Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering
Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of `unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-...
Saved in:
| Published in: | IUCrJ Vol. 2; no. 2; pp. 207 - 217 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
International Union of Crystallography
01.03.2015
|
| Subjects: | |
| ISSN: | 2052-2525, 2052-2525 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of `unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method ( EOM ) [Bernadó et al. (2007). J. Am. Chem. Soc. 129 , 5656–5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. |
|---|---|
| AbstractList | Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of 'unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernadó et al. (2007 ▶). J. Am. Chem. Soc. 129, 5656-5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of `unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM ) [Bernadó et al. (2007[Bernadó, P., Mylonas, E., Petoukhov, M. V., Blackledge, M. & Svergun, D. I. (2007). J. Am. Chem. Soc. 129, 5656-5664.]). J. Am. Chem. Soc. 129, 5656-5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernado et al. (2007). J. Am. Chem. Soc. 129, 5656-5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. 1 Keywords: small-angle scattering; proteins; macromolecular dynamics; unstructured biology; hybrid methods; symmetric oligomers Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of `unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method ( EOM ) [Bernadó et al. (2007). J. Am. Chem. Soc. 129 , 5656–5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of `unstructured' and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernado et al. (2007[Bernado, P., Mylonas, E., Petoukhov, M. V., Blackledge, M. & Svergun, D. I. (2007). J. Am. Chem. Soc. 129, 5656-5664.]). J. Am. Chem. Soc. 129, 5656-5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. New developments in the modelling of flexible biological macromolecules from SAXS data offer extended possibilities of using high-resolution models and provide metrics for quantitative characterization of the reconstructed ensembles. Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of ‘unstructured’ and flexible molecules requires alternative approaches to those traditionally employed in structural biology. Small-angle X-ray scattering (SAXS) is an established method for structural characterization of biological macromolecules in solution, and is directly applicable to the study of flexible systems such as intrinsically disordered proteins and multi-domain proteins with unstructured regions. The Ensemble Optimization Method (EOM) [Bernadó et al. (2007 ▶). J. Am. Chem. Soc. 129, 5656–5664] was the first approach introducing the concept of ensemble fitting of the SAXS data from flexible systems. In this approach, a large pool of macromolecules covering the available conformational space is generated and a sub-ensemble of conformers coexisting in solution is selected guided by the fit to the experimental SAXS data. This paper presents a series of new developments and advancements to the method, including significantly enhanced functionality and also quantitative metrics for the characterization of the results. Building on the original concept of ensemble optimization, the algorithms for pool generation have been redesigned to allow for the construction of partially or completely symmetric oligomeric models, and the selection procedure was improved to refine the size of the ensemble. Quantitative measures of the flexibility of the system studied, based on the characteristic integral parameters of the selected ensemble, are introduced. These improvements are implemented in the new EOM version 2.0, and the capabilities as well as inherent limitations of the ensemble approach in SAXS, and of EOM 2.0 in particular, are discussed. |
| Audience | Academic |
| Author | Svergun, Dmitri I. Tria, Giancarlo Mertens, Haydyn D. T. Kachala, Michael |
| Author_xml | – sequence: 1 givenname: Giancarlo surname: Tria fullname: Tria, Giancarlo – sequence: 2 givenname: Haydyn D. T. surname: Mertens fullname: Mertens, Haydyn D. T. – sequence: 3 givenname: Michael surname: Kachala fullname: Kachala, Michael – sequence: 4 givenname: Dmitri I. surname: Svergun fullname: Svergun, Dmitri I. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25866658$$D View this record in MEDLINE/PubMed |
| BookMark | eNqNkk1r3DAQhk1JadI0P6CXYuill01Hsj7sS2EJTRoI9NAPchOyNNpqka1UskPz7ytnk5KkFIoOEu-88zAzmpfV3hhHrKrXBI4JAfn-CwVOKaeccAAK9PJZdbBIq0Xbe_Der45y3gIAIZRLRl5U-5S3QgjeHlTf1_ZajwZtjWPGoQ9YD9FiCH7c1NHVLuAvf6tqk-IQA5o5YK7nvBguV0nf1DmGefJxrLPR04SpRF5Vz50OGY_u7sPq2-nHryefVhefz85P1hcrwwWfVoR2LdPGGd7pppPAmOiJBUqoEdhYyg1nRlrmUFBoLbUCQWPDEFtuS6A5rM53XBv1Vl0lP-h0o6L26laIaaN0mrwJqDpGjAOHDXGyQNtO9z2jrG81dK3QsrA-7FhXcz-gNThOSYdH0MeR0f9Qm3itWNNRRngBvLsDpPhzxjypwWdTZqlHjHNWpAVgDQX5H1YhG5BUClqsb59Yt3FOY5lqcQmQQFuyFH-8c2106dWPLpYSTTkWB2_K5jhf9DUD0QG0dEl487DbP23er0YxyJ2h_HvOCZ0yftLLPxeyD4qAWvZQ_bWHJZM8ybyH_zvnN2Nu3Yo |
