So far, more than 260 peer reviewed papers have been published on the application of DryLab – a complete list of which you can find here.
DryLab draws on the philosophy described in the three most famous Solvophobic Theory papers I, II, III of Csaba Horváth, which were developed in the years 1975-1977 at Yale University (see also literature by Dr. Imre Molnár).
Computer-Assisted Separation by HPLC with Diode Array Detection and Quantitative Determination of Furanocoumarins from Archangelica Officinalis
W. Markowski, K.L. Czapinska Chem. Anal. (Warsaw), 42, 353 (1997)
Selectivity Control in HPLC Method Development
L.R. Snyder, J.W. Dolan, I. Molnár, N. Djordjevic LCGC, 15, 2, 136 (1997)
Computerized optimization of the high-performance liquid chromatographic enantioseparation of a mixture of 4-dinitrophenyl amino acids on a quinine carbamate-type chiral stationary phase using DRYLAB.
M. Lämmerhofer, P. Di Eugenio, I. Molnár, W. Lindner J Chromatogr B Biomed Sci Appl. , 689, 1, 123-35 (1997)
A method is proposed for the sensitive chiral analysis of amino acid enantiomers by high-performance liquid chromatography (HPLC) using computer modeling with DryLab. Thus the enantiomers of a mixture of seven racemic amino acids were resolved as their DNP derivatives from each other and from the peak of the hydrolyzed reagent, employing a quinine carbamate-based chiral anion exchange-type chiral stationary phase (CSP) and aqueous buffered mobile phases. Average errors of prediction of retention times lay between 2 and 8%. Finally, a highly improved HPLC gradient method resulted in almost all components being baseline separated and equally spaced and accelerated by a factor of more than 3 compared to the initial run.
Changing reversed-phase high performance liquid chromatography selectivity. Which variables should be tried first?
When carrying out HPLC method development, it is often necessary to vary the relative retention of the sample (values of alpha) by changing some experimental variable, e.g., solvent type, pH, etc. The choice of which variable will be most suitable for a change in selectivity depends on two conflicting goals: (a) the attainment of maximum changes in alpha for the better control of resolution and (b) the avoidance of practical problems associated with the use of a given variable to optimize selectivity. This study provides a quantitative evaluation of different variables for their effect on selectivity (alpha). Various practical problems which must be balanced against this ability of a variable to change value of alpha are also discussed. The selection of any two variables for their simultaneous use in controlling alpha is also examined.
The Optimization of Peptide Mapping via Computer Simulation
L.R. Snyder New Methods in Peptide Mapping for the Characterization of Proteins, in: William S. Hancock (ed.), (Crc Pr Inc.,, Boca Raton, FL, 1996), 31-54
Determination of 1,8-dihydroxyanthranoids in senna
Wolfgang Metzger, Klaus Reif J. Chromatogr. A, 740, 1, 133–138 (1996), DOI: 10.1016/0021-9673(96)00141-0
This paper describes the results of a new method for the determination of 1-,-hydroxyanthranoids in senna. This will be illustrated by examples from a study of the occurrence of 17 different 1,8-dihydroxyanthranoids (anthraquinones and their bianthrys) in fruits leaves of PSenna angustifolia amd Senna acutifolia. The anthranoids are extracted using a mixture of acetonitrile and a solution of sodium hydrogencarbonate. The different compounds are separated and detected by HPLC using an Rp-8 column and a photodiode array detector. The method was optimized by means of computer-assisted method development techniques using the DryLab software.