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B Tom Burnley

Pavel V Afonine

Paul D Adams

Piet Gros

(2012)
Modelling dynamics in protein crystal structures by ensemble refinement

eLife 1:e00311.

https://doi.org/10.7554/eLife.00311
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Figures
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14 figures and 5 tables

Figures

Figure 1

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Example of ensemble refinement for dataset 1UOY. (A) Optimisation of empirical ensemble refinement parameters (τ_x, p_TLS and T_bath). Simulations are performed independently and in parallel. The plot …
https://doi.org/10.7554/eLife.00311.004

Figure 2

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Ensemble refinement parameters and results as function of resolution of the datasets. (A) Gain in R_free of ensemble refinement compared with re-refinement using phenix.refine, (B) number of …
https://doi.org/10.7554/eLife.00311.005

Figure 3

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Validation of ensemble refinement using dataset 1YTT with exceptionally high quality experimental phases. (A) Real space cross-correlation of experimentally phased electron density map (|F_obs|exp[iφ_o…
https://doi.org/10.7554/eLife.00311.009

Figure 4

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Sampling reproducibility of ensemble refinement. (A) Cross-correlations (CC) calculated for all pairs from 10 random-number seed repeat ensemble refinements of the 1UOY dataset extending to 1.5-Å …
https://doi.org/10.7554/eLife.00311.010

Figure 5

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Reproducibility of side-chain rotamer distributions. Mean χ₁ and χ₂ distributions of four side-chains from the 10 repeats, with error bars ±1 σ, are shown for 1UOY. The four residues presented are …
https://doi.org/10.7554/eLife.00311.011

Figure 6

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Ramachandran analysis. Distribution of Ramachandran torsion angles classified as outliers (red) and allowed (blue) for ensemble models, 1UOY (A) and 1BV1 (B). Plot shows percentage of classification …
https://doi.org/10.7554/eLife.00311.012

Figure 6—source data 1 Geometries of single-structure models and ensemble models. Rms deviations (RMSD) from ideal bond, angle and dihedral geometries calculated for single structures re-refined using phenix.refine. Geometries for ensemble structures were calculated using two methods, the ‘whole distribution’, where the RMSD was calculated for each restraint (averaged over all structures), √〈(x_ideal − x_model)²〉, and ‘centroid’ where the RMSD was calculated using the mean deviation from ideality for each restraint, √〈(〈x_ideal − x_model〉)²〉, which for unimodal functions equals √〈(x_ideal − 〈x_model〉)²〉.: https://doi.org/10.7554/eLife.00311.013
Download elife-00311-fig6-data1-v1.xlsx
Figure 6—source data 2 Ramachandran statistics for re-refined and ensemble models. The Ramachandran statistics for the ensemble models are calculated in two ways: ‘Ramachandran (mean)’ shows the percentage of outliers, allowed and favoured averaged over all structures in the ensemble (cf. ‘whole distribution’ in Figure 6—source data 1), whereas ‘Ramachandran (mode)’ shows these percentages based on the most frequent occurring classification of each φ,ψ combination (cf. ‘centroid distribution’ in Figure 6—source data 1).: https://doi.org/10.7554/eLife.00311.014
Download elife-00311-fig6-data2-v1.xlsx

Figure 7 with 4 supplements

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Comparison of atomic fluctuations for non-crystallographic symmetry related protein copies for dataset 1M52. (A) Cα trace of the re-refined single structure coloured by B-factor (from blue to red …
https://doi.org/10.7554/eLife.00311.015

Figure 7—figure supplement 1

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Comparison of atomic fluctuations for NCS related protein copies for dataset 2R8Q.

https://doi.org/10.7554/eLife.00311.016

Figure 7—figure supplement 2

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Comparison of atomic fluctuations for NCS related protein copies for dataset 1YTT.

https://doi.org/10.7554/eLife.00311.017

Figure 7—figure supplement 3

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Comparison of atomic fluctuations for NCS related protein copies for dataset 1IEP.

https://doi.org/10.7554/eLife.00311.018

Figure 7—figure supplement 4

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Comparison of atomic fluctuations for NCS related protein copies for dataset 2XFA.

https://doi.org/10.7554/eLife.00311.019

Figure 8

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Ensemble refinement of two isomorphous proline isomerase datasets collected at 100 K and 288 K. (A) Left, basal TLS B-factors of ensemble models for 100 K and 288 K datasets (blue and green, …
https://doi.org/10.7554/eLife.00311.020

