Syntekabio Key Assets

Our platform has worked to identify druggable compounds and
increase your chances of discovering high-quality Hits & Leads.

DeepMatcher®

Understanding interactions between small molecules and their target proteins is crucial for drug discovery. DeepMatcher® is a compound-protein interaction (CPI) prediction platform that offers a unique opportunity to accelerate hit discovery, hit-to-lead, and lead optimization processes.
DeepMatcher® offers CPI prediction based on our proprietary biophysics-informed deep learning and large chemical spaces, thereby enabling more accurate discovery of compounds with novel structures.

DeepMatcher® has been successfully applied across protein families such as kinases, G protein coupled receptors (GPCR), and nuclear receptors.

Modularity of the DeepMatcher® platform offers a broad scope of services such as DeepMatcher®-Hit and DeepMatcher®-Lead. DeepMatcher®-Hit conducts a comprehensive screening to discover hit compounds using up to 10 billion compound library. DeepMatcher®-Lead performs hit-to-lead and lead optimization process by in silico design using a given scaffold generating 100K derivatives to improve binding affinity.

DEEPMATCHER

DeepMatcher®-Hit

DeepMatcher®-Hit conducts a comprehensive screening to discover hit compounds using up to 10 billion compound library.
Through analysis of the binding posture of target proteins and ligands, We provide basic data for discovering effective substances.

DeepMatcher®-Hit DeepMatcher®-Hit

DeepMatcher®-Lead

Physics-based deep learning enables reliable prediction of derivatives with improved potency.
DeepMatcher®-Lead performs hit-to-lead and lead optimization
process by in silico design using a given scaffold generating 100K derivatives to improve binding affinity.

DeepMatcher®-Lead DeepMatcher®-Lead

Data materials

Our platform has worked to identify druggable compounds, can increase the possibility of high-quality AI Hit discovery.

70%Indication coverage

70% Indication coverage 70% Indication coverage

AI models for avout 516 diseases from 747 indications suggested by therapeutic target database (TTD)

1491Targets

1491% Target coverage 1491% Target coverage

AI models for than 1491 targets pretrained and designed to indentify key compounds

99Targets

99% Indication coverage 99% Indication coverage

AI models for tox related 99 target proteins were pretrained and designed to predict side effect of the compound