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gnina — Vecura

gnina

gnina is a molecular docking program with integrated support for scoring and optimizing ligands using Convolutional Neural Networks. It is a fork of smina (itself a fork of AutoDock Vina) with CNN-based scoring and pose refinement.

Job Name

Receptor Structure*

Ligands (SMILES)*

Plain list (no header)

CC(=O)Oc1ccccc1
COc1ccc(cc1)C(=O)N

CSV with header (smiles required, name optional)

smiles,name
CC(=O)Oc1ccccc1,Aspirin

Number of Poses

poses

Box Center*

X

Y

Z

Box Size (Å)*

X

Y

Z

CNN Scoring*

Exhaustiveness

Scoring Function

CNN Model

Flexible Residues

Allow chosen receptor sidechains to rotate during docking (slower, more accurate).

Covalent Docking

Form a covalent bond between a specified receptor atom and a ligand atom (e.g. Michael addition to Cys).

Random Seed

Configure input settings on the left, then click "Run"