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This important new book provides innovative material, including peer-reviewed chapters and survey articles on new applied research and development, in the scientifically important field of QSAR in medicinal chemistry.
QSAR is a growing field because available computing power is continuously increasing, QSAR’s potential is enormous, limited only by the quantity and quality of the available experimental input, which is also continuously improving. The number of possible structures for the design of new organic compounds is difficult to imagine, and QSAR helps to predict their activities even before synthesis.
Features of Chemometrics Applications and Research QSAR in Medicinal Chemistry.
- Presents an overview of recent developments in QSAR methodologies along with a brief history of QSAR.
- Covers the available web resource tools and in silico techniques used in virtual screening and drug discovery processes, compiling an extensive review of web resources in the following categories: databases related to chemical compounds, drug targets, and ADME/toxicity prediction; molecular modeling and drug designing; virtual screening; pharmacophore generation; molecular descriptor calculation software; software for quantum mechanics; ligand binding affinities (docking); and software related to ADME/toxicity prediction.
- Reviews the rm2 as a more stringent measure for the assessment of model predictivity compared to traditional validation metrics, being specifically important since validation is a crucial step in any QSAR study.
- Presents linear model improvement techniques that take into account the conformation flexibility of the modeled molecules.
- Summarizes the building processes of four different pharmacophore models: common-feature, 3D-QSAR, protein-, and protein-ligand complexes.
- Shows the role of different conceptual density functional theory-based chemical reactivity descriptors, such as hardness, electrophilicity, net electrophilicity, and publicity in the design of different QSAR/QSPR/QSTR models.
- Reviews the use of chemometrics in PPAR research highlighting its substantial contribution in identifying essential structural characteristics and understanding the mechanism of action.
- Presents the structures and QSARs of antimicrobial and immunosuppressive cyclopeptides, discussing the balance of antimicrobial and hemolytic activities for designing new antimicrobial cyclic peptides.
- Shows the relationship between DFT global descriptors and experimental toxicity of a selected group of polychlorinated biphenyls, exploring the efficacy of three DFT descriptors.
Table of Contents.
- Overview And Recent Advances In QSAR Studies.
- Software And Web Resources For Computer-Aided Molecular Modeling And Drug Discovery.
- The Rm2 Metrics For Validation Of QSAR/QSPR models.
- Considering The Molecular Conformational Flexibility In QSAR Studies.
- Practical Aspects Of Building, Validation, And Application Of 3D-Pharmacophore Models.
- Application Of Conceptual Density Functional Theory In Developing QSAR Models And Their Usefulness In the Prediction Of Biological Activity And Toxicity Of Molecules.
- Synopsis Of Chemometrics Applications To Model PPAR Agonism.
- Antimicrobial And Immunosuppressive Activitites Of Cyclopeptides As Targets For Medicinal Chemistry.
- On The Use Of Quantitative Structure-Activity Relationships (QSAR) And Global Reactivity Descriptors To Study the Biological Activities Of Polychlorinated Biphenyls (PCBs).
- Applications Of Quantitative Structure-Relative Sweetness Relationships In Food Chemistry.
- QSAR Studies Of 1, 4-Benzodiazepines As CCKA Antagonist.
- Docking-Based Scoring Parameters Based QSAR Modeling On A Dataset Of Bisphenylbenzimidazole As Non-Nucleoside Reverse Transcriptase Inhibitor.
- Potential Anti-Inflammatory And Anti-Proliferative Agents.-1h-Isochromen-1-Ones And Their Thio Analogues and Their QSAR Studies.
- QSAR Studies On Dihydrofolate Reductase Enzyme: From Model To Biological Activity.
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