IFD-MD
Accurate ligand binding mode prediction for novel chemical matter, for on-targets and off-targets
Open new doors to structure-based design for a broader range of targets and off-targets
IFD-MD is a powerful GPU-accelerated solution for predicting receptor-ligand binding poses at an accuracy approaching experimental methods, but at a reduced cost and faster turnaround. Using IFD-MD in combination with FEP+ for model validation allows a full in silico method for deploying high precision structure-based drug discovery starting from homology models, AlphaFold structures, or experimental structures bound to unrelated chemical matter.
Advantages of IFD-MD for ligand-binding mode prediction
Expedite programs without waiting to obtain an experimental structure
Progress structure-based design efforts without waiting for an experimental crystal structure of a new chemical series
Understand and de-risk off-target activities
Eliminate the need to initiate a new crystallization program of a known off-target bound to chemical matter
Applicable to a wide range of modalities
From non-covalent ligands to covalent ligands and macrocycles
Rationalize membrane protein targets
with explicit water molecules in the binding site and explicit lipid molecules in the membrane region
How it works
Incorporates the effects that water molecules have on binding as an important component of the IFD-MD scoring function
Detects and penalizes desolvation of polar groups caused by non-native ligand poses
Utilizes a consensus mode to produce models that can help explain potential liabilities from common promiscuous off-targets
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