Computer assisted-method

Moreover, molecular modeling is one key method of a wide range of computer-assisted methods to analyze and predict relationships between protein sequence, 3D-molecular structure, and biological function (sequence-structure-function relationships). In molecular pharmacology these methods focus predominantly on analysis of interactions between different proteins, and between ligands (hormones, drugs) and proteins as well gaining information at the amino acid and even to atomic level. 

The constantly increasing amount of data coming from high throughput experimental methods, from genome sequences, from functional- and structural genomics has given a rise to a need for computer-assisted methods to elucidate sequence-structure-function relationships. 

Procedures used vary from trial-and-error methods to more sophisticated approaches including the window diagram, the simplex method, the PRISMA method, chemometric method, or computer-assisted methods. Many of these procedures were originally developed for HPLC and were apphed to TLC with appropriate changes in methodology. In the majority of the procedures, a set of solvents is selected as components of the mobile phase and one of the mentioned procedures is then used to optimize their relative proportions. Chemometric methods make possible to choose the minimum number of chromatographic systems needed to perform the best separation. 

Glajch, J.L., Snyder, L.R., editors (1990). Computer-Assisted Method Development for High-Performance Liquid Chromatography. Elsevier, Amsterdam. 

This derivation shows that retention time is dependant on three factors temperature, energies of intermolecular interactions and flow rate. Temperature and flow rate are controlled by the user. Energies of intermolecular interactions are controlled by stationary phase choice. This theory is also the basis for the popular software programs that are available for computer-assisted method development and optimization [4,5,6,7]. More detailed descriptions of the theory behind retention times can be found in the appropriate chapters in the texts listed in the bibliography. 

David F. V. Lewis, Computer-Assisted Methods in the Evaluation of Chemical Toxicity. 

Drablos, F. Anal. Chim. Acta 256, 1992, 145-151. Transformation of mass spectra. Elyashberg, M. E., Blinov, K. A., Molodtsov, S. G., Smumyi, E. D. J. Anal. Chem. 63, 2008, 13-20. New computer-assisted methods for the elucidation of molecular structures from 2-D spectra. 

Mohan, C.G., Gandhi, T, Garg, D. and Shinde, R. (2007) Computer-assisted methods in chemical toxicity prediction. Mini-Reviews in Medicinal Chemistry, 7, 499-507. 

Lewis, D.F.V., Computer-assisted methods in the evaluation of chemical toxicity, Rev. Computational Chem., 3, 173-222, 1992. 

G. Beech, Fortran IV in Chemistry An Introduction to Computer-Assisted Methods, Wiley, Chichester, 1975. 

J. L. Glajch and L. R. Snyder, Computer-Assisted Method Development in Chromatography, in J. Chromatogr., Vol. 485, Elsevier, Amsterdam, The Netherlands, 1989. 

In Chapter 4, David Lewis introduces computer-assisted methods in the evaluation of chemical toxicology. He points out that any substance can be toxic, and thus it is the dose of the substance that determines a toxic response. How, then, does one predict toxicity Lewis examines QSAR methods, pattern recognition techniques, computer modeling, and knowledge-based systems to answer this question. Ideally, one would like to assess toxicity of a structure before the compound is synthesized. To bring all this into focus, emphasis is placed on the cytochromes P450. 

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