Figure 9

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Overview of side-chain dynamics in ensemble structures. Atoms are coloured by their relative probability in the ensemble (see ‘Materials and methods’), reflecting the degree of disorder (ranging …
https://doi.org/10.7554/eLife.00311.021

Figure 10

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Dynamics in the binding pocket of proline isomerase at 288 K. (A) The location of the binding pocket comprised of residues Arg55, Met61, Ser99 and Phe113. (B) Zoom in of binding pocket (as dotted …
https://doi.org/10.7554/eLife.00311.022

Figure 11

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Comparison of ensemble structures of bound and unbound forms of HIV protease. (A) Residues in the P1 binding sites are disordered in the unbound HIV protease (2PC0), left-hand side, with carbon …
https://doi.org/10.7554/eLife.00311.023

Figure 12

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ABL-kinase Imatinib binding site. (A) Imatinib binding site in chain A of the 1IEP dataset showing distribution of the six protein–ligand hydrogen bonds in chain A and chain B (red and blue …
https://doi.org/10.7554/eLife.00311.024

Figure 13

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Correlation of R-values and overall map correlation coefficient for the 1YTT dataset in the block selection procedure. The correlation coefficients are calculated between the experimentally phased …
https://doi.org/10.7554/eLife.00311.026

Figure 14

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Interpretation of global and local details of 1UOY ensemble model is aided by relative atomic probability (as described in ‘Materials and methods’). Ensemble models, left and centre, are colour by …
https://doi.org/10.7554/eLife.00311.027

Tables

Table 1

Ensemble refinement statistics for 20 datasets. Datasets were taken from the PDB or PDB_REDO and were re-refined using ensemble refinement and phenix.refine. The relaxation time τ_x used, the …

https://doi.org/10.7554/eLife.00311.003

PDB ID	Resolution (Å)	Ensemble refinement				phenix.refine		Ensemble—phenix.refine
PDB ID	Resolution (Å)	τ_x (ps)	No. of structures	R_work	R_free	R_work	R_free	ΔR_work	ΔR_free
1KZK	1.1	1.5	600	0.125	0.153	0.136	0.155	−0.011	−0.003
3K0M	1.3	2.0	250	0.104	0.129	0.116	0.132	−0.012	−0.003
3K0N	1.4	1.0	209	0.115	0.133	0.119	0.143	−0.004	−0.010
2PC0	1.4	0.8	250	0.145	0.188	0.161	0.193	−0.016	−0.005
1UOY	1.5	1.0	167	0.104	0.137	0.155	0.185	−0.051	−0.049
3CA7	1.5	0.8	40	0.149	0.184	0.171	0.212	−0.022	−0.029
2R8Q	1.5	1.0	200	0.132	0.162	0.158	0.178	−0.026	−0.016
3QL0	1.6	0.5	70	0.204	0.254	0.229	0.270	−0.024	−0.017
1X6P	1.6	1.0	400	0.121	0.149	0.140	0.175	−0.019	−0.026
1F2F	1.7	0.8	143	0.128	0.168	0.160	0.198	−0.032	−0.031
3QL3	1.8	0.5	80	0.160	0.208	0.170	0.221	−0.010	−0.013
1YTT	1.8	0.3	84	0.139	0.174	0.166	0.189	−0.027	−0.014
3GWH	2.0	1.0	39	0.160	0.200	0.187	0.220	−0.027	−0.021
1BV1	2.0	0.4	78	0.149	0.182	0.154	0.205	−0.005	−0.023
1IEP	2.1	0.5	200	0.183	0.238	0.196	0.245	−0.012	−0.007
2XFA	2.1	1.0	100	0.171	0.217	0.184	0.244	−0.013	−0.027
3ODU	2.5	0.3	50	0.208	0.269	0.219	0.281	−0.010	−0.012
1M52	2.6	0.5	50	0.161	0.211	0.168	0.228	−0.007	−0.017
3CM8	2.9	0.5	67	0.194	0.235	0.205	0.248	−0.011	−0.013
3RZE	3.1	0.1	72	0.210	0.280	0.210	0.291	0.000	−0.011
							Max	−0.051	−0.049
							Min	0.000	−0.003
							Mean	−0.018	−0.018

