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Virtual ADMET Assessment in Target Selection and Maturation.
Today, biologists and medicinal chemists realize that there is a strong relationship between pharmacodynamic (what the drug does to the organism) and pharmacokinetic (what the organism does to the drug) effects. A significant contributing factor to the evolution in drug discovery was the methodologi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
IOS Press,
2006.
|
| Colección: | Solvay Pharmaceuticals Conferences ;
v. 6. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 1 | 0 | |a Virtual ADMET Assessment in Target Selection and Maturation. |
| 260 | |a Amsterdam : |b IOS Press, |c 2006. | ||
| 300 | |a 1 online resource (268 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 490 | 1 | |a Solvay Pharmaceuticals Conferences, |x 1566-7685 ; |v v. 6 | |
| 505 | 0 | |a Preface; List of Contributors; Contents; Conference Preface; The Risky Business of Developing Drugs; Benefits and Limits of in Silico Predictions; Musings on ADME Predictions and Molecular Structure; Lipophilicity: Its Calculation and Application in ADMET Predictions; Interpretation of the Role of the Electrotopological State and Molecular Connectivity Indices in the Prediction of Physical Properties and ADME-Tox Behavior -- Case Study: Human Plasma Protein Binding; Molecular Descriptors for Predicting ADMET Properties; Molecular Fields to Assess Recognition Forces and Property Spaces. | |
| 505 | 8 | |a Extracting Pharmacophores from Bio-Active MoleculesIn Silico Models for Human Bioavailability; In Silico Models to Predict Brain Uptake; Algorithms to Predict Affinity for Transporters; Predicting Affinity for and Metabolism by Cytochromes P450; Expert Systems to Predict Biotransformation; Expert Systems to Predict Toxicity; From in Vivo to in Vitro/in Silico ADME: Progress and Challenges; Author Index. | |
| 520 | |a Today, biologists and medicinal chemists realize that there is a strong relationship between pharmacodynamic (what the drug does to the organism) and pharmacokinetic (what the organism does to the drug) effects. A significant contributing factor to the evolution in drug discovery was the methodological and technological revolution with the advent of combinatorial chemistry, high-throughput screening and profiling, and in silico prediction of target-based activity and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties. High-throughput screening and in silico methods. | ||
| 588 | 0 | |a Print version record. | |
| 504 | |a Includes bibliographical references and index. | ||
| 546 | |a English. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
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| 650 | 0 | |a Drug development |x Data processing |v Congresses. | |
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| 650 | 0 | |a Pharmacokinetics. | |
| 650 | 0 | |a Drugs |x Design. | |
| 650 | 2 | |a Pharmaceutical Preparations | |
| 650 | 2 | |a Pharmacokinetics | |
| 650 | 2 | |a Drug Design | |
| 650 | 2 | |a Computational Biology | |
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| 650 | 6 | |a Médicaments |x Développement |v Congrès. | |
| 650 | 6 | |a Médicaments. | |
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| 700 | 1 | |a Turski, L. | |
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