LITERATURE REVIEWLITERATURE REVIEWIt has been nearly 40 years since the quantitative structure-activity relationship (QSAR) paradigm first found its way into the practice of agro chemistry, pharmaceutical chemistry, toxicology, and eventually most facets of chemistry. Its attributed to the strength of its initial postulate that activity was a function of structure. It is described by electronic attributes, hydrophobicity, and steric properties. Further rapid and extensive development in methodologies and computational techniques that have ensued to describe and refine the many variables and approaches. The overall goals of QSAR retain their original essence and remain focused on the predictive ability of the approach and its receptiveness to mechanistic interpretation. It is well recognized that QSAR is one of the best tools for in silico (using silicon-based computer technologies to perform simulations, modeling and experiments) drug design. There is a dedicated quest for robust QSAR models. Origin of QSAR is from the field of toxicology (1).It was noted by Cros in 1863 that toxicity of substances is governed by their properties, which in turn are determined by their chemical structure. This showed interrelationship exists between structure, properties, and toxicity (2). Structure Activity Relationships (SAR) studies have been published since 1868, when Crum-Brown & Fraser stipulated the idea that the physiological action of a substance in a certain biological system is a function of its chemical constitution (3).Meyer and Overton suggested that the narcotic (depressant) action of a group of organic compounds paralleled their olive oil/water partition coefficients leading to QSAR concepts in field of drugs discovery (4).Use of various physical properties as a descriptor for QSAR study begins with different type of constants and their equation. so, In 1937 Louis P. Hammett had first introduced the concept of Hammett constant They determine the effect of a substituent in the Meta or Para position of the benzene ring upon the rate or upon the equilibrium of a reaction in which the reacting group is in a side chain attached to the ring (5). After the introduction of Hammett constant a new constant has derived by Hantzch and Fujita (6) in 1964. They first introduced the new substituent constant of derived from partition coefficient. The partition coefficient between 1-octanol and water has been determined for 203 mono- and disubstituted benzenes. After that a new researcher Taft (7) devised a way for separating polar, steric, and resonance effects, introducing the first steric parameter ES.The contributions of Hammett and Taft led to the development of the QSAR paradigm by Hansch and Fujita, which combined the hydrophobic constants with Hammetts electronic constants to yield the Hansch Equation (8). In1970 Adamson and coworkers were the first to apply Fragment Descriptor using multiple linear regression analysis (MLR). They find correlation with some biological activities, physiochemical properties and reactivity (9). After the establishment and development of different constants and physiochemical descriptors, researchers find different QSAR methologies as well as approaches. Further development in QSAR a CoMFA (comparative molecular field analysis) method of 3D QSAR was introduced in 1988 by Cramer (10) in which related the shape-dependent steric and electrostatic fields for molecules to their biological activity and also Introduced a new method of data analysis: PLS (Partial Least Squares) and cross-validation, to develop models for activity predictions. Many QSAR studies has been reported for pyridine derivatives in this sequence Yutaka Kawashima et al. in 1993 published a QSAR study using fuzzy adaptive least square method for antihypertensive 1, 4 dihydro pyridine having 2 nitro-oxy alkyl moieties at the 3, 5 positions (11).With the further development of different QSAR methologies A CoMSIA method of 3D QSAR analysis was introduced by Klebe (12) in 1994 , in which using a common probe atom, similarity indices are calculated at regularly spaced grid points for the pre aligned molecules. Later on, Chris L. Waller & Steven D. Wyrick (13) in 1994 used lipophilic and dipole moment characteristics of the molecules as physical descriptor variables in the regression equation for QSAR study. In 1994 Chung and Woo et al. introduced the new antagonist known as Platelet activating factor (PAF) for heterocyclic lipids. Their study shows that PAF is a very powerful antagonist (14). Ki hwan kim et al. developed a new lateral validation equation. This new QSAR equation laterally correlates to other various QSAR equations that support the new equation. This method was originally utilized in the classical QSAR field of physical organic chemistry and has recently been extended to the field of biological sciences. The possibility of supporting a new 3D-QSAR by lateral validation is investigated in this study using one of the most often used 3D-QSAR methodologies, Comparative Molecular Field Analysis (CoMFA) (15).Kaiser et al. in 1996 represent a brief review on microbial metabolism of pyridine. they also discussed the metabolism activity of quinoline ,acridine and their derivatives under aerobic and anaerobic conditions, with emphasis on metabolic pathways (16). In 1996 Kearsley et al. describe alternative forms of the atom pair and topological torsion descriptors that use physiochemical atom types. These types are based on binding property class, atomic log P contribution, and partial atomic charges (17). 