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1.  JLigand: a graphical tool for the CCP4 template-restraint library 
The CCP4 template-restraint library defines restraints for biopolymers, their modifications and ligands that are used in macromolecular structure refinement. JLigand is a graphical editor for generating descriptions of new ligands and covalent linkages.
Biological macromolecules are polymers and therefore the restraints for macromolecular refinement can be subdivided into two sets: restraints that are applied to atoms that all belong to the same monomer and restraints that are associated with the covalent bonds between monomers. The CCP4 template-restraint library contains three types of data entries defining template restraints: descriptions of monomers and their modifications, both used for intramonomer restraints, and descriptions of links for intermonomer restraints. The library provides generic descriptions of modifications and links for protein, DNA and RNA chains, and for some post-translational modifications including glycosylation. Structure-specific template restraints can be defined in a user’s additional restraint library. Here, JLigand, a new CCP4 graphical interface to LibCheck and REFMAC that has been developed to manage the user’s library and generate new monomer entries is described, as well as new entries for links and associated modifications.
PMCID: PMC3322602  PMID: 22505263
macromolecular refinement; restraint library; molecular graphics
2.  Differences in the operational characteristics of the human recombinant somatostatin receptor types, sst1 and sst2, in mouse fibroblast (Ltk-) cells. 
British Journal of Pharmacology  1996;117(4):639-646.
1. The human recombinant somatostatin (SRIF) receptors, sst1 and sst2, have been stably expressed in mouse fibroblast (Ltk-) cells. Two stable clones, LSSR 1/20 and LSSR 11/13, expressing sst1 and sst2 receptors, respectively, have been used to characterize these receptor types using radioligand binding assays as well as measurements of changes in extracellular acidification rates using microphysiometry. 2. [125I]-[Tyr11]-SRIF bound to sst1 and sst2 receptors expressed in Ltk- cells with high affinity, Kd values being 1.52 nM, and 0.23 nM respectively. 3. In Ltk- cells expressing sst1 receptors, SRIF, SRIF-28, [D-Trp8]-SRIF and CGP 23996 all displaced [125I]-[Tyr11]-SRIF binding with high potency (IC50 values of 0.43 - 1.27 nM) whilst seglitide, BIM-23027, BIM-23056 and L-362855 were either weak inhibitors of binding or were ineffective. 4. In contrast MK-678 (seglitide) and BIM-23027 were the most potent inhibitors of [125I]-[Tyr11]-SRIF binding in Ltk- cells expressing sst2 receptors with IC50 values of 0.014 and 0.035 nM, respectively. 5. SRIF and a number of SRIF agonists, including seglitide and BIM-23027, caused concentration-dependent increases in extracellular acidification rates in Ltk- cells expressing sst2 receptors but not in Ltk- cells expressing sst1 receptors. The maximum increase in acidification rate produced by SRIF was 11.3 +/- 0.7% above baseline (0.1-0.28 pH unit min-1). The relative potencies of the SRIF agonists examined in causing increases in extracellular acidification rates in Ltk- cells expressing sst2 receptors correlated well with their relative potencies in inhibiting [125I]-[Tyr11] -SRIF binding (r = 0.94). 6. The increase in extracellular acidification produced by SRIF was markedly inhibited by pretreatment of cells with pertussis toxin (100 ng ml-1) indicating the involvement of pertussis toxin-sensitive G proteins. 7. SRIF (1 microM) had no effect on basal cyclic AMP levels in Ltk- cells expressing sst1 or sst2 receptors nor did it inhibit forskolin stimulated increases in cyclic AMP levels in either cell type. 8. The results from the present study describe the operational characteristics of human sst2 receptors expressed in Ltk- cells where receptor activation causes increases in extracellular acidification rates. This receptor is coupled to a pertussis toxin-sensitive G protein. In contrast, activation of sst1 receptors, at a similar transfection density, did not cause increases in extracellular acidification rates.
PMCID: PMC1909325  PMID: 8646408
3.  Flexible torsion-angle noncrystallographic symmetry restraints for improved macromolecular structure refinement 
Flexible torsion angle-based NCS restraints have been implemented in phenix.refine, allowing improved model refinement at all resolutions. Rotamer correction and rotamer consistency checks between NCS-related amino-acid side chains further improve the final model quality.
One of the great challenges in refining macromolecular crystal structures is a low data-to-parameter ratio. Historically, knowledge from chemistry has been used to help to improve this ratio. When a macromolecule crystallizes with more than one copy in the asymmetric unit, the noncrystallographic symmetry relationships can be exploited to provide additional restraints when refining the working model. However, although globally similar, NCS-related chains often have local differences. To allow for local differences between NCS-related molecules, flexible torsion-based NCS restraints have been introduced, coupled with intelligent rotamer handling for protein chains, and are available in phenix.refine for refinement of models at all resolutions.
