Virtual ADMET Assessment in Target Selection and Maturation.
Drug development MEDICAL sähkökirjat
IOS Press
2006
EISBN 9781429467728
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.
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.
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.
Case Study: Human Plasma Protein Binding; Molecular Descriptors for Predicting ADMET Properties; Molecular Fields to Assess Recognition Forces and Property Spaces.
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.
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.
