By Han van de Waterbeemd, Raimund Mannhold, Povl Krogsgaard-Larsen, Hendrik Timmerman
Using robust desktops has revolutionized molecular layout and drug discovery. completely researched and well-structured, this entire instruction manual covers powerful and effective innovations in 3D-QSAR and complicated statistical research. The emphasis is on exhibiting clients find out how to follow those equipment and steer clear of expensive and time-consuming methodical blunders. themes lined comprise * mixture of statistical tools and molecular modeling instruments * rational use of databases * complicated statistical innovations * neural networks and specialist structures in molecular layout This publication addresses the practitioner in and learn, in addition to the beginner wishing to turn into familiar with sleek instruments in medicinal chemistry.
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Extra info for Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry, Vol 3)
1 Chemometrics and MofecufarModefing 11 logical response are generally not taken into account. In other words, SAR studies try to analyze and model the approach of the ligand to the binding site and the formation of the ligand-macromolecule complex. Therefore, the search for relationships between biological activity and molecular structure can be seen as the search for those stereoelectronic properties required for the recognition process to occur. The set of stereoelectronic requirements necessary for a family of compounds to elicit a certain activity is generally defined as the pharmacophore.
Amer. Chem. , Iwasa, J. , J. Amer. Chem. 86, 5175-5180 (1964) Salt, D. , Livingstone, D. J. and Tinsley, C. , Pestic. Sci. , Med. Chem. S. , J. Med. Chem. , Di Pace, L. Mol. Des. 1 Chemometrics and Molecular Modeling Demetrio Pitea, Ugo Cosentino, Giorgio Moro, Laura Bonati, Elena Fraschini, Murina Lasagni, and Roberto Todeschini Abbreviations 5 -Hydroxytryptamine Arylhydrocarbon Angiotensin IT Comparative Molecular Field Analysis 50% Effective Concentration Ec50 Generating Optimal Linear PLS Estimations GOLPE Highest Occupied Molecular Orbital HOMO 50% Inhibitory Dose IDSO Affinity constant Kd HMG-COA 3-Hydroxy-3-methylglutarylCoenzyme A Linear Discriminant Analysis LDA Linear Discriminant Classification Tree LDCT Lowest Unoccupied Molecular Orbital LUMO Monochlorinated Dibenzo-p-dioxins MCDD Molecular Electrostatic Potential MEP Principal Component PC Principal Component Analysis PCA Polychlorinated Dibenzo-p-dioxins PCDD Potential Energy Surface PES Partial Least Squares PLS Quantitative Structure-Activity Relationships QSAR Squared Correlation Coefficient r2 2 Cross-validated Squared Correlation Coefficient rcv Regularized Discriminant Analysis RDA Structure-Activity Relationships SAR 5-HT Ah A1I CoMFA 10 SCF-HF SD TCDD TrCDD D.
Figure 2. (a) Labels of the nine variable distances (dashed lines) of the pharmacophore; solid lines show the six distances constrained by bond lengths or angles. (b) Selected interatomic distances as conformational descriptors. (Reprinted with permission from Ref. 35, copyright 1990, VCH). strained by bond lengths or bond angles. Thus, in the first instance, nine interatomic distances (Dl -D9) were thought to be necessary to completely describe our system. These nine distances were evaluated for all the conformational minima; the correlation matrix of their autoscaled values was subjected to PCA.
Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry, Vol 3) by Han van de Waterbeemd, Raimund Mannhold, Povl Krogsgaard-Larsen, Hendrik Timmerman