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.     

Princeton_TIGRESS: Protein geometry refinement using simulations and support vector machines

Protein structure refinement aims to perform a set of operations given a predicted structure to improve model quality and accuracy with respect to the native in a blind fashion. Despite the numerous computational approaches to the protein refinement problem reported in the previous three CASPs, an overwhelming majority of methods degrade models rather than improve them. We initially developed a method tested using blind predictions during CASP10 which was officially ranked in 5th place among all methods in the refinement category. Here, we present Princeton_TIGRESS, which when benchmarked on all CASP 7,8,9, and 10 refinement targets, simultaneously increased GDT_TS 76% of the time with an average improvement of 0.83 GDT_TS points per structure. The method was additionally benchmarked on models produced by top performing three‐dimensional structure prediction servers during CASP10. The robustness of the Princeton_TIGRESS protocol was also tested for different random seeds. We make the Princeton_TIGRESS refinement protocol freely available as a web server at http://atlas.princeton.edu/refinement . Using this protocol, one can consistently refine a prediction to help bridge the gap between a predicted structure and the actual native structure. Proteins 2014; 82:794–814. © 2013 Wiley Periodicals, Inc.     

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%.     

Toward better refinement of comparative models: predicting loops in inexact environments

Achieving atomic-level accuracy in comparative protein models is limited by our ability to refine the initial, homolog-derived model closer to the native state. Despite considerable effort, progress in developing a generalized refinement method has been limited. In contrast, methods have been described that can accurately reconstruct loop conformations in native protein structures. We hypothesize that loop refinement in homology models is much more difficult than loop reconstruction in crystal structures, in part, because side-chain, backbone, and other structural inaccuracies surrounding the loop create a challenging sampling problem; the loop cannot be refined without simultaneously refining adjacent portions. In this work, we single out one sampling issue in an artificial but useful test set and examine how loop refinement accuracy is affected by errors in surrounding side-chains. In 80 high-resolution crystal structures, we first perturbed 6-12 residue loops away from the crystal conformation, and placed all protein side chains in non-native but low energy conformations. Even these relatively small perturbations in the surroundings made the loop prediction problem much more challenging. Using a previously published loop prediction method, median backbone (N-Calpha-C-O) RMSD's for groups of 6, 8, 10, and 12 residue loops are 0.3/0.6/0.4/0.6 A, respectively, on native structures and increase to 1.1/2.2/1.5/2.3 A on the perturbed cases. We then augmented our previous loop prediction method to simultaneously optimize the rotamer states of side chains surrounding the loop. Our results show that this augmented loop prediction method can recover the native state in many perturbed structures where the previous method failed; the median RMSD's for the 6, 8, 10, and 12 residue perturbed loops improve to 0.4/0.8/1.1/1.2 A. Finally, we highlight three comparative models from blind tests, in which our new method predicted loops closer to the native conformation than first modeled using the homolog template, a task generally understood to be difficult. Although many challenges remain in refining full comparative models to high accuracy, this work offers a methodical step toward that goal.     

When proteome meets genome: the alpha helix and the beta strand of proteins are eschewed by mRNA splice junctions and may define the minimal indivisible modules of protein architecture

The significance of the intron-exon structure of genes is a mystery. As eukaryotic proteins are made up of modular functional domains, each exon was suspected to encode some form of module; however, the definition of a module remained vague. Comparison of pre-mRNA splice junctions with the three-dimensional architecture of its protein product from different eukaryotes revealed that the junctions were far less likely to occur inside the α-helices and Β-strands of proteins than within the more flexible linker regions (‘turns’ and ‘loops’) connecting them. The splice junctions were equally distributed in the different types of linkers and throughout the linker sequence, although a slight preference for the central region of the linker was observed. The avoidance of the α-helix and the (Β-strand by splice junctions suggests the existence of a selection pressure against their disruption, perhaps underscoring the investment made by nature in building these intricate secondary structures. A corollary is that the helix and the strand are the smallest integral architectural units of a protein and represent the minimal modules in the evolution of protein structure. These results should find use in comparative genomics, designing of cloning strategies, and in the mutual verification of genome sequences with protein structures.     

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.     

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.