Rational design of lead compounds targeting monoamine transporters (MATs) is critical to developing novel therapeutics to treat psychiatric disorders including depression and substance abuse. A 3-D dopamine transporter (DAT) computer model was used to virtually screen a commercially available small molecule library for high DAT affinity drug-like compounds. One hit, coded "MI-4", inhibited human dopamine, norepinephrine, and serotonin transporters in vitro. In vivo administration in mice induced robust, dose-dependent antidepressant-like behaviors in learned helplessness models (tail suspension and forced swim tests). Moreover, chronic administration (21day, 10mg/kg, bid) reduced drinking latencies comparable to fluoxetine (10mg/kg, bid) in the novelty-induced hypophagia test, which requires chronic treatment to produce antidepressant-like effects. MI-4 (10mg/kg, bid) produced rapid (three-day) antidepressant-like effects in the social avoidance test following 10days of social defeat stress. Unlike ketamine, chronic administration of MI-4 increased social interaction scores while improving resiliency to the mood-altering effects of stress to over 70%. Importantly, MI-4 exhibited minimal abuse liability in behavioral and neurological models (conditioned place preference and dopamine in vivo microdialysis). MI-4 was found to be Ro-25-6981, an ifenprodil analog and reputed NMDA antagonist. The data suggest that Ro-25-6981, previously known for rapid-acting glutamatergic antidepressant actions, may also functionally inhibit monoamine reuptake and produces sustained antidepressant effects in vivo. This demonstrates, as proof of principle, the viability of combining these mechanisms to produce rapid and sustained antidepressant-like effects. Overall, these findings suggest MAT computational model-based virtual screening is a viable method for identifying antidepressant lead compounds of unique scaffold.