Partition coefficients computation

Mopman, G., Namboodiri, K. and Schochet, M. (1985) Simple method of computing the partition coefficient. /. Comput. Chem., 6, 28—38. 

K and G M Crippen 1986. Atomic Physicochemical Parameters for Three-dimensional Struc-directed Quantitative Structure-Activity Relationships. I. Partition Coefficients as a Measure ydrophobicity. Journal of Computational Chemistry 7 565-577. 

Y Fu and L Lai 1997. A New Atom-Additive Method for Calculating Partition Coefficients. mal of Chemical Information and Computer Science 37 615-621. 

After phase separation, two sets of equations such as those in Table A-1 describe the polymerization but now the interphase transport terms I, must be included which couples the two sets of equations. We assume that an equilibrium partitioning of the monomers is always maintained. Under these conditions, it is possible, following some work of Kilkson (17) on a simpler interfacial nylon polymerization, to express the transfer rates I in terms of the monomer partition coefficients, and the iJolume fraction X. We assume that no interphase transport of any polymer occurs. Thus, from this coupled set of eighteen equations, we can compute the overall conversions in each phase vs. time. We can then go back to the statistical derived equations in Table 1 and predict the average values of the distribution. The overall average values are the sums of those in each phase. 

Two macromolecular computational problems are considered (i) the atomistic modeling of bulk condensed polymer phases and their inherent non-vectorizability, and (ii) the determination of the partition coefficient of polymer chains between bulk solution and cylindrical pores. In connection with the atomistic modeling problem, an algorithm is introduced and discussed (Modified Superbox Algorithm) for the efficient determination of significantly interacting atom pairs in systems with spatially periodic boundaries of the shape of a general parallelepiped (triclinic systems). 

From an analysis of the key properties of compounds in the World Dmg Index the now well accepted Rule-of-5 has been derived [25, 26]. It was concluded that compounds are most Hkely to have poor absorption when MW>500, calculated octanol-water partition coefficient Clog P>5, number of H-bond donors >5 and number of H-bond acceptors >10. Computation of these properties is now available as a simple but efficient ADME screen in commercial software. The Rule-of-5 should be seen as a qualitative absorption/permeabiHty predictor [43], rather than a quantitative predictor [140]. The Rule-of-5 is not predictive for bioavail-abihty as sometimes mistakenly is assumed. An important factor for bioavailabihty in addition to absorption is liver first-pass effect (metaboHsm). The property distribution in drug-related chemical databases has been studied as another approach to understand drug-likeness [141, 142]. 

Livingstone, D. J., Ford, M. G., Huuskonen, J. J., Salt, D. W. Simultaneous prediction of aqueous solubility and octanol/water partition coefficient based on descriptors derived from molecular structure. J. Comput.-Aided Mol. Des. 2001, 15, 741-752. 

Ruelle, P. Universal model based on the mobile order and disorder theory for predicting lipophilidty and partition coefficients in all mutually immiscible two-phase liquid systems. Chem. Inf. Comput. Sci. 2000, 40, 681-700. 

Klopman, G., Iroff, L. D. Calculation of partition coefficients by the charge density method. J. Comput. Chem. 1981, 2,157-160. 

Gombar, V. K., Enslein, K. Assessment of n-octanol/water partition coefficient when is the assessment reliable. J. Chem. Inf Comput. Sci. 1996, 36, 1127-1134. 

While there are plenty of methods to predict 1-octanol-water partition coefficients, logP (see Chapters 14 and 15), the number of approaches to predict 1-octanol-water distribution coefficients is rather limited. This is due to a lower availability of log D data and, in general, higher computational complexity of this property compared to that of log P. The approaches to predict log D can be roughly classified into two major categories (i) calculation of log D at an arbitrary pH and (ii) calculation of log D at a fixed pH. 

The pH-metric technique used to determine partition coefficients was first used in the 1950s in solvent extraction of metal complexes [280-282], but it is in pharmaceutical research that it is most widely used thanks to the recent development of a fully automated and computer-controlled apparatus [125,283]. The potentiometric approach has been validated in various solvent systems [284-287], and it has become a relevant and expanding experimental technique to obtain lipophilicity descriptors [257,287-289]. 

