QSAR in Development of Antidepressants

QSAR in Development of Antidepressants QSAR in Development of Antidepressants

chem.memphis.edu
from chem.memphis.edu More from this publisher
01.04.2015 Views

Leads and biological activity IC 50 (nM) Drug TCAs imipramine nortriptyline protriptyline trimipramine Second generation Amoxapine mirtazapine venlafazine fluoxetine fluvoxamine paroxetine sertaline Norepinephrine 25 6 10 5000 25 40 300 200 500 70 300 5-HT 50 200 250 10000 600 20000 50 15 5 1 4

QSAR Design • Create training set – consisting of known antidepressant and biological activity • activity –log IC 50 – structures built in MOE – 20 current antidepressant • all descriptors for Cerius2 used – except alignment family • Generate QSAR equation – Genetic Function Approximation(GFA) • Activity independent variable • Descriptors dependent variable • Validate the equation – Test set • 5 other antidepressant with known biological activity • Predict activity – New leads

<strong>QSAR</strong> Design<br />

• Create tra<strong>in</strong><strong>in</strong>g set<br />

– consist<strong>in</strong>g <strong>of</strong> known antidepressant and biological activity<br />

• activity –log IC 50<br />

– structures built <strong>in</strong> MOE<br />

– 20 current antidepressant<br />

• all descriptors for Cerius2 used<br />

– except alignment family<br />

• Generate <strong>QSAR</strong> equation<br />

– Genetic Function Approximation(GFA)<br />

• Activity <strong>in</strong>dependent variable<br />

• Descriptors dependent variable<br />

• Validate the equation<br />

– Test set<br />

• 5 other antidepressant with known biological activity<br />

• Predict activity<br />

– New leads

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!