1996 afterward in 1997 Pourmorad, Shaifee et al. gave the synthesis and calcium channel antagonist activity of 4- imidazolyl -1,4 dihydropyridine .they concluded the symmetrical esters showed that increasing the length of methylene chain of ester more than 3 units decrease calcium channel antagonist activity (18). Quantitative structure activity relationship study is based on structure/ activity as well as required large or small datasets. So, in 1997 A new Genetic Algorithm (GA) strategies for variable selection of QSAR study had been reported by Hasegawa, Miyashita et al. In these study they use GA based PLS analysis and found high internal predictivity for small set of datasets. The GAPLS (GA-based PLS) program is written in FORTRAN language and is running on VAX workstation (19). After the development of 3D QSAR a new method 4D QSAR introduced by Christian D. P. Klein and A. J. Hopfinger in 1998 these 4D-QSAR methods are employed on a set with anti-arrhythmic activity. In their 4d QSAR study molecules are built using CHEM-2 LAB, Semi-empirical calculations carried by MOPAC 6.0(22) package, molecular simulation dynamic package MOLSIM 3.0(23) were used for conformation and energy optimization. Molecular dynamics simulation provided the set of conformation of datasets, which were analyzed using Partial least regression in combination with the genetic function approximation algorithm to construct QSAR model (20).In 1999 R. Katritzky et al.gave overview on the development of QSPR/QSAR equations using various descriptor mining techniques and multilinear regression analysis in the framework of program CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis). The CODESSA software accepts various standard structures formats as input: MDL .mol file; Hyperchem .hin file; SYBYL .mol file; MOPAC/AMPAC regular .out file. In their paper the QSAR and QSPR models derived for eighteen molecular activities and properties (21).In the field of receptor based docking Burden and Winkler in 1999 introduced the concept of a virtual receptor, and this is illustrated by the results of screening a database of 40, 000 molecules. This concept gave a new QSAR model applied to structure activity mapping and combinatorial chemistry (22). Soon after on , in 1999 An-Hu Li et al. synthesized 3,5-Diacyl-2,4-Dialkylpyridine Derivatives and performed QSAR analysis using COMFA approach and partial least square regression studying receptor docking for selective A3 Adenosine Receptor Antagonists activity (23). Further development carried by Ju rgen Schleifer in 1999 and investigated a 3D pseudo receptor modeling approach for stereo selectivity characterization of 1, 4 dihydropyridine binding site at L-type calcium channel in the resting state (24). In the year of 1999 authors was applied only one approach at a time but by Tatiana Netzeva et al. in 2000 showed the importance of the lipophilicity in case of valporic acid for anticonvulsant activity using 2D and 3D QSAR approaches.for 2D qsar analysis Log P and pKa values were obtained with ACD/Labs computer program. Molecular modeling, conformational analysis, quantum mechanics, mechanical optimization and electronic descriptor calculation as well as steric and electrostatic field generation for 3D QSAR and statistical evaluation of the models were performed with the Chem-X computer program (25).Yoshida and topless et al. observed quantitative structure-bioavailability relationship of 232 structurally diverse drugs to evaluate the feasibility of constructing a predictive model. They developed different models for the human oral bioavailability of prospective new medicinal agents in 2000 (26). In 2001 researchers applied principal component analysis neural network algorithm with Hologram Quantitative Structure Activity Relationship (HQSAR) on a set of 1, 4 dihydro pyridine by Viswanadhan and Weinstein. They define that the HQSAR more straight forward and easier as compared to multiple linear regression (27).After that, Yashri and Hart-sough et al. in 2001 gave new combined method for the development of a novel variable selection and neural network model building technique called ARQeDES. The method was successfully applied to both artificial and real biological data sets (28). Many more developments were reported for the synthesis of pyridine derivatives in these sequences in 2001 by Stephanie and Rao et al. gave the synthesis and Evaluation of a New Class of Nifedipine Analogs with T-Type Calcium Channel Blocking Activity (29). Kharkar Prashant et al. in 2002 for developing Three-Dimensional Quantitative Structure-Activity Relationship of 1, 4-Dihydropyridines as Antitubercular Agents (30).In 2002 Victor E. Kuzmin et al. used 4D QSAR approach for the molecular structure of macro cyclic pyridinophanes for anticancer and antiviral activity. This novel 4D QSAR approach is based on simplex representation of molecular structure with PLS regression for developing QSAR models (31).In 2002 by Zefirov, Palyulin et al. gave a new Fragmental approach, this was employed through fragmental descriptors for QSPR/QSAR .They are applicable for modeling of a wide range of properties and biological activities very often providing good predictive models and interpretable results (32).Later on, in 2002 Xing and Glen gave a novel methods for predicting logP, pKa, and logD values using data sets (592 molecules for logP and 1029 for pKa) containing a wide range of molecular structures. logP (based on polarizability and atom charge) and pKa (based on a novel tree structured fingerprint) (33).Sheridan in 2002 enhance the use of biological activity for large data sets , in these order he written a method that extracts one-to-one replacements of chemical groups in pairs of drug-like molecules with the same biological activity .they also counts the frequency of the replacements in a large collection of such molecules (34).Many achievements could be gained by researchers in QSAR methods and descriptors in the previous year after that in 2003 Zamponi and Nat ale et al. performed a unique structure activity relationship for 4- isoxazolyl -1,4 dihydropyridines .they performed this experiment through patch clamp analysis (35).The continued progress of descriptors could be forwarded by Oliferenko, Rogers Zefirov et al. in 2003 through the derivation of new HB descriptors for hydrogen bonding and fluid phase equilibria. These descriptors also functions in ligand docking and in Absorption, Distribution, Metabolism, Excretion (ADME) evaluations (36).In 2003 Golbraikh and Tropsha et al. has reported that topological chirality descriptors can be successfully used to generate 2D QSAR models for data sets containing stereo isomers. In these QSAR study descriptors