PMCID: PMC4014122  PMID: 24816103
macromolecular crystallography; noncrystallographic symmetry; NCS; refinement; automation
4.  Accurate macromolecular crystallographic refinement: incorporation of the linear scaling, semiempirical quantum-mechanics program DivCon into the PHENIX refinement package 
Semiempirical quantum-chemical X-ray macromolecular refinement using the program DivCon integrated with PHENIX is described.
Macromolecular crystallographic refinement relies on sometimes dubious stereochemical restraints and rudimentary energy functionals to ensure the correct geometry of the model of the macromolecule and any covalently bound ligand(s). The ligand stereochemical restraint file (CIF) requires a priori understanding of the ligand geometry within the active site, and creation of the CIF is often an error-prone process owing to the great variety of potential ligand chemistry and structure. Stereochemical restraints have been replaced with more robust functionals through the integration of the linear-scaling, semiempirical quantum-mechanics (SE-QM) program DivCon with the PHENIX X-ray refinement engine. The PHENIX/DivCon package has been thoroughly validated on a population of 50 protein–ligand Protein Data Bank (PDB) structures with a range of resolutions and chemistry. The PDB structures used for the validation were originally refined utilizing various refinement packages and were published within the past five years. PHENIX/DivCon does not utilize CIF(s), link restraints and other parameters for refinement and hence it does not make as many a priori assumptions about the model. Across the entire population, the method results in reasonable ligand geometries and low ligand strains, even when the original refinement exhibited difficulties, indicating that PHENIX/DivCon is applicable to both single-structure and high-throughput crystallography.
PMCID: PMC4014119  PMID: 24816093
X-ray crystallography; quantum-mechanics refinement; regional refinement; stereochemical restraints; ligand strain; high-throughput crystallography
5.  IsoCleft Finder – a web-based tool for the detection and analysis of protein binding-site geometric and chemical similarities 
F1000Research  2013;2:117.
IsoCleft Finder is a web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. The non-redundant dataset developed as part of this study is composed of 7339 entries representing unique Pfam/PDB-ligand (hetero group code) combinations with known levels of cognate ligand similarity. The query cavity can be uploaded by the user or detected automatically by the system using existing PDB entries as well as user-provided structures in PDB format. In all cases, the user can refine the definition of the cavity interactively via a browser-based Jmol 3D molecular visualization interface. Furthermore, users can restrict the search to a subset of the dataset using a cognate-similarity threshold. Local structural similarities are detected using the IsoCleft software and ranked according to two criteria (number of atoms in common and Tanimoto score of local structural similarity) and the associated Z-score and p-value measures of statistical significance. The results, including predicted ligands, target proteins, similarity scores, number of atoms in common, etc., are shown in a powerful interactive graphical interface. This interface permits the visualization of target ligands superimposed on the query cavity and additionally provides a table of pairwise ligand topological similarities. Similarities between top scoring ligands serve as an additional tool to judge the quality of the results obtained. We present several examples where IsoCleft Finder provides useful functional information. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography. IsoCleft Finder can be found at:
PMCID: PMC3892921  PMID: 24555058
6.  IsoCleft Finder – a web-based tool for the detection and analysis of protein binding-site geometric and chemical similarities 
F1000Research  2013;2:117.
IsoCleft Finder is a web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. The non-redundant dataset developed as part of this study is composed of 7339 entries representing unique Pfam/PDB-ligand (hetero group code) combinations with known levels of cognate ligand similarity. The query cavity can be uploaded by the user or detected automatically by the system using existing PDB entries as well as user-provided structures in PDB format. In all cases, the user can refine the definition of the cavity interactively via a browser-based Jmol 3D molecular visualization interface. Furthermore, users can restrict the search to a subset of the dataset using a cognate-similarity threshold. Local structural similarities are detected using the IsoCleft software and ranked according to two criteria (number of atoms in common and Tanimoto score of local structural similarity) and the associated Z-score and p-value measures of statistical significance. The results, including predicted ligands, target proteins, similarity scores, number of atoms in common, etc., are shown in a powerful interactive graphical interface. This interface permits the visualization of target ligands superimposed on the query cavity and additionally provides a table of pairwise ligand topological similarities. Similarities between top scoring ligands serve as an additional tool to judge the quality of the results obtained. We present several examples where IsoCleft Finder provides useful functional information. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography. IsoCleft Finder can be found at:
PMCID: PMC3892921  PMID: 24555058
7.  REFMAC5 for the refinement of macromolecular crystal structures 
The general principles behind the macromolecular crystal structure refinement program REFMAC5 are described.
