous Injection^®). While the interaction of itraconazole and HPβCD is well described, its ability to form complexes with other cyclodextrins is less understood. This creates an intriguing opportunity of screening the structural space of available cyclodextrin derivates by assessing their complexation with a single chemical probe, in this case itraconazole. To this end, a number of cyclodextrin derivatives were assess with regard to their ability to improve the water solubility of the test substrate. In some instances, more detail assessments including the effect of pH and the physical form of the drug probe were also completed. The various cyclodextrins solubilized itraconazole to varying extents (micrograms to milligrams) and by varying inclusion mechanisms and stoichiometries.     

Methionine radical cation: structural studies as a function of pH using X- and Q-band time-resolved electron paramagnetic resonance spectroscopy

A comprehensive high resolution electron paramagnetic resonance (EPR) characterization of the l-methionine radical cation and its N-acetyl derivative in liquid solution at room temperature is presented. The cations were generated photochemically in high yield by excimer laser excitation of a water soluble dye, anthraquinone sulfonate sodium salt, the excited triplet state of which is quenched by electron transfer from the side chain sulfur atom of methionine or N-acetylmethionine. The radicals were detected by continuous wave (CW) time-resolved electron paramagnetic resonance (TREPR) spectroscopy at X-band (9.5 GHz) and Q-band (35 GHz) microwave frequencies. At pH values well below the pK(a) of the protonated amine nitrogen, the cation forms a dimer with another ground-state methionine molecule through a S-S three-electron bond. In basic solution, the lone pair on the nitrogen of the amino acid is available to make an intramolecular S-N three-electron bond with the side chain sulfur atom, leading to a five-membered ring structure for the cation. When the amino acid nitrogen is unsubstituted (methionine itself), rapid deprotonation to an aminyl radical takes place at high pH values. If the nitrogen is substituted (N-acetylmethionine), the cyclic structure is observed within its electron spin relaxation time at about 1 micros. Spectral simulation provides chemical shifts (g-factors) and hyperfine coupling constants for all structures, and isotopic labeling experiments strongly support the assignments.     

Molecular weight parity predicted from the parity values of mass spectral peaks

The fact that an unknown mass spectrum originates from a compound of even (or odd) numbered molecular weight can be predicted for 43% (13%) of unknowns with 95% (80%) reliability.     

SCOUT: A new algorithm for the inference of pseudo-time trajectory using single-cell data

Single cell technology is a powerful tool to reveal intercellular heterogeneity and discover cellular developmental processes. When analyzing the complexity of cellular dynamics and variability, it is important to construct a pseudo-time trajectory using single-cell expression data to reflect the process of cellular development. Although a number of computational and statistical methods have been developed recently for single-cell analysis, more effective and efficient methods are still strongly needed. In this work we propose a new method named SCOUT for the inference of single-cell pseudo-time ordering with bifurcation trajectories. We first propose to use the fixed-radius near neighbors algorithms based on cell densities to find landmarks to represent the cell states, and employ the minimum spanning tree (MST) to determine the developmental branches. We then propose to use the projection of Apollonian circle or a weighted distance to determine the pseudo-time trajectories of single cells. The proposed algorithm is applied to one synthetic and two realistic single-cell datasets (including single-branching and multi-branching trajectories) and the cellular developmental dynamics is recovered successfully. Compared with other popular methods, numerical results show that our proposed method is able to generate more robust and accurate pseudo-time trajectories. The code of the method is implemented in Python and available at https://github.com/statway/SCOUT.     

Detection of single-base mutations using 1-D microfluidic beads array

The application of a 1-D microfluidic beads array that is composed of individually addressable functionalized SiO2 beads has been demonstrated for detection of single-base mutations based on "sandwich" hybridization assay without additional sample labeling and PCR amplification. We concentrated on detection of mutations in the human p53 tumor suppressor gene with more than 50% mutation frequency in the known human cancers. Using a microinjection system, functionalized beads could be selectively and linearly arrayed in a single microfluidic channel comprising many periodic chambers. This 1-D microfluidic beads array was sufficiently sensitive to identify single-nucleotide mutations in 40 pM quantities of DNA targets and could discriminate the mutated alleles in an excess of nonmutated alleles at a level of one mutant in 100 wild-type sequences. The surface of beads was regenerated and rehybridized up to six times without obvious loss of signal. The entire reaction process was done at room temperature within minutes, and only 2-10 microL sample solution was needed to complete the whole detection process. The p53 genotypes of A549, CNE2, and SKBr-3 cell lines were also correctly evaluated by using mRNA extracts as target without need for sample labeling and amplification. Thus, this platform enabled rapid and exact discrimination of gene mutations with the advantages of reusability, simple handling of liquid, low cost, and little reagent consumption.     

Prediction of stability changes upon single-site mutations using database-derived potentials

One of the purposes of studying protein stability changes upon mutations is to get information about the dominating interactions that drive folding and stabilise the native structure. With this in mind, we present a method that predicts folding free-energy variations caused by point mutations using combinations of two types of database-derived potentials, i.e. backbone torsion-angle potentials and distance potentials, describing local and non-local interactions along the chain, respectively. The method is applied to evaluate the folding free-energy changes of 344 single-site mutations introduced in six different proteins and a synthetic peptide. We found that the relative importance of local versus non-local interactions along the chain is essentially a function of the solvent accessibility of the mutated residues. For the subset of totally buried residues, the optimal potential is the sum of a distance potential and a torsion potential weighted by a factor of 0.4. This combination yields a correlation coefficient between measured and computed changes in folding free energy of 0.80. For mutations of partially buried residues, the best potential is the sum of a torsion potential and a distance potential weighted by 0.7. For fully accessible residues, the torsion potentials taken alone perform best, reaching correlation coefficients of 0.87 on all but 10 mutations; the excluded mutations seem to modify the backbone structure or to involve interactions that are atypical for the surface. These results show that the relative weight of non-local interactions along the sequence decreases as the solvent accessibility of the mutated residue increases, and vanishes at the protein surface. On the contrary, the weight of local interactions increases with solvent accessibility. The latter interactions are nevertheless never negligible, even for the most buried residues. Received: 20 May 1998 / Accepted: 3 September 1998 / Published online: 7 December 1998     

Detection of CFTR mutations using temporal temperature gradient gel electrophoresis

Cystic fibrosis (CF), caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, is one of the most common autosomal recessive diseases with variable incidences and mutation spectra among different ethnic groups. Current commercially available mutation panels designed for the analysis of known recurrent mutations have a detection rate between 38 to 95%, depending upon the ethnic background of the patient. We describe the application of a novel mutation detection method, temporal temperature gradient gel electrophoresis (TTGE), to the study of the molecular genetics of Hispanic CF patients. TTGE effectively identified numerous rare and novel mutations and polymorphisms. One interesting observation is that the majority of the novel mutations are splice site, frame shift, or nonsense mutations that cause severe clinical phenotypes. Our data demonstrate that screening of the 27 exons and intron/exon junctions of the CFTR gene by TTGE greatly improves the molecular diagnosis of Hispanic CF patients.