| 1. |
- Norrman, Mathias, et al.
(author)
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Crystallographic characterization of two novel crystal forms of human insulin induced by chaotropic agents and a shift in pH
- 2007
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 7
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Journal article (peer-reviewed)abstract
- Background: Insulin is a therapeutic protein that is widely used for the treatment of diabetes. Its biological function was discovered more than 80 years ago and it has since then been characterized extensively. Crystallization of the insulin molecule has always been a key activity since the protein is often administered by subcutaneous injections of crystalline insulin formulations. Over the years, insulin has been crystallized and characterized in a number of crystal systems. Results: Interestingly, we have now discovered two new crystal forms of human insulin. The crystals were obtained when the two chaotropic agents, urea and thiocyanate were present in the crystallization experiments, and their structures were determined by X-ray crystallography. The crystals belong to the orthorhombic and monoclinic crystal systems, with space groups C222(I) and C2 respectively. The orthorhombic crystals were obtained at pH 6.5 and contained three insulin hexamers in R-6 conformation in the asymmetric unit whilst the monoclinic C2 crystals were obtained at pH 7.0 and contained one R6 hexamer in the asymmetric unit. Common for the two new crystals is a hexamer-hexamer interaction that has not been found in any of the previous crystal forms of insulin. The contacts involve a tight glutamate-glutamate interaction with a distance of 2.3 angstrom between groups. The short distance suggests a low barrier hydrogen bond. In addition, two tyrosine-tyrosine interactions occupying a known phenol binding pocket contribute to the stabilization of the contacts. Within the crystals, distinct binding sites for urea were found, adding further to the discussion on the role of urea in protein denaturation. Conclusion: The change in space group from C222(I) to C2 was primarily caused by an increase in pH. The fewer number of hexamer-hexamer interactions comprising the short hydrogen bond in the C2 space group suggest that pH is the driving force. In addition, the distance between the two glutamates increases from 2.32 angstrom in the C222(I) crystals to 2.4 angstrom in the C2 crystals. However, in both cases the low barrier hydrogen bond and the tyrosine-tyrosine interaction should contribute to the stability of the crystals which is crucial when used in pharmaceutical formulations.
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| 2. |
- Georgi, Benjamin, et al.
(author)
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Partially-supervised protein subclass discovery with simultaneous annotation of functional residues.
- 2009
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In: BMC structural biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 9
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Journal article (peer-reviewed)abstract
- The study of functional subfamilies of protein domain families and the identification of the residues which determine substrate specificity is an important question in the analysis of protein domains. One way to address this question is the use of clustering methods for protein sequence data and approaches to predict functional residues based on such clusterings. The locations of putative functional residues in known protein structures provide insights into how different substrate specificities are reflected on the protein structure level.We have developed an extension of the context-specific independence mixture model clustering framework which allows for the integration of experimental data. As these are usually known only for a few proteins, our algorithm implements a partially-supervised learning approach. We discover domain subfamilies and predict functional residues for four protein domain families: phosphatases, pyridoxal dependent decarboxylases, WW and SH3 domains to demonstrate the usefulness of our approach.The partially-supervised clustering revealed biologically meaningful subfamilies even for highly heterogeneous domains and the predicted functional residues provide insights into the basis of the different substrate specificities.
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| 3. |
- Hennig, Janosch, et al.
