470
N. Ya. Golovenko et al.
between human and rat absorption. The linear relationship between human and rat
absorption forced through the origin, as determined by least squares regression. It
is suggested that the absorption in rats could be used as an alternative method to
human absorption in preclinical oral absorption studies.
Using Abraham descriptors, described in the same paper, the authors report
R
2
= 0.74 when trained on the whole set. However, the authors also highlight the
fact that the training set is heavily biased towards well-absorbed compounds (over
30 % absorbed). Yoshida and Topliss [36] proposed a classification model to predict
bioavailability by using a dataset of 272 drugs, fingerprints and pharmacokinetics
descriptors, with help of a method named ORMUCS (ordered multicategorical classification method using the simplex technique) This approach, after dividing the
bioavailability data in four classes, allowed the authors to get a correct classification
rate of 71 % for the training set and 60 % for the 40 compounds included in the test
set. A quantitative structure-bioavailability relationship model was developed by
Andrews et al. on a dataset including 591 compounds [37]. A stepwise regression
procedure was used to relate oral bioavailability in humans and structural fragments
in drugs. Compared to the Lipinski’s “rule of five”, this model allowed to reduce the
amount of false negatives and positives. Poor bioavailability predictions were false
in only 3 % of cases, but 53 % of predictions of high bioavailability were incorrect.
In addition to the molecular properties discussed by Lipinski, the relation of
other properties to oral bioavailability was also extensively investigated. Navia et
al. has postulated the desirability of molecular flexibility for membrane permeation
[38]. Hirschmann et al. has focused on the undesirable property of water complexation by amide bonds as a negative factor for oral bioavailability [39].The negative
impact of a high polar surface area on intestinal absorption is recognized [40, 41].
Membrane permeation is recognized as a common requirement for oral bioavailability in the absence of active transport, and failure to achieve this usually results
in poor oral bioavailability.
Similar observations were made by others in an effort to define descriptors that
can provide a rationale for establishing qualitative, semiquantitative, and quantitative structure-absorption relationship models [28, 31, 32]. The dependence of
human intestinal absorption on the readily accessible physico-chemical properties
like lipophilicity, molecular size, hydrogen bonding capacity, PSA, and number of
free rotatable bonds has been demonstrated. Identification of these basic physicochemical properties as determinants is consistent with notions regarding the ability
of small organic molecules to pass through lipid bilayer membranes.
14.4.1 QSAR Analysis Using Simplex Representation
of Molecular Structure
Historically, the Simplex approach was developed as a method for the characterization of chirality [42] and only later it was used in QSAR analysis [43]. In the frameworks of Simplex representation of molecular structure (SiRMS) any molecule can
N. Ya. Golovenko et al.
between human and rat absorption. The linear relationship between human and rat
absorption forced through the origin, as determined by least squares regression. It
is suggested that the absorption in rats could be used as an alternative method to
human absorption in preclinical oral absorption studies.
Using Abraham descriptors, described in the same paper, the authors report
R
2
= 0.74 when trained on the whole set. However, the authors also highlight the
fact that the training set is heavily biased towards well-absorbed compounds (over
30 % absorbed). Yoshida and Topliss [36] proposed a classification model to predict
bioavailability by using a dataset of 272 drugs, fingerprints and pharmacokinetics
descriptors, with help of a method named ORMUCS (ordered multicategorical classification method using the simplex technique) This approach, after dividing the
bioavailability data in four classes, allowed the authors to get a correct classification
rate of 71 % for the training set and 60 % for the 40 compounds included in the test
set. A quantitative structure-bioavailability relationship model was developed by
Andrews et al. on a dataset including 591 compounds [37]. A stepwise regression
procedure was used to relate oral bioavailability in humans and structural fragments
in drugs. Compared to the Lipinski’s “rule of five”, this model allowed to reduce the
amount of false negatives and positives. Poor bioavailability predictions were false
in only 3 % of cases, but 53 % of predictions of high bioavailability were incorrect.
In addition to the molecular properties discussed by Lipinski, the relation of
other properties to oral bioavailability was also extensively investigated. Navia et
al. has postulated the desirability of molecular flexibility for membrane permeation
[38]. Hirschmann et al. has focused on the undesirable property of water complexation by amide bonds as a negative factor for oral bioavailability [39].The negative
impact of a high polar surface area on intestinal absorption is recognized [40, 41].
Membrane permeation is recognized as a common requirement for oral bioavailability in the absence of active transport, and failure to achieve this usually results
in poor oral bioavailability.
Similar observations were made by others in an effort to define descriptors that
can provide a rationale for establishing qualitative, semiquantitative, and quantitative structure-absorption relationship models [28, 31, 32]. The dependence of
human intestinal absorption on the readily accessible physico-chemical properties
like lipophilicity, molecular size, hydrogen bonding capacity, PSA, and number of
free rotatable bonds has been demonstrated. Identification of these basic physicochemical properties as determinants is consistent with notions regarding the ability
of small organic molecules to pass through lipid bilayer membranes.
14.4.1 QSAR Analysis Using Simplex Representation
of Molecular Structure
Historically, the Simplex approach was developed as a method for the characterization of chirality [42] and only later it was used in QSAR analysis [43]. In the frameworks of Simplex representation of molecular structure (SiRMS) any molecule can