chapter  3
376 Pages

Chemical Orthogonal Spaces for Structure–Activity Relationship (COS-SAR)

Abstract ................................................................................................. 194 3.1 Introduction .................................................................................. 195 3.2 Spectral Regressions’ Models on Chemical Orthogonal Space ... 197 3.2.1 Introducing SPECTRAL-SAR ......................................... 197 3.2.2 SPECTRAL-Diagonal-SAR ............................................. 209 3.2.3 Algebraic Correlation Factor ............................................ 217 3.2.4 Algebraic vs. Statistic Correlations .................................. 219 3.2.5 Projective QSAR .............................................................. 221 3.2.6 Non-linear Catastrophe QSAR ......................................... 229 3.2.7 QSAR by Quantum Amplitude (Qua-SAR) ..................... 243 3.2.8 From Residual to Structural Alerts’ QSAR

(Res/SA-SAR) ......................................................................... 248 3.2.9 QSAR by SMILES’ Structure and Chemical Reactivity

Principles .......................................................................... 254 3.2.9.1 Electronegativity and Its Minimum Principle ... 260 3.2.9.2 Chemical Hardness and Its Maximum Principle ...262 3.2.9.3 Chemical Power and Its Double Minimum

Principle ............................................................ 264 3.2.9.4 Electrophilicity and Its Triple Minimum

Principle ............................................................ 265 3.2.10 Topo-Reactive QSAR ....................................................... 274

3.2.10.1 A Historical Perspective on Topology and Link to Chemical Graphs ................................ 276

3.2.10.2 Common Construct of Topological Indices..... 280 3.2.10.3 Introducing SuTIs: Super-Topological Indices ....282 3.2.10.4 Topo-Reactivity by Timişoara-Parma Rule ..... 290 3.2.11 Logistic QSAR ................................................................. 300 3.3 Qu-SAR Case Studies on Chemical Orthogonal Space ............... 300 3.3.1 SPECTRAL-SAR Ecotoxicology (on T. pyriformis) ....... 300 3.3.2 Algebraic vs. Statistic Correlation (for Aliphatic

Amines’ Toxicity) ............................................................. 312 3.3.3 Projective QSAR (for Ionic Liquids on Daphnia Magna) ....325 3.3.4 Catastrophe QSAR (for Anti-HIV Pyridinones) .............. 338 3.3.5 Quantum Amplitude (on Breast anti-Cancer Bioactivity) ..... 366 3.3.6 Residual vs. Structural Alerts’ QSAR (for Rats’

Tocicology by High Diversity Molecules) ....................... 382 3.3.7 Screening vs. Structural SMILES QSAR (on Anti-HIV

Pyrimidines) ..................................................................... 427 3.3.7.1 SPECTRAL-SAR Approach ............................. 427 3.3.7.2 SPECTRAL-Diagonal-SAR Approach ............. 486 3.3.8 Topo-Reactive QSAR (for PAHs’ Carcinogenesis) .......... 492 3.3.9 Logistic QSAR (on Inter-species Toxicity) ...................... 503 3.4 Conclusion ................................................................................... 542 Keywords .............................................................................................. 545 References ............................................................................................. 546 Author’s Main References ........................................................... 546 Specific References ...................................................................... 549

ABSTRACT

With the present-day interest in correlating chemical structure with biological activity the quantitative structure-activity relationships (QSARs) is here presented under a plethora of novel, fresh and fruitful picture of regression analysis aiming to closely approach the quantum interpretation

of data and of ligand-receptor interaction by means of systematic orthogonal and scalar (dot) product of either molecular (chemicals or toxicants) descriptors between them and with the observed (recorded, measured) activities. The resulted Spectral-, Diagonal-Spectral-, Projective-, Catastrophe-, Residual-, SMILES (simplified molecular-input lineentry system)-, Topo-Reactive and Logistic-SARs may be conceptually and computationally considered as realization forms of the general Quantum-SAR (Qu-SAR) which widely employs the present data as a whole vectors, to be associated in principle with the eigen-states in quantum Hilbert space, while opening the way for assigning a sort of wave function or wave packet for the congeneric active molecular series rather than for a single molecule as used to be; this way the specific interaction may be eventually modeled by structure (intrinsic)-metabolic (extrinsic) quantum rather quantitative correlation picture so further allowing in establishing the specific “quantum paths” (or what is customarily known as the mechanistically map of ligand-receptor bonding) for a given or designed chemical-biological interaction.