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  • As an alternative to exhaustive searching, our fully automatic 4Dshape+ Similarity & Docking modules use either multiple binding poses generated by MD simulations of a scaffold and/or superposition of multiple scaffolds extracted from X-ray structures.

  • The docking algorithm attempts to resolve ligand-receptor steric clashes by identifying the optimal initial binding pose of the ligand which is further relaxed using the hybrid QM-MD simulations.

AI-Drug Discovery Platform 

Our unique computational platform integrates Machine Learning techniques, 4Dshape+ similarity/Docking modules and hybrid QM/MD simulations to accelerate drug discovery. 

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Our computational solution AI-4Dshape+ includes the state of the art techniques of machine learning algorithms, Multiple ligands shape-based Similarity & Docking, and hybrid QM-MD simulations.
The AI-4Dshape+ software package features:
  • Fully automatic workflows.

  • Improved scaling, supporting thousands of compute resources (CPUs/GPUs).

  • 4Dshape+ Similarity & Docking modules support multi-threaded parallelism, speeding up the search.

  • Provides new chemical starting points for novel targets or design optimized molecules.
  • Previous features described in 4Dshape+ Sim Docking modules.
  • AI platform using multiple optimized and prebuilt machine learning workflows (KNIME).  
  • Plugin Interface to Datawarrior (openmolecules.org/datawarrior/)
  • Virtual screening workflow using AMBER22  & AmberTools22 software packages. (ambermd.org/AmberTools.php)
 
4Dshape+ Sim module
  4Dshape+ Docking module includes MD-QM/MM-GBSA simulations/Binding Free energy calculation 
  AI machine learning  module, includes 6 machine learning algorithms.

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  • The search freedom using Multiple queries Docking process is greatly reduced compared to that in full-flexible docking and exhaustive search methods.
  • The results are ranked according to the docking score or QM/MM-GBSA Binding Energy to identify highly active compounds.

  • The multiple ligands shape-based screening of large ligand libraries can identify more effective active compounds with favorable pharmacokinetics and low cytotoxicity.

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