date: 2021-03-30T13:09:49Z pdf:PDFVersion: 1.7 pdf:docinfo:title: Accurate Receptor-Ligand Binding Free Energies from Fast QM Conformational Chemical Space Sampling xmp:CreatorTool: LaTeX with hyperref access_permission:can_print_degraded: true subject: Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ?Geometry, Frequency, Noncovalent, eXtended Tight Binding? (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ?Statistical Assessment of the Modeling of Proteins and Ligands? (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios. dc:format: application/pdf; version=1.7 pdf:docinfo:creator_tool: LaTeX with hyperref access_permission:fill_in_form: true pdf:encrypted: false dc:title: Accurate Receptor-Ligand Binding Free Energies from Fast QM Conformational Chemical Space Sampling modified: 2021-03-30T13:09:49Z cp:subject: Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ?Geometry, Frequency, Noncovalent, eXtended Tight Binding? (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ?Statistical Assessment of the Modeling of Proteins and Ligands? (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios. pdf:docinfo:subject: Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ?Geometry, Frequency, Noncovalent, eXtended Tight Binding? (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ?Statistical Assessment of the Modeling of Proteins and Ligands? (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios. pdf:docinfo:creator: Esra Boz and Matthias Stein meta:author: Esra Boz and Matthias Stein meta:creation-date: 2021-03-19T05:15:35Z created: 2021-03-19T05:15:35Z access_permission:extract_for_accessibility: true Creation-Date: 2021-03-19T05:15:35Z Author: Esra Boz and Matthias Stein producer: pdfTeX-1.40.21 pdf:docinfo:producer: pdfTeX-1.40.21 pdf:unmappedUnicodeCharsPerPage: 17 dc:description: Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ?Geometry, Frequency, Noncovalent, eXtended Tight Binding? (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ?Statistical Assessment of the Modeling of Proteins and Ligands? (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios. Keywords: ligand binding free energy; DFT; conformational sampling; ligand-receptor binding; GFN2-xTB; conformational entropy access_permission:modify_annotations: true dc:creator: Esra Boz and Matthias Stein description: Small molecule receptor-binding is dominated by weak, non-covalent interactions such as van-der-Waals hydrogen bonding or electrostatics. Calculating these non-covalent ligand-receptor interactions is a challenge to computational means in terms of accuracy and efficacy since the ligand may bind in a number of thermally accessible conformations. The conformational rotamer ensemble sampling tool (CREST) uses an iterative scheme to efficiently sample the conformational space and calculates energies using the semi-empirical ?Geometry, Frequency, Noncovalent, eXtended Tight Binding? (GFN2-xTB) method. This combined approach is applied to blind predictions of the modes and free energies of binding for a set of 10 drug molecule ligands to the cucurbit[n]urils CB[8] receptor from the recent ?Statistical Assessment of the Modeling of Proteins and Ligands? (SAMPL) challenge including morphine, hydromorphine, cocaine, fentanyl, and ketamine. For each system, the conformational space was sufficiently sampled for the free ligand and the ligand-receptor complexes using the quantum chemical Hamiltonian. A multitude of structures makes up the final conformer-rotamer ensemble, for which then free energies of binding are calculated. For those large and complex molecules, the results are in good agreement with experimental values with a mean error of 3 kcal/mol. The GFN2-xTB energies of binding are validated by advanced density functional theory calculations and found to be in good agreement. The efficacy of the automated QM sampling workflow allows the extension towards other complex molecular interaction scenarios. dcterms:created: 2021-03-19T05:15:35Z Last-Modified: 2021-03-30T13:09:49Z dcterms:modified: 2021-03-30T13:09:49Z title: Accurate Receptor-Ligand Binding Free Energies from Fast QM Conformational Chemical Space Sampling xmpMM:DocumentID: uuid:c32c0d09-b17c-4f31-ab82-3ee96c7453f5 Last-Save-Date: 2021-03-30T13:09:49Z pdf:docinfo:keywords: ligand binding free energy; DFT; conformational sampling; ligand-receptor binding; GFN2-xTB; conformational entropy pdf:docinfo:modified: 2021-03-30T13:09:49Z meta:save-date: 2021-03-30T13:09:49Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Esra Boz and Matthias Stein dc:subject: ligand binding free energy; DFT; conformational sampling; ligand-receptor binding; GFN2-xTB; conformational entropy access_permission:assemble_document: true xmpTPg:NPages: 16 pdf:charsPerPage: 3792 access_permission:extract_content: true access_permission:can_print: true meta:keyword: ligand binding free energy; DFT; conformational sampling; ligand-receptor binding; GFN2-xTB; conformational entropy access_permission:can_modify: true pdf:docinfo:created: 2021-03-19T05:15:35Z