| CitedBy_id | crossref_primary_10_1093_nar_gkaa520 crossref_primary_10_1107_S2059798322008579 crossref_primary_10_1038_s41467_019_09769_8 crossref_primary_10_1016_j_str_2017_01_012 crossref_primary_10_1111_febs_16379 crossref_primary_10_1074_jbc_RA118_006864 crossref_primary_10_1080_15548627_2023_2259707 crossref_primary_10_1038_s41467_017_02313_6 crossref_primary_10_1038_s41598_021_00495_0 crossref_primary_10_1107_S2059798317011597 crossref_primary_10_6023_A21120624 crossref_primary_10_1038_ncomms8542 crossref_primary_10_1038_s41598_017_04975_0 crossref_primary_10_1016_j_jmb_2022_167871 crossref_primary_10_1016_j_jmb_2021_167217 crossref_primary_10_1038_s41467_024_49255_4 crossref_primary_10_1107_S2059798317003849 crossref_primary_10_1038_s41467_025_61749_3 crossref_primary_10_1107_S205225251901073X crossref_primary_10_3389_fmolb_2023_1249939 crossref_primary_10_1016_j_str_2016_06_001 crossref_primary_10_1016_j_abb_2016_02_029 crossref_primary_10_1016_j_antiviral_2017_02_005 crossref_primary_10_1021_jacs_1c10173 crossref_primary_10_3390_molecules25235624 crossref_primary_10_1074_jbc_RA119_010390 crossref_primary_10_1073_pnas_2302531120 crossref_primary_10_1002_pro_5200 crossref_primary_10_1073_pnas_2220180120 crossref_primary_10_3390_v12101115 crossref_primary_10_1093_nar_gkw1297 crossref_primary_10_1038_s41598_018_37009_4 crossref_primary_10_1016_j_jmb_2018_07_006 crossref_primary_10_1111_febs_16238 crossref_primary_10_1016_j_bpj_2018_07_009 crossref_primary_10_1038_s41598_020_61972_6 crossref_primary_10_1073_pnas_2217066120 crossref_primary_10_1016_j_bpj_2021_07_022 crossref_primary_10_1093_nar_gkw1183 crossref_primary_10_3389_fmolb_2016_00047 crossref_primary_10_1016_j_bpc_2017_05_016 crossref_primary_10_1093_nar_gkw1165 crossref_primary_10_1093_nar_gkab963 crossref_primary_10_1016_j_sbi_2021_11_014 crossref_primary_10_1093_pnasnexus_pgae521 crossref_primary_10_1016_j_ijbiomac_2019_06_135 crossref_primary_10_1007_s00249_020_01489_y crossref_primary_10_1016_j_str_2018_09_007 crossref_primary_10_1039_D4SC04544K crossref_primary_10_1111_febs_15015 crossref_primary_10_3389_fimmu_2018_03139 crossref_primary_10_1093_nar_gkx140 crossref_primary_10_1016_j_bpj_2019_02_015 crossref_primary_10_1107_S2052252515015626 crossref_primary_10_1016_j_bbagen_2016_05_008 crossref_primary_10_3390_molecules30081793 crossref_primary_10_1002_1873_3468_13437 crossref_primary_10_1016_j_bpj_2023_04_026 crossref_primary_10_1371_journal_ppat_1008342 crossref_primary_10_1074_jbc_M116_732909 crossref_primary_10_1021_jacs_6b10272 crossref_primary_10_3389_fmolb_2022_1100032 crossref_primary_10_1261_rna_064501_117 crossref_primary_10_1016_j_bbrc_2016_06_014 crossref_primary_10_1016_j_str_2017_09_013 crossref_primary_10_1107_S1600576717007786 crossref_primary_10_1074_jbc_M116_715698 crossref_primary_10_7554_eLife_92822_4 crossref_primary_10_1038_s41598_018_30190_6 crossref_primary_10_1016_j_csbj_2021_06_031 crossref_primary_10_1002_ange_202312517 crossref_primary_10_1074_jbc_RA117_001097 crossref_primary_10_1016_j_jmb_2021_167258 crossref_primary_10_1074_jbc_M116_766816 crossref_primary_10_1038_s41598_022_13982_9 crossref_primary_10_1074_jbc_M115_705491 crossref_primary_10_1186_s12915_016_0298_6 crossref_primary_10_1093_nar_gkab635 crossref_primary_10_1016_j_jsb_2020_107573 crossref_primary_10_1016_j_bpj_2018_01_011 crossref_primary_10_1016_j_str_2015_05_013 crossref_primary_10_3390_v14112358 crossref_primary_10_1107_S2059798320013765 crossref_primary_10_1016_j_jmb_2023_168053 crossref_primary_10_1073_pnas_2413100121 crossref_primary_10_3389_fmolb_2018_00060 crossref_primary_10_1021_jacs_8b05366 crossref_primary_10_1107_S2052252521005613 crossref_primary_10_1016_j_foodchem_2024_139455 crossref_primary_10_1016_j_str_2020_09_010 crossref_primary_10_1038_s42003_024_05845_y crossref_primary_10_1107_S2059798316006665 crossref_primary_10_1016_j_bbamem_2024_184368 crossref_primary_10_1111_febs_16150 crossref_primary_10_1016_j_str_2022_03_011 crossref_primary_10_1016_j_bpj_2019_08_032 crossref_primary_10_1016_j_jsb_2020_107463 crossref_primary_10_1093_nar_gkac855 crossref_primary_10_1002_iub_2528 crossref_primary_10_1016_j_jmb_2023_168048 crossref_primary_10_1371_journal_pone_0239702 crossref_primary_10_1111_febs_17239 crossref_primary_10_1016_j_jmb_2019_10_011 crossref_primary_10_1016_j_jmb_2016_03_009 crossref_primary_10_1002_cbic_202300110 crossref_primary_10_3390_ijms23136969 crossref_primary_10_1016_j_str_2019_03_016 crossref_primary_10_1039_C9RA01510H crossref_primary_10_1038_s41598_019_39543_1 crossref_primary_10_1002_prot_25523 crossref_primary_10_1016_j_str_2023_12_006 crossref_primary_10_1038_nchembio_2210 crossref_primary_10_1074_jbc_RA120_015468 crossref_primary_10_1107_S1399004715017721 crossref_primary_10_1016_j_abb_2017_05_005 crossref_primary_10_1016_j_jmb_2019_11_009 crossref_primary_10_1016_j_str_2018_01_010 crossref_primary_10_7554_eLife_92822 