Screening Method for the Discovery of Potential Bioactive Cysteine-Containing Peptides Using 3D Mass Mapping

Abstract

Animal venoms and toxins are a valuable source of bioactive peptides with pharmacologic relevance as potential drug leads. A large subset of biologically active peptides discovered up till now contain disulfide bridges that enhance stability and activity. To discover new members of this class of peptides, we developed a workflow screening specifically for those peptides that contain inter- and intra-molecular disulfide bonds by means of three-dimensional (3D) mass mapping. Two intrinsic properties of the sulfur atom, (1) its relatively large negative mass defect, and (2) its isotopic composition, allow for differentiation between cysteine-containing peptides and peptides lacking sulfur. High sulfur content in a peptide decreases the normalized nominal mass defect (NMD) and increases the normalized isotopic shift (NIS). Hence in a 3D plot of mass, NIS, and NMD, peptides with sulfur appear in this plot with a distinct spatial localization compared with peptides that lack sulfur. In this study we investigated the skin secretion of two frog species; Odorrana schmackeri and Bombina variegata. Peptides from the crude skin secretions were separated by nanoflow LC, and of all eluting peptides high resolution zoom scans were acquired in order to accurately determine both monoisotopic mass and average mass. Both the NMD and the NIS were calculated from the experimental data using an in-house developed MATLAB script. Candidate peptides exhibiting a low NMD and high NIS values were selected for targeted de novo sequencing, and this resulted in the identification of several novel inter- and intra-molecular disulfide bond containing peptides.Graphical AbstractᅟElectronic supplementary materialThe online version of this article (doi:10.1007/s13361-015-1282-z) contains supplementary material, which is available to authorized users.

High Resolution Mass Spectrometry of Cystine-Containing Neuropeptides in Histological Sections of Human FFPE Tissue Banks

“…org/help/Toxins. We cannot but conclude that our previous observation [18] still stands, with 6.66% of all residues being Cys in Tox-prot, whereas only 1.39% of all residues are Cys in UniProt.…”

“…As stated in our previous publication [18], many biologically active secretory peptides contain one or multiple disulfide bridges, in part due to/their contribution to the peptides' stability and activity. We concluded that the presence of Cys can 2d shows a theoretic isotope envelope of oxytocin with its cystine disulfide bridge formed.…”

“…We previously reported data obtained on early generation LTQ Orbitrap Velos PRO Elite and LTQ Orbitrap Velos systems, which were able to detect the secretory neuropeptides in question [16][17][18][19], but in this chapter we will concentrate on the younger ThermoFisher MS systems mentioned above.…”

“…It follows that a relatively high proportion of bioactive secretory peptides share the attribute of having one or more Cys-residues in their primary structure. We have used this feature in the past to filter bioactive peptide candidates from complex LC/MS datasets of animal secretions [18]. The conventional method of determining the presence of disulfide bonds in a peptide is by simply counting the mass shift before and after reduction [22] or after reduction and alkylation [23].…”

“…However, such an approach requires the comparison of two separate analyses, which is not always feasible or desirable. To quickly assign the presence of cysteines in a peptide of unknown nature without the need for disulfide bond reduction, we, therefore, developed an HRMS filtering approach [18], in which we employ two intrinsic characteristics of the sulfur atom to select peptides with cysteine residues. The relatively large negative mass defect (the difference between the isotopic and nominal or integer mass) in combination with the positive isotopic shift (difference between average and monoisotopic mass) [24] allows for rapid identification of sulfur-containing peptide candidates from LCMS datasets of a complex mixture of unknown Cys-containing samples.…”