Author Archives: Vera

Software-aided workflow for predicting protease-specific cleavage sites using physicochemical properties of the natural and unnatural amino acids in peptide-based drug discovery

January 2019.

Radchenko T; Fontaine F; Morettoni L; Zamora I

Abstract

Peptide drugs have been used in the treatment of multiple pathologies. During peptide discovery, it is crucially important to be able to map the potential sites of cleavages of the proteases. This knowledge is used to later chemically modify the peptide drug to adapt it for the therapeutic use, making peptide stable against individual proteases or in complex medias. In some other cases it needed to make it specifically unstable for some proteases, as peptides could be used as a system to target delivery drugs on specific tissues or cells. The information about proteases, their sites of cleavages and substrates are widely spread across publications and collected in databases such as MEROPS.

Therefore, it is possible to develop models to improve the understanding of the potential peptide drug proteolysis. We propose a new workflow to derive protease specificity rules and predict the potential scissile bonds in peptides for individual proteases. WebMetabase stores the information from experimental or external sources in a chemically aware database where each peptide and site of cleavage is represented as a sequence of structural blocks connected by amide bonds and characterized by its physicochemical properties described by Volsurf descriptors. Thus, this methodology could be applied in the case of non-standard amino acid. A frequency analysis can be performed in WebMetabase to discover the most frequent cleavage sites.

These results were used to train several models using logistic regression, support vector machine and ensemble tree classifiers to map cleavage sites for several human proteases from four different families (serine, cysteine, aspartic and matrix metalloproteases). Finally, we compared the predictive performance of the developed models with other available public tools PROSPERous and SitePrediction. 

High resolution Mass Spectrometry with automated data analysis to support structural elucidation of degradation impurities of small peptides

AAPS 2019 PHARMSCI 360, San Antonio (United States of America)… 03 November, 2019 

Abstract

Structural elucidation of drug substance related impurities in drug products to identify specific degradation pathways is important for the development of formulated drugs, optimization of manufacturing process and in certain cases a requirement for regulatory submissions. The present work utilized an in-silico data processing tool MassChemSite, which has been developed to automate data analysis and to facilitate the structural elucidation of drug degradants by LC-MS/MS. The software was customized to work on structure modifications introduced by common degradation chemistries for small peptides. 

Automatization of structural elucidation workflow for detecting degradation impurities in Peptides

February 2020

Elisabeth Ortega-Carrasco, Blanca Serra, Ismael Zamora

Abstract

Detection and identification of drug degradation impurities in drug products is important to the development of formulated drugs. Structures and formation mechanisms of degradation impurities need to be identified once the degradants exceed certain specified levels, as required for the regulatory guidelines.  A rapid structure elucidation of those drug substance related impurities is essential to have a clear understanding of the quality of the new drug. 

For this purpose, liquid chromatography-mass spectrometry (LC-MS) techniques are the most frequently used. However, the processing and rationalization of MS/MS data can be quite time consuming, especially in peptide studies due to their size and multiple charge. In this poster we present a fully automatic workflow for structural elucidation of degradation impurities in peptides implemented in MassChemsite (Molecular Discovery, Ltd., London, UK) program. 

Peptide metabolism: Identification of Metabolite structures of GLP-1 receptor agonists in different in-vitro systems using high resolution mass spectrometry

64th ASMS Conference on Mass Spectrometry and Allied Topics, San Antonio, TX (United States of America) … 05 June 2016 

 

Abstract

Introduction  

Peptide drugs are an important class of therapeutics under investigation in various pharmaceutical companies. Assessment of peptide stability in vitro, the identification of cleavage sites and structure elucidation of degradation products are important tasks of drug metabolism scientists. However, most in vitro systems established to investigate metabolism of small molecules (e.g., microsomes) are not relevant for peptides because most peptides show low cell membrane permeability and are subject to hydrolysis by enzymes expressed on epithelial cell surfaces. In addition to relevant in vitro systems, appropriate mass spectrometry approaches and tailored software tools are required due to the higher molecular weight, presence of multiple-charge stages upon electrospray ionization and increasing molecular complexity (modified amino acids, cyclisation etc.) of peptide drug candidates.  

