BACKGROUND: Bupropion, one of the dual norepinephrine and dopamine reuptake inhibitors (NDRIs), is an aminoketone derivative performed effect in improving cognitive function for depression. However, its therapeutic effect is unsatisfactory due to poor clinical response, and there are only few derivatives in pre-clinical settings. OBJECTIVE: This work attempted to elucidate the essential structural features for the activity and designed a series of novel derivatives with good inhibitive ability, pharmacokinetic and medicinal chemistry properties. METHODS: The field-based QSAR of aminoketone derivatives of two targets were established based on docking poses, and the essential structural properties for designing novel compounds were supplied by comparing contour maps. RESULTS: The selected two models performed good predictability and reliability with R2 of 0.8479 and 0.8040 for training set, Q2 of 0.7352 and 0.6266 for test set respectively, and the designed 29 novel derivatives performed no less than the highest active compound with good ADME/T pharmacokinetic properties and medicinal chemistry friendliness. CONCLUSIONS: Bulky groups in R1, bulky groups with weak hydrophobicity in R3, and potent hydrophobic substituted group with electronegative in R2 from contour maps provided important insights for assessing and designing 29 novel NDRIs, which were considered as candidates for cognitive dysfunction with depression or other related neurodegenerative disorders.

Positive allosteric modulators (PAMs) of metabotropic glutamate receptor 2 (mGlu2) is well-known strategy in treatment of psychiatric disorders with the higher selectivity and lower tolerance risk. A mount of PAMs...

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Mammalian target of rapamycin (mTOR) is a protein serine/threonine kinase playing the central downstream role in multiple mitogenic signalling pathways. As a c entral regulator of cell growth, proliferation, differentiation and survival, mTOR has b een reported to modulate proliferation and angiogenesis in neoplastic processes. Curre ntly, sirolimus and its analogues the only five mTOR inhibitors approved for clinical u se, which shows a great capacity in anticancer therapy. However, endocrine resistance in cancer therapy has been observed in sirolimus analogues, and the unavailability of n ew mTOR inhibitor besides similar structure of sirolimus analogues makes the resistan ce even worse. It is urgent to discovery new mTOR inhibitors as candidates for develo pment of effective anticancer drugs. In this study, support vector machine (SVM) as a virtual screening strategy was proposed. SVM models of mTOR inhibitors were constr ucted by training data published before 2012, and the ones published after 2012 as test set were used to verify according to cross validation. The selected model performed thi n false hit rates of 0.12% and 0.46% by screening PubChem and MDDR chemical libr aries respectively. As results, 9 novel novel scaffolds for mTOR were identified, and 6 of them have been reported their anticancer-related therapeutic capacity. In summary, SVM performed its ability to identify novel mTOR inhibitors, which can supply some candidates for mTOR anticancer drugs, and supply effective method for anticancer dru g discovery in future.