obtained using Molconn-Z program, predictive ability of a model obtained using MATLAB, RS configurations for chiral atoms were assigned using a SYBYL Programming Language (SPL) script (37).In 2003 Hansch and Hoek-man et al. explained the importance of electronic effects in their role in the QSAR of chemical-biological interactions. They also discussed the polarizability effects in ligand-substrate interactions in terms of molecular polarizability (MR) and NVE (number of valence electrons) using additive values for valence electrons (38).Arakawa et al. In 2003 investigated and proposed a novel molecular alignment method with the Hopfield neural network (HNN). They successfully obtained a robust 3D QSAR model for 12 pairs of enzyme inhibitors (39). In 2003 Alberto and Goobi describes Directed Sphere Exclusion (DISE), a modification of the Sphere Exclusion algorithm, which retains all positive properties of the Sphere Exclusion algorithm but generates a more even distribution of the selected compounds in the chemical space (40).In 2003 Herve et al. describe a Probe feature selection method that can be applied directly to models that are linear with respect to their parameters, and indirectly to others. It is independent of the target machine. This method is very useful for those who cannot expert in statics (41). Bleck-mann and Miler et al. in 2003 investigated the relation between the structure of epothilones (a new class of anti-tumor agents) and their potential to influence the tubulin-microtubule equilibrium (42). Du and Chou et al. in 2004 reported a 2D QSAR study to Liver alcohol Dehydrogenase (LADH) of molecular family and pyrazole derivatives. They used quantum chemical and structure-based technique heuristic molecular lipophilicity potential (HMLP) in the liver alcohol dehydrogenase (LADH) for pyrazole derivatives (43).For the further development of QSAR a new descriptor could be proposed by Stanton et al. in 2004 developed a new series of 25 whole-molecule molecular structure descriptors. The new descriptors are termed Hydrophobic Surface Area, or HSA descriptors. This descriptor designed to capture information regarding the structural features responsible for hydrophobic and hydrophilic intermolecular interactions (44). In progress of descriptors the Marius Olaha et al. in their paper, An automated PLS search for biologically relevant QSAR descriptors studied two major categories of descriptors: the 2D descriptors, and the 1D descriptors, based on chemical substructures in 2004 (45).many statistical methods could be mentioned by different authors in these sequence , In 2004 Heloisa de Mello et al. used multiple regression and non linear parabolic relationship for QSAR study on antileishmanial Pyrazolo pyridine Derivatives (46). Later on, In 2004 Abbas shaffei et al. diagnosed anticonvulsant activity as well as synthesized some 1, 4 dihydropyridine derivatives having nitro-imidazol moiety. They analyzed anticonvulsant activity on mice. They observed that new synthesized dihydropyridine derivatives are more potent than reference drug (47). In 2005 Matheus P. Freitas and Jose A. Martins established a simple quantitative structureactivity relationship (QSAR) method of analysis used to predict biological activity for co generic series of compounds. This method is based on the application of bilinear or multilinear partial least squares regression to a data set, which is a binary matrix representing the various substituents of a framework (48).Abilash Thakur in 2005 reported a QSAR study on benzenesulfonamide dissociation constant pKa made using the physicochemical parameter surface tension (ST). The regression analysis has shown that even in mono-parametric regression this physicochemical parameter gave significant results (49). Later on, In 2005 Gieleciak, Polanski et al. compare the results of Comparative molecular field analysis (CoMFA) and Comparative Molecular Surface Analysis (CoMSA), a 3D QSAR method. They show that a sector CoMSA formalism enables an analysis of the biological activity that is more directly related to the molecular shape and individual molecular functionalities than the traditional uniform and directionless CoMFA field (50).Fabrizio Manetti et al. In 2005 synthesized pyrazolo [3, 4 b] pyridines and developed a new 3D QSAR approach using partial least component analysis for potent and selective inhibitors of A1 adenosine receptors method (51).Dervarics et al. in 2006 introduced a newly devised chirality -sensitive flexibility (CSF) descriptor, which is based on the distance between a pharmacophore point and a plane defined by three pharmacophore points. These descriptors are used for 3+3D QSAR (52).In 2005 Gramatica et al. they compare different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals in Pimephales promelas (Fathead Minnow).they applied multiple linear regression based on theoretical descriptor. For QSAR modeling, descriptors were selected by the Genetic Algorithm-Variable Subset Selection procedure. They verified the effectiveness of Genetic Algorithms as a fast and efficient procedure to select (not by chance)significant variables to manage complex systems (53).Hammeteja et al. In 2005 evaluated three different factor selection procedures including Eigen value ranking, correlation ranking, and genetic algorithm .PC-ANN modeling method is applied to predict the carcinogenic activity of 735 drugs using 1350 theoretically derived descriptors. They found that both genetic algorithm and correlation ranking resulted in more generalized models. They concluded that the correlation ranking procedure is much simpler than GA (54).A study by P Jain et al. in 2005 subjected a series of DHFR analogs of 2,4-diaminopyrido[2,3-d] pyrimidines and 2,4-diaminopyrrolo [2,3-d] pyrimidines to quantitative structure-activity relationship analysis. The results showed that the electronic properties, energy of lowest non occupied molecular orbital (LUMO) and Z-component of dipole moment (DPL3) of the molecule could be explored to design the potent DHFR inhibitors (55)Huabei Zhang et al. reported two three-dimensional QSAR techniques and one two-dimensional QSAR technique were used to correlate the molecular structure with the biological activity of 64 analogues of 3-pyridyl ethers.