nvidia
Build A Generative Virtual Screening Pipeline
EnterpriseThis blueprint shows how generative AI and accelerated NIM microservices can design optimized small molecules smarter and faster.
Input
OpenFold2Virtual screening will be performed against the protein entered here. Enter the amino acid sequence of the protein or select an example to predict its 3D structure.
Protein
ProteinAmino Acid Sequence. Sequence must be at least 50 characters long for docking to work.
Amino Acid Sequence. Sequence must be at least 50 characters long for docking to work.MMseqs2 Multiple Sequence Alignment
The predictions of OpenFold2 use a multiple sequence alignment (MSA). Specify here how to perform the MSA search.
Select databases to search for similar sequences.
Uniref30_2303
PDB70_220313
colabfold_envdb_202108
Select e-value and iterations to set the inclusion threshold.
GenMol
This module uses GenMol to generate molecules to screen for activity against the protein. Choose how to generate optimized molecules for the virtual screening.
Molecule Examples
Molecule ExamplesMolecule Sequence
Molecule SequenceSelect one of the available properties to be compute.
Select one of the available properties to be compute.DiffDock InputsThe final step of virtual screening uses DiffDock to predict how each generated molecule will interact with the target protein. Choose how the generated molecules and the protein will be docked.
PDB Generated by OpenFold2
PDB Generated by OpenFold2Molecule Input Generated by GenMol
Molecule Input Generated by GenMolFree APIs for development
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GOVERNING TERMS: Your use of this API is governed by the NVIDIA API Trial Service Terms of Use; and the use of this blueprint is governed by the NVIDIA AI Foundation Models Community License.
Output
Click generateAdjust the settings and click generate to see your outcome here.