NightShift: NMR shift inference by general hybrid model training--a framework for NMR chemical shift prediction.

BACKGROUND: NMR chemical shift prediction plays an important role in various applications in computational biology. Among others, structure determination, structure optimization, and the scoring of docking results can profit from efficient and accurate chemical shift estimation from a three-dimensional model.A variety of NMR chemical shift prediction approaches have been presented in the past, but nearly all of these rely on laborious manual data set preparation and the training itself is not automatized, making retraining the model, e.g., if new data is made available, or testing new models a time-consuming manual chore. RESULTS: In this work, we present the framework NightShift (NMR Shift Inference by General Hybrid Model Training), which enables automated data set generation as well as model training and evaluation of protein NMR chemical shift prediction.In addition to this main result - the NightShift framework itself - we describe the resulting, automatically generated, data set and, as a proof-of-concept, a random forest model called Spinster that was built using the pipeline. CONCLUSION: By demonstrating that the performance of the automatically generated predictors is at least en par with the state of the art, we conclude that automated data set and predictor generation is well-suited for the design of NMR chemical shift estimators.The framework can be downloaded from https://bitbucket.org/akdehof/nightshift. It requires the open source Biochemical Algorithms Library (BALL), and is available under the conditions of the GNU Lesser General Public License (LGPL). We additionally offer a browser-based user interface to our NightShift instance employing the Galaxy framework via https://ballaxy.bioinf.uni-sb.de/.

Human SAP18 mediates assembly of a splicing regulatory multiprotein complex via its ubiquitin-like fold.

RNPS1, Acinus, and SAP18 form the apoptosis- and splicing-associated protein (ASAP) complex, which is also part of the exon junction complex. Whereas RNPS1 was originally identified as a general activator of mRNA processing, all three proteins have been found within functional spliceosomes. Both RNPS1 and Acinus contain typical motifs of splicing regulatory proteins including arginine/serine-rich domains. Due to the absence of such structural features, however, a function of SAP18 in splicing regulation is completely unknown. Here we have investigated splicing regulatory activities of the ASAP components. Whereas a full-length Acinus isoform displayed only limited splicing regulatory activity, both RNPS1 and, surprisingly, SAP18 strongly modulated splicing regulation. Detailed mutational analysis and three-dimensional modeling data revealed that the ubiquitin-like fold of SAP18 was required for efficient splicing regulatory activity. Coimmunoprecipitation and immunofluorescence experiments demonstrated that SAP18 assembles a nuclear speckle-localized splicing regulatory multiprotein complex including RNPS1 and Acinus via its ubiquitin-like fold. Our results therefore suggest a novel function of SAP18 in splicing regulation.

Automated bond order assignment as an optimization problem.

MOTIVATION: Numerous applications in Computational Biology process molecular structures and hence strongly rely not only on correct atomic coordinates but also on correct bond order information. For proteins and nucleic acids, bond orders can be easily deduced but this does not hold for other types of molecules like ligands. For ligands, bond order information is not always provided in molecular databases and thus a variety of approaches tackling this problem have been developed. In this work, we extend an ansatz proposed by Wang et al. that assigns connectivity-based penalty scores and tries to heuristically approximate its optimum. In this work, we present three efficient and exact solvers for the problem replacing the heuristic approximation scheme of the original approach: an A*, an ILP and an fixed-parameter approach (FPT) approach. RESULTS: We implemented and evaluated the original implementation, our A*, ILP and FPT formulation on the MMFF94 validation suite and the KEGG Drug database. We show the benefit of computing exact solutions of the penalty minimization problem and the additional gain when computing all optimal (or even suboptimal) solutions. We close with a detailed comparison of our methods. AVAILABILITY: The A* and ILP solution are integrated into the open-source C++ LGPL library BALL and the molecular visualization and modelling tool BALLView and can be downloaded from our homepage www.ball-project.org. The FPT implementation can be downloaded from http://bio.informatik.uni-jena.de/software/.

BALL--biochemical algorithms library 1.3.

BACKGROUND: The Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements. RESULTS: Here, we discuss BALL's current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics. CONCLUSIONS: BALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at http://www.ball-project.org. Recently, it has been accepted into the debian project; integration into further distributions is currently pursued.

Isolation and structural analysis of peptide mimotopes for the disialoganglioside GD2, a neuroblastoma tumor antigen.

The disialoganglioside GalAcbeta1-4(NeuAcalpha2-8NeuAcalpha2-3)Galbeta1-4Glcbeta1-1Cer (GD2) is expressed on various tumors, including neuroblastoma, and was defined as a relevant tumor antigen. The monoclonal anti-GD2 antibody 14.18 is widely used for diagnostic purposes in neuroblastoma, and in its mouse/human chimeric form (ch14.18) now enters passive immunotherapeutic regimens in phase II clinical trials. This study aimed to generate structural mimics of the 14.18 epitope of GD2. Therefore, we used the ch14.18 antibody for selecting immunoreactive GD2 peptide mimotopes from a decamer phage display library. In all, 13 GD2 peptide mimics could be determined by biopanning and their specificity was demonstrated by exclusive recognition by the ch14.18 antibody. Furthermore, their nature of being GD2 mimics and their degree of mimicry was confirmed by competition with the natural antigen. When performing a comparative visualization of the GD2 epitope and selected mimotopes using a three-dimensional computer modeling system (BALLView), we demonstrated fitting of the GD2 molecule and the mimotopes in the antigen-binding pouch of a GD2 specific antibody. Moreover, the computer modeling argued for optimal affinity of the GD2 mimotopes. We thus provide evidence that the generation of GD2 peptide mimotopes is successful when using the neuroblastoma antibody ch14.18 for selection, and that this approach might offer a tool to develop a vaccination strategy against this malignant pediatric tumor.

Instruction of haematopoietic lineage choices, evolution of transcriptional landscapes and cancer stem cell hierarchies derived from an AML1-ETO mouse model.

The t(8;21) chromosomal translocation activates aberrant expression of the AML1-ETO (AE) fusion protein and is commonly associated with core binding factor acute myeloid leukaemia (CBF AML). Combining a conditional mouse model that closely resembles the slow evolution and the mosaic AE expression pattern of human t(8;21) CBF AML with global transcriptome sequencing, we find that disease progression was characterized by two principal pathogenic mechanisms. Initially, AE expression modified the lineage potential of haematopoietic stem cells (HSCs), resulting in the selective expansion of the myeloid compartment at the expense of normal erythro- and lymphopoiesis. This lineage skewing was followed by a second substantial rewiring of transcriptional networks occurring in the trajectory to manifest leukaemia. We also find that both HSC and lineage-restricted granulocyte macrophage progenitors (GMPs) acquired leukaemic stem cell (LSC) potential being capable of initiating and maintaining the disease. Finally, our data demonstrate that long-term expression of AE induces an indolent myeloproliferative disease (MPD)-like myeloid leukaemia phenotype with complete penetrance and that acute inactivation of AE function is a potential novel therapeutic option.