(56) In 2006 Shuxing Zhang et al. developed a novel automated lazy learning quantitative structure-activity relationship (ALL-QSAR) modeling approach based on the lazy learning theory. ALL-QSAR modeling approach gave for anticonvulsant activity of chemically diverse functionalized amino acid (FAA) structures. Various approaches used in their study are k-Nearest Neighbors (KNN), Simulated Annealing-Partial Least Squares (SA-PLS), Support Vector Machines (SVM), and the Automated Lazy Learning QSAR (ALL-QSAR) (57). Nazneen Khan et al. in 2006 investigated the relationship between the various physiochemical parameters and antibacterial activity of N-alkyl derivatives of imidazole that may be helpful in development of potent antibacterial agent using both 2D and 3D QSAR approaches. Stepwise Multi Linear Regression (MLR) was used to obtain QSAR equation from calculated descriptors (58).In 2006 Tingjun Houa et al. gave a brief review on many physiochemical descriptors .among all these descriptors authors discussed about one of descriptor known as Abraham descriptor. They concluded that Abraham Descriptor is the simplest way of calculating the hydrogen bonding capacity is to count the number of hydrogen bond donor and acceptor atoms or to count the number of lone pairs of electrons on certain kinds of atoms (59).Zhang et al. in 2006 developed two quantitative pKa prediction models for aliphatic carboxylic acids and alcohols using MLR with empirical atomic inductive descriptors. They demonstrated that pKa has captured the substitutents inductive effect on the acidic center. Therefore it can also be used for QSAR/QSPR studies of reactivity in organic compounds (60).Later on, In 2006 Abraham and Ibrahim et al. had investigated gas to olive oil partition coefficient through linear free energy equation for 218 compounds. The linear free energy Equation shows that olive oil is not very polar as a solvent but is reasonably basic, although with a weaker hydrogen bond base than ethyl acetate or acetone, and has no hydrogen bond acidity (61). In 2007 Gupta et al. developed a QSAR equation using De novo, Hansch approach and Fujita-ban analysis for estrogen analogues (62).Urmila J. Joshi et al. in 2007 reported the development of a QSAR equation relating the ligand binding activity of various literature reported aryl piperazines acting as agonists at the 5-HT1A receptor to their 2D descriptors. Significant equation was generated using MOE 2004.03 and validated subsequently using leave one out and test set prediction methods. The equation revealed the importance of combination of electronic and lipophilic parameters in explaining the observed variance (63).Yangjeh et al. in 2007 developed two new descriptor for non-linear computational neural network. Descriptor has been developed for prediction of acidity constant. These descriptors are used for substituted acetic acids in water (64).Authors used Quantitative Structure Activity relationship (QSAR) for descriptor generation. In 2007 Pattan and Desai et al. synthesized some new derivatives of 1, 4 dihyro pyridine. They evaluate their antihypertensive activity through tail-cuff method over rat. Conformation of newly synthesized compounds was obtained by the results of IR, 1NMR, MASS spectroscopy (65).In 2007 B. Hemmateenejad et al. studied the effects of the structural features of some 4, 5-dichloroimidazolyl-1, 4-dihydro pyridine on their calcium channel antagonist activity, using molecular modeling and quantitative structure activity-relationship analysis. Semi-empirical quantum chemical calculation was used to find the optimum 3-D geometry of the molecules. For molecular modeling chemical structures of the molecules were constructed using HYPERCHEM software (Version 7, Hypercube Inc.), all constructed structure were transform to GUASSIAN 98 program for semi empirical (AM1) calculation. A large number of descriptors were calculated using HYPERCHEM, GUASSIAN 98 and DRAGON software (66).In 2007 R. Sabet et al. studied antimicrobial and antifungal activity of some 3hydroxypyridine-4-one and 3-hydroxypyran-4-one derivatives against a variety of microorganisms. QSAR equation was developed using Multiple Linear Regression (67).In 2007,Piyush Trivedi et al. Reported the effects of the structural features of some 4, 5-dichloroimidazolyl-1, 4-dihydropyridine on their calcium channel antagonist activity, using molecular modeling and Quantitative Structure Activity-Relationship analysis. They used both symmetrical and asymmetrical dihydropyridine derivatives (68). In 2008 A.S.Narute et al. performed Quantitative structure activity relationship study on a series of (substituted 1,2 dihydro)4-thoazolidinones and 2-azetidinones bearing benzo -thiophene nucleus with anti-tubercular activity.QSAR study has been carried out using a combination of various physiochemical descriptors (69).In 2008 further studies were conducted by the same author comparing QSAR models obtained through different chemometric methods, including factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR) and partial least squares combined with genetic algorithm for variable selection (GA-PLS) to establish connections between structural parameters and antimicrobial activity against S. aureus and C. albicans (70). In 2008 a concept came about related to Fragment Descriptors by Alexendar vaskien . It is occupy a special place and represent selected sub graphs of a 2D molecular graph (71).In 2008 Michielan et al. described the application of Molecular Electrostatic Potential auto correlated vectors (autoMEPs). These autoMEPs are used for generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, he was also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM) (72). Sciabola et al. in 2008 used free Wilson QSAR analysis for predicting kinase inhibitors selectivity (73).More than century ago Hantzch developed the preparation method of 1 ,4 dihydro pyridine later than In 2008 S. Sandhu et al. discussed a detailed review on the recent advance on 