molecular descriptor such as AMR or molar refracrtivity is an important
parameter because when a radiation with infinite wavelength, molar refractivity
represents the real volume of a molecule but also to the London dispersive
forces that act in between drug-receptor interaction, Ghose–Crippen is the
SPARTAN default method of calculating log P. This method depends only on the
connectivity of the molecule, and it is independent of the wavefunction (i.e.,
one will get the same results for semi-empirical, HF, and DFT methods but this
depends on how the molecule is drawn/connected). The Ghose–Crippen model is
parameterized for 110 atom types, including common bonds of H, C, N, O, S, and
the halogens. Avoiding correction factors was obtained evaluating the
hydrophobicity on an individual atom basis, accounting for the undeniable
intramolecular interactions by employing a large number of atom types, as we
know the amount of ionization potential will increase with each removal of
electron from the atom; it occurs due to the increasing order in the firmness
of the remaining positive charged atom with each other, here in the QSAR model
ionization potential must be in decreasing order for the better activity
against small lung cancer cell line and in case of Radial distribution function
- 100 / weighted by relative mass, which was a descriptors
are based on the distance distribution in the molecule, which was interpreted
as the probability distribution of finding an atom in a spherical volume of
radius R. This descriptor
encoded with 3D chemical structure weighted by polarizability,
electronegativity and molar volume as well as it correlates with the in?uence
of the electronic structure and state in electroluminescence [25, 26]. There were some external validation
parameters without scaling and after scaling. The external validation
parameters without scaling were r^2 :0.61064, r0^2 :-1.63343, reverse
r0^2:0.4828,rm^2(test) :-0.30411,reverse rm^2(test) :0.39231, average
rm^2(test) :0.0441, delta rm^2(test) :0.69642, rmsep:1.12933, rpred^2
:-0.36387, Q2f1 :-0.36387, Q2f2 :-2.37916 and after scaling were rm^2(test)
:0.13331, reverse rm^2(test) :0.4531, average rm^2(test) :0.2932, delta
rm^2(test) :0.31978. Then the model was validated through Golbraikh and Tropsha
acceptable model criteria's as Q^2:0.77691 Passed (Threshold value
Q^2>0.5),r^2: 0.61064 Passed (Threshold value r^2>0.6, |r0^2-r'0^2|:
0.11623 Passed with Threshold value |r0^2-r'0^2|<0.3). As well as the
greater q2 value was suggested the model sustainability. Applicabilty domain
was identified by Euclidean and Mahalanobis Distance Method and all the results
were diagrammatized at Table 4, 5, 6, 7.
The data from Euclidean distance method was confirmed that cyclodisone from
training set and mitozolomide from test set were outside the applicability
domain. The outcomes from mahalanobis distance was suggested that all the data
from training set were normally distributed within 0.197387 to 3.05896 and in
case of test set this distribution was occurred in between most of the
molecules were inside the 0.741646 to 3.05323. Finally calculate the observed
and predicted IC50 value and diagrammatized in Table 8 and Figure 1 was showed
that all the points were merely overlapped with each other.
It can be easily concluded that if in future we have to develop a
small molecule working against small lung cancer cell line, the developed QSAR
model will work as a great predictor of its activity with any chemical scaffold
and by which we can produce a good molecule with higher activity profile.
is no conflict of interest associated with the authors of this paper.
of the authors is highly acknowledged towards Prof. Veerma Ram, Head of the
Department SBSPGI for his unconditional support and well beings.
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