Versatility to address multiple modalities and MoA
No matter the complexity of your project—from designing a small molecule inhibitor or a protein-protein interaction (PPI) inhibitor to finding molecular glues—our platform is built to deliver.
We don't rely on a single approach. Instead, we utilize an integrated, proprietary suite of tools that combines trusted methods with advanced quantum mechanics, ensuring we apply the exact blend of techniques needed to achieve your specific objectives.
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Our unique blend of familiar tools such as FEP and Boltz2, with our advanced quantum methods such as QMMM, DFT and post-Hartree Fock calculations in our Molecular Modeling engine, provide high resolution understanding of the active site.
Unlike other technologies, we can model the transition state with unparalleled accuracy enabling the design of compounds with exquisite potency and selectivity, combined with valuable insights that drive compound optimisation.
Kuano has repeatedly delivered such outcomes across target classes such as metalloproteases, methyltransferases, and phosphatases. For our case studies click here
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Successfully tackling allosteric sites requires accurately modelling dynamic, long-range conformational changes within a protein. This complex task pushes traditional computational methods beyond their limits, leading to high failure rates when attempting to design selective and effective modulators.
Kuano’s integrated approach, blending essential industry tools like FEP and Boltz2 with our proprietary, advanced quantum methods within our Molecular Modeling engine, enables us to accurately map and model allosteric binding sites within the protein. We can predict precisely how binding at a distal site alters the active site, providing unparalleled mechanistic insight into function and regulation. This intelligence guides the design of highly selective, effective allosteric compounds.
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The successful design of molecular glues is severely hindered by the limitations of traditional modelling, which struggle to accurately capture shallow, dynamic protein-protein interfaces and the critical phenomenon of induced proximity required to form the active ternary complex.
Kuano’s solution brings a high-resolution approach integrating familiar, high-performance industry tools like FEP and virtual screening with our proprietary, advanced Molecular Modelling engine.
This engine leverages state-of-the-art quantum methods, such as DFT and QM/MM, to provide enhanced accuracy and predictive power.
This unique combination will allow us to move beyond simple docking to model the interactions necessary for binding with unparalleled accuracy. We will provide the enhanced understanding of induced proximity and novel, mechanistic insights needed to drive the design and optimization of molecular glue compounds with confidence and speed.
Please talk to us about how our platform could be tailored for your project.
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Only advanced quantum methods can reveal the influence of other residues, the environment, and ligand chemistry on covalent reactivity, This holistic picture enables predictivity beyond the simplistic world of ‘residue + warhead’ to explain real-world observations.
At Kuano, we create ‘quantum fingerprints’ that describe the system at quantum level, from which we can pick out the reactivity.
This approach is amino-acid agnostic: we can look as easily ‘beyond Cysteine’ than at cysteine; we can explore novel warheads . The first step was to prove that our platform explained covalent reactivity in a way that no other methods could: check out our case study on JAK3 and EGFR here
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Designing successful PPI inhibitors requires methods that can manage the complexity of large, shallow, and highly dynamic protein interfaces. In many cases, a lack of high-resolution accuracy prevents reliable prediction of binding and severely limits the discovery of novel compounds.
Our integrated approach can be applied to overcome these challenges. We leverage a blend of established industry tools, such as FEP and PharmacoJump, alongside our proprietary, advanced quantum methods within our Molecular Modeling engine.
Our powerful combination enables us to accurately model the full dynamic interface, capture subtle conformational changes upon binding, and predict the precise energetic hotspots.
This deep mechanistic understanding and valuable, predictive insights, facilitate the optimization of compounds against challenging protein surfaces.
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Our platform can tackle multiple modalities: the specialist quantum techniques, deep expertise and integration with high-power conventional tools, produces a specific technology with a versatile range of applications. Exactly what is needed in an industry that innovates fast and where modalities are evolving everyday.
But successful solutions still begin with a proper understanding of the challenge.
We will work with you to elucidate which of our traditional or proprietary Kuano tools should be deployed to solve your practical drug discovery problem.