Derivatives activities were selected for the study.


                         Derivatives of an
anti-tuberculosis agent PA-824 were used for this study. PA-824 is a
2-nitroimidazooxazine prodrug currently in Phase II clinical trial for
tuberculosis therapy. This releases toxic reactive nitrogen species which may
be responsible for its anti-mycobacterial activity. There are no published
reports of mammalian enzymes bio activating this prodrug. (3)

structure of PA-824 was retrieved from Pub Chem Database. The derivatives were
drawn using the drawing tool Marvin Sketch. The 3D structure of the drug target
protein 420-dependent glucose -6- phosphate dehydrogenase (FGD1) was retrieved
from the RCSB Protein Data Bank (PDB id: 3C8N with resolution 1.90 A). Energy
minimization of 3C8N protein was done by using Swiss PDB Viewer. (9)

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structure of apo-FGD1 from Mycobacterium tuberculosis.


are the 2D structure of the 20 derivatives under investigation;





























 Physiochemical properties for these
derivatives were taken from the drawing tool Chemsketch, Power MV. The
biological activities were obtained from the online tool PASS INET.In order to
carried out docking simulation, experiments were conducted to find out the
molecule which will lock the protein to the most effective manner using Auto
dock. The pharmacokinetic properties were predicted by OSIRIS Property Explorer
and Molinspiration. Software Lazar was used for toxicity prediction. Software
excel provided with MS office 2010 was used for analysis of experimental
results and graphical representation.




           Chemical drawing and visualization
of the structures under investigation were carried out by using the drawing
tool Marvin Sketch.


biological activities of these compounds were obtained from an online tool PASS
online (Prediction of Activity Spectra of Substances). Antitubercular,
Antimycobacterial, Antibacterial activities were selected for the study. These
activities showed a probability greater than 0.6 for these derivatives


          Theoretical molecular descriptors
were calculated using Chemsketch and Power MV. The chemical structures drawn
and the corresponding descriptors were obtained. The molecular descriptors that
were taken into account include; Molecular Weight (MW) (g/mol), Molar Volume,
Number of Hydrogen bond acceptors, Number of Hydrogen bond donors, Number of
rotatable bonds, Molar refractivity, Density, Parachor, logP, Polarizability,
Polar surface area and Surface tension.

Molar volume

molar volume, symbol Vm, is the volume occupied by one mole of a substance
(chemical element or chemical compound) at a given temperature and pressure. It
is equal to the molar mass (M) divided by the mass density (?). It has the SI
unit cubic metres per mole (m3/mol),1 although it is more practical to use
the units cubic decimetres per mole (dm3/mol) for gases and cubic centimetres
per mole (cm3/mol) for liquids and solids.

Polar surface area

polar surface area (PSA) of a molecule is the surface sum over all polar atoms,
primarily oxygen and nitrogen, also including their attached hydrogens.

Hydrogen bond acceptor and donor

order for a hydrogen bond to occur there must be both a hydrogen donor and an
acceptor present. The donor in a hydrogen bond is the atom to which the
hydrogen atom participating in the hydrogen bond is covalently bonded, and is usually
a strongly electronegative atom such as N, O, or F. The hydrogen acceptor is
the neighbouring electronegative ion or molecule, and must possess a lone
electron pair in order to form a hydrogen bond.

Surface tension

is a contractive tendency of the surface of a liquid that allows it to resist
an external force


is a scientific quantity defined according to the formula:

= ?1/4 * M / d, where ?1/4 is the fourth root of surface tension, M is the
molar mass, and d is the density. Parachor has been used in solving various
structural problems.


allows us to better understand the interactions between nonpolar atoms and
molecules and other electrically charged species, such as ions or polar
molecules with dipole moment.

Molar refractivity, A

is a measure of the total Polarizability of a mole of a substance and is
dependent on the temperature, the index of refraction, and the pressure.


           QSAR analysis was done in order to
correlate the molecular descriptors with biological activity. Microsoft Excel
2010 was used to develop the regression analysis for the QSAR studies. Multiple
regression analysis was performed between antitubercular, Antimycobacterial and
antibacterial activities against all the physiochemical properties. The
accuracies of the models were predicted by the r2 values. 


