Stereochemistry and drug efficacy and development: relevance of chirality to antidepressant and antipsychotic drugs
Bibliographic record
Abstract
Many drugs contain a chiral center or a center of unsaturation, or such centers result during metabolism of these drugs. Often such drugs are marketed as a mixture of the resultant enantiomers (racemates) or of geometric isomers, respectively. These enantiomers (molecules that are not superimposible on their mirror image) or geometric isomers may differ markedly from each other with regard to their pharmacodynamic and/or pharmacokinetic properties. This review deals primarily with drugs with chiral centers, and possible complications arising from the use of racemates are discussed. Recent developments in resolution of enantiomers, increased knowledge of the molecular structure of specific drug targets and a heightened awareness of several possible advantages of using single enantiomers rather than racemic mixtures of drugs have led to an increased emphasis on understanding the role of chirality in drug development. This has resulted in increased investigation of individual enantiomers early on in the development of drugs and in 'chiral switching', i.e. the replacement of a racemate of a drug which has already been approved or marketed by a single enantiomer. Although stereochemistry is an important matter to consider in drugs of virtually all classes, this review focuses on the relevance of chirality to antidepressant and antipsychotic drugs. Examples of the effects of chiral centers on the properties of antidepressants (tricyclics, selective serotonin reuptake inhibitors, monoamine oxidase inhibitors, viloxazine, bupropion, mianserin, venlafaxine, mirtazapine and reboxetine), antipsychotics and/or some of their metabolites are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".