Cieplak, P., Caldwell, J. W., Kollman, P. A., Molecular mechanical models for organic and biological systems going beyond the atom centered two body additive approximation aqueous solution free energies of methanol and IV-methyl acetamide, nucleic acid base, and amide hydrogen bonding and chloroform/water partition coefficients of the nucleic acid bases, J. Comput. Chem. 2001, 22, 1048-1057... 

McFarland et al. recently [1] published the results of studies carried out on 22 crystalline compounds. Their water solubilities were determined using pSOL [21], an automated instrument employing the pH-metric method described by Avdeef and coworkers [22]. This technique assures that it is the thermodynamic equilibrium solubility that is measured. While only ionizable compounds can be determined by this method, their solubilities are expressed as the molarity of the unionized molecular species, the intrinsic solubility, SQ. This avoids confusion about a compound s overall solubility dependence on pH. Thus, S0, is analogous to P, the octanol/water partition coefficient in both situations, the ionized species are implicitly factored out. In order to use pSOL, one must have knowledge of the various pKas involved therefore, in principle, one can compute the total solubility of a compound over an entire pH range. However, the intrinsic solubility will be our focus here. There was one zwitterionic compound in this dataset. To obtain best results, this compound was formulated as the zwitterion rather than the neutral form in the HYBOT [23] calculations. 

Katritzky, A. R., Wang, Y., Sild, S., Tamm, T., QSPR studies on vapor pressure, aqueous solubility, and the prediction of water-air partition coefficients, J. Chem. Inf. Comput. Sci. 1998, 38, 720-725. 

The genesis of in silico oral bioavailability predictions can be traced back to Lip-inski s Rule of Five and others qualitative attempts to describe drug-like molecules [13-15]. These processes are useful primarily as a qualitative tool in the early stage library design and in the candidate selection. Despite its large number of falsepositive results, Lipinski s Rule of Five has come into wide use as a qualitative tool to help the chemist design bioavailable compounds. It was concluded that compounds are most likely to have poor absorption when the molecular weight is >500, the calculated octan-l-ol/water partition coefficient (c log P) is >5, the number of H-bond donors is >5, and the number of H-bond acceptors is >10. Computation of these properties is now available as an ADME (absorption, distribution, metabolism, excretion) screen in commercial software such as Tsar (from Accelrys). The rule-of-5 should be seen as a qualitative, rather than quantitative, predictor of absorption and permeability [16, 17]. 

Absorption, in general, is treated as a physicochemical transport process based on computations of logP (the octanol/water partition coefficient) and solubility governed by factors such as polar surface area on the molecule. It is conceivable that SNPs in drug transporter genes will affect the pharmacokinetic properties of compounds and, therefore, these may have to be taken into consideration in the design process. 

There is a continuing effort to extend the long-established concept of quantitative-structure-activity-relationships (QSARs) to quantitative-structure-property relationships (QSPRs) to compute all relevant environmental physical-chemical properties (such as aqueous solubility, vapor pressure, octanol-water partition coefficient, Henry s law constant, bioconcentration factor (BCF), sorption coefficient and environmental reaction rate constants from molecular structure). 

Chou, J.T., Jurs, PC. (1979) Computation of partition coefficients from molecular structures by a fragment addition method. In Physical Chemical Properties of Drugs. Medical Research Series, Vol. 10, Yalkowsky, S.H., Sindula, A.A., Valvani, S.C., Editors, Marcel Dekker, New York. pp. 163-199. 

Whilst this Chapter is primarily concerned with the methods of determining the free energies of tautomeric or ionisation equilibria via computer simulation of free energy differences, many of the issues raised relate also to the determination of other molecular properties upon which behaviour of the molecule within the body may depend, such as the redox potential or the partition coefficient.6 In the next section, we shall give a brief explanation of the methods used to calculate these free energy differences -namely the use of a thermodynamic cycle in conjunction with ab initio and free energy perturbation (FEP) methods. This enables an explicit representation of the solvent environment to be used. In depth descriptions of the various simulation protocols, or the accuracy limiting factors of the simulations and methods of validation, have not been included. These are... 

Ghose, A. K. and Crippen, G. M. (1986) Atomic physiochemical parameters for three-dimensional structure-directed quantitative structure-activity relationships I. Partition coefficients as a measure of hydrophobicity. J. Comput. Chem. 4, 565-577. 

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