Gast ::
| Hauptseite > Publikationsdatenbank > Open-Boundary Molecular Mechanics/Coarse-Grained Framework for Simulations of Low-Resolution G-Protein-Coupled Receptor–Ligand Complexes > print |
| Hauptseite > Publikationsdatenbank > Open-Boundary Molecular Mechanics/Coarse-Grained Framework for Simulations of Low-Resolution G-Protein-Coupled Receptor–Ligand Complexes > print |
| 001 | 861313 | ||
| 005 | 20240625095116.0 | ||
| 024 | 7 | _ | |a 10.1021/acs.jctc.9b00040 |2 doi |
| 024 | 7 | _ | |a 1549-9618 |2 ISSN |
| 024 | 7 | _ | |a 1549-9626 |2 ISSN |
| 024 | 7 | _ | |a 2128/21824 |2 Handle |
| 024 | 7 | _ | |a pmid:30763087 |2 pmid |
| 024 | 7 | _ | |a WOS:000461533000052 |2 WOS |
| 024 | 7 | _ | |a altmetric:55856231 |2 altmetric |
| 037 | _ | _ | |a FZJ-2019-01806 |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Tarenzi, Thomas |0 P:(DE-Juel1)176580 |b 0 |u fzj |
| 245 | _ | _ | |a Open-Boundary Molecular Mechanics/Coarse-Grained Framework for Simulations of Low-Resolution G-Protein-Coupled Receptor–Ligand Complexes |
| 260 | _ | _ | |a Washington, DC |c 2019 |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1552412673_13869 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a G-protein-coupled receptors (GPCRs) constitute as much as 30% of the overall proteins targeted by FDA-approved drugs. However, paucity of structural experimental information and low sequence identity between members of the family impair the reliability of traditional docking approaches and atomistic molecular dynamics simulations for in silico pharmacological applications. We present here a dual-resolution approach tailored for such low-resolution models. It couples a hybrid molecular mechanics/coarse-grained (MM/CG) scheme, previously developed by us for GPCR–ligand complexes, with a Hamiltonian-based adaptive resolution scheme (H-AdResS) for the solvent. This dual-resolution approach removes potentially inaccurate atomistic details from the model while building a rigorous statistical ensemble—the grand canonical one—in the high-resolution region. We validate the method on a well-studied GPCR–ligand complex, for which the 3D structure is known, against atomistic simulations. This implementation paves the way for future accurate in silico studies of low-resolution ligand/GPCRs models. |
| 536 | _ | _ | |a 574 - Theory, modelling and simulation (POF3-574) |0 G:(DE-HGF)POF3-574 |c POF3-574 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Calandrini, Vania |0 P:(DE-Juel1)166168 |b 1 |e Corresponding author |u fzj |
| 700 | 1 | _ | |a Potestio, Raffaello |0 0000-0001-6408-9380 |b 2 |e Corresponding author |
| 700 | 1 | _ | |a Carloni, Paolo |0 P:(DE-Juel1)145614 |b 3 |
| 773 | _ | _ | |a 10.1021/acs.jctc.9b00040 |g p. acs.jctc.9b00040 |0 PERI:(DE-600)2166976-4 |n 3 |p 2101–2109 |t Journal of chemical theory and computation |v 15 |y 2019 |x 1549-9626 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/861313/files/Invoice.pdf |
| 856 | 4 | _ | |x pdfa |u https://juser.fz-juelich.de/record/861313/files/Invoice.pdf?subformat=pdfa |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/861313/files/acs.jctc.9b00040-2.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/861313/files/acs.jctc.9b00040-2.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:861313 |p openaire |p open_access |p OpenAPC |p driver |p VDB |p openCost |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)176580 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)166168 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)145614 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-574 |2 G:(DE-HGF)POF3-500 |v Theory, modelling and simulation |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2019 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J CHEM THEORY COMPUT : 2017 |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b J CHEM THEORY COMPUT : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1150 |2 StatID |b Current Contents - Physical, Chemical and Earth Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-5-20120330 |k IAS-5 |l Computational Biomedicine |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-9-20140121 |k INM-9 |l Computational Biomedicine |x 1 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-5-20120330 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-9-20140121 |
| 980 | _ | _ | |a APC |
| 980 | 1 | _ | |a APC |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|