{"id":39257184,"url":"https://github.com/ccdc-opensource/science-paper-rf-machine-learned-scoring-2022","last_synced_at":"2026-01-18T00:18:23.778Z","repository":{"id":43039479,"uuid":"472736395","full_name":"ccdc-opensource/science-paper-rf-machine-learned-scoring-2022","owner":"ccdc-opensource","description":null,"archived":false,"fork":false,"pushed_at":"2025-12-16T22:55:44.000Z","size":186,"stargazers_count":11,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-12-20T13:22:06.652Z","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ccdc-opensource.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2022-03-22T11:26:29.000Z","updated_at":"2025-12-16T22:55:07.000Z","dependencies_parsed_at":"2024-12-18T10:34:00.145Z","dependency_job_id":"2f3721dc-44dd-4f5d-a898-bc9d19b3e4ff","html_url":"https://github.com/ccdc-opensource/science-paper-rf-machine-learned-scoring-2022","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ccdc-opensource/science-paper-rf-machine-learned-scoring-2022","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ccdc-opensource","download_url":"https://codeload.github.com/ccdc-opensource/science-paper-rf-machine-learned-scoring-2022/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28523627,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-17T23:53:28.710Z","status":"ssl_error","status_checked_at":"2026-01-17T23:52:20.131Z","response_time":85,"last_error":"SSL_read: 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":"2026-01-18T00:18:23.073Z","updated_at":"2026-01-18T00:18:23.769Z","avatar_url":"https://github.com/ccdc-opensource.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# science-paper-rf-machine-learned-scoring-2022\n\n---\n\n## Docking and scoring workflows\n\n---\n\n### Template based docking using GOLD\n\nTo setup a docking run, generate the following files and folders:\n\n- [docking_home]/tmp_aligned_3d_sdf_sanitized/ligand_templates_for_mcs_manual.sdf \\\ncontains the manually curated ligand\ntemplates in 3D. Manual curation of the templates is highly recommended to ensure proper tautomers, avoid low quality\nstructures\n- [docking_home]/tmp_aligned_for_MOE_sanitized/*.pdb \\\ncontains aligned protein structures from MOE projects\n\n```bash\nmkdir docking\ncd docking\nbsub \u003c dock.sh\n#after docking has finished\njoin_docked_rf_counts.py -t [target]\n```\n\n---\n\n### Template based docking in Python\n\n`docking.py --input_ligands ligands.sdf -t default -fr=Met713 Met712`\n\n---\n\n### Template based docking from MOE\n\nOne can either dock into one of the prepared projects or into an MDB of binding sites.\nThe binding sites MDB should have the same structure as a Roche Projects DB.\nIf one of the defined projects is selected, the return results will include the RF Score.\n\n---\n\n### Generating project specific parameters\n\n- Series definitions are stored in rf_scoring/series_definitions/[target].json\n\n```bash\n# Change to your docking directory \ncd /path/to/docking_dir\n\n# fit RF-PLP\nccdc_roche_scoring/stat_potential.py -t pde-10\n```\n\n---\n\n## Applications for MOE\n\n- Start a webserver:\n\n```bash\n# LOAD ENV\nmoeweb -load /rf_scoring/soap_scoring_client.svl -load /template_docking/soap_template_docking_client.svl \n```\n\n- Adapt the SVL scripts to point to the webserver: \\\n`const SERVER_URL = 'server address';`\n\n---\n\n## Scoring in MOE\n\n---\n\n## Score an MDB of ligand poses for the active protein\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fccdc-opensource%2Fscience-paper-rf-machine-learned-scoring-2022/lists"}