crossref_primary_10_1038_s41598_021_92280_2 crossref_primary_10_1038_s41594_022_00811_w crossref_primary_10_1016_j_fbio_2025_107304 crossref_primary_10_1016_j_tibs_2016_11_002 crossref_primary_10_1038_s41467_023_39808_4 crossref_primary_10_1016_j_molp_2017_08_003 crossref_primary_10_1016_j_str_2017_11_019 crossref_primary_10_1002_1873_3468_12729 crossref_primary_10_3390_toxins15110637 crossref_primary_10_1016_j_sbi_2021_05_002 crossref_primary_10_1038_s41598_017_03323_6 crossref_primary_10_3390_v7112919 crossref_primary_10_15252_embj_2020107505 crossref_primary_10_3390_biom10101408 crossref_primary_10_1016_j_yjsbx_2024_100119 crossref_primary_10_1016_j_ijbiomac_2024_138614 crossref_primary_10_1016_j_molstruc_2019_07_050 crossref_primary_10_3390_ijms241814258 crossref_primary_10_1016_j_bbapap_2021_140719 crossref_primary_10_26508_lsa_202302051 crossref_primary_10_1093_nar_gkaa107 crossref_primary_10_1016_j_bpj_2023_12_001 crossref_primary_10_1038_ncomms15231 crossref_primary_10_1016_j_bbagen_2023_130376 crossref_primary_10_1111_febs_13801 crossref_primary_10_1093_plphys_kiaf392 crossref_primary_10_1016_j_bpc_2022_106843 crossref_primary_10_1186_s12915_018_0542_3 crossref_primary_10_1038_s41467_019_14196_w crossref_primary_10_3389_fimmu_2024_1434463 crossref_primary_10_1074_jbc_M116_761809 crossref_primary_10_1107_S2052252518005900 crossref_primary_10_1371_journal_pgen_1010269 crossref_primary_10_1038_s41467_022_33693_z crossref_primary_10_1038_nchembio_2434 crossref_primary_10_1016_j_jmb_2020_06_002 crossref_primary_10_15252_embr_201846293 crossref_primary_10_1016_j_str_2023_08_011 crossref_primary_10_1107_S1600576722001923 crossref_primary_10_1016_j_sbi_2016_10_011 crossref_primary_10_1371_journal_pbio_3001148 crossref_primary_10_1074_jbc_M117_799114 crossref_primary_10_1038_s41467_024_44859_2 crossref_primary_10_1074_jbc_M115_684928 crossref_primary_10_1073_pnas_2425831122 crossref_primary_10_1038_srep29040 crossref_primary_10_1038_s41594_023_00920_0 crossref_primary_10_1002_1873_3468_13954 crossref_primary_10_1038_s41598_019_52537_3 crossref_primary_10_1016_j_bpj_2016_04_009 crossref_primary_10_1371_journal_ppat_1007656 crossref_primary_10_1016_j_str_2018_09_013 crossref_primary_10_1093_nar_gkx1083 crossref_primary_10_1074_jbc_RA118_004481 crossref_primary_10_1016_j_ijbiomac_2021_11_074 crossref_primary_10_3390_cryst8030109 crossref_primary_10_1016_j_bbamem_2020_183256 crossref_primary_10_1016_j_jmb_2022_167708 crossref_primary_10_1073_pnas_1911489116 crossref_primary_10_3390_ijms24119308 crossref_primary_10_1038_s41467_019_12097_6 crossref_primary_10_1038_s41419_020_2504_2 crossref_primary_10_1093_nar_gkw1147 crossref_primary_10_3390_ijms21249413 crossref_primary_10_1038_s42003_024_06644_1 crossref_primary_10_1371_journal_ppat_1009824 crossref_primary_10_3389_fmolb_2021_749052 crossref_primary_10_1016_j_bpj_2021_10_003 crossref_primary_10_1038_srep33671 crossref_primary_10_1039_C5CP04886A crossref_primary_10_3390_biom10081192 crossref_primary_10_1038_s41467_024_51972_9 crossref_primary_10_1038_s41589_019_0444_x crossref_primary_10_1021_jacs_8b04792 crossref_primary_10_1126_science_aaw4388 crossref_primary_10_1016_j_toxicon_2018_01_007 crossref_primary_10_3390_cells9010035 crossref_primary_10_3389_fimmu_2018_02898 crossref_primary_10_1038_s41467_022_29322_4 crossref_primary_10_3389_fmolb_2022_1026724 crossref_primary_10_1093_nar_gkac451 crossref_primary_10_1073_pnas_1712450114 crossref_primary_10_1016_j_febslet_2015_08_027 crossref_primary_10_1016_j_sbi_2016_11_018 crossref_primary_10_1073_pnas_1818206116 crossref_primary_10_1107_S205225251901707X crossref_primary_10_1021_acschemneuro_5c00106 crossref_primary_10_1107_S2059798322000729 crossref_primary_10_1021_jacs_4c11768 crossref_primary_10_1074_jbc_RA119_007847 crossref_primary_10_1016_j_ijbiomac_2023_125792 crossref_primary_10_1073_pnas_1613040114 crossref_primary_10_1038_s41598_019_45709_8 crossref_primary_10_1007_s12551_021_00916_4 crossref_primary_10_1016_j_str_2016_03_025 crossref_primary_10_1038_s41586_024_08336_6 crossref_primary_10_1038_nprot_2016_113 crossref_primary_10_1016_j_chembiol_2018_10_016 crossref_primary_10_1038_s41598_019_52344_w crossref_primary_10_1016_j_jmb_2018_11_003 crossref_primary_10_3390_nano11061476 crossref_primary_10_1063_4_0000013 crossref_primary_10_1074_jbc_RA120_014534 crossref_primary_10_1016_j_jmb_2021_166930 crossref_primary_10_1038_s41598_017_05364_3 crossref_primary_10_1007_s12551_016_0194_x crossref_primary_10_1038_s41598_017_01102_x crossref_primary_10_1073_pnas_1611118114 crossref_primary_10_1073_pnas_2215556120 crossref_primary_10_1038_s41557_023_01361_4 crossref_primary_10_3390_molecules29122768 crossref_primary_10_1186_s12915_022_01381_5 crossref_primary_10_3390_biom11091324 crossref_primary_10_1093_nar_gkac1277 crossref_primary_10_1016_j_abb_2020_108468 crossref_primary_10_1038_s41467_025_57478_2 crossref_primary_10_1371_journal_pone_0195355 crossref_primary_10_1038_s42003_018_0203_7 