{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/using-the-fast-fourier-transform-in-binding","title":"Using the Fast Fourier Transform in Binding Free Energy Calculations","arxiv_id":"1708.07045","date":"2017-07-27","proceeding":null,"authors":["Trung Hai Nguyen","Huan-Xiang Zhou","David D. L. Minh"],"abstract":"According to implicit ligand theory, the standard binding free energy is an\nexponential average of the binding potential of mean force (BPMF), an\nexponential average of the interaction energy between the ligand apo ensemble\nand a rigid receptor. Here, we use the Fast Fourier Transform (FFT) to\nefficiently estimate BPMFs by calculating interaction energies as rigid ligand\nconfigurations from the apo ensemble are discretely translated across rigid\nreceptor conformations. Results for standard binding free energies between T4\nlysozyme and 141 small organic molecules are in good agreement with previous\nalchemical calculations based on (1) a flexible complex (R ~ 0.9 for 24\nsystems) and (2) flexible ligand with multiple rigid receptor configurations (R\n~ 0.8 for 141 systems). While the FFT is routinely used for molecular docking,\nto our knowledge this is the first time that the algorithm has been used for\nrigorous binding free energy calculations.","url_abs":"http://arxiv.org/abs/1708.07045v1","url_pdf":"http://arxiv.org/pdf/1708.07045v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"using-the-fast-fourier-transform-in-binding","repo_url":"https://github.com/nguyentrunghai/BPMFwFFT","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"molecular-docking","task_name":"Molecular Docking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1708.07045","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}