1,4 dihyro pyridine through Hantzch reaction . Their present review present production procedure, major reaction of current interest, oxidation and reduction of Hantzch 1,4 dihyro pyridine, besides indication of some existing gaps and areas to be developed (74). Further QSAR study conducted on the inhibition of Bacillus subtilis and Salmonella enteritidis by 1, 2, 4-triazoles. For these QSAR study Dimova and jenjic et al. were using several physicochemical descriptors in 2009 (75). Polishchuk and Muratov et al. in 2009 developed a random forest statistical approach for Tetrahymena pyriformis through various 2D descriptors .They explained that the Principle Linear Regression (PLS), K-Nearest Neighbor (KNN), Random Forest (RF) is insignificantly gave better results rather than any separate model (76). In 2009 B.B. Subhudhi et al. synthesized 3, 5 Diethoxycarbonyl-1, 4 dihydro-2, 6 dimethyl- 4-(substituted)- pyridine by Hantzch method and evaluate their antiulcer activity. They accomplished that antiulcer activity of 1, 4 dihyro pyridine enhanced significantly on conjuction with sulfanilamide (77).In 2009,Yas and Joshi et al. Some new derivatives of cynopyridine and cynopyrane has been synthesized .they evaluate their antimicrobial and antitubercular activity towards mycobacterium tuberculosis and other microorganism (78).The medicinal chemistry approach which led to the discovery of a novel pyridine-3-carboxamide series of CB2 receptor agonists was described by Mitchell et al. in 2009 (79). Mahesh Kumar et al. in 2010 a 2-D QSAR model has been developed for correlating activity of 1, 4- dihydropyridines as calcium channel blockers with physicochemical properties (80).In 2010 Su et al. developed a QSAR model based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage. These models are applicable to both virtual screening and limited chemical modification. These studies based on interpretation of the models (81).In 2010 Riadh Hammami and Ismail Fliss gave a detailed review about the progress in the development of computational methods, tools and databases used for organizing and extracting biological meaning from antimicrobial research. They also mentioned that the QSAR modeling is one of the most broadly used chemo informatics approach. This is widely used as a tool for antimicrobial drug discovery (82).In 2011 Mukesh Sharma et al. A 2D QSAR studies were conducted with a series of angiotensin 2 antagonist .The physiochemical and alignment independent descriptors were found to have an important role governing the change in antihypertensive activity (83).In 2011 Sabet et al. showed the importance of topological, geometrical and quantum chemical descriptor through QSAR using Feature analysis- Multiple Linear Regression (FA-MLR), Genetic Algorithm-Principal Component Analysis (GAPLS), and Principal Component Regression Analysis (PCRA) (84).Noolvi and Bhardwaj et al. in 2011developed various QSAR models using MLR, PLS and PCR. They showed that the MLR is the best method among PLS and PCR. For model validation authors used sphere exclusion method successfully (85).In 2010 Michielan and Stefano Moro focused on the development of QSAR models by machine learning methods as an attractive and helpful strategy in drug discovery. They combined several types of molecular descriptors with powerful nonlinear techniques. These molecular descriptors properly describe the relationship existing between the structural features and the desired property (86). In 2011 G.Swarnlatha et al. presented a detail review on 1, 4 dihyro pyridine . Their review concludes that 1,4-DHP as a Multifunctional potent lead Molecule, which has various feasible positions for substitution and exhibit several pharmacological activities such as calcium channel antagonist activity (87), antihypertensive activity (88),antianginal activity (89),antioxidant activity (90)1,4 dihyro pyridine apart from CVS activities also exhibit other pharmacological activities such as antitubercular activity (91),antibacterial activity (92),anti-inflammatory activity (93), anticonvulsant activity (94),analgesic activity (95) and soon. Sadek and Elz et al. in 2011 a new derivatives of m- nifedipine have been successfully synthesized by substituting an ester moiety with an amide (5-phenylcarbamoyl) moiety, use modified Hantzsch reaction. They concluded that these new compounds have increased metabolic stability and consequently longer duration of actions as compared to nifidipine (96).Again, in 2011 Prakash, Aneja et al. Synthesized some new derivatives of 1, 4 dihyro-4 pyrazolyl pyridines and 4-pyrazolypyridines and also evaluate their antimicrobial activity using agar diffusion method (97).In 2011 Al-Said and Ghorab et al. observed the anti-breast cancer activity of some novel 1,2-dihydropyridine, thiophene and thiazole derivatives (98).Again for anticancer activity, some new 1,4 dihydropyridine derivatives has been synthesized by Surendra Kumar et al. in 2011 and their activity screened against HepG2(liver), Hepa (cervical) ,MCF-7 breast cancer cells (99).Ramin miri et al. in 2011 performed an investigation about the intrinsic cytotoxicity of some derivatives of DHP containing nitroimidazole moiety on their C4 position on four different cancer cell lines (Raji, K562, Fen and HeLa). The result showed that these compounds had moderate-good cytotoxic activity. They also developed QSAR model and shows the importance of N atom in cytotoxicity Ca2+ channels (100). In 2012, Datar and Auti et al. Applied a 2D QSAR approach on a series of novel 1, 4-dihydropyridines as antihypertensive agent and developed different models based on multiple linear regressions (MLR), to find out correlation between the physicochemical parameters and the biological activity (101).In 2013 Das and Grovac et al. reported the some properties of Zagber eccentricity indices. They concluded that hydrogen depleted tool derived from topological indices is used to predict the structure property correlation of organic compounds (102).

REFERENCES:

