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Although lung adenocarcinoma patients have benefited from the development of targeted therapy, patients with lung squamous cell carcinoma (SqCC) have no effective treatment due to the complexity and heterogeneity of the disease. Therefore, basing on the genetic analysis of mutations in lung squamous cell carcinoma to design multi-target inhibitors represents a potential strategy for the medical treatment. In this study, through screening an in-house focused library, we identified an interesting indazole scaffold. And following with binding analysis, we elaborated the structure-activity relationship of this hit compound by optimizing four parts guided by the DDR2 enzymatic assay, which resulted in a potent lead compound 10a. We conducted further optimization of dual enzymatic inhibitions towards FGFR1 and DDR2, two important kinases in lung squamous cell carcinoma. Finally, from the cellular antiproliferative activity tests and in vivo pharmacokinetic test, 3-substituted indazole derivative 11k was found to be a promising candidate and subjected to in vivo pharmacology study with the mouse xenograft models, demonstrating profound anti-tumor efficacy. Additional in vitro druglike assessment reinforced that compound 11k could be valuable for SqCC drug development.

The introduction of the multi-objective optimization has dramatically changed the virtual combinatorial library design, which can consider many objectives simultaneously, such as synthesis cost and drug-likeness, thus may increase positive rates of biological active compounds. Here we described a software called CCLab (Combinatorial Chemistry Laboratory) for combinatorial library design based on the multi-objective genetic algorithm. Tests of the convergence ability and the ratio to re-take the building blocks in the reference library were conducted to assess the software in silico, and then it was applied to a real case of designing a 5 × 6 HDAC inhibitor library. Sixteen compounds in the resulted library were synthesized, and the histone deactetylase (HDAC) enzymatic assays proved that 14 compounds showed inhibitory ratios more than 50% against tested 3 HDAC enzymes at concentration of 20 μg/mL, with IC50 values of 3 compounds comparable to SAHA. These results demonstrated that the CCLab software could enhance the hit rates of the designed library and would be beneficial for medicinal chemists to design focused library in drug development (the software can be downloaded at: http://202.127.30.184:8080/drugdesign.html ).