Table 2

Rms (mF_obs − DF_model)exp[iφ_model] difference densities obtained from ensemble refinement and re-refinement in phenix.refine

https://doi.org/10.7554/eLife.00311.006

PDB ID	Resolution (Å)	σ_mFo−DFc (e/Å³)
PDB ID	Resolution (Å)	Ensemble	phenix.refine
1KZK	1.1	0.138	0.161
3K0M	1.3	0.016	0.018
3K0N	1.4	0.007	0.008
2PCO	1.4	0.099	0.099
1UOY	1.5	0.115	0.162
3CA7	1.5	0.132	0.148
2R8Q	1.5	0.104	0.118
3QL0	1.6	0.124	0.138
1X6P	1.6	0.098	0.105
1F2F	1.7	0.104	0.126
3QL3	1.8	0.131	0.139
1YTT	1.8	0.170	0.215
3GWH	2.0	0.125	0.138
1BV1	2.0	0.109	0.119
1IEP	2.1	0.084	0.091
2XFA	2.1	0.069	0.074
3ODU	2.5	0.105	0.113
1M52	2.6	0.088	0.093
3CM8	2.9	0.036	0.036
3RZE	3.1	0.070	0.070

Table 3

Effect of input structure on ensemble refinement. For three datasets ensemble refinement was performed using a starting structure from three different refinement programs. For each structure three …

https://doi.org/10.7554/eLife.00311.007

PDB	Re-refinement			Ensemble refinement
	Re-refinement			Repeat 1		Repeat 2		Repeat 3		Mean
	Program	R_work	R_free	R_work	R_free	R_work	R_free	R_work	R_free	R_work	R_free
1UOY	Buster	0.167	0.196	0.108	0.144	0.112	0.145	0.110	0.146	0.110	0.145
	Refmac	0.147	0.170	0.104	0.137	0.103	0.140	0.105	0.144	0.104	0.140
	Phenix	0.155	0.185	0.109	0.142	0.109	0.147	0.111	0.149	0.110	0.146
3CA7	Buster	0.177	0.208	0.137	0.186	0.137	0.192	0.141	0.197	0.138	0.192
	Refmac	0.170	0.205	0.139	0.187	0.135	0.189	0.138	0.193	0.137	0.189
	Phenix	0.171	0.212	0.138	0.180	0.142	0.189	0.148	0.193	0.142	0.187
1BV1	Buster	0.161	0.204	0.137	0.184	0.138	0.185	0.137	0.186	0.138	0.185
	Refmac	0.178	0.231	0.140	0.182	0.143	0.184	0.143	0.189	0.142	0.185
	Phenix	0.154	0.205	0.139	0.188	0.138	0.189	0.140	0.189	0.139	0.189

Table 4

F_model cross-correlation scores for ensembles generated with different input models. Three different refinement programs generated alternative starting structures, see Table 3. The best ensemble was …

https://doi.org/10.7554/eLife.00311.008

PDB	Ensemble pair		CC
PDB	Re-refined input	Re-refined input	CC
1UOY	Refmac	Buster	0.997
	Refmac	Phenix	0.997
	Buster	Phenix	0.999
3CA7	Refmac	Buster	0.993
	Refmac	Phenix	0.992
	Buster	Phenix	0.996
1BV1	Refmac	Buster	0.992
	Refmac	Phenix	0.990
	Buster	Phenix	0.992

Table 5

Comparison of three B-factor models for ensemble refinement. Burling et al. (Burling and Brunger, 1994) had shown previously that the choice of ADPs for ensemble refinement can affect the resultant …

https://doi.org/10.7554/eLife.00311.025

PDB	Resolution (Å)	Global isotropic B-factor				Refined ADPs			Fitted TLS ADPs
PDB	Resolution (Å)	R_work	R_free	Wilson B-factor (Å²)	Global B-factor (Å²)	R_work	R_free	Scale factor	R_work	R_free	pTLS
3K0M	1.3	0.117	0.147	12.0	12.0	0.125	0.146	0.9	0.103	0.130	0.3
3K0N	1.4	0.121	0.153	19.1	19.1	0.126	0.153	0.9	0.114	0.133	0.1
1UOY	1.5	0.103	0.148	10.4	9.4	0.107	0.144	0.9	0.101	0.136	0.3
3CA7	1.5	0.129	0.194	16.8	13.4	0.142	0.192	0.9	0.142	0.190	0.5
1X6P	1.6	0.108	0.158	15.9	12.7	0.113	0.152	0.8	0.121	0.150	0.8
1F2F	1.7	0.116	0.184	15.6	14.8	0.123	0.167	0.8	0.126	0.167	0.7
1BV1	2.0	0.125	0.192	22.6	18.1	0.135	0.191	0.8	0.145	0.182	0.6
Mean	-	0.117	0.168	-	-	0.125	0.164	-	0.122	0.155	-