Computational absorption prediction

The computational prediction of vibrational spectra is among the important areas of application for modem quantum chemical methods because it allows the interpretation of experimental spectra and can be very instrumental for the identification of unknown species. A vibrational spectrum consists of two characteristics, the frequency of the incident light at which the absorption occurs and how much of the radiation is absorbed. The first quantity can be obtained computationally by calculating the harmonic vibrational frequencies of a molecule. As outlined in Chapter 8 density functional methods do a rather good job in that area. To complete the picture, one must also consider the second quantity, i. e., accurate computational predictions of the corresponding intensities have to be provided. 

This volume gives an overview of the current status and an outlook to future more reliable predictive approaches. It is subdivided in five sections dealing with studies of membrane permeability and oral absorption, drug dissolution and solubility, the role of transporters and metabolism in oral absorption, computational approaches to drug absorption and bioavailability, and finally with certain drug development issues. 

Johnson, S.R. and Zheng, W. (2006) Recent progress in the computational prediction of aqueous solubility and absorption. AAPS Journal, 8, E27-E30. 

Hou, T., Wang, J Zhang, W Wang, W. and Xu, X. (2006) Recent advances in computational prediction of drug absorption and permeability in drug discovery. Current Medicinal Chemistry, 13, 2653-2667. 

The first step of peroxidase catalysis involves binding of the peroxide, usually H2C>2, to the heme iron atom to produce a ferric hydroperoxide intermediate [Fe(IE)-OOH]. Kinetic data identify an intermediate prior to Compound I whose formation can be saturated at higher peroxide concentrations. This elusive intermediate, labeled Compound 0, was first observed by Back and Van Wart in the reaction of HRP with H2O2 [14]. They reported that it had absorption maxima at 330 and 410 nm and assigned these spectral properties to the ferric hydroperoxide species [Fe(III)-OOH]. They subsequently detected transient intermediates with similar spectra in the reactions of HRP with alkyl and acyl peroxides [15]. However, other studies questioned whether the species with a split Soret absorption detected by Back and Van Wart was actually the ferric hydroperoxide [16-18], Computational prediction of the spectrum expected for Compound 0 supported the structure proposed by Baek and Van Wart for their intermediate, whereas intermediates observed by others with a conventional, unsplit Soret band may be complexes of ferric HRP with undeprotonated H2O2, that is [Fe(III)-HOOH] [19]. Furthermore, computational analysis of the peroxidase catalytic sequence suggests that the formation of Compound 0 is preceded by formation of an intermediate in which the undeprotonated peroxide is coordinated to the heme iron [20], Indeed, formation of the [Fe(III)-HOOH] complex may be required to make the peroxide sufficiently acidic to be deprotonated by the distal histidine residue in the peroxidase active site [21],... 

A schematic of the flow-through nanohole array concept is shown in Fig. 13a. Figure 13b shows computationally predicted biomarker transport within the nanoholes for in-hole average fluid velocities of 1 pm/s and 1 cm/s (as indicated). Reaction rate constants characteristic of surface-based antibody-antigen reactions (with reaction rate constant k - 10 /M/s) [69] were applied at the nanohole walls. For the low average velocity, diffusion of the biomarker (with diffusivity D - 4x10 m s ) to the nanohole surface is effectively complete in one diameter. This result reflects the rapid diffusion characteristic of nanoconfinement. For the higher flow rate case, the absorption of the analyte stream is delayed however, over 90% bulk adsorption of analyte is attained with the flow rates and nanohole... 

Johnson S and Zheng W. Recent Progress in the Computational Prediction of Aqueous Solubility and Absorption. AAPSJ2000 8 E27-E40. 

The simultaneous absorption of two gases that react with the solvent at different rates has been studied by Ouwerkerk. The specific system which he selected for analysis was the selective absorption of HjS in the presence of CO2 into amine solutions. This operation is a feature of several commercially important gas purification processes. Bench scale experiments were conducted to collect the necessary pi sico-chemical data. An absorption rate equation was developed for H2S based on the assumption of instantaneous reaction. For CO2 it was found that the rate of absorption into diisopropanolamine (DIPA) solution at low CO2 partial pressures can best be correlated on the l is of a fast pseudo-first-order reaction. A computer program was developed which took into account the competition between H2S and CC>2 when absorbed simultaneously, and the computer predictions were verified by experiments in a pilot scale absorber. Finally, the methodology was employed successfully to design a large commercial plant absorber. 

Drag-drag interactions can be a physical (e.g., changing the pH, which depends on the absorption of these compounds as ketoconazole and glipizide), chemical (e.g., ciprofloxacin is a chelator of cations such as aluminum, magnesium and iron), and biological, which depends on interactions with human proteins. The last type of interaction is of great interest for computational predictions. 

While ejqierimental methods always require sufficient amount of chemicals for the estimation of drag absorption, computational in silico) methods can lead to the prediction of intestinal absorption based on chemical structure, and can thus be used before synthesis of compoimds. In silico predictions could be based both on relatively simple quantitative structure-activity relationships (QSAR) analysis and more complex physiologically based pharmacokinetic and/or pharmacodynamic models. Whichever the approach used for model building, computational methods should be based on experimental data that were obtained for a wide range of structurally diverse compoimds (training set). It should be noted, however, that current in silico methods, are not as reliable as experimental models. 

Use Configuration Interaction to predict the electronic spectra of molecules. The Configuration Interaction wave function computes a ground state plus low lying excited states. You can obtain electronic absorption frequencies from the differences between the energies of the ground state and the excited states. 

Pharmacokinetics—The science of quantitatively predicting the fate (disposition) of an exogenous substance in an organism. Utilizing computational techniques, it provides the means of studying the absorption, distribution, metabolism and excretion of chemicals by the body. 

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