This paper describes various components of the macromolecular crystallographic refinement program REFMAC5, which is distributed as part of the CCP4 suite. REFMAC5 utilizes different likelihood functions depending on the diffraction data employed (amplitudes or intensities), the presence of twinning and the availability of SAD/SIRAS experimental diffraction data. To ensure chemical and structural integrity of the refined model, REFMAC5 offers several classes of restraints and choices of model parameterization. Reliable models at resolutions at least as low as 4 Å can be achieved thanks to low-resolution refinement tools such as secondary-structure restraints, restraints to known homologous structures, automatic global and local NCS restraints, ‘jelly-body’ restraints and the use of novel long-range restraints on atomic displacement parameters (ADPs) based on the Kullback–Leibler divergence. REFMAC5 additionally offers TLS parameterization and, when high-resolution data are available, fast refinement of anisotropic ADPs. Refinement in the presence of twinning is performed in a fully automated fashion. REFMAC5 is a flexible and highly optimized refinement package that is ideally suited for refinement across the entire resolution spectrum encountered in macromolecular crystallography.
PMCID: PMC3069751  PMID: 21460454
REFMAC5; refinement
8.  Rappertk: a versatile engine for discrete restraint-based conformational sampling of macromolecules 
Macromolecular structures are modeled by conformational optimization within experimental and knowledge-based restraints. Discrete restraint-based sampling generates high-quality structures within these restraints and facilitates further refinement in a continuous all-atom energy landscape. This approach has been used successfully for protein loop modeling, comparative modeling and electron density fitting in X-ray crystallography.
Here we present a software toolkit (Rappertk) which generalizes discrete restraint-based sampling for use in structural biology. Modular design and multi-layered architecture enables Rappertk to sample conformations of any macromolecule at many levels of detail and within a variety of experimental restraints. Performance against a Cα-tracing benchmark shows that the efficiency has not suffered despite the overhead required by this flexibility. We demonstrate the toolkit's capabilities by building high-quality β-sheets and by introducing restraint-driven sampling. RNA sampling is demonstrated by rebuilding a protein-RNA interface. Ability to construct arbitrary ligands is used in sampling protein-ligand interfaces within electron density. Finally, secondary structure and shape information derived from EM are combined to generate multiple conformations of a protein consistent with the observed density.
Through its modular design and ease of use, Rappertk enables exploration of a wide variety of interesting avenues in structural biology. This toolkit, with illustrative examples, is freely available to academic users from .
PMCID: PMC1847436  PMID: 17376228
9.  Conformation-independent structural comparison of macromolecules with ProSMART  
The Procrustes Structural Matching Alignment and Restraints Tool (ProSMART) has been developed to allow local comparative structural analyses independent of the global conformations and sequence homology of the compared macromolecules. This allows quick and intuitive visualization of the conservation of backbone and side-chain conformations, providing complementary information to existing methods.
The identification and exploration of (dis)similarities between macromolecular structures can help to gain biological insight, for instance when visualizing or quantifying the response of a protein to ligand binding. Obtaining a residue alignment between compared structures is often a prerequisite for such comparative analysis. If the conformational change of the protein is dramatic, conventional alignment methods may struggle to provide an intuitive solution for straightforward analysis. To make such analyses more accessible, the Procrustes Structural Matching Alignment and Restraints Tool (ProSMART) has been developed, which achieves a conformation-independent structural alignment, as well as providing such additional functionalities as the generation of restraints for use in the refinement of macromolecular models. Sensible comparison of protein (or DNA/RNA) structures in the presence of conformational changes is achieved by enforcing neither chain nor domain rigidity. The visualization of results is facilitated by popular molecular-graphics software such as CCP4mg and PyMOL, providing intuitive feedback regarding structural conservation and subtle dissimilarities between close homologues that can otherwise be hard to identify. Automatically generated colour schemes corresponding to various residue-based scores are provided, which allow the assessment of the conservation of backbone and side-chain conformations relative to the local coordinate frame. Structural comparison tools such as ProSMART can help to break the complexity that accompanies the constantly growing pool of structural data into a more readily accessible form, potentially offering biological insight or influencing subsequent experiments.
PMCID: PMC4157452  PMID: 25195761
ProSMART; Procrustes; structural comparison; alignment; external restraints; refinement
10.  Understanding Uncertainties in Model-Based Predictions of Aedes aegypti Population Dynamics 
Aedes aegypti is one of the most important mosquito vectors of human disease. The development of spatial models for Ae. aegypti provides a promising start toward model-guided vector control and risk assessment, but this will only be possible if models make reliable predictions. The reliability of model predictions is affected by specific sources of uncertainty in the model.
