RESUMO
Mutant KRAS is a major driver of oncogenesis in a multitude of cancers but remains a challenging target for classical small molecule drugs, motivating the exploration of alternative approaches. Here, we show that aggregation-prone regions (APRs) in the primary sequence of the oncoprotein constitute intrinsic vulnerabilities that can be exploited to misfold KRAS into protein aggregates. Conveniently, this propensity that is present in wild-type KRAS is increased in the common oncogenic mutations at positions 12 and 13. We show that synthetic peptides (Pept-ins™) derived from two distinct KRAS APRs could induce the misfolding and subsequent loss of function of oncogenic KRAS, both of recombinantly produced protein in solution, during cell-free translation and in cancer cells. The Pept-ins exerted antiproliferative activity against a range of mutant KRAS cell lines and abrogated tumor growth in a syngeneic lung adenocarcinoma mouse model driven by mutant KRAS G12V. These findings provide proof-of-concept that the intrinsic misfolding propensity of the KRAS oncoprotein can be exploited to cause its functional inactivation.
Assuntos
Neoplasias Pulmonares , Proteínas Proto-Oncogênicas p21(ras) , Animais , Camundongos , Linhagem Celular Tumoral , Neoplasias Pulmonares/genética , Mutação , Proteínas Oncogênicas/metabolismo , Proteínas Proto-Oncogênicas p21(ras)/genética , Dobramento de ProteínaRESUMO
BACKGROUND: Next-generation sequencing technologies yield large numbers of genetic alterations, of which a subset are missense variants that alter an amino acid in the protein product. These variants can have a potentially destabilizing effect leading to an increased risk of misfolding and aggregation. Multiple software tools exist to predict the effect of single-nucleotide variants on proteins, however, a pipeline integrating these tools while starting from an NGS data output list of variants is lacking. RESULTS: The previous version SNPeffect 4.0 (De Baets in Nucleic Acids Res 40(D1):D935-D939, 2011) provided an online database containing pre-calculated variant effects and low-throughput custom variant analysis. Here, we built an automated and parallelized pipeline that analyzes the impact of missense variants on the aggregation propensity and structural stability of proteins starting from the Variant Call Format as input. The pipeline incorporates the AlphaFold Protein Structure Database to achieve high coverage for structural stability analyses using the FoldX force field. The effect on aggregation-propensity is analyzed using the established predictors TANGO and WALTZ. The pipeline focuses solely on the human proteome and can be used to analyze proteome stability/damage in a given sample based on sequencing results. CONCLUSION: We provide a bioinformatics pipeline that allows structural phenotyping from sequencing data using established stability and aggregation predictors including FoldX, TANGO, and WALTZ; and structural proteome coverage provided by the AlphaFold database. The pipeline and installation guide are freely available for academic users on https://github.com/vibbits/snpeffect and requires a computer cluster.