INDEX structure-activity relationships

Structure-Activity Relationship Index = SAR Index Stmcture/Response Correlations... 

Another index for evaluating presence of activity cliffs is the SAR Index (or Structure-Activity Relationship Index), defined as a function of two separately calculated scores that assess intraclass diversity and activity differences of similar compounds [Peltason and Bajorath, 2007] ... 

B Mohney and L B Kier 1991. The Electrotopological State An Atom Index for QSAR. ntitative Structure-Activity Relationships 10 43-51. 

The CHI index is reportedly a relevant parameter in quantitative structure-activity relationship (QSAR) studies [41]. With this approach, log P could be determined in the range -0.45more than 25000 compounds with excellent reproducibility (within 2 index units) and reported in a GlaxoSmithKline database [11]. Two main drawbacks were identified using this approach (i) the assumptions used in Ref [7], i.e. that S is constant for all compounds and that the system dwell volume is excluded in calculations, yield some discrepancies in the resulting log P, and (ii) the set of gradient calibration... 

McMorris TC, Kelner MJ, Wang W, Estes LA, Montoya MA, Taetle R. (1992) Structure-activity relationships of illudins Analogs with improved therapeutic index. J Org Chem 57 6876-6883. 

Budavari, S., ed. (1996) The Merck Index, 12th ed., Whitehouse Station, NJ, Merck Co., p. 53 Eder, E., Neudecker, T., Lutz, D. Henschler, D. (1980) Mutagenic potential of allyl and allylic compounds. Structure-activity relationship as determined by alkylating and direct in vitro... 

US Environmental Protection Agency [USEPA]. 1994. USEPA/EC joint project on the evaluation of (quantitative) structure activity relationships. Washington (DC) US Environmental Protection Agency. http //intranet.epa.gov/oppthome/testsite/MPD-SAR/index.html (accessed December 28, 2007). 

Peltason L, Bajorath J (2007) SAR index quantifying the nature of structure-activity relationships. J Med Chem 50(23) 5571-5578... 

The next step was made by Klebe et al. [50]. Two 3D-QSAR methods were applied to get three-dimensional quantitative structure-activity relationships using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities toward Factor Xa to yield statistically reliable models of good predictive power [51-54] the widely used CoMFA method (for steric and electrostatic properties) and the comparative molecular similarity index analysis (CoMSlA) method (for steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor properties). These methods allowed the consideration of various physicochemical properties, and the resulting contribution maps could be intuitively interpreted. 

L. H. Hall, B. Mohney and L. B. Kier, The electrotopological state-an atom index for QSAR., Quantitative Structure-Activity Relationships, 1991, 10, 43-51. 

Gombar, V.K., Kumar, A. and Murthy, M.S. (1987b). Quantitative Structure-Activity Relationships Part IX - A Modified Connectivity Index as Structure Quantifier. Indian J.Chem., 26B, 1168-1170. 

Lobato, M., Amat, L., Besalil, E. and Carbd-Dorca, R. (1997). Structure-Activity Relationships of a Steroid Family Using Quantum Similarity Measures and Topological Quantum Similarity Indexes. Quant.Struct.-Act.Relat., 16,465-472. 

In the lead optimization phase of discovery and development is the iterative process of testing molecules, assessing their activity, and synthesizing new molecules based on that data (determining a structure-activity relationship, SAR). If there is a single index of activity, then the attainment of an improved potency (as determined by statistics) is a useful approach. One way to do this is to test the molecules repeatedly, determine a mean value with a measure of variation (standard deviation), and use those measurements to determine a confidence limit for that estimate. One proposed confidence limit that rapidly leads to comparison of multiple estimates is the 84% confidence limit of a mean [19]. For example, if four measurements yield a mean estimate pIC50 of 7.1 with a standard deviation (sx) of 0.13, then the 84% confidence limits can be calculated as... 

The dectrotopological state index (Si) is an extension of the purely topological index [55]. Electronic properties (i.e., the charge distribution in the molecule) are also considered. Atoms with identical T may differ in their Si. Electrotopological state indices have been used successfully to predict physico-chemical data, such as basicity (pJCa) or Hpophilicity (logP), as well as for quantitative structure-activity relationship (QSAR) or QSPR studies. 

Quantitative Structure Activity Relationships (QSAR) and Modeling Society. URL http //www.ndsu.nodak.edu/qsar soc/index.htm. Classical QSAR, multivariate statistical modeling, molecular modeling, computer-aided drug design, and environmental chemistry. 

Other pharmacological activities have also been correlated with quantum-chemically derived descriptors. For instance, the quantitative structure-activity relationship developed for the antibacterial activity of a series of monocyclic (i-lactam antibiotics included the atomic charges, the bond orders, the dipole moment, and the first excitation energy of the compound [103]. The fungicidal activity of A3-l,2,4-thiadiazolines has been correlated with an index of frontier orbital electron density derived from semi-empirical PM3 molecular orbital calculations [104],... 

Three major approaches to the prediction of aqueous solubility of organic chemicals using Quantitative Structure Activity Relationship (QSAR) techniques arc reviewed. The rationale behind six QSAR models derived from these three approaches, and the quality of their fit to the experimental data are summarized. Their utility and predictive ability are examined and compared on a common basis. Three of the models employed octanol-water partition coefficient as the primary descriptor, while two others used the solvatochromic parameters. The sixth model utilized a combination of connectivity indexes and a modified polarizability parameter. Considering the case of usage, predictive ability, and the range of applicability, the model derived from the connectivity- polarizability approach appears to have greater utility value. 

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