Topological Difference MTD

The Minimum Topological Difference (MTD) approach developed by Z. Simon and T. Oprea, especially in its newer MTD-PLS variant employing the PLS regression analysis, successfully relates the activity to the presence and physicochemical parameters of the atoms and fragments defined over a quasi-3D hypermolecule as well as global physicochemical descriptors. Despite some methodological problems and limitations, this approach is promising and in active current development. ... 

Simon and his coworkers have developed (426) a quantitative 3D-QSAR approach, the minimal steric (topologic) difference (MTD) approach. Oprea et al. (452) compared MTD and CoMFA on affinity of steroids for their binding proteins and found similar results. Snyder and colleagues (453) developed an automated method for pharmacophore extraction that can provide a clear-cut distinction between agonist and antagonist pharmacophores. Klopman (404,454) developed a procedure for the automatic detection of common molecular structural features present in a training set of compounds. This has been used to produce candidate pharmacophores for a set of antiulcer compounds (404). Extensions (454)of this approach allow differentiation between substructures responsible for activity and those that modulate the activity. 

They are - molecular descriptors or - substituent descriptors calculated by difference between the considered compound (or functional group, fragment) and a -> reference structure or a - hyperstructure. Examples of differential descriptors are those obtained by the -> minimal topological difference (MTD) and - molecular shape analysis (MSA). 

Results from CoMFA studies have been compared with those from Hansch analyses [38, 1019 — 1023] and the minimal topological difference (MTD) method [1024]. Examples for the comparison of Hansch equations with CoMFA studies are e.g. the papain hydrolysis of N-(X-benzoyl)glycine pyridyl esters (60) (eqs. 204, 205 Zn = PLS component n of the corresponding field compare chapter 7.1) [1019, 1020], the emulsin-catalyzed hydrolysis of phenyl-P-D-glucosides [1020], the mutagenic activities of substituted (o-phenylenediamine)platinum dichlorides [1020], dihydrofolate reductase (DHFR) inhibition [1020], and some other biological activities [38, 1021—1023]. 

In another approach, with an aim to offer a realistic motive towards handling millions of databases and hundreds of descriptors for a fruitful structure-activity relationship (SAR), Putz and coworkers have proposed a unique QSAR model called spectral-SAR (S-SAR) [220], which considers the spectral norm in quantifying toxicity and reactivity with molecular structure. A handful of applications of the S-SAR algorithm in dealing with ecotoxicity, enzyme activity, and anticancer bioactivity are well established [221-227]. The S-SAR model coupled with Element Specific Influence Parameter (ESIP) formulations [228] are also utilized for predicting ecotoxicity measures. QSAR studies on the anti-HIV-1 activity of HEPT (l-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine) [229] and further studies involving the minimum topological difference (MTD) method [230, 231] are also reported [232]. 

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