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For thousands of years, pharmacological knowledge coming from natural remedies, has been handed down from generation to generation, without any awareness of the ways in which preparations are made to face diseases. The advent of pharmaceutical chemistry and of the modern drug industry turned that lack of awareness into a scientific knowledge that changed the destiny of the human race. The twenty-eight chapters of this book, are taken from the lectures held by Professor Ettore Novellino every year in his course “Pharmaceutical Chemistry and Toxicology 2”. The first chapters address the basic notions of drugs, homeostasis, pharmacopoeia, and receptor; then, the different pharmaceutical classes are introduced by analyzing their pharmacological and chemical aspects. In particular, the structural study of the interaction between drugs and receptors or biological enzymes gives the fundamentals to connect the chemical and stereochemical properties of a compound family, with the biological activity, a correlation better known as Quantitative Structure-Activity Relationship (QSAR). Several examples of the synthesis of some of the most historically renown drugs, provided at the end of each chapter, integrate the book.

Metabotropic receptor --- Pharmaceutical Chemistry --- Quantitative Structure-Activity Relationship

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QSAR in Safety Evaluation and Risk Assessment provides comprehensive coverage on QSAR methods, tools, data sources, and models focusing on applications in products safety evaluation and chemicals risk assessment. Organized into five parts, the book covers almost all aspects of QSAR modeling and application. Topics in the book include methods of QSAR, from both scientific and regulatory viewpoints; data sources available for facilitating QSAR models development; software tools for QSAR development; and QSAR models developed for assisting safety evaluation and risk assessment. Chapter contributors are authored by a lineup of active scientists in this field. The chapters not only provide professional level technical summarizations but also cover introductory descriptions for all aspects of QSAR for safety evaluation and risk assessment.

Drugs --- QSAR (Biochemistry) --- Quantitative structure-activity relationships (Biochemistry) --- Structure-activity relationships (Biochemistry) --- Structure-activity relationship (Pharmacology) --- Pharmaceutical chemistry --- Pharmacology --- Structure-activity relationships. --- Quantitative Structure-Activity Relationship --- Consumer Product Safety --- Environmental Pollutants --- Toxicity Tests

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Drugs --- Xenobiotics --- QSAR (Biochemistry) --- Biology --- Chemistry --- Models, Molecular --- Structure-Activity Relationship --- Médicaments --- Xénobiotiques --- Relations structure-activité quantitatives (Biochimie) --- Structure-activity relationships --- Relations structure-activité --- Relationship, Structure-Activity --- Relationships, Structure-Activity --- Structure Activity Relationship --- Structure-Activity Relationships --- Molecular Models --- Model, Molecular --- Molecular Model --- Quantitative structure-activity relationships (Biochemistry) --- Foreign chemical compounds --- Foreign compounds --- Xenobiotic compounds --- Medicaments --- Medications --- Medicine (Drugs) --- Medicines (Drugs) --- Pharmaceuticals --- Prescription drugs --- Molecular Conformation --- Molecular Structure --- Structure-activity relationships (Biochemistry) --- Biochemistry --- Chemicals --- Bioactive compounds --- Medical supplies --- Pharmacopoeias --- Chemotherapy --- Materia medica --- Pharmacology --- Pharmacy --- Biology. --- Chemistry. --- Computer Graphics. --- Models, Molecular. --- Pharmacoloogy. --- Structure-Activity Relationship. --- Pharmacology. --- Computer Graphic --- Graphic, Computer --- Graphics, Computer --- Pharmacologies --- Pharmaceutical Preparations --- pharmacology

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Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates.

Machine learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Drugs --- Drug development. --- QSAR (Biochemistry) --- Cheminformatics. --- Machine learning --- Quantitative Structure-Activity Relationship --- Cheminformatics --- Machine Learning --- Drug Design --- Structure-activity relationships. --- Therapeutic use.

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Chemistry --- QSAR (Biochemistry) --- Structure-activity relationships (Biochemistry) --- Drugs --- Quantitative Structure-Activity Relationship. --- Combinatorial Chemistry Techniques. --- Biology. --- Pharmacology. --- Relations structure-activité quantitatives (Biochimie) --- Relations structure-activité (Biochimie) --- Médicaments --- Structure-activity relationships --- Relations structure-activité --- Structure-activity relationships. --- Health Sciences --- Life Sciences --- Biochemistry --- Pharmacy and Pharmacology --- Biochemorphology --- Biomolecules --- Chemical structure-biological activity relationships --- Relationships, Structure-activity (Biochemistry) --- Quantitative structure-activity relationships (Biochemistry) --- Structure-activity relationship (Pharmacology) --- Pharmacologies --- Pharmaceutical Preparations --- Chemistry Technic, Combinatorial --- Chemistry Technics, Combinatorial --- Chemistry Technique, Combinatorial --- Combinatorial Chemistry Technic --- Combinatorial Chemistry Technics --- Combinatorial Chemistry Technique --- Technic, Combinatorial Chemistry --- Technics, Combinatorial Chemistry --- Technique, Combinatorial Chemistry --- Chemistry Techniques, Combinatorial --- Techniques, Combinatorial Chemistry --- 3D-QSAR --- QSAR --- QSPR Modeling --- Quantitative Structure Property Relationship --- Structure Activity Relationship, Quantitative --- 3D QSAR --- 3D-QSARs --- Modeling, QSPR --- Quantitative Structure Activity Relationship --- Quantitative Structure-Activity Relationships --- Relationship, Quantitative Structure-Activity --- Relationships, Quantitative Structure-Activity --- Structure-Activity Relationship, Quantitative --- Structure-Activity Relationships, Quantitative --- Medicaments --- Medications --- Medicine (Drugs) --- Medicines (Drugs) --- Pharmaceuticals --- Prescription drugs --- pharmacology --- Physical biochemistry --- Pharmaceutical chemistry --- Pharmacology --- Gene Library --- Peptide Library --- Oligonucleotide Array Sequence Analysis --- High-Throughput Screening Assays --- Click Chemistry --- Bioactive compounds --- Medical supplies --- Pharmacopoeias --- Chemotherapy --- Materia medica --- Pharmacy --- Pharmacy, Therapeutics, & Pharmacology