Methodology/Principal Findings
This study quantifies uncertainties in the predicted mosquito population dynamics at the community level (a cluster of 612 houses) and the individual-house level based on Skeeter Buster, a spatial model of Ae. aegypti, for the city of Iquitos, Peru. The study considers two types of uncertainty: 1) uncertainty in the estimates of 67 parameters that describe mosquito biology and life history, and 2) uncertainty due to environmental and demographic stochasticity. Our results show that for pupal density and for female adult density at the community level, respectively, the 95% prediction confidence interval ranges from 1000 to 3000 and from 700 to 5,000 individuals. The two parameters contributing most to the uncertainties in predicted population densities at both individual-house and community levels are the female adult survival rate and a coefficient determining weight loss due to energy used in metabolism at the larval stage (i.e. metabolic weight loss). Compared to parametric uncertainty, stochastic uncertainty is relatively low for population density predictions at the community level (less than 5% of the overall uncertainty) but is substantially higher for predictions at the individual-house level (larger than 40% of the overall uncertainty). Uncertainty in mosquito spatial dispersal has little effect on population density predictions at the community level but is important for the prediction of spatial clustering at the individual-house level.
This is the first systematic uncertainty analysis of a detailed Ae. aegypti population dynamics model and provides an approach for identifying those parameters for which more accurate estimates would improve model predictions.
Author Summary
Dengue is one of the most important insect-vectored human viral diseases. The principal vector is Aedes aegypti, a mosquito that lives in close association with humans. Currently, there is no effective vaccine available and the only means for limiting dengue outbreaks is vector control. To help design vector control strategies, spatial models of Ae. aegypti population dynamics have been developed. However, the usefulness of such models depends on the reliability of their predictions, which can be affected by different sources of uncertainty including uncertainty in the model parameter estimation, uncertainty in the model structure, measurement errors in the data fed into the model, individual variability, and stochasticity in the environment. This study quantifies uncertainties in the mosquito population dynamics predicted by Skeeter Buster, a spatial model of Ae. aegypti, for the city of Iquitos, Peru. The uncertainty quantification should enable us to better understand the reliability of model predictions, improve Skeeter Buster and other similar models by targeting those parameters with high uncertainty contributions for further empirical research, and thereby decrease uncertainty in model predictions.
PMCID: PMC2946899  PMID: 20927187
11.  Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations 
PLoS ONE  2011;6(7):e22701.
Skeeter Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed to predict the outcome of vector population control methods. In this study, we apply the model to two specific locations, the cities of Iquitos, Peru, and Buenos Aires, Argentina. These two sites differ in the amount of field data that is available for location-specific customization. By comparing output from Skeeter Buster to field observations in these two cases we evaluate population dynamics predictions by Skeeter Buster with varying degrees of customization.
Methodology/Principal Findings
Skeeter Buster was customized to the Iquitos location by simulating the layout of houses and the associated distribution of water-holding containers, based on extensive surveys of Ae. aegypti populations and larval habitats that have been conducted in Iquitos for over 10 years. The model is calibrated by adjusting the food input into various types of containers to match their observed pupal productivity in the field. We contrast the output of this customized model to the data collected from the natural population, comparing pupal numbers and spatial distribution of pupae in the population. Our results show that Skeeter Buster replicates specific population dynamics and spatial structure of Ae. aegypti in Iquitos. We then show how Skeeter Buster can be customized for Buenos Aires, where we only had Ae. aegypti abundance data that was averaged across all locations. In the Argentina case Skeeter Buster provides a satisfactory simulation of temporal population dynamics across seasons.
This model can provide a faithful description of Ae. aegypti populations, through a process of location-specific customization that is contingent on the amount of data available from field collections. We discuss limitations presented by some specific components of the model such as the description of food dynamics and challenges that these limitations bring to model evaluation.
PMCID: PMC3143176  PMID: 21799936
12.  A conformation-dependent stereochemical library improves crystallographic refinement even at atomic resolution 
A script was created to allow SHELXL to use the new CDL v.1.2 stereochemical library which defines the target values for main-chain bond lengths and angles as a function of the residue’s ϕ/ψ angles. Test refinements using this script show that the refinement behavior of structures at resolutions even better than 1 Å is substantially enhanced by the use of the new conformation-dependent ideal geometry paradigm.
To utilize a new conformation-dependent backbone-geometry library (CDL) in protein refinements at atomic resolution, a script was written that creates a restraint file for the SHELXL refinement program. It was found that the use of this library allows models to be created that have a substantially better fit to main-chain bond angles and lengths without degrading their fit to the X-ray data even at resolutions near 1 Å. For models at much higher resolution (∼0.7 Å), the refined model for parts adopting single well occupied positions is largely independent of the restraints used, but these structures still showed much smaller r.m.s.d. residuals when assessed with the CDL. Examination of the refinement tests across a wide resolution range from 2.4 to 0.65 Å revealed consistent behavior supporting the use of the CDL as a next-generation restraint library to improve refinement. CDL restraints can be generated using the service at
PMCID: PMC3144852  PMID: 21795811
stereochemical libraries; refinement; conformation-dependent library
13.  Conjoined Use of EM and NMR in RNA Structure Refinement 
PLoS ONE  2015;10(3):e0120445.
