Proteolysis-targeting chimeras (PROTACs) offer a novel therapeutic strategy for degrading disease-causing proteins, but designing effective degraders remains challenging. PROTACs function by inducing a ternary complex between the target protein and an E3 ligase, requiring structural insights for rational design. Key factors include linker optimization, attachment points, and warhead refinement. Computational approaches, particularly protein-protein docking, are essential for modeling ternary complexes and predicting critical interactions. However, existing docking methods struggle with cereblon (CRBN)-based ternary complexes. To address this, we introduce a computational approach combining HADDOCK protein-protein docking with induced fit PROTAC docking. Validated against 26 crystal structures from the Protein Data Bank (PDB), this method demonstrated high accuracy, especially for CRBN-based complexes. Additionally, molecular dynamics (MD) simulations of CRBN-BRD4-BD1 complexes (PDB IDs 6BN7, 6BOY) provided insights into complex stability through buried surface area and radius of gyration calculations. This validated approach was then applied to five Ataxia telangiectasia and RAD3-related (ATR) kinase PROTACs, enabling modeling in the absence of experimental structures. Our method provides a robust framework for optimizing and designing novel PROTACs targeting diverse proteins.

Background/Objectives: Acute myeloid leukemia (AML) is a hematological malignancy frequently driven by mutations in the FLT3 gene, particularly internal tandem duplications (FLT3-ITD), which contribute to aberrant cell proliferation and resistance to tyrosine kinase inhibitors (FLT3i). The limitations of current FLT3i therapies, including drug resistance, off-target effects, and poor selectivity, necessitate the development of novel therapeutic strategies. Proteolysis-targeting chimeras (PROTACs) represent a promising approach to achieving degradation of oncogenic proteins. Methods: We developed FLT3-targeting PROTACs based on the previously described compound MA49, with a focus on linker modifications to improve degradation efficiency and pharmacokinetic properties. Results: Among these, compounds MA190 and MA191, containing rigid cyclohexyl-piperidine/piperazine linkers, demonstrate superior degradation of FLT3-ITD in MV4-11 AML cells at nanomolar concentrations, achieving >95% reduction in FLT3-ITD levels, outperforming MA49. In addition to improved kinase selectivity, good solubility, and plasma stability, MA190 and MA191 also exhibit excellent metabolic stability, whereas the predecessor PROTAC MA49 was unstable in microsomal assays. In cellular assays, MA190 and MA191 induce potent apoptosis in FLT3-ITD⁺ AML cells but have minimal effects on cells with wild-type FLT3. Proteomics reveal that MA191 also degrades MAPK14 (p38α), a kinase upregulated in leukemia, in addition to FLT3. Conclusions: Dual targeting of FLT3-ITD and MAPK14 enhances proapoptotic signaling without any cytotoxic effect on normal human HEK293 cells. The co-inhibition using MA191 or a combination of doramapimod (a MAPK14 inhibitor) with a non-degrading FLT3 inhibitor result in greater caspase-3 activation than either treatment alone. This synergistic effect can be a therapeutic advantage, as several oncogenic drivers are switched off simultaneously by MA191.

Acute myeloid leukemia (AML) is a hematological malignancy frequently driven by mutations in the FLT3 gene, particularly internal tandem duplications (FLT3-ITD), which contribute to aberrant cell proliferation and resistance to tyrosine kinase inhibitors (FLT3i). The limitations of current FLT3i therapies, including drug resistance, off-target effects, and poor selectivity, necessitate the development of novel therapeutic strategies. Proteolysis-targeting chimeras (PROTACs) represent a promising approach to achieve selective degradation of oncogenic proteins. We developed and characterized an optimized series of FLT3-targeting PROTACs based on our previously described compound MA49, with a focus on linker modifications and pharmacophore optimization to improve degradation efficiency and pharmacokinetic properties. Among these, compounds MA190 and MA191,containing rigid cyclohexyl-piperidine/piperazine linkers, demonstrate superior degradation of FLT3-ITD in MV4-11 AML cells at nanomolar concentrations, achieving >95% reduction in FLT3-ITD levels, outperforming MA49. These compounds exhibit good solubility, high chemical and plasma stability, and improved kinase selectivity. In cellular assays, MA190 and MA191 induce potent apoptosis in FLT3-ITD+ AML cells but have minimal effects on cells with wild-type FLT3. Proteomic analysis reveal that MA191 also degrades MAPK14 (p38α), a kinase upregulated in leukemia, in addition to FLT3. Dual targeting of FLT3-ITD and MAPK14 enhances pro-apoptotic signaling. The co-inhibition using MA191 or a combination of doramapimod (a MAPK14 inhibitor) with a non-degrading FLT3 inhibitor results in greater caspase-3 activation than either treatment alone. This synergistic effect underscores the therapeutic advantage of degrading multiple oncogenic drivers simultaneously.

Proteolysis targeting chimeras (PROTACs) have proven to be a novel approach for the degradation of disease-causing proteins in drug discovery. One of the E3 ligases for which efficient PROTACs have been described is the Von-Hippel-Lindau factor (VHL). However, the development of PROTACs has so far often relied on a minimum of computational tools, so that it is mostly based on a trial-and-error process. Therefore, there is a great need for resource- and time-efficient structure-based or computational approaches to streamline PROTAC design. In this study, we present a combined computational approach that integrates static ternary complex formation, induced fit docking, and molecular dynamics (MD) simulations. Our methodology was tested using four experimentally derived ternary complex structures of VHL PROTACs, reported for BRD4, SMARCA2, FAK and WEE1. In addition, we applied the validated approach to model a recently in-house developed FLT3-targeted PROTAC (MA49). The results show that static ternary models generated with a protein-protein docking method implemented in the software MOE have a high predictive power for reproducing the experimental 3D structures. The induced fit-docking of different active PROTACs to their respective models showed the reliability of this model for the development of new VHL-mediated degraders. In particular, the induced-fit docking was sensitive to structural changes in the PROTACs, as evidenced by the failed binding modes of the PROTAC negative controls. Furthermore, MD simulations confirmed the stability of the generated complexes and emphasized the importance of dynamic studies for understanding the relationship between PROTAC structure and function.

Proteolysis-targeting chimeras (PROTACs) offer a novel therapeutic strategy for degrading disease-causing proteins, but designing effective degraders remains challenging. PROTACs function by inducing a ternary complex between the target protein and an E3 ligase, requiring structural insights for rational design. Key factors include linker optimization, attachment points, and warhead refinement. Computational approaches, particularly protein-protein docking, are essential for modeling ternary complexes and predicting critical interactions. However, existing docking methods struggle with cereblon (CRBN)-based ternary complexes. To address this, we introduce a computational approach combining HADDOCK protein-protein docking with induced fit PROTAC docking. Validated against 26 crystal structures from the Protein Data Bank (PDB), this method demonstrated high accuracy, especially for CRBN-based complexes. Additionally, molecular dynamics (MD) simulations of CRBN-BRD4-BD1 complexes (PDB IDs 6BN7, 6BOY) provided insights into complex stability through buried surface area and radius of gyration calculations. This validated approach was then applied to five Ataxia telangiectasia and RAD3-related (ATR) kinase PROTACs, enabling modeling in the absence of experimental structures. Our method provides a robust framework for optimizing and designing novel PROTACs targeting diverse proteins.