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.     

Benchmarking B cell epitope prediction: underperformance of existing methods

Sequence profiling is used routinely to predict the location of B-cell epitopes. In the postgenomic era, the need for reliable epitope prediction is clear. We assessed 484 amino acid propensity scales in combination with ranges of plotting parameters to examine exhaustively the correlation of peaks and epitope location within 50 proteins mapped for polyclonal responses. After examining more than 10(6) combinations, we found that even the best set of scales and parameters performed only marginally better than random. Our results confirm the null hypothesis: Single-scale amino acid propensity profiles cannot be used to predict epitope location reliably. The implication for studies using such methods is obvious.     

Understanding protein non-folding

This review describes the family of intrinsically disordered proteins, members of which fail to form rigid 3-D structures under physiological conditions, either along their entire lengths or only in localized regions. Instead, these intriguing proteins/regions exist as dynamic ensembles within which atom positions and backbone Ramachandran angles exhibit extreme temporal fluctuations without specific equilibrium values. Many of these intrinsically disordered proteins are known to carry out important biological functions which, in fact, depend on the absence of a specific 3-D structure. The existence of such proteins does not fit the prevailing structure–function paradigm, which states that a unique 3-D structure is a prerequisite to function. Thus, the protein structure–function paradigm has to be expanded to include intrinsically disordered proteins and alternative relationships among protein sequence, structure, and function. This shift in the paradigm represents a major breakthrough for biochemistry, biophysics and molecular biology, as it opens new levels of understanding with regard to the complex life of proteins. This review will try to answer the following questions: how were intrinsically disordered proteins discovered? Why don't these proteins fold? What is so special about intrinsic disorder? What are the functional advantages of disordered proteins/regions? What is the functional repertoire of these proteins? What are the relationships between intrinsically disordered proteins and human diseases?     

Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer library

Accurate prediction of the placement and comformations of protein side chains given only the backbone trace has a wide range of uses in protein design, structure prediction, and functional analysis. Prediction has most often relied on discrete rotamer libraries so that rapid fitness of side-chain rotamers can be assessed against some scoring function. Scoring functions are generally based on experimental parameters from small-molecule studies or empirical parameters based on determined protein structures. Here, we describe the NCN algorithm for predicting the placement of side chains. A predominantly first-principles approach was taken to develop the potential energy function incorporating van der Waals and electrostatics based on the OPLS parameters, and a hydrogen bonding term. The only empirical knowledge used is the frequency of rotameric states from the PDB. The rotamer library includes nearly 50,000 rotamers, and is the most extensive discrete library used to date. Although the computational time tends to be longer than most other algorithms, the overall accuracy exceeds all algorithms in the literature when placing rotamers on an accurate backbone trace. Considering only the most buried residues, 80% of the total residues tested, the placement accuracy reaches 92% for chi(1), and 83% for chi(1 + 2), and an overall RMS deviation of 1 A. Additionally, we show that if information is available to restrict chi(1) to one rotamer well, then this algorithm can generate structures with an average RMS deviation of 1.0 A for all heavy side-chains atoms and a corresponding overall chi(1 + 2) accuracy of 85.0%.     

Structural Analysis ofArabidopsis thaliana Chromosome 5. VI. Sequence Features of the Regions of 1,367,185 bp Covered by 19 Physically Assigned P1 and TAC Clones

Nineteen Pl and TAC clones, which have been mapped on the finephysical map of the Arabidopsis thaliana chromosome 5, weresequenced according to the shotgun-based strategy, and theirstructural features were analysed. The total length of the regionssequenced in this study was 1,367,185 bp. Combining this withthe regions covered by 90 P1 and TAC clones proviously reported,the total length of chromosome 5 sequenced to date becomes 8,058,855bp. On the basis of similarity search against protein and ESTdatabases and gene modeling with computer programs, a totalof 330 potential protein-coding regions were identified, bringingan average density of the genes to approximately one gene per4.1 kb. Introns were identified in 81.0% of the potential proteingenes for which the entire gene structure was predicted, withan average number per gene of 4.2 and an average length of theintrons of 180 bp. The RNA-coding genes identified were 9 tRNAgenes corresponding to 8 amino acid species and 2 genes forU2 nuclear RNA. These sequence features are essentially identicalto those in the previously reported sequences. The sequencedata and gene information are available on the World Wide Webdatabase KAOS (Kazusa Arabidopsis data Opening Site) at http://www.kazusa.or.jp/arabi/.     

Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects

Mixed linear model approach was proposed for mapping QTLs with the digenic epistasis and QTL by environment (QE) interaction as well as additive and dominant effects. Monte Carlo simulations indicated that the proposed method could provide unbiased estimations for both positions and genetic main effects of QTLs, as well as unbiased predictions for QE interaction effects. A method was suggested for predicting heterosis based on individual QTL effects. The immortalized F₂ (IF₂) population constructed by random mating among RI or DH lines is appropriate for mapping QTLs with epistasis and their QE interaction. Based on the models and methodology proposed, we developed a QTL mapping software, QTLMapper 2.0 on the basis of QTLmapper 1.0, which is suitable for analyzing populations of DH, RIL, F₂ and IF₂. Data of thousand grain weight of IF₂ population with 240 lines derived from elite hybrid rice Shanyou 63 were analyzed as a worked example.     

Microsatellite‐enriched genomic libraries as a source of polymorphic loci for Schistosoma mansoni

Microsatellite markers for Schistosoma mansoni were developed using four genomic microsatellite‐enriched libraries. Microsatellites were observed in 65.4% of all sequences. Primer pairs were designed and tested for 23 loci. Eighteen loci produced amplification products, out of which 11 were polymorphic and were further characterized on 100 individuals of S. mansoni. Two to 19 alleles per locus were detected. The average values of expected and observed heterozygosities among the 11 loci were 0.79 and 0.59, respectively.     

Prognostic molecular markers in pediatric liver disease – Are there any?

Pediatric liver disease (PLD) is a major cause of severe morbidity and prolonged hospitalizations in children. Stratifying patients in terms of prognosis remains challenging. The limited knowledge about molecular mechanisms causing and accompanying PLD remains the main obstacle in a search for reliable prognostic biomarkers. A systematic search of MEDLINE via PubMed and Embase via OVID was conducted on studies published between August 2007 and August 2017. Molecular markers with a prognostic potential in terms of survival, need for liver transplantation or disease progression/regression were selected. In general, identified studies were single center smaller case-control studies or case series with a low level of evidence and a high risk of bias. Only 23 studies comprising 898 patients could be included, mostly focusing on biliary atresia, non-alcoholic fatty liver disease, viral hepatitis, and LT; and markers related to morphogenesis and fibrosis. Furthermore, molecular markers in metabolic pathways and inflammation shown to be relevant, however requiring further validation. Hence, further biological and clinical studies are needed to gain greater molecular insight into PLD.     

火棘不同组织内生细菌群落多样性

为了解火棘不同组织内生细菌群落多样性,该研究采用高通量测序技术对火棘内生细菌16S rRNA V5～V7可变区进行测序,分析火棘不同组织部位内生细菌群落多样性。结果表明:(1)从火棘根、茎、叶组织中共获得内生细菌OTU 1 818个,其中根部754个,茎部 308 个,叶部756个,三者共有 OTU 152 个。(2)物种分类显示,不同火棘组织内生细菌具有丰富的群落多样性,火棘根部内生细菌种类隶属于23门53纲137目216科373属557种,其中异样根瘤菌属(Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium)和链霉菌属(Streptomyces)为优势属,其相对丰度分别为 10.57%和 8.00%; 茎部内生细菌种类隶属于21门32纲76目126科204属270种,其中马赛菌属(Massilia)和未知分类的丛毛单胞菌科属(unclassified_f_Comamonadaceae)为优势属,其相对丰度分别为31.10%和12.82%; 叶部内生细菌种类隶属于21门52纲130目210科380属581种,其中土芽孢杆菌属(Geobacillus)和假单胞菌属(Pseudomonas)为优势属,其相对丰度分别为12.31%和9.84%。(3)PICRUSt功能预测表明,根部内生细菌物种最丰富,参与各种代谢调控的细菌丰度最高。该研究结果为进一步探讨植物内生细菌功能,挖掘新的有益微生物资源提供了参考。