crossref_primary_10_1038_s41573_025_01220_6 crossref_primary_10_1371_journal_pone_0182056 crossref_primary_10_1016_j_bpj_2018_11_020 crossref_primary_10_1016_j_foodres_2021_110653 crossref_primary_10_1016_j_ymeth_2022_08_008 crossref_primary_10_1111_mmi_14800 crossref_primary_10_1016_j_jmb_2021_166954 crossref_primary_10_1016_j_jmb_2017_10_027 crossref_primary_10_1016_j_pep_2025_106749 crossref_primary_10_3390_ijms23020923 crossref_primary_10_1016_j_str_2017_05_018 crossref_primary_10_1016_j_ijbiomac_2022_10_135 crossref_primary_10_1016_j_jmb_2017_01_008 crossref_primary_10_1016_j_csbj_2021_09_009 crossref_primary_10_4049_jimmunol_1900494 crossref_primary_10_1016_j_bbapap_2025_141075 crossref_primary_10_1038_s41598_021_89613_6 crossref_primary_10_1093_nar_gkab290 crossref_primary_10_1107_S1600576720013412 crossref_primary_10_1002_pro_70122 crossref_primary_10_1074_jbc_M115_674176 crossref_primary_10_1038_s41598_018_20320_5 crossref_primary_10_3390_biomedicines10102347 crossref_primary_10_1016_j_bbrc_2019_10_086 crossref_primary_10_1111_1462_2920_16624 crossref_primary_10_1038_ncomms16065 crossref_primary_10_7554_eLife_22510 crossref_primary_10_3390_molecules25204783 crossref_primary_10_1016_j_neuron_2018_02_010 crossref_primary_10_1038_s41467_023_42012_z crossref_primary_10_1107_S2059798325005303 crossref_primary_10_3389_fmolb_2024_1347741 crossref_primary_10_3390_biom10040623 crossref_primary_10_1016_j_foodres_2023_113787 crossref_primary_10_1111_febs_16616 crossref_primary_10_15252_emmm_201911248 crossref_primary_10_1016_j_xphs_2016_07_021 crossref_primary_10_1074_jbc_RA118_003939 crossref_primary_10_1016_j_bbagen_2018_07_025 crossref_primary_10_1016_j_ijbiomac_2017_01_058 crossref_primary_10_7554_eLife_29154 crossref_primary_10_1098_rsob_200386 crossref_primary_10_1074_jbc_RA120_014865 crossref_primary_10_1007_s00018_021_04032_0 crossref_primary_10_1016_j_jmb_2019_05_047 crossref_primary_10_1038_s41467_017_01485_5 crossref_primary_10_1002_pro_5093 crossref_primary_10_3389_fnut_2022_1039762 crossref_primary_10_1002_anie_202312517 crossref_primary_10_1016_j_jmb_2020_01_030 crossref_primary_10_1016_j_bbagen_2018_07_011 crossref_primary_10_1021_acs_jpcb_5c04293 crossref_primary_10_1016_j_ultsonch_2023_106510 crossref_primary_10_3389_fmolb_2021_621128 crossref_primary_10_1088_2399_1984_abfb7c crossref_primary_10_1093_nar_gkab080 crossref_primary_10_1038_s43586_021_00064_9 crossref_primary_10_1016_j_str_2020_04_020 crossref_primary_10_1042_BCJ20180405 crossref_primary_10_1016_j_jmb_2018_02_020 crossref_primary_10_3390_biom12121876 crossref_primary_10_3389_fmolb_2022_862910 crossref_primary_10_1002_bab_1577 crossref_primary_10_1016_j_str_2023_09_004 crossref_primary_10_1002_wcms_1359 crossref_primary_10_1074_jbc_M117_804195 crossref_primary_10_1038_s41467_023_37988_7 crossref_primary_10_1038_s41598_024_74335_2 crossref_primary_10_1107_S2052252515010891 crossref_primary_10_1016_j_carbpol_2021_117814 crossref_primary_10_1016_j_ymeth_2016_12_002 crossref_primary_10_1038_nmicrobiol_2017_47 crossref_primary_10_1371_journal_pone_0186110 crossref_primary_10_1016_j_jmb_2023_168154 crossref_primary_10_1016_j_jbc_2023_104592 crossref_primary_10_1016_j_biochi_2023_10_006 crossref_primary_10_1016_j_jsb_2019_04_003 crossref_primary_10_1007_s12551_025_01321_x crossref_primary_10_1016_j_jsbmb_2018_06_011 crossref_primary_10_1016_j_str_2023_04_004 crossref_primary_10_1016_j_jmb_2022_167465 crossref_primary_10_1107_S1600576725003590 crossref_primary_10_1038_s41598_020_77706_7 crossref_primary_10_1038_s41598_020_76522_3 crossref_primary_10_1016_j_jmb_2020_03_014 crossref_primary_10_1016_j_bbagen_2017_10_015 crossref_primary_10_1074_jbc_M115_705160 crossref_primary_10_3390_ijms19113401 crossref_primary_10_1140_epje_s10189_024_00409_8 crossref_primary_10_1093_nar_gkaa1285 crossref_primary_10_1016_j_jmb_2021_167174 crossref_primary_10_1002_cphc_202300439 crossref_primary_10_7554_eLife_67605 crossref_primary_10_1038_nsmb_3232 crossref_primary_10_1038_s41467_024_51681_3 crossref_primary_10_3390_ijms21155277 crossref_primary_10_1073_pnas_1904813116 crossref_primary_10_1107_S205979831900264X crossref_primary_10_3390_ijms23126596 crossref_primary_10_1093_nar_gkaf154 crossref_primary_10_1074_jbc_M115_662379 crossref_primary_10_1186_s12964_015_0125_7 crossref_primary_10_1002_pro_70068 crossref_primary_10_1038_s41598_017_15299_4 crossref_primary_10_1126_sciimmunol_abm3723 crossref_primary_10_1016_j_bbagen_2018_04_006 crossref_primary_10_3389_fimmu_2024_1389494 crossref_primary_10_1016_j_bbapap_2017_07_013 crossref_primary_10_1107_S205979832101247X crossref_primary_10_7554_eLife_21848 crossref_primary_10_1021_jacs_4c13473 crossref_primary_10_1107_S2052252520008830 crossref_primary_10_1016_j_jbc_2021_100776 crossref_primary_10_1016_j_str_2025_07_008 crossref_primary_10_1073_pnas_2009596117 crossref_primary_10_1021_jacs_5b06027 crossref_primary_10_1107_S2059798315024328 crossref_primary_10_1111_febs_15660 crossref_primary_10_1093_nar_gkaa1021 