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Structure-based molecular modeling in SAR analysis and lead optimization.

ABSTRACT: In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose.

SUBMITTER: Temml V

PROVIDER: S-EPMC7979990 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Many agents targeting the colchicine binding site in tubulin have been developed as potential anticancer agents. However, none has successfully made it to the clinic, due mainly to dose limiting toxicities and the emergence of multi-drug resistance. Chalcones targeting tubulin have been proposed as a safe and effective alternative. We have shown previously that quinolone chalcones target tubulin and maintain potent anti-proliferative activity vis-à-vis colchicine, while also having high tolerability and low toxicity in mouse models of cancer and refractivity to multi-drug resistance mechanisms. To identify the most effective anticancer chalcone compound, we synthesized 17 quinolone-chalcone derivatives based on our previously published CTR-17 and CTR-20, and then carried out a structure-activity relationship study. We identified two compounds, CTR-21 [((E)-8-Methoxy-3-(3-(2-methoxyphenyl)-3-oxoprop-1-enyl) quinolin-2(1H)-one)] and CTR-32 [((E)-3-(3-(2-ethoxyphenyl)-3-oxoprop-1-enyl) quinolin-2(1H)-one)] as potential leads, which contain independent moieties that play a significant role in their enhanced activities. At the nM range, CTR-21 and CTR-32 effectively kill a panel of different cancer cells originated from a variety of different tissues including breast and skin. Both compounds also effectively kill multi-drug resistant cancer cells. Most importantly, CTR-21 and CTR-32 show a high degree of selectivity against cancer cells. In silico, both of them dock near the colchicine-binding site with similar energies. Whereas both CTR-21 and CTR-32 effectively prevents tubulin polymerization, leading to the cell cycle arrest at G2/M, CTR-21 has more favorable metabolic properties. Perhaps not surprisingly, the combination of CTR-21 and ABT-737, a Bcl-2 inhibitor, showed synergistic effect in killing cancer cells, since we previously found the "parental" CTR-20 also exhibited synergism. Taken together, CTR-21 can potentially be a highly effective and relatively safe anticancer drug.

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Structure-based molecular modeling in SAR analysis and lead optimization.

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