(author)
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MTMDAT-HADDOCK : high-throughput, protein complex structure modeling based on limited proteolysis and mass spectrometry
- 2012
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 12:29
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Journal article (peer-reviewed)abstract
- BackgroundMTMDAT is a program designed to facilitate analysis of mass spectrometry data of proteins and biomolecular complexes that are probed structurally by limited proteolysis. This approach can provide information about stable fragments of multidomain proteins, yield tertiary and quaternary structure data, and help determine the origin of stability changes at the amino acid residue level. Here, we introduce a pipeline between MTMDAT and HADDOCK, that facilitates protein-protein complex structure probing in a high-throughput and highly automated fashion.ResultsA new feature of MTMDAT allows for the direct identification of residues that are involved in complex formation by comparing the mass spectra of bound and unbound proteins after proteolysis. If 3D structures of the unbound components are available, this data can be used to define restraints for data-driven docking to calculate a model of the complex. We describe here a new implementation of MTMDAT, which includes a pipeline to the data-driven docking program HADDOCK, thus streamlining the entire procedure. This addition, together with usability improvements in MTMDAT, enables high-throughput modeling of protein complexes from mass spectrometry data. The algorithm has been validated by using the protein-protein interaction between the ubiquitin-binding domain of proteasome component Rpn13 and ubiquitin. The resulting structural model, based on restraints extracted by MTMDAT from limited proteolysis and modeled by HADDOCK, was compared to the published NMR structure, which relied on twelve unambiguous intermolecular NOE interactions. The MTMDAT-HADDOCK structure was of similar quality to structures generated using only chemical shift perturbation data derived by NMR titration experiments.ConclusionsThe new MTMDAT-HADDOCK pipeline enables direct high-throughput modeling of protein complexes from mass spectrometry data. MTMDAT-HADDOCK can be downloaded from http://www.ifm.liu.se/chemistry/molbiotech/maria_sunnerhagens_group/mtmdat/webcitetogether with the manual and example files. The program is free for academic/non-commercial purposes.
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| 4. |
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| 5. |
- Sivertsen, A, et al.
(author)
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Synthetic cationic antimicrobial peptides bind with their hydrophobic parts to drug site II of human serum albumin
- 2014
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 14:1
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Journal article (peer-reviewed)abstract
- Background Many biologically active compounds bind to plasma transport proteins, and this binding can be either advantageous or disadvantageous from a drug design perspective. Human serum albumin (HSA) is one of the most important transport proteins in the cardiovascular system due to its great binding capacity and high physiological concentration. HSA has a preference for accommodating neutral lipophilic and acidic drug-like ligands, but is also surprisingly able to bind positively charged peptides. Understanding of how short cationic antimicrobial peptides interact with human serum albumin is of importance for developing such compounds into the clinics. Results The binding of a selection of short synthetic cationic antimicrobial peptides (CAPs) to human albumin with binding affinities in the μM range is described. Competitive isothermal titration calorimetry (ITC) and NMR WaterLOGSY experiments mapped the binding site of the CAPs to the well-known drug site II within subdomain IIIA of HSA. Thermodynamic and structural analysis revealed that the binding is exclusively driven by interactions with the hydrophobic moieties of the peptides, and is independent of the cationic residues that are vital for antimicrobial activity. Both of the hydrophobic moieties comprising the peptides were detected to interact with drug site II by NMR saturation transfer difference (STD) group epitope mapping (GEM) and INPHARMA experiments. Molecular models of the complexes between the peptides and albumin were constructed using docking experiments, and support the binding hypothesis and confirm the overall binding affinities of the CAPs. Conclusions The biophysical and structural characterizations of albumin-peptide complexes reported here provide detailed insight into how albumin can bind short cationic peptides. The hydrophobic elements of the peptides studied here are responsible for the main interaction with HSA. We suggest that albumin binding should be taken into careful consideration in antimicrobial peptide studies, as the systemic distribution can be significantly affected by HSA interactions.
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| 6. |
- Kirscht, Andreas, et al.
