Comment on "Computation of isotopic peak center-mass distribution by fourier transform"

Complete Molecular Weight Profiling of Low-Molecular Weight Heparins Using Size Exclusion Chromatography-Ion Suppressor-High-Resolution Mass Spectrometry

Low-molecular weight heparins (LMWH) prepared by partial depolymerization of unfractionated heparin are used globally to treat coagulation disorders on an outpatient basis. Patent protection for several LMWH has expired and abbreviated new drug applications have been approved by the Food and Drug Administration. As a result, reverse engineering of LMWH for biosimilar LMWH has become an active global endeavor. Traditionally, the molecular weight distributions of LMWH preparations have been determined using size exclusion chromatography (SEC) with optical detection. Recent advances in liquid chromatography-mass spectrometry methods have enabled exact mass measurements of heparin saccharides roughly up to degree-of-polymerization 20, leaving the high molecular weight half of the LMWH preparation unassigned. We demonstrate a new LC-MS system capable of determining the exact masses of complete LMWH preparations, up to dp30. This system employed an ion suppressor cell to desalt the chromatographic effluent online prior to the electrospray mass spectrometry source. We expect this new capability will impact the ability to define LMWH mixtures favorably.

BRAIN 2.0: time and memory complexity improvements in the algorithm for calculating the isotope distribution

Recently, an elegant iterative algorithm called BRAIN (Baffling Recursive Algorithm for Isotopic distributioN calculations) was presented. The algorithm is based on the classic polynomial method for calculating aggregated isotope distributions, and it introduces algebraic identities using Newton-Girard and Viète's formulae to solve the problem of polynomial expansion. Due to the iterative nature of the BRAIN method, it is a requirement that the calculations start from the lightest isotope variant. As such, the complexity of BRAIN scales quadratically with the mass of the putative molecule, since it depends on the number of aggregated peaks that need to be calculated. In this manuscript, we suggest two improvements of the algorithm to decrease both time and memory complexity in obtaining the aggregated isotope distribution. We also illustrate a concept to represent the element isotope distribution in a generic manner. This representation allows for omitting the root calculation of the element polynomial required in the original BRAIN method. A generic formulation for the roots is of special interest for higher order element polynomials such that root finding algorithms and its inaccuracies can be avoided.