crossref_primary_10_1016_j_jmb_2017_12_014 crossref_primary_10_1021_acs_biochem_5c00156 crossref_primary_10_1038_s41467_020_20262_5 crossref_primary_10_1074_jbc_RA119_008218 crossref_primary_10_1016_j_sbi_2019_04_004 crossref_primary_10_1016_j_jbc_2023_105356 crossref_primary_10_1002_advs_202302035 crossref_primary_10_1016_j_ijbiomac_2023_126288 crossref_primary_10_1038_s41580_023_00673_0 crossref_primary_10_1371_journal_pone_0156105 crossref_primary_10_1107_S1600577519005113 crossref_primary_10_1093_nar_gky206 crossref_primary_10_1107_S2052252517008740 crossref_primary_10_3389_fmolb_2022_823174 crossref_primary_10_1016_j_jbc_2025_110392 crossref_primary_10_3389_fmolb_2022_986121 crossref_primary_10_1073_pnas_2319998121 crossref_primary_10_1371_journal_pcbi_1006641 crossref_primary_10_1016_j_str_2024_05_018 crossref_primary_10_1002_cm_21773 crossref_primary_10_1038_nature16503 crossref_primary_10_1016_j_bpj_2018_04_018 crossref_primary_10_1016_j_jcis_2022_12_024 crossref_primary_10_1016_j_bpj_2019_06_024 crossref_primary_10_1128_spectrum_02373_23 crossref_primary_10_1038_srep40405 crossref_primary_10_1371_journal_pgen_1008435 crossref_primary_10_1038_s41598_020_67002_9 crossref_primary_10_1038_ncomms11343 crossref_primary_10_1016_j_str_2021_08_002 crossref_primary_10_1107_S1600576725002481 crossref_primary_10_3390_biom12091302 crossref_primary_10_1016_j_bpj_2019_12_025 crossref_primary_10_1261_rna_072595_119 crossref_primary_10_1107_S2059798317005745 crossref_primary_10_1016_j_bpj_2018_10_016 crossref_primary_10_1074_jbc_M117_799700 crossref_primary_10_1107_S205225252401217X crossref_primary_10_1016_j_pbiomolbio_2018_09_005 crossref_primary_10_1093_nar_gkaf043 crossref_primary_10_1242_jcs_239202 crossref_primary_10_1021_jacs_0c02088 crossref_primary_10_3390_polym11122104 crossref_primary_10_1016_j_bpj_2017_02_024 crossref_primary_10_1371_journal_pone_0202391 crossref_primary_10_3390_nano12030390 crossref_primary_10_1038_s41467_017_02312_7 crossref_primary_10_3389_fcimb_2021_673122 crossref_primary_10_1002_pro_4941 crossref_primary_10_1074_jbc_RA119_008011 crossref_primary_10_1261_rna_060343_116 crossref_primary_10_1042_BCJ20240110 crossref_primary_10_1074_jbc_RA119_010697 crossref_primary_10_1038_s41598_017_14448_z crossref_primary_10_1111_jnc_14556 |
| Cites_doi | 10.1038/ncomms2611 10.1073/pnas.0403643101 10.1006/jmbi.1997.1309 10.1073/pnas.0506202102 10.1107/S0021889812007662 10.1074/jbc.M112.398404 10.1002/bip.21638 10.1016/j.str.2014.03.012 10.2174/138920312799277901 10.1107/S0907444913018714 10.1016/j.jmb.2007.05.022 10.1016/j.jmb.2011.12.058 10.1021/ja069124n 10.1021/bi4008337 10.1006/jmbi.1993.1330 10.1093/acprof:oso/9780199639533.001.0001 10.1016/j.jsb.2009.08.009 10.1093/bioinformatics/bts172 10.1007/978-1-4614-3704-8_7 10.1073/pnas.1004569107 10.1038/471151a 10.4149/gpb_2009_02_174 10.15252/embj.201488143 10.1073/pnas.1113813108 10.1016/S0021-9258(18)96726-8 10.1002/prot.22153 10.1007/s00249-009-0549-3 10.1007/978-1-4757-6624-0 10.1038/nsmb.2160 10.1073/pnas.1323876111 10.1016/j.sbi.2011.03.012 10.1016/0022-2836(92)90324-D 10.1073/pnas.0404236101 10.1093/bioinformatics/bts701 10.1146/annurev.biophys.37.032807.125924 10.1021/bi00255a006 10.1016/j.str.2010.10.006 10.1073/pnas.1304749110 10.1371/journal.pone.0074783 10.1039/C0OB00535E 10.1107/S0021889806004699 10.1038/nchembio.1009 10.1073/pnas.1400340111 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2015 International Union of Crystallography Copyright International Union of Crystallography Mar 2015 Giancarlo Tria et al. 2015 2015 |
| Copyright_xml | – notice: COPYRIGHT 2015 International Union of Crystallography – notice: Copyright International Union of Crystallography Mar 2015 – notice: Giancarlo Tria et al. 2015 2015 |
| DBID | AAYXX CITATION NPM 7SR 7U5 8BQ 8FD 8FE 8FG ABJCF ABUWG AFKRA AZQEC BENPR BGLVJ CCPQU D1I DWQXO EHMNL HCIFZ JG9 KB. L7M PDBOC PHGZM PHGZT PIMPY PKEHL PQEST PQGLB PQQKQ PQUKI PRINS 7X8 5PM DOA |
| DOI | 10.1107/S205225251500202X |
| DatabaseName | CrossRef PubMed Engineered Materials Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Technology Collection ProQuest One Community College ProQuest Materials Science Collection ProQuest Central Korea UK & Ireland Database (ProQuest) SciTech Premium Collection Materials Research Database Materials Science Database Advanced Technologies Database with Aerospace Materials Science Collection Proquest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database Materials Research Database Technology Collection Technology Research Database ProQuest One Academic Middle East (New) ProQuest Central Essentials Materials Science Collection ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences Engineered Materials Abstracts ProQuest Central Korea Materials Science Database ProQuest Central (New) Advanced Technologies Database with Aerospace ProQuest Materials Science Collection ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection METADEX UK & Ireland Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection Solid State and Superconductivity Abstracts ProQuest One Academic ProQuest One Academic (New) MEDLINE - Academic |
