Tesorai Refine
Reducing false discovery in high-throughput assays
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High-throughput assays are built for speed/scale, at the cost of high false discovery rates (in some cases over 90%)
Proteomics and mass spectrometry data is instrumental in discovery efforts but can be challenging to interpret
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Types of assays
Affinity purification with mass spectrometry (APMS), covalent fragment screens with mass spectrometry, DNA-encoded libraries, phage displays, small-molecule binding/activity assays, ribosome profiling
False discovery rate
Assays are noisy, resulting in high false-positive rates (for example, only ~5% of interactions detected in APMS are biologically relevant), with likely large false-negative rates too
Challenges with interpreting data
Biases like sampling and detection favor abundant analytes, alongside unspecific interactions and plate/batch effects, impacting analysis. Limited labels hinder standard AI/ML in custom applications.
Impact
Relying on intensities measured by the assays alone can be misleading, and can lead to high failure rates
Tesorai is replacing current experiment-constrained manual engineering and simplistic modeling with data integration and deep learning
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Current ranking model improves upon the gold standard ranking algorithm
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Identification of High Potential Protein-Protein Interactions (PPI)
* This evaluation is performed on the ProteomeTools dataset (a set of chemically synthesized peptides)
** This rate represents an identification rate of 92%
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Identification of High Potential Protein-Protein Interactions (PPI)
* evaluated on a left-out organism and PRIDE project (Arabidopsis thaliana)
Assay types that Onyx suite can be applied to
Identification of new Protein-Protein Interactions (PPI)
Affinity purification & mass spectrometry (AP-MS)
Antibody-antigen mapping
Molecular glues validation
Identification of New Protein- Ligand Interactions (PLI)
Chemoproteomics
Hit identification from High-throughput assays, including by improving batch and plate effects
DNA-encoded libraries
Improving properties of individual molecules
Protein stability
Peptide solubility
Small-molecule library design
Custom Fine-Tuned AI Model
We can leverage our foundation models to address unique challenges in analyzing high-throughput assays with proteins, peptides, and/or small molecules.
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