More than 40% of the RNA structures have been determined using nuclear magnetic resonance (NMR) technique. NMR mainly provides local structural information of protons and works most effectively on relatively small biomacromolecules. Hence structural characterization of large RNAs can be difficult for NMR alone. Electron microscopy (EM) provides global shape information of macromolecules at nanometer resolution, which should be complementary to NMR for RNA structure determination. Here we developed a new energy term in Xplor-NIH against the density map obtained by EM. We conjointly used NMR and map restraints for the structure refinement of three RNA systems — U2/U6 small-nuclear RNA, genome-packing motif (ΨCD)2 from Moloney murine leukemia virus, and ribosome-binding element from turnip crinkle virus. In all three systems, we showed that the incorporation of a map restraint, either experimental or generated from known PDB structure, greatly improves structural precision and accuracy. Importantly, our method does not rely on an initial model assembled from RNA duplexes, and allows full torsional freedom for each nucleotide in the torsion angle simulated annealing refinement. As increasing number of macromolecules can be characterized by both NMR and EM, the marriage between the two techniques would enable better characterization of RNA three-dimensional structures.
PMCID: PMC4370883  PMID: 25798848
14.  Structure of the Archaeoglobus fulgidus orphan ORF AF1382 determined by sulfur SAD from a moderately diffracting crystal 
The crystal structure of the 11.14 kDa orphan ORF 1382 from Archaeoglobus fulgidus (AF1382) has been determined by sulfur SAD phasing using data collected from a moderately diffracting crystal and 1.9 Å synchrotron X-rays.
The crystal structure of the 11.14 kDa orphan ORF 1382 from Archaeoglobus fulgidus (AF1382) has been determined by sulfur SAD phasing using a moderately diffracting crystal and 1.9 Å wavelength synchrotron X-rays. AF1382 was selected as a structural genomics target by the Southeast Collaboratory for Structural Genomics (SECSG) since sequence analyses showed that it did not belong to the Pfam-A database and thus could represent a novel fold. The structure was determined by exploiting longer wavelength X-rays and data redundancy to increase the anomalous signal in the data. AF1382 is a 95-­residue protein containing five S atoms associated with four methionine residues and a single cysteine residue that yields a calculated Bijvoet ratio (ΔF anom/F) of 1.39% for 1.9 Å wavelength X-rays. Coupled with an average Bijvoet redundancy of 25 (two 360° data sets), this produced an excellent electron-density map that allowed 69 of the 95 residues to be automatically fitted. The S-SAD model was then manually completed and refined (R = 23.2%, R free = 26.8%) to 2.3 Å resolution (PDB entry 3o3k). High-resolution data were subsequently collected from a better diffracting crystal using 0.97 Å wavelength synchrotron X-rays and the S-SAD model was refined (R = 17.9%, R free = 21.4%) to 1.85 Å resolution (PDB entry 3ov8). AF1382 has a winged-helix–turn–helix structure common to many DNA-binding proteins and most closely resembles the N-terminal domain (residues 1–82) of the Rio2 kinase from A. fulgidus, which has been shown to bind DNA, and a number of MarR-family transcriptional regulators, suggesting a similar DNA-binding function for AF1382. The analysis also points out the advantage gained from carrying out data reduction and structure determination on-site while the crystal is still available for further data collection.
PMCID: PMC3489105  PMID: 22948926
AF1382; orphan ORFs; sulfur SAD; Archaeoglobus fulgidus
15.  Application of DEN refinement and automated model building to a difficult case of molecular-replacement phasing: the structure of a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum  
DEN refinement and automated model building with AutoBuild were used to determine the structure of a putative succinyl-diaminopimelate desuccinylase from C. glutamicum. This difficult case of molecular-replacement phasing shows that the synergism between DEN refinement and AutoBuild outperforms standard refinement protocols.
Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 Å resolution is described using a combination of homology modeling with MODELLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence.
PMCID: PMC3322598  PMID: 22505259
reciprocal-space refinement; DEN refinement; real-space refinement; automated model building; succinyl-diaminopimelate desuccinylase
16.  Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling 
PLoS ONE  2013;8(6):e65770.
Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from
PMCID: PMC3688807  PMID: 23824634
17.  NMR data-driven structure determination using NMR-I-TASSER in the CASD-NMR experiment 
Journal of biomolecular NMR  2015;62(4):511-525.