| DatabaseTitleList | PubMed Publicly Available Content Database CrossRef Materials Research Database MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: KB. name: Materials Science Database url: http://search.proquest.com/materialsscijournals sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Biology |
| DocumentTitleAlternate | Advanced ensemble modelling of flexible macromolecules |
| EISSN | 2052-2525 |
| EndPage | 217 |
| ExternalDocumentID | oai_doaj_org_article_941cf0fe31f74c789abb424b8a0986a7 PMC4392415 3615028051 A406900827 25866658 10_1107_S205225251500202X |
| Genre | Journal Article |
| GroupedDBID | 5VS 8FE 8FG AAFWJ AAYXX ABJCF ABUWG ADBBV ADRAZ AENEX AFFHD AFKRA AFPKN ALMA_UNASSIGNED_HOLDINGS AOIJS BCNDV BENPR BGLVJ BPHCQ CCPQU CITATION D1I EBS EHMNL EJD GROUPED_DOAJ H13 HCIFZ HYE IAO IPNFZ ITC KB. KQ8 M48 M~E OK1 PDBOC PGMZT PHGZM PHGZT PIMPY PQGLB PQQKQ PROAC RCJ RIG RPM ZBA NPM 7SR 7U5 8BQ 8FD AZQEC DWQXO JG9 L7M PKEHL PQEST PQUKI PRINS 7X8 PUEGO 5PM |
| ID | FETCH-LOGICAL-c565t-12984acfc59a3970446b1d0212c6e3d25c54c7d4fe6208d2d6e0ae34ee85dc7d3 |
| IEDL.DBID | KB. |
| ISICitedReferencesCount | 485 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000356866400011&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2052-2525 |
| IngestDate | Fri Oct 03 12:44:03 EDT 2025 Tue Nov 04 02:04:20 EST 2025 Sun Aug 24 03:49:05 EDT 2025 Sun Nov 09 11:19:48 EST 2025 Fri Jul 25 12:06:02 EDT 2025 Tue Nov 04 17:58:24 EST 2025 Mon Jul 21 06:04:22 EDT 2025 Sat Nov 29 07:54:21 EST 2025 Tue Nov 18 21:20:29 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Keywords | unstructured biology symmetric oligomers hybrid methods macromolecular dynamics small-angle scattering proteins |
| Language | English |
| License | This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c565t-12984acfc59a3970446b1d0212c6e3d25c54c7d4fe6208d2d6e0ae34ee85dc7d3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://www.proquest.com/docview/1660702817?pq-origsite=%requestingapplication% |
| PMID | 25866658 |
| PQID | 1660702817 |
| PQPubID | 2035043 |
| PageCount | 11 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_941cf0fe31f74c789abb424b8a0986a7 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4392415 proquest_miscellaneous_1800432075 proquest_miscellaneous_1673072762 proquest_journals_1660702817 gale_infotracacademiconefile_A406900827 pubmed_primary_25866658 crossref_citationtrail_10_1107_S205225251500202X crossref_primary_10_1107_S205225251500202X |
| PublicationCentury | 2000 |
| PublicationDate | 2015-03-01 |
| PublicationDateYYYYMMDD | 2015-03-01 |
| PublicationDate_xml | – month: 03 year: 2015 text: 2015-03-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: Chester |
| PublicationTitle | IUCrJ |
| PublicationTitleAlternate | IUCrJ |
| PublicationYear | 2015 |
| Publisher | International Union of Crystallography |
| Publisher_xml | – name: International Union of Crystallography |
| References | Møller (fc5007_bb26) 2013; 8 Calmettes (fc5007_bb9) 1993; 231 Xu (fc5007_bb44) 2012; 416 Bernadó (fc5007_bb3) 2010; 39 Devarakonda (fc5007_bb12) 2011; 108 Tanford (fc5007_bb39) 1966; 241 Uversky (fc5007_bb42) 2008; 37 Tompa (fc5007_bb40) 2011; 21 Chouard (fc5007_bb10) 2011; 471 fc5007_bb17 Jensen (fc5007_bb18) 2014; 111 Receveur-Brechot (fc5007_bb31) 2012; 13 Chattopadhyaya (fc5007_bb51) 1992; 228 fc5007_bb16 fc5007_bb38 Rambo (fc5007_bb30) 2011; 95 fc5007_bb14 Pérard (fc5007_bb28) 2013; 4 fc5007_bb35 Pelikan (fc5007_bb27) 2009; 28 Ozenne (fc5007_bb2) 2012; 11 Kleywegt (fc5007_bb19) 1997; 273 Cook (fc5007_bb52) 1994; 33 Sander (fc5007_bb34) 2013; 69 Sterckx (fc5007_bb37) 2014; 22 Mertens (fc5007_bb25) 2012; 287 Luan (fc5007_bb24) 2014; 53 Krissinel (fc5007_bb22) 2007; 372 Wang (fc5007_bb43) 2014; 111 Bernadó (fc5007_bb6) 2012; 896 Brewer (fc5007_bb8) 2011; 9 Kohn (fc5007_bb20) 2004; 101 fc5007_bb50 Tompa (fc5007_bb41) 2012; 8 Rubio-Cosials (fc5007_bb33) 2011; 18 Różycki (fc5007_bb32) 2011; 19 Bernadó (fc5007_bb4) 2005; 102 Petoukhov (fc5007_bb29) 2012; 45 Konarev (fc5007_bb21) 2006; 39 Fitzkee (fc5007_bb15) 2004; 101 Bernadó (fc5007_bb5) 2007; 129 Das (fc5007_bb11) 2013; 110 Banavali (fc5007_bb1) 2009; 74 Krzeminski (fc5007_bb23) 2013; 29 Yang (fc5007_bb45) 2010; 107 Soykan (fc5007_bb36) 2014; 33 Durand (fc5007_bb13) 2010; 169 |
