AxDrug® – AI & Computational Chemistry Platform

ChemBio-SAR

  • Generative Chemistry (GC) – Generation of potent, selective, and drug-like compounds with graph-based transformers in a Reinforcement Learning framework
  • In vivo and in vitro ADME-Tox models to reinforce the transformers in GC
  • Empowering the discovery by GC and ADME-Tox models-driven proprietary database
  • Unlocking new possibilities with advanced biological models for selectivity and polypharmacology
  • Combining the AI models with computational chemistry to create a new era in drug discovery
AxDrug® Platform components – ML models – Computational tools

Drug-X

  • Recurrent Geometric Network (RGN) for end-to-end modeling of orphan proteins
  • Unlocking the proteins by identifying the druggable pockets with mixed solvent sampling, and evolutionary methods
  • Fragment-based scanning and geometry-based fingerprint generation for high-speed virtual screening of large databases
  • Discovery of high-affinity molecules for difficult targets utilizing GC & Molecular Dynamic Simulations (MDS)
  • Docking, MDS, water thermodynamics, and FEP for prioritizing the desired compounds

MedChem

  • Improving the desired properties and synthetic feasibility of the selected molecules
  • Synthetic route estimation using big data
  • Reaction mechanism estimation for solving complex bottlenecks with better yields
  • Bioisostere replacement for improving the druggable properties
  • Impurity predictions for a better understanding of the synthetic protocols

Platform Highlights

  • Accurate protein structure prediction for complicated and orphan targets
  • Identifying the cryptic pocket and druggability analysis
  • AI-generated large proprietary drug-like database
  • Flexible framework applicable to any target
  • Automated multi-parameter optimization with integrated AI and computational techniques

Platform Advantages

  • Integrated AI and CADD platform to generate drug candidates with less turnaround time
  • Generates quick hypothesis with validation
  • Rapid virtual screening AI protocols
  • Coordination of in-house AI, MedChem, and Synthetic teams to convert the virtual compounds into reality reduces cost and time
  • Accurate prediction of efficacy, selectivity, and safety

Case studies

  • AxDrug® applied for 30 different targets with a 100% success rate in discovering drug candidates
  • Identified first-in-class molecules for the most intricate targets
  • Successfully innovated best-in-class molecules with polypharmacology
  • Modeled 3D structures and generated drug candidates forhighly disordered proteins
  • POC established for each program by synthesizing ~ 200 molecules
Get in touch
For more details on how we can accelerate your drug discovery & development project, please contact us using the form below.