Unknown

Dataset Information

0

COTI-2, a novel small molecule that is active against multiple human cancer cell lines in vitro and in vivo.


ABSTRACT: Identification of novel anti-cancer compounds with high efficacy and low toxicity is critical in drug development. High-throughput screening and other such strategies are generally resource-intensive. Therefore, in silico computer-aided drug design has gained rapid acceptance and popularity. We employed our proprietary computational platform (CHEMSAS®), which uses a unique combination of traditional and modern pharmacology principles, statistical modeling, medicinal chemistry, and machine-learning technologies to discover and optimize novel compounds that could target various cancers. COTI-2 is a small molecule candidate anti-cancer drug identified using CHEMSAS. This study describes the in vitro and in vivo evaluation of COTI-2. Our data demonstrate that COTI-2 is effective against a diverse group of human cancer cell lines regardless of their tissue of origin or genetic makeup. Most treated cancer cell lines were sensitive to COTI-2 at nanomolar concentrations. When compared to traditional chemotherapy or targeted-therapy agents, COTI-2 showed superior activity against tumor cells, in vitro and in vivo. Despite its potent anti-tumor efficacy, COTI-2 was safe and well-tolerated in vivo. Although the mechanism of action of COTI-2 is still under investigation, preliminary results indicate that it is not a traditional kinase or an Hsp90 inhibitor.

SUBMITTER: Salim KY 

PROVIDER: S-EPMC5173065 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

COTI-2, a novel small molecule that is active against multiple human cancer cell lines in vitro and in vivo.

Salim Kowthar Y KY   Maleki Vareki Saman S   Danter Wayne R WR   Koropatnick James J  

Oncotarget 20160701 27


Identification of novel anti-cancer compounds with high efficacy and low toxicity is critical in drug development. High-throughput screening and other such strategies are generally resource-intensive. Therefore, in silico computer-aided drug design has gained rapid acceptance and popularity. We employed our proprietary computational platform (CHEMSAS®), which uses a unique combination of traditional and modern pharmacology principles, statistical modeling, medicinal chemistry, and machine-learni  ...[more]

Similar Datasets

| S-EPMC3789203 | biostudies-literature
| S-EPMC3899067 | biostudies-literature
| S-EPMC3823742 | biostudies-literature
| S-EPMC5694348 | biostudies-literature
| S-EPMC1794057 | biostudies-literature
| S-EPMC5050114 | biostudies-literature
| S-EPMC4174574 | biostudies-literature
| S-EPMC7016295 | biostudies-literature
| S-EPMC8125180 | biostudies-literature
| S-EPMC6091197 | biostudies-literature