NMR-I-TASSER, an adaption of the I-TASSER algorithm combining NMR data for protein structure determination, recently joined the second round of the CASD-NMR experiment. Unlike many molecular dynamics-based methods, NMR-I-TASSER takes a molecular replacement-like approach to the problem by first threading the target through the PDB to identify structural templates which are then used for iterative NOE assignments and fragment structure assembly refinements. The employment of multiple templates allows NMR-I-TASSER to sample different topologies while convergence to a single structure is not required. Retroactive and blind tests of the CASD-NMR targets from Rounds 1 and 2 demonstrate that even without using NOE peak lists I-TASSER can generate correct structure topology with 15 of 20 targets having a TM-score above 0.5. With the addition of NOE-based distance restraints, NMR-I-TASSER significantly improved the I-TASSER models with all models having the TM-score above 0.5. The average RMSD was reduced from 5.29 to 2.14 Å in Round 1 and 3.18 to 1.71 Å in Round 2. There is no obvious difference in the modeling results with using raw and refined peak lists, indicating robustness of the pipeline to the NOE assignment errors. Overall, despite the low-resolution modeling the current NMR-I-TASSER pipeline provides a coarse-grained structure folding approach complementary to traditional molecular dynamics simulations, which can produce fast near-native frameworks for atomic-level structural refinement.
PMCID: PMC4560687  PMID: 25737244
NMR restraints; NOE assignment; CASD-NMR; I-TASSER; Protein structure prediction
18.  Molecular dynamics re-refinement of two different small RNA loop structures using the original NMR data suggest a common structure 
Journal of Biomolecular Nmr  2012;53(4):321-339.
Restrained molecular dynamics simulations are a robust, though perhaps underused, tool for the end-stage refinement of biomolecular structures. We demonstrate their utility—using modern simulation protocols, optimized force fields, and inclusion of explicit solvent and mobile counterions—by re-investigating the solution structures of two RNA hairpins that had previously been refined using conventional techniques. The structures, both domain 5 group II intron ribozymes from yeast ai5γ and Pylaiella littoralis, share a nearly identical primary sequence yet the published 3D structures appear quite different. Relatively long restrained MD simulations using the original NMR restraint data identified the presence of a small set of violated distance restraints in one structure and a possibly incorrect trapped bulge nucleotide conformation in the other structure. The removal of problematic distance restraints and the addition of a heating step yielded representative ensembles with very similar 3D structures and much lower pairwise RMSD values. Analysis of ion density during the restrained simulations helped to explain chemical shift perturbation data published previously. These results suggest that restrained MD simulations, with proper caution, can be used to “update” older structures or aid in the refinement of new structures that lack sufficient experimental data to produce a high quality result. Notable cautions include the need for sufficient sampling, awareness of potential force field bias (such as small angle deviations with the current AMBER force fields), and a proper balance between the various restraint weights.
Electronic supplementary material
The online version of this article (doi:10.1007/s10858-012-9642-5) contains supplementary material, which is available to authorized users.
PMCID: PMC3405240  PMID: 22714631
RNA structure; Molecular dynamics; Residual dipolar coupling restraints; Bulge structure; Force fields; Ion binding
19.  Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions 
A description is given of new tools to facilitate model building and refinement into electron cryo-microscopy reconstructions.
The recent rapid development of single-particle electron cryo-microscopy (cryo-EM) now allows structures to be solved by this method at resolutions close to 3 Å. Here, a number of tools to facilitate the interpretation of EM reconstructions with stereochemically reasonable all-atom models are described. The BALBES database has been repurposed as a tool for identifying protein folds from density maps. Modifications to Coot, including new Jiggle Fit and morphing tools and improved handling of nucleic acids, enhance its functionality for interpreting EM maps. REFMAC has been modified for optimal fitting of atomic models into EM maps. As external structural information can enhance the reliability of the derived atomic models, stabilize refinement and reduce overfitting, ProSMART has been extended to generate interatomic distance restraints from nucleic acid reference structures, and a new tool, LIBG, has been developed to generate nucleic acid base-pair and parallel-plane restraints. Furthermore, restraint generation has been integrated with visualization and editing in Coot, and these restraints have been applied to both real-space refinement in Coot and reciprocal-space refinement in REFMAC.
PMCID: PMC4304694  PMID: 25615868
model building; refinement;  electron cryo-microscopy reconstructions; LIBG
20.  Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks 
Prediction of protein structures from their sequences is still one of the open grand challenges of computational biology. Some approaches to protein structure prediction, especially ab initio ones, rely to some extent on the prediction of residue contact maps. Residue contact map predictions have been assessed at the CASP competition for several years now. Although it has been shown that exact contact maps generally yield correct three-dimensional structures, this is true only at a relatively low resolution (3–4 Å from the native structure). Another known weakness of contact maps is that they are generally predicted ab initio, that is not exploiting information about potential homologues of known structure.