(author)
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A structural preview of aquaporin 8 via homology modeling of seven vertebrate isoforms
- 2018
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 18:1
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Journal article (peer-reviewed)abstract
- Background: Aquaporins (AQPs) facilitate the passage of small neutral polar molecules across membranes of the cell. In animals there are four distinct AQP subfamilies, whereof AQP8 homologues constitute one of the smallest subfamilies with just one member in man. AQP8 conducts water, ammonia, urea, glycerol and H2O2 through various membranes of animal cells. This passive channel has been connected to a number of phenomena, such as volume change of mitochondria, ammonia neurotoxicity, and mitochondrial dysfunction related to oxidative stress. Currently, there is no experimentally determined structure of an AQP8, hence the structural understanding of this subfamily is limited. The recently solved structure of the plant AQP, AtTIP2;1, which has structural and functional features in common with AQP8s, has opened up for construction of homology models that are likely to be more accurate than previous models. Results: Here we present homology models of seven vertebrate AQP8s. Modeling based on the AtTIP2;1 structure alone resulted in reasonable models except for the pore being blocked by a phenylalanine that is not present in AtTIP2;1. To achieve an open pore, these models were supplemented with models based on the bacterial water specific AQP, EcAqpZ, creating a chimeric monomeric model for each AQP8 isoform. The selectivity filter (also named the aromatic/arginine region), which defines the permeant substrate profile, comprises five amino acid residues in AtTIP2;1, including a histidine coming from loop C. Compared to AtTIP2;1, the selectivity filters of modelled AQP8s only deviates in that they are slightly more narrow and more hydrophobic due to a phenylalanine replacing the histidine from loop C. Interestingly, the models do not exclude the existence of a side pore beneath loop C similar to that described in the structure of AtTIP2;1. Conclusions: Our models concur that AQP8s are likely to have an AtTIP2;1-like selectivity filter. The detailed description of the expected configuration of residues in the selectivity filters of AQP8s provides an excellent starting point for planning of as well as rationalizing the outcome of mutational studies. Our strategy to compile hybrid models based on several templates may prove useful also for other AQPs for which structural information is limited.
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| 7. |
- Peng, Xubiao, et al.
(author)
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A three dimensional visualisation approach to protein heavy-atom structure reconstruction
- 2014
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 14, s. 27-
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Journal article (peer-reviewed)abstract
- BackgroundA commonly recurring problem in structural protein studies, is the determination of all heavy atom positions from the knowledge of the central α-carbon coordinates.ResultsWe employ advances in virtual reality to address the problem. The outcome is a 3D visualisation based technique where all the heavy backbone and side chain atoms are treated on equal footing, in terms of the Cα coordinates. Each heavy atom is visualised on the surfaces of a different two-sphere, that is centered at another heavy backbone and side chain atoms. In particular, the rotamers are visible as clusters, that display a clear and strong dependence on the underlying backbone secondary structure.ConclusionsWe demonstrate that there is a clear interdependence between rotameric states and secondary structure. Our method easily detects those atoms in a crystallographic protein structure which are either outliers or have been likely misplaced, possibly due to radiation damage. Our approach forms a basis for the development of a new generation, visualization based side chain construction, validation and refinement tools. The heavy atom positions are identified in a manner which accounts for the secondary structure environment, leading to improved accuracy.
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| 8. |
- Peng, Xubiao, et al.
(author)
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Clustering and percolation in protein loop structures
- 2015
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In: BMC Structural Biology. - : Springer Science and Business Media LLC. - 1472-6807. ; 15
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Journal article (peer-reviewed)abstract
- Background: High precision protein loop modelling remains a challenge, both in template based and template independent approaches to protein structure prediction. Method: We introduce the concepts of protein loop clustering and percolation, to develop a quantitative approach to systematically classify the modular building blocks of loops in crystallographic folded proteins. These fragments are all different parameterisations of a unique kink solution to a generalised discrete nonlinear Schrodinger (DNLS) equation. Accordingly, the fragments are also local energy minima of the ensuing energy function. Results: We show how the loop fragments cover practically all ultrahigh resolution crystallographic protein structures in Protein Data Bank (PDB), with a 0.2 Angstrom root-mean-square (RMS) precision. We find that no more than 12 different loop fragments are needed, to describe around 38 % of ultrahigh resolution loops in PDB. But there is also a large number of loop fragments that are either unique, or very rare, and examples of unique fragments are found even in the structure of a myoglobin. Conclusions: Protein loops are built in a modular fashion. The loops are composed of fragments that can be modelled by the kink of the DNLS equation. The majority of loop fragments are also common, which are shared by many proteins. These common fragments are probably important for supporting the overall protein conformation. But there are also several fragments that are either unique to a given protein, or very rare. Such fragments are probably related to the function of the protein. Furthermore, we have found that the amino acid sequence does not determine the structure in a unique fashion. There are many examples of loop fragments with an identical amino acid sequence, but with a very different structure.
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