High Resolution Mass Spectrometry for Rapid Characterization of Combinatorial Peptide Libraries

Bottom-Up Design Approach for OBOC Peptide Libraries

One-bead-one-compound peptide libraries, developed following the top-down experimental approach, have attracted great interest in the identification of potential ligands or active peptides. By exploiting a reverse experimental design approach based on the bottom-up strategy, we aimed to develop simplified, maximally diverse peptide libraries that resulted in the successful characterization of mixture components. We show that libraries of 32 and 48 components can be successfully detected in a single run using chromatography coupled to mass spectrometry (UPLC-MS). The proposed libraries were further theoretically evaluated in terms of their composition and physico-chemical properties. By combining the knowledge obtained on single libraries we can cover larger sequence spaces and provide a controlled exploration of the peptide chemical space both theoretically and experimentally. Designing libraries by using the bottom-up approach opens up the possibility of rationally fine-tuning the library complexity based on the available analytical methods.

An index for characterization of natural and non-natural amino acids for peptidomimetics

Bioactive peptides and peptidomimetics play a pivotal role in the regulation of many biological processes such as cellular apoptosis, host defense, and biomineralization. In this work, we develop a novel structural matrix, Index of Natural and Non-natural Amino Acids (NNAAIndex), to systematically characterize a total of 155 physiochemical properties of 22 natural and 593 non-natural amino acids, followed by clustering the structural matrix into 6 representative property patterns including geometric characteristics, H-bond, connectivity, accessible surface area, integy moments index, and volume and shape. As a proof-of-principle, the NNAAIndex, combined with partial least squares regression or linear discriminant analysis, is used to develop different QSAR models for the design of new peptidomimetics using three different peptide datasets, i.e., 48 bitter-tasting dipeptides, 58 angiotensin-converting enzyme inhibitors, and 20 inorganic-binding peptides. A comparative analysis with other QSAR techniques demonstrates that the NNAAIndex method offers a stable and predictive modeling technique for in silico large-scale design of natural and non-natural peptides with desirable bioactivities for a wide range of applications.

Diversity, isomer composition, and design of combinatorial libraries of tetrapyrrole macrocycles

Combinatorial libraries of substituted tetrapyrrole macrocycles, which can now be prepared via a variety of approaches, typically are rich in isomers. Terminology for describing such isomers (due to distinct patterns of peripheral substituents) is delineated in several illustrative examples. A hierarchical relationship exists of molecular formula, condensed formula(s) of substituents, set(s) of pyrrole collocates (conveying each pair of β-pyrrolic substituents), and isomers of substituted tetrapyrrole macrocycles. Isomers with identical pyrrole collocate sets can arise owing to distinct positions or orientations of the (homo- or hetero-substituted) pyrrolic units in a macrocycle. Consideration of a handful of virtual combinatorial libraries illustrates tradeoffs of library size, chemical richness, and isomeric content. As one example, octa-derivatization of a tetrapyrrole scaffold with eight reactants A–H affords 2,099,728 members (99.7% isomers, 82,251 pyrrole collocate sets, and 6,435 condensed formulas) whereas the reversible self-condensation of four pyrroles that bear the same eight entities (AB, CD, EF, GH) affords 538 members (93.5% isomers, 35 pyrrole collocate sets, and 35 condensed formulas). Derivatization affords all combinations and permutations whereas self-condensation of substituted pyrroles carries collocational restrictions. Understanding such tradeoffs and the structural origin of isomerism are important aspects in the design of tetrapyrrole combinatorial libraries.

Quality control based on isotopic distributions for high-throughput MALDI-TOF and MALDI-FTICR serum peptide profiling

In this study, we have implemented a new quality control (QC) parameter for peptide profiling based on isotopic distributions. This QC parameter is an objective measure and facilitates automatic sorting of large numbers of peptide spectra. Peptides in human serum samples were enriched using reversed-phase C(18)-functionalized magnetic beads using a high-throughput robotic platform. High-resolution MALDI-TOF and ultrahigh resolution MALDI-FTICR mass spectra were obtained and a workflow was developed for automated analysis and evaluation of these profiles. To this end, the isotopic distributions of multiple peptides were quantified from both MALDI-TOF and MALDI-FTICR spectra. Odd peptide isotope distributions in TOF spectra could be rationalized from ultrahigh resolution FTICR spectra that showed overlap of different peptides. The comparison of isotope patterns with estimated polyaveragine distributions was used to calculate a QC value for each single mass spectrum. Sorting these QC values enabled the best MALDI spectrum to be selected from replicate spots. Moreover, using this approach spectra containing high intensities of polymers or other contaminants and lacking peptides of interest can be efficiently removed from a clinical dataset. In general, this method simplifies the exclusion of low quality spectra from further statistical analysis.

Transformative effects of higher magnetic field in Fourier transform ion cyclotron resonance mass spectrometry

The relationship of magnetic field strength and Fourier transform ion cyclotron resonance mass spectrometry performance was tested using three instruments with the same design but different fields of 4.7, 7, and 9.4 tesla. We found that the theoretically predicted "transformative" effects of magnetic field are indeed observed experimentally. The most striking effects were that mass accuracy demonstrated approximately second to third order improvement with the magnetic field, depending upon the charge state of the analyte, and that peak splitting, which prohibited automated data analysis at 4.7 T, was not observed at 9.4 T.

A novel mass spectrometry cluster for high-throughput quantitative proteomics

We have developed and implemented a novel mass spectrometry (MS) platform combining the advantages of high mass accuracy and resolving power of Fourier transform ion cyclotron resonance (FTICR) with the economy and speed of multiple ion traps for tandem mass spectrometry. The instruments are integrated using novel algorithms and software and work in concert as one system. Using chromatographic time compression, a single expensive FTICR mass spectrometer can match the throughput of multiple relatively inexpensive ion trap instruments. Liquid chromatography (LC)-mass spectrometry data from the two types of spectrometers are aligned and combined to hybrid datasets, from which peptides are identified using accurate mass from the FTICR data and tandem mass spectra from the ion trap data. In addition, the high resolving power and dynamic range of a 12 tesla FTICR also allows precise label-free quantitation. Using two ion traps in parallel with one LC allows simultaneous MS/MS experiments and optimal application of collision induced dissociation and electron-transfer dissociation throughout the chromatographic separation for increased proteome coverage, characterization of post-translational modifications and/or simultaneous measurement in positive and negative ionization mode. An FTICR-ion trap cluster can achieve similar performance and sample throughput as multiple hybrid ion trap-FTICR instruments, but at a lower cost. We here describe the first such FTICR-ion trap cluster, its performance and the idea of chromatographic compression.