We introduce a new class of distance restraints for protein structures: multi-class distance maps. We show that Cα trace reconstructions based on 4-class native maps are significantly better than those from residue contact maps. We then build two predictors of 4-class maps based on recursive neural networks: one ab initio, or relying on the sequence and on evolutionary information; one template-based, or in which homology information to known structures is provided as a further input. We show that virtually any level of sequence similarity to structural templates (down to less than 10%) yields more accurate 4-class maps than the ab initio predictor. We show that template-based predictions by recursive neural networks are consistently better than the best template and than a number of combinations of the best available templates. We also extract binary residue contact maps at an 8 Å threshold (as per CASP assessment) from the 4-class predictors and show that the template-based version is also more accurate than the best template and consistently better than the ab initio one, down to very low levels of sequence identity to structural templates. Furthermore, we test both ab-initio and template-based 8 Å predictions on the CASP7 targets using a pre-CASP7 PDB, and find that both predictors are state-of-the-art, with the template-based one far outperforming the best CASP7 systems if templates with sequence identity to the query of 10% or better are available. Although this is not the main focus of this paper we also report on reconstructions of Cα traces based on both ab initio and template-based 4-class map predictions, showing that the latter are generally more accurate even when homology is dubious.
Accurate predictions of multi-class maps may provide valuable constraints for improved ab initio and template-based prediction of protein structures, naturally incorporate multiple templates, and yield state-of-the-art binary maps. Predictions of protein structures and 8 Å contact maps based on the multi-class distance map predictors described in this paper are freely available to academic users at the url .
PMCID: PMC2654788  PMID: 19183478
21.  Structural Refinement from Restrained-Ensemble Simulations Based on EPR/DEER Data: Application to T4 Lysozyme 
The journal of physical chemistry. B  2013;117(17):4740-4754.
DEER (Double Electron Electron Resonance) is a powerful pulsed ESR (electron spin resonance) technique allowing the determination of distance histograms between pairs of nitroxide spin-labels linked to a protein in a native-like solution environment. However, exploiting the huge amount of information provided by ESR/DEER histograms to refine structural models is extremely challenging. In this study, a restrained ensemble (RE) molecular dynamics (MD) simulation methodology is developed to address this issue. In RE simulation, the spin-spin distance distribution histograms calculated from a multiple-copy MD simulation are enforced, via a global ensemble-based energy restraint, to match those obtained from ESR/DEER experiments. The RE simulation is applied to 51 ESR/DEER distance histogram data from spin-labels inserted at 37 different positions in T4 lysozyme (T4L). The rotamer population distribution along the five dihedral angles connecting the nitroxide ring to the protein backbone is determined and shown to be consistent with available information from X-ray crystallography. For the purpose of structural refinement, the concept of a simplified nitroxide dummy spin-label is designed and parameterized on the basis of these all-atom RE simulations with explicit solvent. It is demonstrated that RE simulations with the dummy nitroxide spin-labels imposing the ESR/DEER experimental distance distribution data are able to systematically correct and refine a series of distorted T4L structures, while simple harmonic distance restraints are unsuccessful. This computationally efficient approach allows experimental restraints from DEER experiments to be incorporated into RE simulations for efficient structural refinement.
PMCID: PMC3684008  PMID: 23510103
Structural refinement; spin-labeled T4 Lysozyme; ESR/DEER; rotamer population; molecular dynamics (MD); restrained ensemble (RE)
22.  TagDock: An efficient rigid body docking algorithm for oligomeric protein complex model construction and experiment planning 
Biochemistry  2013;52(33):5577-5584.
We report here new computational tools and strategies to efficiently generate three-dimensional models for oligomeric biomolecular complexes in cases where there is limited experimental restraint data to guide the docking calculations. Our computational tools are designed to rapidly and exhaustively enumerate all geometrically possible docking poses for an oligomeric complex, rather than generate detailed, atomic-resolution models. Experimental data, such as inter-atomic distance measurements, are then used to select and refine docking poses that are consistent with the experimental restraints. Our computational toolkit is designed for use with sparse datasets to generate intermediate-resolution docking models, and utilizes distance difference matrix analysis to identify further restraint measurements that will provide maximum additional structural refinement. Thus, these tools can be used to help plan optimal residue positions for probe incorporation in labor-intensive biophysical experiments such as chemical crosslinking, EPR, or FRET spectroscopy studies. We present benchmark results for docking the collection of all 176 heterodimer protein complexes from the ZDOCK database, as well as a protein homodimer with recently collected experimental distance restraints, to illustrate the toolkit’s capabilities and performance, and to demonstrate how distance difference matrix analysis can automatically identify and prioritize additional restraint measurements that allow us to rapidly optimize docking poses.
PMCID: PMC3804560  PMID: 23875708
23.  Use of intensity quotients and differences in absolute structure refinement 
Differences and quotients can be defined using Friedel pairs of reflections and applied in refinement to enable absolute structure to be determined precisely even for light atom crystal structures.