| References_xml | – volume: 4 start-page: 1612 year: 2013 ident: fc5007_bb28 publication-title: Nature Commun. doi: 10.1038/ncomms2611 – volume: 101 start-page: 12491 year: 2004 ident: fc5007_bb20 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0403643101 – volume: 273 start-page: 371 year: 1997 ident: fc5007_bb19 publication-title: J. Mol. Biol. doi: 10.1006/jmbi.1997.1309 – volume: 102 start-page: 17002 year: 2005 ident: fc5007_bb4 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0506202102 – volume: 45 start-page: 342 year: 2012 ident: fc5007_bb29 publication-title: J. Appl. Cryst. doi: 10.1107/S0021889812007662 – volume: 287 start-page: 34304 year: 2012 ident: fc5007_bb25 publication-title: J. Biol. Chem. doi: 10.1074/jbc.M112.398404 – volume: 95 start-page: 559 year: 2011 ident: fc5007_bb30 publication-title: Biopolymers doi: 10.1002/bip.21638 – volume: 22 start-page: 854 year: 2014 ident: fc5007_bb37 publication-title: Structure doi: 10.1016/j.str.2014.03.012 – ident: fc5007_bb17 – volume: 13 start-page: 55 year: 2012 ident: fc5007_bb31 publication-title: Curr. Protein Pept. Sci. doi: 10.2174/138920312799277901 – volume: 69 start-page: 2050 year: 2013 ident: fc5007_bb34 publication-title: Acta Cryst. D doi: 10.1107/S0907444913018714 – volume: 372 start-page: 774 year: 2007 ident: fc5007_bb22 publication-title: J. Mol. Biol. doi: 10.1016/j.jmb.2007.05.022 – volume: 416 start-page: 629 year: 2012 ident: fc5007_bb44 publication-title: J. Mol. Biol. doi: 10.1016/j.jmb.2011.12.058 – volume: 129 start-page: 5656 year: 2007 ident: fc5007_bb5 publication-title: J. Am. Chem. Soc. doi: 10.1021/ja069124n – volume: 53 start-page: 39 year: 2014 ident: fc5007_bb24 publication-title: Biochemistry doi: 10.1021/bi4008337 – volume: 231 start-page: 840 year: 1993 ident: fc5007_bb9 publication-title: J. Mol. Biol. doi: 10.1006/jmbi.1993.1330 – ident: fc5007_bb38 doi: 10.1093/acprof:oso/9780199639533.001.0001 – volume: 169 start-page: 45 year: 2010 ident: fc5007_bb13 publication-title: J. Struct. Biol. doi: 10.1016/j.jsb.2009.08.009 – volume: 11 start-page: 1463 year: 2012 ident: fc5007_bb2 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts172 – volume: 896 start-page: 107 year: 2012 ident: fc5007_bb6 publication-title: Methods Mol. Biol. doi: 10.1007/978-1-4614-3704-8_7 – volume: 107 start-page: 15757 year: 2010 ident: fc5007_bb45 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1004569107 – volume: 471 start-page: 151 year: 2011 ident: fc5007_bb10 publication-title: Nature doi: 10.1038/471151a – volume: 28 start-page: 174 year: 2009 ident: fc5007_bb27 publication-title: Gen. Physiol. Biophys. doi: 10.4149/gpb_2009_02_174 – volume: 33 start-page: 2113 year: 2014 ident: fc5007_bb36 publication-title: EMBO J. doi: 10.15252/embj.201488143 – volume: 108 start-page: 18678 year: 2011 ident: fc5007_bb12 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1113813108 – volume: 241 start-page: 1921 year: 1966 ident: fc5007_bb39 publication-title: J. Biol. Chem. doi: 10.1016/S0021-9258(18)96726-8 – ident: fc5007_bb35 – volume: 74 start-page: 378 year: 2009 ident: fc5007_bb1 publication-title: Proteins doi: 10.1002/prot.22153 – volume: 39 start-page: 769 year: 2010 ident: fc5007_bb3 publication-title: Eur. Biophys. J. doi: 10.1007/s00249-009-0549-3 – ident: fc5007_bb14 doi: 10.1007/978-1-4757-6624-0 – volume: 18 start-page: 1281 year: 2011 ident: fc5007_bb33 publication-title: Nature Struct. Mol. Biol. doi: 10.1038/nsmb.2160 – volume: 111 start-page: E1557 year: 2014 ident: fc5007_bb18 publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1323876111 – volume: 21 start-page: 419 year: 2011 ident: fc5007_bb40 publication-title: Curr. Opin. Struct. Biol. doi: 10.1016/j.sbi.2011.03.012 – ident: fc5007_bb16 – ident: fc5007_bb50 – volume: 228 start-page: 1177 year: 1992 ident: fc5007_bb51 publication-title: J. Mol. Biol. doi: 10.1016/0022-2836(92)90324-D – volume: 101 start-page: 12497 year: 2004 ident: fc5007_bb15 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0404236101 – volume: 29 start-page: 398 year: 2013 ident: fc5007_bb23 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts701 – volume: 37 start-page: 215 year: 2008 ident: fc5007_bb42 publication-title: Annu. Rev. Biophys. doi: 10.1146/annurev.biophys.37.032807.125924 – volume: 33 start-page: 15259 year: 1994 ident: fc5007_bb52 publication-title: Biochemistry doi: 10.1021/bi00255a006 – volume: 19 start-page: 109 year: 2011 ident: fc5007_bb32 publication-title: Structure doi: 10.1016/j.str.2010.10.006 – volume: 110 start-page: 13392 year: 2013 ident: fc5007_bb11 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1304749110 – volume: 8 start-page: e74783 year: 2013 ident: fc5007_bb26 publication-title: PLoS One doi: 10.1371/journal.pone.0074783 – volume: 9 start-page: 777 year: 2011 ident: fc5007_bb8 publication-title: Org. Biomol. Chem. doi: 10.1039/C0OB00535E – volume: 39 start-page: 277 year: 2006 ident: fc5007_bb21 publication-title: J. Appl. Cryst. doi: 10.1107/S0021889806004699 – volume: 8 start-page: 597 year: 2012 ident: fc5007_bb41 publication-title: Nature Chem. Biol. doi: 10.1038/nchembio.1009 – volume: 111 start-page: E1559 year: 2014 ident: fc5007_bb43 publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1400340111 |
| SSID | ssj0001125741 |
| Score | 2.5316029 |
