| | import html |
| | import io |
| | import random |
| | import zipfile |
| | import gradio as gr |
| | import py3Dmol |
| | import json |
| | import os |
| |
|
| | from tempfile import TemporaryDirectory |
| | from Bio.PDB import PDBList |
| |
|
| | from utils import * |
| | from multiana import * |
| | import datetime |
| |
|
| | default_file = "static/test.pdb" |
| |
|
| | TEMP_DIR = "static/tmp/" |
| | os.makedirs(TEMP_DIR, exist_ok=True) |
| |
|
| |
|
| | def render_structure(structure_str, summary, entity_color_dict, add_label=True): |
| | view = py3Dmol.view(width=233, height=233) |
| | view.addModel(structure_str) |
| | set_default_styles(view, summary, entity_color_dict, add_label=add_label) |
| | view.zoomTo() |
| | return view |
| |
|
| |
|
| | def render_html(view, entity_color_dict): |
| | output = view._make_html().replace( |
| | "height: 233px;", |
| | "height: 700px; max-height: 100%;" |
| | ).replace( |
| | "width: 233px;", |
| | "width: 100%;" |
| | ) |
| | |
| | |
| | legend_items = "".join([ |
| | f"<div style='display:inline-block; margin: 4px;'>" |
| | f"<span style='display:inline-block; width: 12px; height: 12px; background:{color}; margin-right:5px; border:1px solid #333;'></span>" |
| | f"<span>{label}</span></div>" |
| | for label, color in entity_color_dict.items() |
| | ]) |
| | legend_html = f"<div style='margin-top:20px; text-align:center;'>{legend_items}</div>".replace("'", '"') |
| | |
| | |
| | escaped_output = html.escape(output) |
| | escaped_legend_html = html.escape(legend_html) |
| |
|
| | |
| | html_content = f"""<!DOCTYPE html><html><body><center>{escaped_output}</center>{escaped_legend_html}</body></html>""" |
| |
|
| | html_framework = f"""<iframe style=\"width: 100%; height: 800px;\" name=\"result\" |
| | allow=\"midi; geolocation; microphone; camera; display-capture; encrypted-media;\" |
| | sandbox=\"allow-modals allow-forms allow-scripts allow-same-origin allow-popups |
| | allow-top-navigation-by-user-activation allow-downloads\" |
| | allowfullscreen=\"\" allowpaymentrequest=\"\" frameborder=\"0\" |
| | srcdoc='{html_content}'></iframe>""" |
| | |
| | with open(os.path.join(TEMP_DIR, "structure_view.html"), "w") as f: |
| | f.write(html_content) |
| | return html_framework |
| |
|
| | def analyze_contacts(selected_str, cutoff, structure_cache): |
| | keys = selected_str |
| |
|
| | if len(keys) < 2: |
| | debug_text = "<b style='color:red'>请至少选择两个实体进行分析</b>" |
| | return gr.update(), debug_text |
| | |
| | summary = structure_cache["summary"] |
| | structure_str = structure_cache["structure_str"] |
| | entity_color_dict = structure_cache["entity_color_dict"] |
| |
|
| | result = extract_contact_residues(summary, keys, cutoff) |
| | view = render_structure(structure_str, summary, entity_color_dict, add_label=False) |
| | for name, residue_list in result.items(): |
| | highlight_residues(view, residue_list, name=name) |
| | flush_html = render_html(view, entity_color_dict) |
| |
|
| | report = {k: [x['resn'] + str(x['resi']) for x in v] for k, v in result.items()} |
| |
|
| | return flush_html, report |
| |
|
| | def load_structure(file_path): |
| | structure_str, summary, entity_color_dict, structure_dict = read_file(file_path) |
| | view = render_structure(structure_str, summary, entity_color_dict) |
| | html_out = render_html(view, entity_color_dict) |
| | return html_out, gr.Dropdown(label="选择实体", choices=list(summary.keys()), interactive=True, value=[]), structure_dict |
| |
|
| | def update_selected(selected, current): |
| | if selected in current: |
| | return current |
