ProteinQure uses artificial intelligence and physics-based methods for the computational design of de-novo protein therapeutics. Antibodies, peptides, and other protein-based drugs are capable of targeting a broad range of biological targets outside the scope of traditional small molecule therapeutics. Due to their structural complexity, size and dynamic flexibility, computational methods for biologics are just now becoming possible. Our computational platform enables the world leading drug discovery companies to advance their early stage programs and is less data dependent than the alternatives.
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Welcome to computational protein drug design.
We are unlocking the potential of protein-based therapeutics
We design novel peptides (incl. cyclic and non-natural), with 100x better drug-like properties.
We do not need large experimental data sets.
We optimize for any functional assay
with < 100 data points.
Peptides can deliver numerous payloads intracellularly
with tissue specificity (ASOs, siRNA, radioisotopes).
High-performance supercomputing, artificial
intelligence and molecular dynamics simulations.
We use computational tools to enable peptide ligands which are 100x more drug-like and specific than natural ligands. This enables the next generation of therapeutic applications with a focus on next generation therapeutic payloads (nucleotides, siRNA, radioisotopes, etc.) delivered with de-novo peptides.
ProteinQure has built a world-class computational platform for peptide drug discovery, combining high-performance computing, molecular simulations and machine learning to design and optimize small exotic peptide therapeutics. These physics-based methods enable the structure-based design of novel ligands and make us less dependent on large data sets. We routinely work with less than 100 experimental data points for lead optimization.
We have three collaborations with top 25 pharma companies and have successfully validated our compounds in their experimental assays. We use our computational platform as well as wetlab validation to solve our drug design challenges and are now beginning to develop an internal pipeline.
We engineer hits which are novel chemical entities. Peptides are one of the fastest growing classes of therapeutics with applications across all major disease indications. Our platform is designed to iterate with experimental results to save you money and time.
We perform iterative optimization of therapeutic leads to preserve properties like binding affinity, selectivity, stability and solubility. This multi-parameter optimization requires a search over vast areas of sequence space.
We own proprietary structure-biased libraries based on display methods that we can screen. We also work with partners to create custom computationally designed libraries to incorporate specific constraints and motifs.
Despite their inherent advantages, it is very difficult to design protein-based therapeutics.
Computational tools have been previously held back because of proteins' larger size and the lack of available structural data.
We leverage physics-based methods and novel machine learning algorithms to overcome these challenges.
By choosing tissue-restricted targets which undergo internalization, we ensure that the therapeutic payload is going to the right cells. Their small size also enhances tissue penetration.
Peptides can be engineered to be non-immunogenic by design, we can also achieve an unprecedented range of necessary PK profiles.
Peptide conjugates are much easier to manufacture. Novel chemistries allow for a wide range of conjugations and they can succeed in many routes of administration.
We are located in downtown Toronto; one of the fastest growing tech hubs in North America. At the heart of the university and life sciences ecosystems, we benefit from great relationships with the surrounding players in AI and biotech.
Interested in learning more? Come talk to us!
Office Address: 119 Spadina Ave Suite 304, Toronto, ON M5V 2L1, Canada
E-Mail: team@proteinqure.com
Web: www.proteinqure.com
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