| Snippet | Dynamic ensembles of macromolecules mediate essential processes in biology. Understanding the mechanisms driving the function and molecular interactions of... New developments in the modelling of flexible biological macromolecules from SAXS data offer extended possibilities of using high-resolution models and provide... |
| SourceID | doaj pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | 207 |
| SubjectTerms | Algorithms Biology hybrid methods macromolecular dynamics Macromolecules Mathematical models Optimization Pools Protein folding Protein research Proteins Research Papers SAXS small-angle scattering Structure symmetric oligomers unstructured biology X-rays |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1La9wwEBYl9NAeSpu-3KZBhUKhYGLLevm4LQ05hUIf7E3oMW4DqTfsbgr9952RvYtNIL3kqpFhNRppvlnNfMPYO3RhsfapLX0XYilNgLINFZU-1RKMb6JKKTebMOfndrlsv0xafVFO2EAPPCjupJV17KoOmrozMhrb-hCkkMH6qrXa5zpyRD2TYCr_u4J-2-S2laJSohRKqPFJE8Odk680SGOIhhAuieXMKWXu_ps39MRFzdMnJ_7o9DF7NAJJvhgW8ITdg_6QPZzQCz5lPxbjAz_HWBV-h0vgufENVaDzVcc7IsPMoz5n5eVGubDhlAv_ky_Ltf_Ld6bJNzEzcaLkGft--vnbp7Ny7KNQRoRr2xJdupU-dlG1HuEHPeGGOhG3e9TQJKGiQs0m2YFGVSaRNFQeGglgVUJB85wd9KseXjKuQXa6CRUgEJIYm7RaxBoMdSuzQSdTsGqnSBdHknHqdXHpcrBRGXdD9wX7sP_kamDYuG3yR9qd_UQix84DaDJuNBn3P5Mp2HvaW0dHGH9c9GMlAi6RyLDcgqqBCRvhzKPd9rvxbG9crTXek8LWKH67F-OppKcW38PqmubgzYnQUItb5tjMh4iYrWAvBovar0soi3GlsgUzM1ubLXwu6S9-ZXZwRJiEyl7dhaZeswcIENWQc3fEDrbra3jD7sc_24vN-jgfuX_EACx- priority: 102 providerName: Directory of Open Access Journals |
| Title | Advanced ensemble modelling of flexible macromolecules using X-ray solution scattering |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/25866658 https://www.proquest.com/docview/1660702817 https://www.proquest.com/docview/1673072762 https://www.proquest.com/docview/1800432075 https://pubmed.ncbi.nlm.nih.gov/PMC4392415 https://doaj.org/article/941cf0fe31f74c789abb424b8a0986a7 |
| Volume | 2 |
| WOSCitedRecordID | wos000356866400011&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: DOA dateStart: 20140101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: M~E dateStart: 20140101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Materials Science Database customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: KB. dateStart: 20140101 isFulltext: true titleUrlDefault: http://search.proquest.com/materialsscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: BENPR dateStart: 20140101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: PIMPY dateStart: 20140101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVPQU databaseName: UK & Ireland Database (ProQuest) customDbUrl: eissn: 2052-2525 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001125741 issn: 2052-2525 databaseCode: EHMNL dateStart: 20140101 isFulltext: true titleUrlDefault: https://search.proquest.com/ukireland providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1La9wwEBZN0kNz6Dut23RxoVAouLFlvXwquyWhpXRZ-sI9GVmS00Bip-tNof--M1rtZk1gL71KY9Dg0cw30ugbQl5BCDOZtkWim9okTNYuKeoUnz5lzEmdG26tbzYhp1NVlsUsHLj1oaxy5RO9o7adwTPyo0wIsE6qMvnu8neCXaPwdjW00Nghe8iSgK0bPk3eXp-xQPSGiBkuMyHROfpKUwAcHII6R6BEy0E48qz9N33zRnAaFk5uRKKTe_-rw31yN2DQeLw0mgfklmsfkv0NZsJH5Mc41AbEkOa6i_rcxb5nDj5ej7smbpBH049qX9Dne-y6PsYy-tO4TOb6b7yy6rg3nsQTZh6T7yfH395_SEILhsQA0lskgAYU06YxvNCAXPD2t84s0sIb4XJLueHMSMsaJ2iqLLXCpdrlzDnFLUzkB2S37Vr3lMTCsUbkdeoAQzFIawpBTeYkNjpTtbAyIunqT1Qm8JNjm4zzyucpqaxu_LyIvFl_crkk59gmPMHfuxZEXm0_0M1Pq7BNq4Jlpkkbl2eNBMVUoeuaUVYrnRZKaFjkazSOCnc_LM7o8IgBVEQerWqMD4kRVoHk4coGquAW-uraACLycj0NGxpvaXTruiuUAacLqFLQLTLKUykC3IvIk6VJrvWiXEFKylVE5MBYB4oPZ9qzX55YHMApArpn25f-nNwB1MiXhXiHZHcxv3IvyG3zZ3HWz0dkR5ZqRPYmx9PZl5E_4hj5XQljs4-fZz__Ad8BPYI |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEB6VFAk48KYECiwSCAnJqr1er9cHhMKjatQ2ikRB4WTWu-u2UnFKnIL6p_iNzGzsNFGl3Hrg6h1bO_Y8vvHOA-AVujATaZsFuixMINLCBVkRUulTJFyqY5NY64dNpIOBGo2y4Rr8bWthKK2ytYneUNuxoX_kW5GUKJ1cRen7018BTY2i09V2hMZMLHbd-R8M2ep3_U_4fV9zvv354ONO0EwVCAyCl2mADk4JbUqTZBqdMR1oFpGlTudGutjyxCTCpFaUTvJQWW6lC7WLhXMqsbgQ43OvwbpAYVcdWB_294ffL_7qIF5AH90cn2JotfWFhwhxEoQRCUEzPlpygH5OwGVvsOAOl1M1F3zf9p3_7a3dhdsNyma9mVrcgzVX3YdbC70XH8C3XpP9wDCQdz-LE8f8VCAqz2fjkpXUKdRf1T5l0U8RdjWjQoFDNgom-py1estq49uU4spD-HoljD2CTjWu3GNg0olSxkXoECUKDNwyyU3kUhrlpgpp0y6E7ZfPTdOBnQaBnOQ-EgvT_JKwdOHt_JbTWfuRVcQfSJzmhNQ53F8YTw7zxhDlmYhMGZYujsoUGVOZLgrBRaF0mCmpcZNvSBhzsm-4OaObMg1kkTqF5T0qlSbgiJSbrczljeGr8wuB68LL-TKaLDqH0pUbnxENuhXEzZKvoFG-WSQC2i5szFRgzhcqHgbdiepCuqQcS4wvr1THR751OsJvgqxPVm_9BdzYOdjfy_f6g92ncBMxcjJLO9yEznRy5p7BdfN7elxPnjf6z-DHVSvPPwJllzw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Advanced+ensemble+modelling+of+flexible+macromolecules+using+X-ray+solution+scattering&rft.jtitle=IUCrJ&rft.au=Tria%2C+Giancarlo&rft.au=Mertens%2C+Haydyn+D+T&rft.au=Kachala%2C+Michael&rft.au=Svergun%2C+Dmitri+I&rft.date=2015-03-01&rft.eissn=2052-2525&rft.volume=2&rft.issue=2&rft.spage=207&rft.epage=217&rft_id=info:doi/10.1107%2FS205225251500202X&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2052-2525&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2052-2525&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2052-2525&client=summon |