{"id":44964490,"url":"https://github.com/bioinfomachinelearning/tulip","last_synced_at":"2026-02-18T14:09:40.248Z","repository":{"id":238403395,"uuid":"529289287","full_name":"BioinfoMachineLearning/tulip","owner":"BioinfoMachineLearning","description":"Template-based modeling for accurate prediction of ligand-protein complex structures (TULIP)","archived":false,"fork":false,"pushed_at":"2024-06-05T05:20:05.000Z","size":15052,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-09-09T16:34:17.570Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BioinfoMachineLearning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2022-08-26T14:26:44.000Z","updated_at":"2024-06-05T05:20:08.000Z","dependencies_parsed_at":"2025-09-10T06:31:00.486Z","dependency_job_id":null,"html_url":"https://github.com/BioinfoMachineLearning/tulip","commit_stats":null,"previous_names":["bioinfomachinelearning/tulip"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BioinfoMachineLearning/tulip","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2Ftulip","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2Ftulip/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2Ftulip/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2Ftulip/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BioinfoMachineLearning","download_url":"https://codeload.github.com/BioinfoMachineLearning/tulip/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BioinfoMachineLearning%2Ftulip/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29581626,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-18T13:56:48.962Z","status":"ssl_error","status_checked_at":"2026-02-18T13:54:34.145Z","response_time":162,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-02-18T14:09:39.404Z","updated_at":"2026-02-18T14:09:40.228Z","avatar_url":"https://github.com/BioinfoMachineLearning.png","language":"Python","readme":"## TULIP\nThe template-based modeling for accurate ligand-protein complex structure prediction (TULIP).\n\n``Input`` : Query protein, Ligand molecule (``.smiles`` ), Protein Template Hits\n\n``Output`` : ``.sdf`` file of ligand molecule that potentially binds to input query protein\n\n## Setup Environment\n1. The required packages are found in ``environment.yml`` \n\n``conda env create -f environment.yml``\n\n2. Once the installation is completed, activate the conda environment\n\n``conda activate tulip``\n\n3. The pipeline makes use of UCSF Chimera and PyRosetta. Please install them through their websites\n\n[UCSF Chimera Download](https://www.cgl.ucsf.edu/chimera/download.html) , this link will take users to: ```https://www.cgl.ucsf.edu/chimera/download.html```\n\n[PyRosetta Download](https://www.pyrosetta.org/downloads) , this link will take users to: ```https://www.pyrosetta.org/downloads```\n\n\nTo adjust the target ligand's binding pose and orientation by rotation and translation, TULIP uses LS-align to align the target ligand with template ligands of higher similarity by both flexible and rigid alignments.\n\n\nThe LS-align tool can be downloaded and compiled into local machine from the below link:\n\n[LS-align](https://zhanggroup.org/LS-align/) , this link will take users to: ```https://zhanggroup.org/LS-align/```\n\n## Run\n\nTo run TULIP pipeline run the following:\n\n```\ngit clone https://github.com/BioinfoMachineLearning/tulip.git\ncd ProteinLigand\npython3 complex_generator.py --config=../configs/configs.yml\n```\n\n\n``configs/configs.yml`` contains the configuration of the pipeline. Enter the correct paths in config file.\n\n## Post Processing\n\nOnce the ligand templates are identified using the above script, use the script below to run the post-processing for multi-atom ligands. Update the ``ls_align_path`` variable in the script to the path where LS-align is installed.\n\n``python3 post_process.py ``\n\nFor ions and small molecules run:\n\n``python3 process_small_mol.py ``\n\n## Clustering \nTo perform clustering in case we have same ligand SMILES for a protein.\n\n``python3 cluster_files.py``\n\n## Outputs\nTULIP returns the identified ligand molecules in ranks. Example : `rank_0.sdf`, `rank_1.sdf`, and so on for each protein.\n\n\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinfomachinelearning%2Ftulip","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbioinfomachinelearning%2Ftulip","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinfomachinelearning%2Ftulip/lists"}