Abstract IA008: Leveraging conformational dynamics for improved selectivity

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Abstract Maximizing the clinical activity and combinability of oncogene inhibitors requires the development of molecules that can achieve necessary levels of target inhibition at a tolerated and feasible human dose. This is enabled by improving selectivity against off-targets and/or for the mutant form of the target over wild-type. While conventional structural insights can inform the design of selective drug candidates, there are often cases where clear selectivity hypotheses are not readily identifiable. Here, we present two examples illustrating how conformational dynamics can be leveraged to obtain improved selectivity for validated oncogene targets. The first example focuses on the selective inhibition of FGFR2, a well-established target in various cancers harboring FGFR2 fusions or rearrangements. Although clinical efficacy of pan-FGFR inhibitors has been demonstrated, their benefit is limited by FGFR1- and FGFR4- mediated toxicities. We leveraged differences in conformational dynamics between FGFR2 and other FGFRs observed through molecular dynamics simulations to enable the development of Lirafugratinib, the first FGFR2 selective inhibitor. Lirafugratinib inhibits FGFR2 with a high degree of selectivity in pre-clinical models. In cancer patients, Lirafugratinib achieves >95% FGFR2 occupancy at a dose of 70mg once daily, with minimal evidence of inhibition of other FGFR isoforms. This improved selectivity translates to higher objective response rates compared to pan-FGFR inhibitors across multiple tumor types harboring FGFR2 fusions or rearrangements. The second example illustrates mutant-selective targeting of PI3Kα, the most frequently mutated kinase in cancer. While non-mutant selective inhibitors have shown clinical efficacy, their benefit is limited by hyperglycemia caused by inhibition of wild-type PI3Kα. Conformational differences between mutant and wild-type PI3Kα were identified using structural insights combined with molecular dynamics simulations, leading to the discovery of RLY-2608- the first mutant-selective inhibitor of PI3Kα. RLY-2608 binds to a novel allosteric pocket and demonstrates mutant selective inhibition in pre-clinical models. RLY-2608 has a favorable pharmacokinetic profile in cancer patients, with dose-dependent increases in exposure and low peak to trough fluctuations, resulting in high levels of target coverage throughout the dosing interval. When combined with fulvestrant, this translates into a higher objective response rate and lower rate of hyperglycemia in patients with hormone-receptor positive, PI3Kα-mutant breast cancer compared to non-mutant selective PI3Kα inhibitors. These examples demonstrate the power of leveraging conformational dynamics to obtain selective target inhibition, ultimately translating into improved patient outcomes. Citation Format: James Watters. Leveraging conformational dynamics for improved selectivity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr IA008.