import time import gradio as gr from gradio_molecule3d import Molecule3D def predict (input_sequence, input_ligand,input_msa, input_protein): start_time = time.time() # Do inference here # return an output pdb file with the protein and ligand with resname LIG or UNK. end_time = time.time() run_time = end_time - start_time return ["test_out.pdb", "test_docking_pose.sdf"], run_time with gr.Blocks() as app: gr.Markdown("# Template for inference") gr.Markdown("Title, description, and other information about the model") with gr.Row(): input_sequence = gr.Textbox(lines=3, label="Input Protein sequence (FASTA)") input_ligand = gr.Textbox(lines=3, label="Input ligand SMILES") with gr.Row(): input_msa = gr.File(label="Input Protein MSA (FASTA)") input_protein = gr.File(label="Input protein monomer") # define any options here # for automated inference the default options are used # slider_option = gr.Slider(0,10, label="Slider Option") # checkbox_option = gr.Checkbox(label="Checkbox Option") # dropdown_option = gr.Dropdown(["Option 1", "Option 2", "Option 3"], label="Radio Option") btn = gr.Button("Run Inference") gr.Examples( [ [ "SVKSEYAEAAAVGQEAVAVFNTMKAAFQNGDKEAVAQYLARLASLYTRHEELLNRILEKARREGNKEAVTLMNEFTATFQTGKSIFNAMVAAFKNGDDDSFESYLQALEKVTAKGETLADQIAKAL:SVKSEYAEAAAVGQEAVAVFNTMKAAFQNGDKEAVAQYLARLASLYTRHEELLNRILEKARREGNKEAVTLMNEFTATFQTGKSIFNAMVAAFKNGDDDSFESYLQALEKVTAKGETLADQIAKAL", "COc1ccc(cc1)n2c3c(c(n2)C(=O)N)CCN(C3=O)c4ccc(cc4)N5CCCCC5=O", "test_out.pdb" ], ], [input_sequence, input_ligand, input_protein], ) reps = [ { "model": 0, "style": "cartoon", "color": "whiteCarbon", }, { "model": 1, "style": "stick", "color": "greenCarbon", } ] out = Molecule3D(reps=reps) run_time = gr.Textbox(label="Runtime") btn.click(predict, inputs=[input_sequence, input_ligand, input_msa, input_protein], outputs=[out, run_time]) app.launch()