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 1 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 1 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