Send Orders for Reprints to [email protected] Mini-Reviews in Medicinal Chemistry, 2014, 14, 35-55 35 Recent Advances in Multidimensional QSAR (4D-6D): A Critical Review Manoj G. Damale1, Sanjay N. Harke1, Firoz A. Kalam Khan2, Devanand B. Shinde3 and Jaiprakash N. Sangshetti*2 1Department of Bioinformatics, MGM’s Institute of Biosciences and Technology, Aurangabad (MS) India-431003; 2Y.B. Chavan College of Pharmacy, Dr. Rafiq Zakaria Campus, Rauza Baugh, Aurangabad (MS) India-431001; 3Department of Chemical Technology, Dr. B.A.M. University, Aurangabad (MS) India-431004 Abstract: The quantitative structure activity relationship (QSAR) study is the most cited and reliable computational technique used for decades to obtain information about a substituent’s physicochemical property and biological activity. There is step-by-step development in the concept of QSAR from 0D to 2D. These models suffer various limitations that led to the development of 3D-QSAR. There are large numbers of literatures available on the utility of 3D-QSAR for drug design. Three-dimensional properties of molecules with non-covalent interactions are served as important tool in the selection of bioactive confirmation of compounds. With this view, 3D-QSAR has been explored with different advancements like COMFA, COMSA, COMMA, etc. Some reports are also available highlighting the limitations of 3D-QSAR. In a way, to overcome the limitations of 3D-QSAR, more advanced QSAR approaches like 4D, 5D and 6D-QSAR have been evolved. Here, in this present review we have focused more on the present and future of more predictive models of QSAR studies. The review highlights the basics of 3D to 6D-QSAR and mainly emphasizes the advantages of one dimension over the other. It covers almost all recent reports of all these multidimensional QSAR approaches which are new paradigms in drug discovery. Keywords: Biological activity, Molecular descriptors, Multidimensional QSAR, Physicochemical property, QSAR. INTRODUCTION model which indicates the association between molecular descriptors and biological activity, is validated internally and The account of Rational Drug design starts with the externally in order to assess the predicative power of the discovery of lead molecule by trial-and-error process or QSAR model (Fig. 1). The interpretations of these models screening the library of lead compounds [1]. Nowadays, a are carried out by various methods like pattern recognition, Quantitative Structure Activity Relationship analysis is mostly machine and artificial intelligence. The first structure activity used in high-throughput screening of combinatorial libraries relationship study was conducted in the late eighteenth of small chemical compounds and moved further to check century when different alkaloids were studied, by Crum- the activity of a diverse set of designed small compounds Brown and Fraser. To demonstrate the alkylation of basic [2]. The QSAR is a knowledge-based method where a statistical nitrogen, of a ring system results in the formation of quaternary prediction model is made about biological activity and the t-amine compounds which are different from basic amines, presence of molecular descriptor. The aim of carrying out a and that now have significant change in its biological action. QSAR study is with the help of computational methods the Since then a variety of quantitative structure activity relationship QSAR model can help evaluate biological activity; this is studies have been reported to predict cytotoxicities, depressant mostly done to reduce failure rate in the drug development and antibacterial activity of chemical compounds [5-7]. process [3]. The historical aim of QSAR studies is to predict the specific biological activity of a series of test compounds. Thousands of QSAR equations have been formulated Nowadays the main objective of these studies is to predict using the QSAR methodology to validate and elucidate the biological activity of Insilico-designed compounds on the predicative power of QSAR hypothesis about the mechanism basis of already synthesized compounds [4]. of action of drugs at the molecular level and a more complete understanding of physicochemical phenomena such as In a QSAR study molecules are characterized based on hydrophobicity. In 1962 Hansch and Muir published their the presence of molecular descriptors and these descriptors brilliant study on the 2D structure-activity relationships of are mostly used to calculate the basis of physicochemical plant growth regulators and their dependency on Hammett properties of ligand molecule such as logP, pKa, mol. wt, constants and hydrophobicity [2]. The present review covers logD, molecular refractive index, molecular surface area, all recent developments in the field