IBM continues to lead the quantum cloud, but faces real competition to service early quantum applications. Building the future of this market still looks like a long game. It may be more important to pick a partner with the right strategy than just to compare today’s product features. The post...
In contrast to the hype, the early applications of quantum computers look modest. But they do exist. The talented teams developing quantum algorithms still have a fight on their hands to bring forward the date of true broad quantum advantage. What might be achieved and when? The post Quantum Algorithms...
IBM continues to dominate the quantum cloud. However access to new more powerful processors will increase competition in the early adopter market. Ideas for user-engagement and education continue to explode with innovation. In the long term, supporting developers is a challenge the conventional software industry understands, but don’t forget that...
AlphaFold 2.0 is widely regarded as a breakthrough milestone in predicting 3D structures of proteins using a Deep Neural Network approach. Naturally, when the AlphaFold paper was published and its source code made publicly available earlier this month, we curious...
In the previous post, we discussed using Visual Studio Code to enhance Python editing with various features, such syntax highlighting and keyboard shortcuts. This post introduces the tools Pylint and Black for automatically resolving the problems of Python code style.If you’re...
Choosing a good code editor for scienceIf an artist is only as good as their tools, then I spent years finger-painting, followed by years getting hand cramps from paint-brushes I couldn’t figure out how to hold correctly.When I was in High...
(is there any other type of scientist?)Although there are many Python tutorials for beginners and scientists, there aren’t any that guide a fledgling Scientific Pythonista through the wide range of Python features and tools. After you’ve mastered functions and familiarized...
Underrated Machine Learning Papers for Protein DesignProteinQure is a top 100 AI Company determined by CB InsightsCB Insights (a leading tech and startup publication) has included ProteinQure as a top AI company in the Healthcare space for 2020. We thought we could...
Computational protein drug design.
ProteinQure uses artificial intelligence and quantum computing for the computational design of protein drugs. Antibodies, peptides, and other protein-based drugs have low toxicity and are capable of targeting a broad range of biological targets outside the scope of traditional small molecule therapeutics. Due to their structural complexity and dynamic flexibility, novel protein-based drugs are challenging to discover. Our software enables the rational design of protein-based drugs via atomistic simulations of the protein folding and binding process.
ProteinQure is a Toronto based biotech firm. We create computational R&D tools to perform drug design in silico. We leverage quantum computing, molecular simulations and reinforcement learning to engineer novel therapeutics.
Protein drugs of tomorrow
Despite their inherent advantages, it is very difficult to design protein based therapeutics.
ProteinQure is building scalable technologies to aid in structure based protein design.
We design small peptide based therapeutics (including cyclic peptides).
Structure Based Design
Exploring protein structures without data or known crystal structures.
Quantum computing, artificial intelligence and molecular dynamics simulations.
The first step to designing large protein-based drugs beyond the current paradigm.