1. Berger's. Burger's Medicinal Chemistry And Drug Discovery. [ed.] Donald J. Abraham. Sixth . s.l.: A John and Willey;. pp. 3-4:. Vol. 1:.2. AFA., Cros. Action de1'alcool amylique sur 1'organisme. 1863.page3. On the connection between chemical constitution and physiochemical action Part 1- On the physiological action of the salts of the ammonium bases,derived from strychina,brucia,thebia,codeia,morphia and nicotia. Fraser and A, Crum -Brown. London: s.n., 1868, Philosophical transaction of the royal society , Vol. 25, pp. 151-2003.4. On bond order and valences in the ab initio quantum chemical theory. et.al., Mayer& Overton. 1, 1986, International journal of quantum chemistry, Vol. 29, pp. 73-84.5. The Effect of Structure Opon The Reaction of Organic Compounds.Benzen Derivatives :. Hammet:, Louis. 1937:, Vol. 59, pp. 96-103.journal6. A new substituent constant pi derived from partiton coefficient. Fujita, Hansch. 1964, Vol. 86, pp. 5175-5180.journal7. Concerning linear relationship between the u ant T electron effects of unshared pair substituents .The role of n(p-d) conjugation. Taft. 19, 1965, Journal of the American Chemical society, Vol. 87, pp. 4387-4388.8. Analysis of the Structure Activity Relationship of the sulfonamide drugs using substituent constant. Toshio, Hansch Crowin & Fujita. 6, 1967, Journal of Medicinal Chemistry, Vol. 10, pp. 991-1000.9. et.al., Adamson. 1977, Proceedings of the analytical divison of the chemical society, Vol. 14, pp. 26-28.journal10. 110, 5959 (1988). Cramer III, Richard D, Patterson, David E. and Bunce, Jeffrey D. s.l.: American chemical society, 1988, J. Amer. Chem. Soc., Vol. 110, p. 5959.11. Structure Activity study of antihypertensive 1,4-dihydropyridine derivatives having nitrooxyalkyl moieties at the 3 and 5 positions. Kawashima, Yutaka and et.al. 6, 1993, Chem Pharm Bulletin , Vol. 41, pp. 1060-1065.12. Molecular Similarity Indices in a Comparative Analysis (CoMSIA) of Drug Moleculesto Correlate and Predict Their Biological Activity. Klebe, G., Abraham, U. and Mietzner, T. 1994, J. Med. Chem., Vol. 37, pp. 4130-4146.13. Conformational analysis , moleculer modeling and qsar studies of agents for the inhibition of astrocytic chloride transport. Waller, Chris L and Wyrick, Steven D. 1, 1994, Pharmaceutical research , Vol. 11.14. Synthesis and bioactivities of heterocyclic lipids as PAF antagonist . al., Chung S.K. & Woo S.H. et. 10, 1995, Bioorganic & Medicinal Chemistry Letters, Vol. 5, pp. 1091-1096.15. Ki, Kim Hwan. Comparison of classical QSAR and comparative moleculer field analysis. In classical and three dimensional QSAR in agrochemistry. Washigton: American Chemical Society, 1995, Chapter-23, pp. 303-317.16. Microbial Metabolism of Pyridine , Quinoline,Acridine and their derivatives under aerobic and anaerobic conditions. Jean, Kaiser Pierre. 1996, American Society of Microbiology:Microbiological Reviews , pp. 483-498.17. Chemical Similarity Using Physiochemical Property Descriptors. al., Kearsley K. Simon et. 1996, J.Chem.Inf.Comput.Sci., Vol. 36, pp. 118-127.18. Synthesis and calcium channel antagonist activity of 4- imidozolyl 1,4-dihyropyridines. 1997, Pharmaceutical Science, Vol. 3, pp. 165-168.19. GA Strategy for Variable Selection in QSAR Calcium Channel Antagonist . . Hasegawa, Miyashita, Fanatsu et. al. 1997, J.Chem.Info.Comput.Sci., Vol. 37, pp. 306-310.20. Pharmacological activity and membren interactions of antiarrhythmics:4D-QSAR/QSPR analysis. Klein P.D.Christian, Hopfinger J.A. 2, 1998, Pharmaceutical Research, Vol. 15, pp. 303-311.21. QSPR and QSAR Models Derived with CODESSA Multipurpose Statistical Analysis Software. Katritzky, Alan R., et al. s.l.: AAAI Press, 1999. AAAI Technical Report SS 99-01.22. New QSAR methods applied to structure -Activity mapping and combinatorial chemistry. Burden R. Frank, Winkler A.David. 1999, J.Chem.Inf.Comput.Sci., Vol. 39, pp. 236-242.23. Synthesis, CoMFA Analysis, and Receptor Docking of 3,5-Diacyl-2,4-Dialkylpyridine Derivatives as Selective A3 Adenosine Receptor Antagonists. An-Hu Li, Stefano Moro, Nancy Forsyth, Neli Melman, Xiao-duo Ji, and Kenneth A. Jacobson. s.l.: ACS, 1999, J. Med. Chem.24. Stereoselective characterization of the 1,4 -dihyropyridine binding site at L-type calcium channels in the resting state and the opened/inactive state. Jur"gen-Klaus, Schleifer. 1999, J.Med.Chem., Vol. 42, pp. 2204-2211.25. 2D and 3D QSAR Analysis of Some Valproic Acid Metabolites and analogues as Anticonvulsant Agents. Netzeva, Tatiana, Doytchinova, Irini and Natcheva, Roumiana. 6, 2000, Pharmaceutical Research, Vol. 17.26. QSAR model for drug human oral bioavailability. Yoshida Fumitaka, Topliss G. John. 2000, J.Med.Chem., Vol. 43, pp. 2575-2585.27. Comparison of a Neural Net -Based QSAR Algorithum (PCANN) with Hologram and Multiple linear Regression based QSAR Approaches: Application to 1,4 Dihyropyridine -based Calcium Channel Antagonist. viswanadhan, Mueller,Basak,Weinstein et. al. 2001, J.Chem.Inf.Comput.Sci., Vol. 41, pp. 505-511.28. Toward an optimal procedure for variable selection and QSAR model building . Yasri A., Hartsough D. 2001, J.Chem.Inf.Comput.Sci., Vol. 41, pp. 1218-1227.29. Synthesis and evalution of a new class of nifedipine analougs with T-type calcium channel blocking activity. C, et. al. Stotz Stephani. 3, 2002, Mol.Pharmacol, Vol. 61, pp. 649-658.30. Three-Dimensional Quantitative Structure-Activity Relationship of 1,4-Dihydropyridines As Antitubercular Agents. Kharkar, Prashant S., et al. 2002, J. Med. Chem., Vol. 45, pp. 4858-4867.31. The analysis of structure - anticancer and antiviral activity relationships for macrocyclic pyridinophanes and their analogues on the basis of 4D QSAR models ( simplex representation of moleculer structure. Kuz'min, Victor E. 1, 2002, Acta Biochimica Polonica, Vol. 49, pp. pp. 157-168.32. Fragmental approach in QSPR. palyulin, Zefirov and. 2002, j.chem.info.comput.sci., Vol. 42, pp. 1112-1122.33. Novel methods for the prediction of logP,pKa and logD. Glen, Xing and. 2002, Vol. 42, pp. 796-805.34. The most common chemical replacement in drug -like compounds. Sheridan. 