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Radchenko T, Brink A, Siegrist Y, Kochansky C, Bateman A, Fontaine F, Morettoni L, Zamora I. Software-aided approach to investigate peptide structure and metabolic susceptibility of amide bonds in peptide drugs based on high resolution mass spectrometry. PLoS One 2017; 12:e0186461. [PMID: 29091918 PMCID: PMC5665424 DOI: 10.1371/journal.pone.0186461] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 10/02/2017] [Indexed: 01/08/2023] Open
Abstract
Interest in using peptide molecules as therapeutic agents due to high selectivity and efficacy is increasing within the pharmaceutical industry. However, most peptide-derived drugs cannot be administered orally because of low bioavailability and instability in the gastrointestinal tract due to protease activity. Therefore, structural modifications peptides are required to improve their stability. For this purpose, several in-silico software tools have been developed such as PeptideCutter or PoPS, which aim to predict peptide cleavage sites for different proteases. Moreover, several databases exist where this information is collected and stored from public sources such as MEROPS and ExPASy ENZYME databases. These tools can help design a peptide drug with increased stability against proteolysis, though they are limited to natural amino acids or cannot process cyclic peptides, for example. We worked to develop a new methodology to analyze peptide structure and amide bond metabolic stability based on the peptide structure (linear/cyclic, natural/unnatural amino acids). This approach used liquid chromatography / high resolution, mass spectrometry to obtain the analytical data from in vitro incubations. We collected experimental data for a set (linear/cyclic, natural/unnatural amino acids) of fourteen peptide drugs and four substrate peptides incubated with different proteolytic media: trypsin, chymotrypsin, pepsin, pancreatic elastase, dipeptidyl peptidase-4 and neprilysin. Mass spectrometry data was analyzed to find metabolites and determine their structures, then all the results were stored in a chemically aware manner, which allows us to compute the peptide bond susceptibility by using a frequency analysis of the metabolic-liable bonds. In total 132 metabolites were found from the various in vitro conditions tested resulting in 77 distinct cleavage sites. The most frequent observed cleavage sites agreed with those reported in the literature. The main advantages of the developed approach are the abilities to elucidate metabolite structure of cyclic peptides and those containing unnatural amino acids, store processed information in a searchable format within a database leading to frequency analysis of the labile sites for the analyzed peptides. The presented algorithm may be useful to optimize peptide drug properties with regards to cleavage sites, stability, metabolism and degradation products in drug discovery.
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Affiliation(s)
- Tatiana Radchenko
- Pompeu Fabra University, Barcelona, Spain
- Lead Molecular Design, S.L, Sant Cugat del Vallés, Spain
- * E-mail: (TR); (IZ)
| | - Andreas Brink
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Yves Siegrist
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Christopher Kochansky
- Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck & Co., Inc., West Point, Pennsylvania, United States of America
| | - Alison Bateman
- Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck & Co., Inc., West Point, Pennsylvania, United States of America
| | | | | | - Ismael Zamora
- Pompeu Fabra University, Barcelona, Spain
- Lead Molecular Design, S.L, Sant Cugat del Vallés, Spain
- * E-mail: (TR); (IZ)
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Chakravorty DK, Li P, Tran TT, Bayse CA, Merz KM. Metal Ion Capture Mechanism of a Copper Metallochaperone. Biochemistry 2016; 55:501-9. [DOI: 10.1021/acs.biochem.5b01217] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Dhruva K. Chakravorty
- Institute
for Cyber Enabled Research, Michigan State University, 567 Wilson
Road, East Lansing, Michigan 48824, United States
- Department
of Chemistry, University of New Orleans, 2000 Lakeshore Drive, New Orleans, Louisiana 70148, United States
- Department
of Chemistry and Quantum Theory Project, University of Florida, Gainesville, Florida 32611-8435, United States
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Pengfei Li
- Department
of Chemistry and Quantum Theory Project, University of Florida, Gainesville, Florida 32611-8435, United States
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Trang T. Tran
- Department
of Chemistry, University of New Orleans, 2000 Lakeshore Drive, New Orleans, Louisiana 70148, United States
| | - Craig A. Bayse
- Department of Chemistry & Biochemistry, Old Dominion University, Norfolk, Virginia 23529, United States
| | - Kenneth M. Merz
- Institute
for Cyber Enabled Research, Michigan State University, 567 Wilson
Road, East Lansing, Michigan 48824, United States
- Department
of Chemistry and Quantum Theory Project, University of Florida, Gainesville, Florida 32611-8435, United States
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
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