Advanced Cyclopeptide Sequencing and Antibiotic Identification Solutions
Delve into the world of non-ribosomally produced cyclopeptides like Obyanamide for antitumor properties. Explore an innovative approach involving mass spectrometry and branch-and-bound algorithms for antibiotic identification. Understand the high-level steps of cyclopeptide sequencing using spectral data analysis methods.
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Presentation Transcript
Cyclopeptide Sequencing Obyanamide, a non-ribosomally produced antitumor. From Norine database. TAYLA ISENSEE
Problem: Antibiotics are not in the genome Solution: Mass Spectrometry Coding Problem: Brute force takes too long Solution: Branch and bound Candidates: ['PG', 'PA', 'PS', 'PP', 'PV', 'PT', 'PC', 'PI', 'PL', 'PN', 'PD', 'PK', 'PQ', 'PE', 'PM', 'PH', 'PF', 'PR', 'PY', 'PW', 'PG', 'PA', 'PS', 'PP', 'PV', 'PT', 'PC', 'PI', 'PL', 'PN', 'PD', 'PK', 'PQ', 'PE', 'PM', 'PH', 'PF', 'PR', 'PY', 'PW', 'VG', 'VA', 'VS', 'VP', 'VV', 'VT ...] Peptides Kept: ['PV', 'PT', 'PC', 'VP', 'VV', 'VT', 'VC', 'TP', 'TV', 'TT', 'CP', 'CV']
Data Spectrum = [0, 97, 97, 99, 101, 103, 196, 198, 198, 200, 202, 295, 297, 299, 299, 301, 394, 396, 398, 400, 400, 497]
High Level Steps CyclopeptideSequencing(Spectrum) Peptides a list while Final Peptides is empty: Peptides Expand(Peptides) for each peptide Peptide in Peptides if Mass(Peptide) is in Spectrum KeptPeps = KeptPeps + peptide if Cyclospectrum(Peptide) = Spectrum Final Peptides + Peptide output Final Peptide Peptides = KeptPeps CyclopeptideSequencing(Spectrum) Peptides a set containing only the empty peptide while Peptides is nonempty Peptides Expand(Peptides) for each peptide Peptide in Peptides if Mass(Peptide) = ParentMass(Spectrum) if Cyclospectrum(Peptide) = Spectrum output Peptide remove Peptide from Peptides else if Peptide is not consistent with Spectrum remove Peptide from Peptides clear KeptPeps
Results Program can sequence cyclic peptides! But runtime limits the length of peptide (no leaderboard) And LOTS of assumptions about the fidelity of the data Spectrum = [0, 97, 97, 99, 101, 103, 196, 198, 198, 200, 202, 295, 297, 299, 299, 301, 394, 396, 398, 400, 400, 497] Possible Amino Acid Sequence = PVCPT Mass Sequence = 97-99-103-97-101
Conclusion Program works on highly improbable, perfect datasets Improving runtime, either with more expansive bounding or implementing a leaderboard But NRPs can contain more than 20 aa s (100s), It isn t science unless you find a cool database =
