Synthesis of isothermal reactor—separator—recycle systems

PILOT_PROTEIN: identification of unmodified and modified proteins via high-resolution mass spectrometry and mixed-integer linear optimization

A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag procedure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at http://pumpd.princeton.edu.

A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry

A novel algorithm, PILOT_PTM, has been developed for the untargeted identification of post-translational modifications (PTMs) on a template sequence. The algorithm consists of an analysis of an MS/MS spectrum via an integer linear optimization model to output a rank-ordered list of PTMs that best match the experimental data. Each MS/MS spectrum is analyzed by a preprocessing algorithm to reduce spectral noise and label potential complimentary, offset, isotope, and multiply charged peaks. Postprocessing of the rank-ordered list from the integer linear optimization model will resolve fragment mass errors and will reorder the list of PTMs based on the cross-correlation between the experimental and theoretical MS/MS spectrum. PILOT_PTM is instrument-independent, capable of handling multiple fragmentation technologies, and can address the universe of PTMs for every amino acid on the template sequence. The various features of PILOT_PTM are presented, and it is tested on several modified and unmodified data sets including chemically synthesized phosphopeptides, histone H3-(1-50) polypeptides, histone H3-(1-50) tryptic fragments, and peptides generated from proteins extracted from chromatin-enriched fractions. The data sets consist of spectra derived from fragmentation via collision-induced dissociation, electron transfer dissociation, and electron capture dissociation. The capability of PILOT_PTM is then benchmarked using five state-of-the-art methods, InsPecT, Virtual Expert Mass Spectrometrist (VEMS), Mod(i), Mascot, and X!Tandem. PILOT_PTM demonstrates superior accuracy on both the small and large scale proteome experiments. A protocol is finally developed for the analysis of a complete LC-MS/MS scan using template sequences generated from SEQUEST and is demonstrated on over 270,000 MS/MS spectra collected from a total chromatin digest.

A Multi-Level Methodology for Conceptual Reaction-Separation Process Design

Generic technology is presented for the optimal screening of reaction and separation process interactions. The proposed scheme enables the use of particularly rich superstructure formulations that are comprised of two types of generic synthesis units with flexible representation modes. A reaction unit enables a detailed representation of the reaction and a conceptual representation of separation systems is facilitated through separation task units. Possible process design interactions are embedded in the superstructure formulations as combinations of generic units. The design options are explored using stochastic optimisation techniques suitable for this class of problems. The synthesis scheme supports the decision making process in early process design stages and prepares problem definitions for later stages. Conceptual screening functionalities reveal design insights into the performance of complex reaction-separation systems based on the limited modelling information available early in design. This enables the identification and inclusion of the relevant design information into the superstructure formulations employed in the subsequent design stages.

A Mixed-Integer Optimization Framework for De Novo Peptide Identification

A novel methodology for the de novo identification of peptides by mixed-integer optimization and tandem mass spectrometry is presented in this article. The various features of the mathematical model are presented and examples are used to illustrate the key concepts of the proposed approach. Several problems are examined to illustrate the proposed method's ability to address (1) residue-dependent fragmentation properties and (2) the variability of resolution in different mass analyzers. A preprocessing algorithm is used to identify important m/z values in the tandem mass spectrum. Missing peaks, resulting from residue-dependent fragmentation characteristics, are dealt with using a two-stage algorithmic framework. A cross-correlation approach is used to resolve missing amino acid assignments and to identify the most probable peptide by comparing the theoretical spectra of the candidate sequences that were generated from the MILP sequencing stages with the experimental tandem mass spectrum.