Dynamic QSAR

The concept of property space is progressively being used to gain a deeper understanding of the dynamic behavior of a single compound in different media (as we illustrate below with acetylcholine, see Section 1.4.2) or bound to biological targets (the carnosine-carnosinase complex, see Section 1.4.3), but it can be used also with a set of compounds to derive fertile descriptors for dynamic QSAR analyses (4D QSAR, see Section 1.4.4). 

From a methodological viewpoint, our results suggest that range and sensitivity are useful descriptors of property spaces and can parameterize the capacity of a given molecule to span broad conformational and property spaces. In other words, range and sensitivity appear as promising descriptors of the dynamic behavior of a molecule. Their application to other dynamic QSAR studies [in particular, absorphon, distribution, metabolism and excretion (ADME) behavior] is under investigahon. 

Vistoli, G., Pedretti, A., Villa, L., Testa, B. Range and sensitivity as descriptors of molecular property spaces in dynamic QSAR analyses. /. Med. Chem. 2005, 48, 4947-4952. 

Mekenyan, O.G., Ivanov, J.M., Veith, G.D., and Bradbury, S.P., DYNAMIC QSAR a search for active conformations and significant stereoelectronic indices, Quant. Struct.-Act. Relat., 13, 302-307, 1994. 

Finally, the stereodynamic representation of a molecule is a time-dependent representation which adds structural properties to the 3D representations, such as flexibility, conformational behaviour, transport properties, etc. - Dynamic QSAR is an example of a multi-conformational approach. 

Dynamic QSAR (also called 4D-QSAR) denotes those recently developed SRC techniques that take conformation variability of the molecules into account [Meken-yan et al, 1994 Dimitrov and Mekenyan, 1997]. Binary QSAR refers to those techniques where attention is paid to modelling binary responses such as active/inactive compounds [Gao etal, 1999]. 

D-QSAR dynamic QSAR structure/response correiations... 

D-QSAR = dynamic QSAR structure/response correlations 4D-Relative Molecular Similarity Analysis 4D Molecular Similarity Analysis... 

Dimitrov, S.D. and Mekenyan, O. (1997) Dynamic QSAR least squares fits with multiple predictors. Chemom. Intell. Lab. Syst., 39, 1-9. 

Mekenyan, O. 2002. Dynamic QSAR techniques Applications in drug design and toxicology. Curr Pharm Des 8 1605-21. 

Mekenyan, O. Schultz, T. W. Veith, G. D. Kamenska, V. Dynamic QSAR for semicarbazide-induced mortality in frog embryos. J. Appl. Toxicol. 1996,16, 355-363. 

PLS (partial least-squares) algorithm used for 3D QSAR calculations PM3 (parameterization method three) a semiempirical method PMF (potential of mean force) a solvation method for molecular dynamics calculations... 

Fanelli, F., Menziani, M.C. and De Benedetti, P.G. (1995) Molecular dynamics simulations of m3-muscarinic receptor activation and QSAR analysis. Bioorganic el Medicinal Chemistry, 3, 1465-1477. 

Membrane-Interaction (MI)-QSAR approach developed by Iyer et al. was used to develop predictive models of some organic compounds through BBB, and to simulate the interaction of a solute with the phospholipide-rich regions of cellular membranes surrounded by a layer of water. Molecular dynamics simulations were used to determine the explicit interaction of each test compound with the DMPC-water model (a model of dimyristoylphosphatidylcholine membrane monolayer, constructed using the software Material Studio according to the work done by van der Ploeg and Berendsen). Six MI-QSAR equations were constructed (Eqs. 74-79) ... 

Various endeavors have been undertaken to get insight into the 3D selector-selectand complex structures and to elucidate chiral recognition mechanisms of cinchonan carbamate selectors for a few model selectands (in particular, DNB-Leu). Such studies comprised NMR [92-94], ET-IR [94-96], X-ray diffraction [33,59,92,94], and molecular modeling investigations (the latter focusing on molecular dynamics [92,93,97], and 3D-QSAR CoMFA studies [98]). 

These four components may appear trivial by themselves, but combining them results in a dynamic method to create a QSAR model. Unfortunately, these main components of CoMFA are more complicated than a quick glance might suggest. 

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