title: Using the partial least squares method to model the electrospray ionization response produced by small pharmaceutical molecules in positive mode.
abstract: BACKGROUND
  The signal intensity in electrospray ionization mass spectrometry (ESI-MS) positive mode is affected by parameters that are related to the physicochemical properties and structural features of a molecule. Accordingly, the combined interactions of an analyte and the mobile phase used is still an area that demands further clarifications since there is no general pattern regarding the nature of a molecule and the mechanism by which vapor-phase ions are produced.
  
  
  METHODS
  A multivariate analysis method, such as Partial Least Squares (PLS), provides the opportunity to correlate the effect of a large number of parameters interpreting this complex procedure with the use of appropriate mathematical algorithms. This work involves the development of models containing up to 84 X variables which characterize the analytes studied (99) focusing on their positive or negative effect on the vapor-phase ion formation process. These descriptors are correlated with the signal response of the positively charged analyte ions which corresponds to the Y variable.
  
  
  RESULTS
  The results showed that parameters referring or directly related to the ionization percentage of basic or acidic groups of an analyte can be used to determine the signal response on positive ESI-MS mode. Structural characteristics, polar surface area, lipophilicity, the ability of analytes to acts as hydrogen bond donors or acceptors, water solubility, density of a solid, surface tension of the substance and the number of free rotatable bonds are descriptors which are of secondary importance, still they cannot be considered negligible.
  
  
  CONCLUSIONS
  The models derived are proved to be reliable for the investigation of such mechanisms, with a small number of components and good linearity (R(2) >83%, Q(2) >70%).
authors.affiliation: Laboratory of Pharmaceutical Analysis, Department of Pharmaceutical Technology, School of Pharmacy, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
authors.forename: Varvara J
authors.initials: VJ
authors.lastname: Mandra
authors.affiliation: Laboratory of Pharmaceutical Analysis, Department of Pharmaceutical Technology, School of Pharmacy, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
authors.forename: Maria G
authors.initials: MG
authors.lastname: Kouskoura
authors.affiliation: Laboratory of Pharmaceutical Analysis, Department of Pharmaceutical Technology, School of Pharmacy, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
authors.forename: Catherine K
authors.initials: CK
authors.lastname: Markopoulou
mesh_terms: D000465:Algorithms; D007477:Ions / Q000032:analysis / Q000737:chemistry*; D016018:Least-Squares Analysis; D008956:Models, Chemical; D004364:Pharmaceutical Preparations / Q000032:analysis / Q000737:chemistry*; D012997:Solvents; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*
chemical_list: D007477:Ions; D004364:Pharmaceutical Preparations; D012997:Solvents