2002, j.chem.info.comput.sci., Vol. 42, pp. 103-108.35. Unique structure activity relationship for 4-isoxazolyl-1,4-dihyropyridines. Natale, Zamponi et. al. 2003, j.med.chem. , Vol. 46, pp. 87-96.36. Theoretical scales of hydrogen bond acidity and basicity for application in QSAR/QSPR studies and drug design. et.al., Oliferenko. 2003, j.chem.info.comput.sci., pp. 1025-1055.37. QSAR modelling using chirality descriptors derived from molecular topology. Tropsha, Golbraikh and. 2003, j.chem.info.comput.sci., Vol. 43, pp. 144-145.38. On the role of polarizability in chemical biological interactions. al., Hansch Crowin et. 2003, J.chem.inf.comput.sci., Vol. 43, pp. 120-125.39. Application of the novel moleculer alingment network to 3D-QSAR. al., Arakawa et. 2003, J.chem.inf.comput.sci., Vol. 43, pp. 1396-1402.40. DISE: Directed sphere exclusion. al., Goobi et. 2003, J.chem.inf.comput.sci., Vol. 43, pp. 317-323.41. Ranking a random feature for variable and feature selection. Herye, Stoppiglia. 2003, Journal of machine learning research, pp. 1399-1414.42. Epothilones:Quantitative Structure activity relations studied by support vector machines and artificial neural networks. Bleckmann, Meiler. 2003, QSAR and Combinatorial science, Vol. 22, pp. 722-728.43. Heuristic moleculer lipophilicity potential (HMPL): A 2D-QSAR study to LADH of moleculer family pyrazole and derivatives. al., Chou et. 2005, J.comput.chem., Vol. 26, pp. 461-470.44. Development and use of hydrophobic surface area(HSA) descriptors for computer -assisted quantitative struture-activity and structure property relationship studies . et.al., Tanton. 2004, J.chem.inf.comput.sci., Vol. 44, pp. 1010-1023.45. An automated PLS search for biologically relevant QSAR descriptors. Olaha, Marius, Bologaa, Cristian and Opreaa, Tudor I. 2004, Journal of Computer-Aided Molecular Design , Vol. 18, pp. pp.437-449.46. Multiple regression and non linear parabolic relationship. De Mello, Heloisa, Echevarria, Aurea and Bernardino, Alice M. s.l.: ACS, 2004, J. Med. Chem., Vol. 47, pp. 5427-5432.47. Anticonvulsant activities of new 1,4-dihyropyridine derivatives containing 4-nitroimidazolyl substituents . al., Shafiee Abbas et. 2, 2004, DARU, Vol. 12, pp. 81-87.48. Simple and highly predictive QSARmethod : application to a series of (S)-N-[(1-ethyl -2-pyrrolidinyl)methyl]-6-methoxybenzamides. Freitas, Matheus P. and Martins, Jose A. s.l.: Elsevier, 2005, Bioorganic & Medicinal chemistry , Vol. 67, pp. 182-186.49. QSAR study on benzenesulfonamide dissociation constant pKa: Physicochemical approach using surface tension. Abhilash, Thakur. s.l.: ARKAT, 2005, ARKIVOC, Vol. 14, pp. 49-58.50. Modelling robust QSAR coding molecules in 3D-QSAR from a point to surface sectors and moleculer volumes. al., Polanski et. 2005, J.chem.inf.model, Vol. 45, pp. 1447-1455.51. Synthesis and 3D QSAR of New Pyrazolo[3,4-b]pyridines: Potent and Selective Inhibitors of A1 Adenosine Receptors method. Fabrizio Manetti. s.l.: American Chemical Society, 2005, J.Med.Chem. , Vol. 48, pp. 7172-7185.52. Development of a chirality -sensitive flexibility descriptor for 3+3D-QSAR . al., Dervarics M et. 2006, J.Chem.Inf.Model, Vol. 46, pp. 1431-1438.53. Statistically validated QSARs, based on theoretical descriptors ,for modelling aquatic toxicity of organic chemicals in Pimephales Promelas {Fathead Minnow) . al., Gramatica P et. 2005, J.Chem.Inf.Model, Vol. 45, pp. 1256-1266.54. Toward an Optimal Procedure for PC-ANN Model Building:Prediction of the Carcinogenic Activity of a Large Sets of Drugs: . Hammateenejad, Safarpour et. al. :. 2005, J.Chem.Inf.Model,, Vol. 45, pp. 190-199.55. QSAR analysis of 2,4-diaminopyrido[2,3-d]pyrimidines and2,4-diaminopyrrolo[2,3-d]pyrimidines as dihydrofolate reductase inhibitors . Jain, P, et al. October 2005, Indian Journal of Biochemistry & Biophysics, Vol. 42, pp. 315-320.56. CoMFA,CoMSIA and moleculer hologram QSAR studies of novel neuronal nAChRs ligands -open ring analobues of 3-pyridyl ether. Huabei, Zhang. 2005, J.Chem.Inf.Model, Vol. 45, pp. 440-448.57. A Novel Autometed Lazy Learning QSAR(ALL QSAR ) Approach: Method Development, Application and Virtual Screnning of Chemical Databases Using Validated ALL-QSAR Models. Zhang, Shuxing. 5, 2006, J.Chem.Info.Model., Vol. 46, pp. 1984-1995.58. QSAR analysis of N-Alkyl imidazole analogues as antibacterial agents. Khan, Nazneen, et al. 3, 2006, Indian Journal of Pharmaceutical Science, Vol. 68, pp. 341-346.59. Recent advance in computational prediction of drug absorption and permability in drug discovery . al., Hou Tingjun et. 2006, Current Medicinal Chemistry, Vol. 13, pp. 2653-2667.60. Prediction of pKa values aliphatic carboxylic acids and alcohals with empirical atomic charge descriptors. al., Zhang Jinhua et. 2006, J.Chem.Inf.Model, Vol. 46, pp. 2256-2266.61. Gas to olive oil partition coefficients: A linear free energy analysis . Michael, Abraham H. 2006, J.Chem.Inf.Model, Vol. 46, pp. 1735-1741.62. Structure feature indenture for estrogen analougs as anticancer agent :Denovo and Hansch approach. .......... 2007, Indian Journal of Chemistry , Vol. 46B, pp. 1148-1153.63. 2D QSAR of arylpiperazines as 5-HT1A receptor agonists . Joshi, Urmila J and et.al. 2007, indian j pharma sci., Vol. 69, pp. 800-804.64. Prediction of acidity constant for substituted acetic acid in water using artificial neural network. Habibi-Yangjeh, Aziz and Danandeh-Jnagharad, Mohammed. 2007, Indian journal of chemistry B, Vol. 46, pp. 478-487.65. Synthesis and Evalution of some 1,4 dihyropyridines and their derivatives as antihypertensive agents. ........ 2007, Indian Journal of Chemistry, Vol. 46B, pp. 698-701.66. Molecular Modeling and QSAR Analysis of Some 4,5 Dichloroimidazolyl-1,4-DHPBased Calcium Channel Blockers. B. Hemmateenejad, R. Miria, N. Edrakia, M. Khoshneviszadeha, A. Shafiee. 2, June 2007, J. Iran. Chem. Soc. , Vol. 4, pp. 182-193.67. Preliminary MLR studies of antimicrobial activity of some 3-hydroxypyridine-4-one and 3-hydroxypyran-4-one derivatives. Sabet, R., Fassihi, A. and Moeinifard, B. 2, Oct 2007, Research in Pharmaceutical Sciences, Vol. 2, pp. 103-112.68. QSAR studies of cytotoxic acridine 5,7 diones:A comparative study using P-VSA descriptors and topological descriptors. ........ 