 

Methods  

Glucagon-Like Peptide-1, (GLP-1) and three analogs (taspoglutide, liraglutide, exenatide) were incubated with the human recombinantly expressed enzymes dipeptidyl-peptidase-IV (DPP-4) and neutral endopeptidase (NEP) as well as with various cellular systems, namely primary and immortalized human umbilical vein endothelial cells (HUVEC cells), TERT1-immortalized renal proximal tubule epithelial cells (RPTECs-TERT1 cells) and human hepatocytes. Samples were analyzed up to 24 hours using a Q Exactive™ Hybrid Quadrupole-Orbitrap Mass Spectrometer in data dependent scan mode. The mass inclusion list set-up (up to z = 5) and the post-acquisition data analyses were performed using the recently introduced peptide mode integrated in MassMetaSite (MMS 3.2.0). MMS extracted metabolite peaks and interpreted MS/MS fragmentation to provide structural proposals. The results were reviewed using WebMetabase (version 3.1.4).  

 

Preliminary Data  

The peptide mode of the MassMetaSite software was successfully applied to process full scan HRMS data to detect and identify metabolites of 4 model peptides. MMS proposed definitive metabolite structures to the identified metabolite peaks based on the interpretation of MS2 fragmentation data. Based on these metabolite structures, peptide bond cleavage sites could be demonstrated. WebMetabase was able to sort and match metabolites based on retention time and MS2 fragmentation across the different in vitro experiments resulting in an efficient workflow to compile results for comparison of different in vitro systems regarding metabolites formed. The results showed that GLP-1 was metabolized rapidly in the presence of DPP-4 (t1/2 ≈ 7 min). The main metabolite identified by MMS (< 2 ppm) resulted from N-terminal cleavage after amino acid 8 (Ala), corresponding to GLP-1 (9-37). This observation was in line with reports from literature.  

The same metabolite increased with time in incubates with primary HUVEC, immortalized HUVEC and hepatocytes indicative of functional DPP-4 activity in these cell lines. Turnover in presence of DPP-4 was as well seen for taspoglutide and liraglutide, however at a slower rate compared to GLP-1. Analog to GLP-1 the cleavage sites were assigned after amino acid 8 at the N-terminus resulting in liraglutide (9-37) and taspoglutide(9-37). Taspoglutide in presence of NEP was initially cleaved between the amino acids Ser18-Tyr19 and Tyr19-Leu20 position (analog for liraglutide).

Further peptidic cleavage lead to shorter peptides mainly seen in human hepatocytes. For taspoglutide and liraglutide, mostly the same metabolites were seen in HUVEC cells when compared with the isolated enzyme systems NEP and DPP-4 alone. Preliminary data suggest that no significant qualitative difference was observed between primary and immortalized HUVEC cells for degradation products of GLP-1 and its structural analogs. In conclusion this approach might be used for peptide metabolism investigations. Novel Aspect New software-aided approach to analyze HRMS data to investigate stability and cleavage sites of peptides in different in vitro systems. 

Peptide metabolism: High resolution Mass Spectrometry tool to investigate Peptide structure and amine bond metabolic susceptibility

American Peptide Symposium, Whistler (Canada)… 17 June 2017 

 

Abstract

Several in-silico approaches have been developed such as PeptideCutter to predict peptide cleavage sites for different proteases. Moreover, several databases exist where this information is collected and stored such as MEROPS. Despite these new methodologies there are still some limitations in their usage: inability to handle unnatural amino acids and cyclic peptides. The aim of this work is to develop a new methodology to analyze the mass spectrometry driven experimental data to find those metabolites, then determine their structures, database all the results in a chemistry aware manner and finally to compute the peptide bond susceptibility by using a frequency analysis of the metabolic liability.

This approach uses ultra-performance liquid chromatography with high resolution mass spectrometry to obtain the analytical data from incubations of peptides with different enzyme matrices. Metabolite identification was performed on 13 commercial peptide compounds and 4 positive substrates for the four selected proteases (serine and aspartic). The peptides were incubated for three hours with five time points being taken during the experiment. The compounds were diverse with respect to linear and cyclic structure, containing natural and unnatural amino acids and ranged in molecular weight.

The analysis of this data set resulted in 45 metabolites that were annotated in the database. The frequency analysis revealed 26 site of cleavage and the Trp-Ser being the most frequently cleaved bond for all cases. Selectivity was identified for pancreatic elastase and trypsin/chymotrypsin because the Ser-Tyr and Leu-Ser were revealed as a most frequently cleaved bond, respectively. These results agreed with previous studies.