QSAR studies/models

Quantitative Structure—Activity Relationships (QSAR). Quantitative Stmcture—Activity Relationships (QSAR) is the name given to a broad spectmm of modeling methods which attempt to relate the biological activities of molecules to specific stmctural features, and do so in a quantitative manner (see Enzyme INHIBITORS). The method has been extensively appHed. The concepts involved in QSAR studies and a brief overview of the methodology and appHcations are given here. 

T Kimura, K Hasegawa, K Funatsu. GA strategy for variable selection m QSAR studies GA-based region selection for CoMFA modeling. J Chem Inf Comput Sci 38 276-282, 1998. 

When applied to QSAR studies, the activity of molecule u is calculated simply as the average activity of the K nearest neighbors of molecule u. An optimal K value is selected by the optimization through the classification of a test set of samples or by the leave-one-out cross-validation. Many variations of the kNN method have been proposed in the past, and new and fast algorithms have continued to appear in recent years. The automated variable selection kNN QSAR technique optimizes the selection of descriptors to obtain the best models [20]. 

A key requirement of QSAR is that the compounds used in the modeling and prediction processes should have the same mechanism of action, and for this reason most QSAR studies are made with congeneric series of compounds. However, if a diverse set of compounds can reasonably be assumed to have the same mechanism of action, QSAR modeling can justihably be carried out. For example, Dearden et al. [43] developed a QSAR for the ratio of brain levels of 22 very diverse drugs in the wild-type mouse and the P-glycoprotein knockout mouse (R+/ ) ... 

H-bonding is an important, but not the sole, interatomic interaction. Thus, total energy is usually calculated as the sum of steric, electrostatic, H-bonding and other components of interatomic interactions. A similar situation holds with QSAR studies of any property (activity) where H-bond parameters are used in combination with other descriptors. For example, five molecular descriptors are applied in the solvation equation of Kamlet-Taft-Abraham excess of molecular refraction (Rj), which models dispersion force interactions arising from the polarizability of n- and n-electrons the solute polarity/polarizability (ir ) due to solute-solvent interactions between bond dipoles and induced dipoles overall or summation H-bond acidity (2a ) overall or summation H-bond basicity (2(3 ) and McGowan volume (VJ [53] ... 

Calculated molecular descriptors including H-bond parameters were used for QSAR studies on different types of permeabiUty. For example, the new H-bond descriptor characterizing the total H-bond ability of a compound, was successfully appUed to model Caco-2 cell permeability of 17 drugs [30]. A similar study on human jejunal in vivo permeabiUty of 22 structurally diverse compounds is described in Ref. [62]. An exceUent one-parameter correlation of human red ceU basal permeabiUty (BP) was obtained using the H-bond donor strength [63] ... 

A CRO may also allow for the in-house introduction of specialized lipophilic scales by transferring routine measurements. While the octanol-water scale is widely applied, it may be advantageous to utilize alternative scales for specific QSAR models. Solvent systems such as alkane or chloroform and biomimetic stationary phases on HPLC columns have both been advocated. Seydel [65] recently reviewed the suitabihty of various systems to describe partitioning into membranes. Through several examples, he concludes that drug-membrane interaction as it relates to transport, distribution and efficacy cannot be well characterized by partition coefficients in bulk solvents alone, including octanol. However, octanol-water partition coefficients will persist in valuable databases and decades of QSAR studies. 

QSARs based on ionic compounds have thus been dramatically restricted due to the neglect of ion partitioning, which consequently meant that no technique was dedicated to such measurements and that modeling never took account of ionic species. To become fully accepted, potentiometry and electrochemistry at the ITIES need now to prove interesting in QSARs. As numerous lipophilicity data of ionizable compounds become available, one can expect that solvatochromic equations for ions will soon be developed in various solvent systems, which would greatly facilitate QSAR studies. 

QEKIRVRLSA antimicrobial peptide, 26 799-800 Qiana, 19 764 QikProp, 6 18 Qinghai Lake, 5 784 Q parameter, impeller, 16 676 QSAR analysis, 10 327t, 328-329. See also Quantitative structure—activity relationship (QSAR) studies 3D QSAR models... 

The literature of the past three decades has witnessed a tremendous explosion in the use of computed descriptors in QSAR. But it is noteworthy that this has exacerbated another problem rank deficiency. This occurs when the number of independent variables is larger than the number of observations. Stepwise regression and other similar approaches, which are popularly used when there is a rank deficiency, often result in overly optimistic and statistically incorrect predictive models. Such models would fail in predicting the properties of future, untested cases similar to those used to develop the model. It is essential that subset selection, if performed, be done within the model validation step as opposed to outside of the model validation step, thus providing an honest measure of the predictive ability of the model, i.e., the true q2 [39,40,68,69]. Unfortunately, many published QSAR studies involve subset selection followed by model validation, thus yielding a naive q2, which inflates the predictive ability of the model. The following steps outline the proper sequence of events for descriptor thinning and LOO cross-validation, e.g.,... 

A relevant aspect in QSAR studies and pharmacophore modeling is the choice of the most appropriate molecular descriptors with respect to both the molecular series... 

Martin H) has written a perceptive analysis of the possible ways in which an ionized species may behave in various models and contribute to or be responsible for a given activity. QSAR studies that have dealt with ion-pair partitioning include a study of fibrinolytics ( ) and the effect of benzoic acids on the K ion flux in mollusk neurons ( ). Schaper (10) recently reanalyzed a large number of absorption studies to include terms for the absorption of ionized species. Because specific values were not available for log Pj, he let the relation between log Pi and log P be a parameter in a nonlinear regression analysis. In most cases he used the approximation that the difference between the two values is a constant in a given series. This same assumption was made in the earlier studies (, ) Our work suggests that the pKa of an acid can influence this differential (see below). The influence of structure on the log P of protonated bases or quaternary ammonium compounds is much more complex (11,12) and points out the desirability of being able to easily measure these values. 

For quantitative structure-activity relationship (QSAR) studies a three-dimensional model of a DNA-quinoIone complex was built using molecular modeling techniques. It was based on the intercalation of quinolone into the double helix of DNA. It was concluded that the intercalation model is consistent with most available data on the structure of the quinolone complex. This predicted... 

Ragno, R., Simeoni, S., Valente, S., Massa, S. and Mai, A. (2006) 3-D QSAR studies on histone deacetylase inhibitors. A GOLPE/GRID approach on different series of compounds. Journal of Chemical Information and Modeling 46,1420-1430. 

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