2008, Indian Journal of Chemistry, Vol. 46B, pp. 177-184.69. QSAR studies on 4-thiazolidiones and 2-azetidinones bearing benzothiophene nucleus as potential anti-tubercular agents. ........ 2008, Indian Journal of Chemistry, Vol. 47B, pp. 586-591.70. QSAR Study of Antimicrobial 3-Hydroxypyridine-4-one and 3-Hydroxypyran-4-one Derivatives Using Different Chemometric Tools. Sabet, Razieh and Fassihi, Afshin. 12, December 2008, int J Mol Sci. , Vol. 9 , pp. 24072423.71. Building a chemical space based on fragment descriptor. baskin, Varnek &. 2008, Combinatorial chemistry & high throughput screening, Vol. 11, pp. 1-8.72. Linear and nonlinear 3D-QSAR approaches in tandem with ligand -based homology modeling as a computational strategy to depict the pyrazolo -triazolo-pyrimidine antagonist binding site of the human adenosine A2A receptor. et.al., Michielan Lisa. 2008, J.Chem.Inf.Model, Vol. 48, pp. 350-363.73. Predicting kinase selectivity profiles using free-wilson QSAR analysis. Simone, Sciabola. 2008, J.Chem.Inf.Model, Vol. 48, pp. 1851-1867.74. Hantzsch reaction: recent advance in Hantzsch 1,4 dihyropyridines . ........ 2008, Journal of Scientific & Industrial Research, Vol. 67, pp. 95-111.75. QSAR study by 1,2,4-triazoles using several physiochemical descriptors. Vesna, Dimova. 1, 2009, Macedonian Journal of Chemistry and Chemical Engineering, Vol. 28, pp. 79-89.76. Application of random forest approach to QSAR prediction of aquatic toxicity. al., Polishchuk G.Pavel et. 2009, J.Chem.Inf.Model, Vol. 49, pp. 2481-2488.77. Synthesis and antiulcer activity study of 1,4-dihyropyridines and their mannich bases with sulphanilamide. B.B., Subhudhi. 2009, Indian Journal of Chemistry, Vol. 48B, pp. 725-728.78. Synthesis and antimicrobial activity of some cyanopyridine and cynopyrans towards mycobacterium tuberculosis and other microorganism. 2009, Indian Journal of Chemistry, Vol. 48B, pp. 833-839.author79. Pyridine-3-carboxamides as novel CB2 agonists for analgesia. Mitchell, William L., et al. 2009, Bioorganic & Medicinal Chemistry Letters , Vol. 19, pp. 259263.80. 2D-QSAR studies on 1,4 dihyropyridines as Ca++ chennel blockers. al., Kumar Mahesh et. 4, 2010, J.Chem.Pharm.Res., Vol. 2, pp. 159-165.81. In silico binary classification QSAR model based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage. al., Su Han-bo et. 2010, J.Chem.Inf.Model, Vol. 50, pp. 1304-1318.82. Current trend in antimicrobial agent research :chemo and bioinformatics approaches. 13, 2010, Drug Discovery Today, Vol. 15.83. Exploration of Quantitative Structure Activity Relationship studies on a series of substituted Quinazolonones as angiotensin -2 AT1 antagonists. et.al., Sharma Mukesh. 11, 2011, World Applied sciences Journal , Vol. 12, pp. 2111-2119.84. Application of different chemometric tools in QSAR study of azoloadamantanes against influenza A virus . R, Sabet. 1, 2011, Research in Pharmaceutical Sciences, Vol. 6, pp. 23-33.85. A comparative QSAR analysis of Quinazoline analogues as tyrosine kinase (erbB-2) inhibitors. Noolvi, Bhardwaj. 2011, Medicinal Chemistry, Vol. 7, pp. 200-212.86. Perspective:Pharmaceutical perspective of nonlinear QSAR strategies . Michielan. 2010, J.Chem.Inf.Model, Vol. 50, pp. 961-978.87. 1, 4 Dihyropyridines : A Multifunctional Molecule - A Review. Swarnalatha, Sirisha,Chetty et. al. (1), 2011, Int. j.Chem.Tech.Res., Vol. 3, pp. 75-89.88. The new generation dihyropyridine type calcium blockers,bearing 4-phenyl oxypropanolamine adrenoceptor antagonist and long -acting antihypertensive activities. al., Liang Chong-Jhy et. 2002, Bioorganic & Medicinal Chemistry , Vol. 10, pp. 719-730.89. Solid phase synthesis of 4-aryl-1,4-dihyropyridines via the Hantzsch three component condensation. al., J.G. Breitenbucher et. 2000, Tetrahedron Letters, Vol. 41, pp. 4311-4315.90. Synthesis ,characterization and in-vitro antioxidant activity of mannish bases of novel 1,4-dihyropyridine derivatives. al., Aanandhi Vijey M et. 4, 2010, Research Journal of Pharmaceutical ,Biological and Chemical Sciences, Vol. 1, pp. 926-932.91. Antimycobacterial activity of substituted isosters of pyridines and pyrazine carboxylic acids. G.A., Watchter. 1998, J.Med.Chem., Vol. 41, pp. 2436-2438.92. Synthesis of novel dihyropyrimidine-2(1H)-ones derivatives using lipase and their antimicrobial activity. N, Borse Bhushan. 2012, Current Chemistry Letters, Vol. 1, pp. 59-68.93. Synthesis and anti-inflammatory activity of 1,4-dihyropyridines . Sushilkumar, Bahekar. 4, 2002, Acta Pharmaceutica, Vol. 52, pp. 281-287.94. Anticonvulsant activity of -HCH , calcium channel blockers and calmodulin antagonist in seizures induced by lindane and other convulsant . al., Tusell J.M. et. 1993, Drug.Brain Res, Vol. 622, pp. 99-104.95. Antibacterial activity of the antiiflammatory agent diclofenac sodium . S., Annadurai. 1, 1998, Indian Journal of Experimental Biology , Vol. 36, pp. 86-90.96. Synthesis and calcium channel blocking activity of 1,4 -dihyropyridine derivatives containing ester substitute and phenyl carbomyl group. al., Sadek Bassem et. 4, 2011, american Journal of Applied Sciences, Vol. 8, pp. 303-309.97. Synthesis and antimicrobial evaluation of new 1,4 -dihydro-4-pyrazolylpyridines and 4-pyrazolylpyridines. al., Aneja Prakash et. 2011, Organic and Medicinal Chemistry Letters.98. Anti-breast cancer activity of some novel 1,2 -dihyropyridine , thiophene and thiazole derivatives. al, Ghorab M Mostafa et. 2011, European Journal of Medicinal Chemistry , Vol. 46, pp. 147-141.99. Synthesis and antimicrobial activity of a new series of 1,4 -dihydropyridine derivatives. al., Kumar Surendra et. 1, 2011, J.Serb.Chem.Soc., Vol. 76, pp. 1-11.100. Cytotoxic effect of some 1,4-dihyropyridine derivatives containing nitroimidazole moiety . al., Miri Ramin et. 3, 2011, Iranian Journal of Pharmaceutical Research, Vol. 10, pp. 497-503.101. 2D QSAR of novel 4-substituted 1,4 dihyropyridines-3,5-dicarboxylate as potential antihypertensive agent. Auti, Datar &. 3, 2012, Journal of Computational Methods in Molecular Design, Vol. 2, pp. 85-91.102. Some properties of the zagerb eccentricity indices. al., Das Ch. Kinkar et. 2013, Arc Mathematica Contemporanea, Vol. 6, pp. 117-125.

116