| | current = current + "; " + selected if current else selected |
| | return current |
| |
|
| | def delete_selected(selected, current): |
| | current = "; ".join([s for s in current.split("; ") if s != selected]) |
| | return current |
| |
|
| | def clear_selected(): |
| | return "" |
| |
|
| | def handle_file_upload(file): |
| | if file: |
| | return load_structure(file.name) |
| | else: |
| | |
| | return gr.update(), gr.update(), gr.update() |
| |
|
| | def handle_pdb_id_input(pdb_id): |
| | try: |
| | pdb_id = pdb_id.strip().lower() |
| | pdbl = PDBList() |
| | |
| | with TemporaryDirectory() as temp_dir: |
| | pdbl.retrieve_pdb_file(pdb_id, pdir=temp_dir, file_format='pdb') |
| | pdb_file_path = os.path.join(temp_dir, f"pdb{pdb_id}.ent") |
| | html_out, dd, structure_dict = load_structure(pdb_file_path) |
| | return html_out, dd, structure_dict |
| | except Exception as e: |
| | error_message = f"<b style='color:red'>获取PDB ID {pdb_id} 失败 {e}</b>" |
| | return error_message, gr.update(), gr.update() |
| |
|
| | def render_cache(structure_cache): |
| | summary = structure_cache["summary"] |
| | structure_str = structure_cache["structure_str"] |
| | entity_color_dict = structure_cache["entity_color_dict"] |
| | view = render_structure(structure_str, summary, entity_color_dict) |
| | html_out = render_html(view, entity_color_dict) |
| | return html_out |
| |
|
| | |
| | def multi_uniprot(uniprot_id, pdb_num): |
| | uniprot_id = uniprot_id.strip() |
| | print(f"Fetching structures for UniProt ID: {uniprot_id} with limit {pdb_num}") |
| | sequence, pdb_list = get_uniprot_info(uniprot_id) |
| | |
| | selected_pdb_ids = random.sample(pdb_list, min(pdb_num, len(pdb_list))) |
| | pdbl = PDBList() |
| | print("Zipping PDB files") |
| |
|
| | timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S") |
| | zip_file_path = os.path.join(TEMP_DIR, f"{uniprot_id}_structures_{timestamp}.zip") |
| |
|
| | with TemporaryDirectory() as group_path: |
| | for pdb_id in selected_pdb_ids: |
| | pdbl.retrieve_pdb_file(pdb_id, pdir=group_path, file_format='pdb') |
| | |
| | with zipfile.ZipFile(zip_file_path, 'w') as z: |
| | for pdb_id in selected_pdb_ids: |
| | pdb_file_path = os.path.join(group_path, f"pdb{pdb_id.lower()}.ent") |
| | z.write(pdb_file_path, arcname=os.path.basename(pdb_file_path)) |
| | |
| | return zip_file_path, sequence, selected_pdb_ids |
| |
|
| | def multi_zip(zip_file, seq_input, |
| | multi_cutoff, identity_threshold, |
| | target_entity_keys=None, |
| | cnt_by_file=True): |
| | |
| | if zip_file is None: |
| | return gr.update(value="<b style='color:red'>无效的ZIP文件</b>"), None |
| | with TemporaryDirectory() as group_path: |
| | if isinstance(zip_file, str): |
| | |
| | with zipfile.ZipFile(zip_file, 'r') as z: |
| | z.extractall(group_path) |
| | |
| | os.remove(zip_file) |
| | else: |
| | |
| | zip_bytes = io.BytesIO(zip_file) |
| | with zipfile.ZipFile(zip_bytes, 'r') as z: |
| | z.extractall(group_path) |
| |
|
| | seq_fixed = sequence_fix(seq_input) |
| | if not seq_fixed: |
| | return gr.update(value="<b style='color:red'>无效的序列格式，请输入有效的FASTA或纯氨基酸序列</b>"), None |
| | |
| | result = analyze_group( |
| | group_path, |
| | seq_fixed, |
| | cutoff=multi_cutoff, |
| | match_ratio=identity_threshold / 100, |
| | target_entity_keys=target_entity_keys, |
| | cnt_by_file=cnt_by_file |
| | ) |
| | svg_html = logo_plot(seq_fixed, result) |
| | return svg_html, result |
| |
|
| | with gr.Blocks() as demo: |
| | gr.HTML(get_text_content("static/gr_head.html")) |
| | gr.HTML(get_text_content("static/gr_info.html")) |
