Efficient estimation of contact probabilities from inter-bead distance distributions in simulated polymer chains.

The estimation of contact probabilities (CP) from conformations of simulated bead-chain polymer models is a key step in methods that aim to elucidate the spatial organization of chromatin from analysis of experimentally determined contacts between different genomic loci. Although CPs can be estimated simply by counting contacts between beads in a sample of simulated chain conformations, reliable estimation of small CPs through this approach requires a large number of conformations, which can be computationally expensive to obtain. Here we describe an alternative computational method for estimating relatively small CPs without requiring large samples of chain conformations. In particular, we estimate the CPs from functional approximations to the cumulative distribution function (cdf) of the inter-bead distance for each pair of beads. These cdf approximations are obtained by fitting the extended generalized lambda distribution (EGLD) to inter-bead distances determined from a sample of chain conformations, which are in turn generated by Monte Carlo simulations. We find that CPs estimated from fitted EGLD cdfs are significantly more accurate than CPs estimated using contact counts from samples of limited size, and are more precise with all sample sizes, permitting as much as a tenfold reduction in conformation sample size for chains of 200 beads and samples smaller than 10(5) conformations. This method of CP estimation thus has potential to accelerate computational efforts to elucidate the spatial organization of chromatin.

Interpretation of tandem mass spectra obtained from cyclic nonribosomal peptides.

Natural and non-natural cyclic peptides are a crucial component in drug discovery programs because of their considerable pharmaceutical properties. Cyclosporin, microcystins, and nodularins are all notable pharmacologically important cyclic peptides. Because these biologically active peptides are often biosynthesized nonribosomally, they often contain nonstandard amino acids, thus increasing the complexity of the resulting tandem mass spectrometry data. In addition, because of the cyclic nature, the fragmentation patterns of many of these peptides showed much higher complexity when compared to related counterparts. Therefore, at the present time it is still difficult to annotate cyclic peptides MS/MS spectra. In this current work, an annotation program was developed for the annotation and characterization of tandem mass spectra obtained from cyclic peptides. This program, which we call MS-CPA is available as a web tool (http://lol.ucsd.edu/ms-cpa_v1/Input.py). Using this program, we have successfully annotated the sequence of representative cyclic peptides, such as seglitide, tyrothricin, desmethoxymajusculamide C, dudawalamide A, and cyclomarins, in a rapid manner and also were able to provide the first-pass structure evidence of a newly discovered natural product based on predicted sequence. This compound is not available in sufficient quantities for structural elucidation by other means such as NMR. In addition to the development of this cyclic annotation program, it was observed that some cyclic peptides fragmented in unexpected ways resulting in the scrambling of sequences. In summary, MS-CPA not only provides a platform for rapid confirmation and annotation of tandem mass spectrometry data obtained with cyclic peptides but also enables quantitative analysis of the ion intensities. This program facilitates cyclic peptide analysis, sequencing, and also acts as a useful tool to investigate the uncommon fragmentation phenomena of cyclic peptides and aids the characterization of newly discovered cyclic peptides encountered in drug discovery programs.