of QSAR. molecular interaction field, etc. The constructed mathematical SCHEME OF QSAR STUDY *Address correspondence to this author at the Dr. Rafiq Zakaria Campus, The QSAR model studies are mostly carried out in three Y.B. Chavan College of Pharmacy, Aurangabad-431001 (M.S.), India; different steps. Tel:/Fax: +91-240-23801129; E-mail: [email protected] 1875-5607/14 $58.00+.00 © 2014 Bentham Science Publishers 36 Mini-Reviews in Medicinal Chemistry, 2014, Vol. 14, No. 1 Damale et al. Fig. (1). Schematic overview of the QSAR process. i. Understanding and Selection of Potential Molecular Table 1. List of desirable attributes of molecular descriptors Descriptors from Set of Biologically Active Conformers for use in QSAR studies. Understanding and selection of potential molecular descriptors from set of biologically active conformers is Sr. No. Desirable Features Associated with Descriptors most critical step in QSAR model generation as it helps to understand the nature of molecular descriptors prior to actual 1. Structural interpretation QSAR model construction. This mostly helps to reduce un-necessary error in study data. The specified properties of 2. Show good correlation with at least one property chemical compound are used to select the potential molecular 3. Preferably allow for the discrimination of isomers descriptors like physicochemical properties; quantum-chemical, geometrical and topological (Table 1). As we do select the 4. Applicable to local structure potential molecular descriptor the necessary biological 5. Generalizable to “higher” descriptors information will be obtained from them. One of the earliest approaches for selection of molecular 6. Independence descriptor by manual inspection was plotting a (2D) plot of 7. Simplicity important molecular descriptor of bioactive conformers. And as of then several methods have developed but first and most 8. Not to be based on properties important computational method was cluster analysis 9. Not to be trivially related to other descriptors developed by Hansch which made easier to select compounds with diverse substituent on it [7]. Selection of relevant 10. Allow for efficient construction molecular descriptors is covered under 1D-QSAR model. 11. Use familiar structural concepts 1D-QSAR 12. Show the correct size dependence Various parameters are used to select the potential molecular descriptor that defines the specific molecular 13. Show gradual change with gradual change in structures properties of conformer like electronic constraints, hydrophobic constraints and steric constraints. Hammett was the first to study the electronic nature of a. Electronic Constraints chemical compound in case of benzoic acid ionization with water in a chemical reaction to determine activation energy The main aim behind the calculation of electronic effect (G). The various substitutions at meta and ortho positions is to know about inter and intra- molecular interactions, with the help of electron-withdrawing and donating groups which significantly contribute to biological action. Here the are studied. The analysis of both reactions was done, which common constant in the QSAR equation is studied, i.e. helps in understanding that electron donating groups will Hammett constants which include quantum chemical indices assist the rate of reaction. From the above observation one such as the lowest unoccupied molecular orbital, the highest can make meaningful correlation about change the in the unoccupied molecular orbital and polarizabilty. Recent Advances in Multidimensional QSAR (4D-6D): A Critical Review Mini-Reviews in Medicinal Chemistry, 2014, Vol. 14, No. 1 37 electronic nature of substituent and change in the activation ii. Analysis of Potential Molecular Descriptors in the energy. Context of Analysis of Activity As the QSAR methodology developed most intensively The correlations of biological activity to physicochemical with the help of the computational method, the electronic property are made by using the manual method by forming a nature of chemical compounds is now studied as a wave linear relationship between them [8]. The effects of Hammett function using methods like calculation of quantum chemical and Taft constant are studied for biological activity. The descriptor and the semi-empirical method. The quantum numbers of equation are generated to significantly intercorrelate chemical descriptor method uses constraints such as net the activity using a narrow gap between the number of atomic changes, highest occupied molecular orbital/lowest descriptors and the set of dataset. Once the set of molecular unoccupied molecular orbital (HOMO-LUMO) energies, descriptors is selected from them most informative sets can frontier orbital electron densities, and super