         The 3D structure with resolution 1.90
A of 420-dependent glucose-6-phosphate dehydrogenase (FGD1) was retrieved from
the Protein Data Bank (PDB id: 3C8N). Energy minimization of 3C8N protein was
done by using Swiss PDB Viewer.

.mol formats of the structures drawn from Marvin Sketch were converted into
.pdb format using the software Open Babel GUI.


           The protein-ligand docking
calculations were done using Autodock. It is an open source molecular modelling
simulation software. The Lamarckian Genetic Algorithm (LGA) was chosen to
search for the best conformers. During the docking process, a maximum of 10
conformers was considered for each compound. The Autodock scoring function is a
subset of the AMBER force fields that treats molecule using the United Atom


            Bio-safety of the developed new
molecules was also explored. Pharmacodynamic and pharmacokinetic behaviour of
the developed molecules was studied over insilico tools like ‘OSIRIS Property
Explorer’ and ‘Molinspiration’ to understand the behaviour of newly developed
molecules inside the human body. Toxicity studies were carried out using LAZAR
Toxicity Prediction.


web based software was used to obtain parameter such as MiLogP, TPSA, drug
likeness. MiLogP is calculated by the methodology developed by Molinspiration
as a sum of fragment based contributions and correction factors. MiLog P
parameter is used to check good permeability across the cell membrane. TPSA is
related to hydrogen bonding potential of compound .Calculation of volume
developed at Molinspiration is based on group contributors. Number of rotatable
bonds measures molecular flexibility. It is a very good descriptor of
absorption and bioavailability of drugs. Through drug likeness datas of
molecule, it can be checked molecular properties and structure feature in
respect to known drugs.

    Bioactivity of the drug can be checked by
calculating the activity score of GPCR ligand, ion channel modulator, nuclear
receptor legend, kinase inhibitor, protease inhibitor, enzyme inhibitor. All
the parameters were checked with the help of software Molinspiration
drug-likeness score online ( Calculated drug likeness
score of each compounds and compared with the specific activity of each
compound, and the results were compared with standard drug. For organic
molecules the probability is if the bioactivity score is (>0), then it is
active, if (-5.0-0.0) then moderately active, if (< -5.0) then inactive. ·        OSIRIS Property Explorer Osiris can calculate lipophilicity, expressed as CLogP, solubility in water, expressed as logS, molecular weight, drug-likeness indices and drug scores. Moreover, the toxicological properties of the compounds may be shown. Prediction results are valued and colour coded. Properties with high risks of undesired effects like mutagenicity or a poor intestinal absorption are shown in red. Whereas a green colour indicates drug-confirm behaviour. Ø LIPINSKI'S RULE Drug likenesses of these compounds were evaluated on the basis of Lipinski's rule of five.        Lipinski's rule of five also known as the Pfizer's rule of five or simply the Rule of five (RO5) is a rule of thumb to evaluate drug likeness or determine if a chemical compound with a certain pharmacological or biological activity has properties that would make it a likely orally active drug in humans. The rule was formulated by Christopher A. Lipinski in 1997. The rule describes molecular properties important for a drug's pharmacokinetics in the human body, including their absorption, distribution, metabolism and excretion (ADME). The rule is important for drug development where a pharmacologically active lead structure is optimized stepwise for increased activity and selectivity, as well as drug like properties. The modification of the molecular structure often leads to drugs with higher molecular weight, more rings, more rotatable bond and a higher lipophilicity. Physicochemical parameters play a vital role in generation and escalation of bioactivity of chemical entity Lipinski's rule states:     Not more than 5 hydrogen bond donors (nitrogen or oxygen atoms with one or more hydrogen atoms)     Not more than 10 hydrogen bond acceptors (nitrogen or oxygen atoms)     A molecular mass less than 500 Daltons     An octanol-water partition coefficient log P not greater than 5     No more than one number of violations. (10, 11)