| | structure_cache = gr.State(value={"structure_str": None, "summary": None, "entity_color_dict": None}) |
| | multi_result_cache = gr.State(value=None) |
| | zip_cache = gr.State(value=None) |
| |
|
| | |
| | with gr.Tab("Single Structure"): |
| | output = gr.HTML() |
| | with gr.Row(): |
| | with gr.Column(scale=1): |
| | |
| |
|
| | pdb_input = gr.Textbox( |
| | label="输入 PDB ID 获取结构", |
| | placeholder="Input PDB ID", |
| | interactive=True |
| | ) |
| | pdb_btn = gr.Button("获取结构") |
| |
|
| | file_input = gr.File(label="或直接上传 PDB 文件", file_types=[".pdb", ".cif", ".ent"]) |
| | with gr.Column(scale=2): |
| | with gr.Row(): |
| | entity_selector = gr.Dropdown(choices=[], interactive=True, multiselect=True, label="选择实体", scale=2) |
| | cutoff_slider = gr.Slider(1, 10, value=3.5, step=0.5, label="Cutoff 距离 (Å)", scale=1) |
| |
|
| | run_btn = gr.Button("分析并渲染", variant="primary") |
| | cln_btn = gr.Button("还原模型") |
| |
|
| | |
| | with gr.Tab("Multi Structure"): |
| | multi_logo = gr.HTML(MULTI_HTML_HOLDER) |
| | with gr.Row(): |
| | with gr.Column(): |
| | with gr.Tab("从 UniProt 获取"): |
| | uniprot_input = gr.Textbox( |
| | label="输入 UniProt ID 获取结构", |
| | placeholder="Input UniProt ID", |
| | interactive=True, |
| | scale=2, |
| | ) |
| | with gr.Row(): |
| | pdb_num_slider = gr.Slider(1, 100, value=10, step=1, label="获取 PDB 数量上限（按设定数量随机采样）", interactive=True, scale=2) |
| | uniprot_btn = gr.Button("抓取蛋白数据", variant="primary", scale=1) |
| |
|
| | with gr.Tab("手动上传结构压缩文件"): |
| | zip_input = gr.File( |
| | label="上传包含 .pdb/.ent/.cif 的 zip 压缩文件", |
| | file_types=[".zip"], |
| | type="binary", |
| | scale=1, |
| |
|
| | ) |
| | seq_input = gr.Textbox( |
| | label="目标蛋白质序列", |
| | placeholder="上传文件时需手动输入 FASTA 格式序列或纯氨基酸序列...", |
| | lines=8, |
| | scale=3, |
| | ) |
| | |
| | with gr.Group(): |
| | mult_target_selector = gr.Dropdown( |
| | value=['Ligand'], |
| | choices=['Ligand', 'Protein', 'DNA', 'RNA', 'Ion'], |
| | label="选择互作对象类型（可多选，无选择则统计全部）", |
| | multiselect=True, |
| | interactive=True, |
| | ) |
| | with gr.Row(): |
| | multi_cutoff_slider = gr.Slider(1, 10, value=3.5, step=0.5, label="Cutoff 距离 (Å)", interactive=True, scale=3) |
| | cnt_checkbox = gr.Checkbox(label="Yes", info="单文件内不重复统计位点", value=True, interactive=True) |
| |
|
| | identity_threshold = gr.Slider(0, 100, value=80, step=5, label="序列一致性阈值 (%)", interactive=True) |
| | multi_run_btn = gr.Button("开始分析", variant="primary") |
| | |
| | |
| | debug_text = gr.Textbox(label="调试信息", interactive=False) |
| |
|
| |
|
| | |
| | run_btn.click( |
| | fn=analyze_contacts, |
| | inputs=[entity_selector, cutoff_slider, structure_cache], |
| | outputs=[output, debug_text] |
| | ) |
| |
|
| | cln_btn.click( |
| | fn=render_cache, |
| | inputs=[structure_cache], |
| | outputs=[output] |
| | ) |
| |
|
| | file_input.change( |
| | fn=handle_file_upload, |
| | inputs=file_input, |
| | outputs=[output, entity_selector, structure_cache] |
| | ) |
| |
|
| | pdb_btn.click( |
| | fn=handle_pdb_id_input, |
| | inputs=pdb_input, |
| | outputs=[output, entity_selector, structure_cache] |
| | ) |
| |
|
| | demo.load( |
| | fn=lambda: load_structure(default_file), |
| | inputs=[], |
| | outputs=[output, entity_selector, structure_cache] |
| | ) |
| |
|
| | |
| | multi_run_btn.click( |
| | fn=multi_zip, |
| | inputs=[zip_input, seq_input, multi_cutoff_slider, identity_threshold, mult_target_selector, cnt_checkbox], |
| | outputs=[multi_logo, multi_result_cache] |
| | ) |
| | uniprot_btn.click( |
| | fn=multi_uniprot, |
| | inputs=[uniprot_input, pdb_num_slider], |
| | outputs=[zip_input, seq_input, debug_text] |
| | ) |
| |
|
| | demo.launch() |