Several methods for absolute structure refinement were tested using single-crystal X-ray diffraction data collected using Cu Kα radiation for 23 crystals with no element heavier than oxygen: conventional refinement using an inversion twin model, estimation using intensity quotients in SHELXL2012, estimation using Bayesian methods in PLATON, estimation using restraints consisting of numerical intensity differences in CRYSTALS and estimation using differences and quotients in TOPAS-Academic where both quantities were coded in terms of other structural parameters and implemented as restraints. The conventional refinement approach yielded accurate values of the Flack parameter, but with standard uncertainties ranging from 0.15 to 0.77. The other methods also yielded accurate values of the Flack parameter, but with much higher precision. Absolute structure was established in all cases, even for a hydrocarbon. The procedures in which restraints are coded explicitly in terms of other structural parameters enable the Flack parameter to correlate with these other parameters, so that it is determined along with those parameters during refinement.
PMCID: PMC3661305  PMID: 23719469
intensity quotients; absolute structure refinement
24.  Modelling dynamics in protein crystal structures by ensemble refinement 
eLife  2012;1:e00311.
Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated Rfree values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships.
eLife digest
It has been clear since the early days of structural biology in the late 1950s that proteins and other biomolecules are continually changing shape, and that these changes have an important influence on both the structure and function of the molecules. X-ray diffraction can provide detailed information about the structure of a protein, but only limited information about how its structure fluctuates over time. Detailed information about the dynamic behaviour of proteins is essential for a proper understanding of a variety of processes, including catalysis, ligand binding and protein–protein interactions, and could also prove useful in drug design.
Currently most of the X-ray crystal structures in the Protein Data Bank are ‘snap-shots’ with limited or no information about protein dynamics. However, X-ray diffraction patterns are affected by the dynamics of the protein, and also by distortions of the crystal lattice, so three-dimensional (3D) models of proteins ought to take these phenomena into account. Molecular-dynamics (MD) computer simulations transform 3D structures into 4D ‘molecular movies’ by predicting the movement of individual atoms.
Combining MD simulations with crystallographic data has the potential to produce more realistic ensemble models of proteins in which the atomic fluctuations are represented by multiple structures within the ensemble. Moreover, in addition to improved structural information, this process—which is called ensemble refinement—can provide dynamical information about the protein. Earlier attempts to do this ran into problems because the number of model parameters needed was greater than the number of observed data points. Burnley et al. now overcome this problem by modelling local molecular vibrations with MD simulations and, at the same time, using a course-grain model to describe global disorder of longer length scales.
Ensemble refinement of high-resolution X-ray diffraction datasets for 20 different proteins from the Protein Data Bank produced a better fit to the data than single structures for all 20 proteins. Ensemble refinement also revealed that 3 of the 20 proteins had a ‘molten core’, rather than the well-ordered residues core found in most proteins: this is likely to be important in various biological functions including ligand binding, filament formation and enzymatic function. Burnley et al. also showed that a HIV enzyme underwent an order–disorder transition that is likely to influence how this enzyme works, and that similar transitions might influence the interactions between the small-molecule drug Imatinib (also known as Gleevec) and the enzymes it targets. Ensemble refinement could be applied to the majority of crystallography data currently being collected, or collected in the past, so further insights into the properties and interactions of a variety of proteins and other biomolecules can be expected.
PMCID: PMC3524795  PMID: 23251785
protein; crystallography; structure; function; dynamics; None
25.  CaspR: a web server for automated molecular replacement using homology modelling 
Nucleic Acids Research  2004;32(Web Server issue):W606-W609.
Molecular replacement (MR) is the method of choice for X-ray crystallography structure determination when structural homologues are available in the Protein Data Bank (PDB). Although the success rate of MR decreases sharply when the sequence similarity between template and target proteins drops below 35% identical residues, it has been found that screening for MR solutions with a large number of different homology models may still produce a suitable solution where the original template failed. Here we present the web tool CaspR, implementing such a strategy in an automated manner. On input of experimental diffraction data, of the corresponding target sequence and of one or several potential templates, CaspR executes an optimized molecular replacement procedure using a combination of well-established stand-alone software tools. The protocol of model building and screening begins with the generation of multiple structure–sequence alignments produced with T-COFFEE, followed by homology model building using MODELLER, molecular replacement with AMoRe and model refinement based on CNS. As a result, CaspR provides a progress report in the form of hierarchically organized summary sheets that describe the different stages of the computation with an increasing level of detail. For the 10 highest-scoring potential solutions, pre-refined structures are made available for download in PDB format. Results already obtained with CaspR and reported on the web server suggest that such a strategy significantly increases the fraction of protein structures which may be solved by MR. Moreover, even in situations where standard MR yields a solution, pre-refined homology models produced by CaspR significantly reduce the time-consuming refinement process. We expect this automated procedure to have a significant impact on the throughput of large-scale structural genomics projects. CaspR is freely available at
PMCID: PMC441538  PMID: 15215460

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