3Drefine: consistent protein structure refinement by optimizing hydrogen bonding network and atomic-level energy minimization

3Drefine: an interactive web server for efficient protein structure refinement

3Drefine is an interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative optimization of hydrogen bonding network combined with atomic-level energy minimization on the optimized model using a composite physics and knowledge-based force fields for efficient protein structure refinement. The method has been extensively evaluated on blind CASP experiments as well as on large-scale and diverse benchmark datasets and exhibits consistent improvement over the initial structure in both global and local structural quality measures. The 3Drefine web server allows for convenient protein structure refinement through a text or file input submission, email notification, provided example submission and is freely available without any registration requirement. The server also provides comprehensive analysis of submissions through various energy and statistical feedback and interactive visualization of multiple refined models through the JSmol applet that is equipped with numerous protein model analysis tools. The web server has been extensively tested and used by many users. As a result, the 3Drefine web server conveniently provides a useful tool easily accessible to the community. The 3Drefine web server has been made publicly available at the URL: http://sysbio.rnet.missouri.edu/3Drefine/.

The selectivity and promiscuity of brain-neuroregenerative inhibitors between ROCK1 and ROCK2 isoforms: An integration of SB-QSSR modelling, QM/MM analysis and in vitro kinase assay

The Rho-associated kinases (ROCKs) have long been recognized as an attractive therapeutic target for various neurological diseases; selective inhibition of ROCK1 and ROCK2 isoforms would result in distinct biological effects on neurogenesis, neuroplasticity and neuroregeneration after brain surgery and traumatic brain injury. However, the discovery and design of isoform-selective inhibitors remain a great challenge due to the high conservation and similarity between the kinase domains of ROCK1 and ROCK2. Here, a structure-based quantitative structure-selectivity relationship (SB-QSSR) approach was used to correlate experimentally measured selectivity with the difference in inhibitor binding to the two kinase isoforms. The resulting regression models were examined rigorously through both internal cross-validation and external blind validation; a nonlinear predictor was found to have high fitting stability and strong generalization ability, which was then employed to perform virtual screening against a structurally diverse, drug-like compound library. Consequently, five and seven hits were identified as promising candidates of 1-o-2 and 2-o-1 selective inhibitors, respectively, from which seven purchasable compounds were tested in vitro using a standard kinase assay protocol to determine their inhibitory activity against and selectivity between ROCK1 and ROCK2. The structural basis, energetic property and biological implication underlying inhibitor selectivity and promiscuity were also investigated systematically using a hybrid quantum mechanics/molecular mechanics (QM/MM) scheme.

Large-scale model quality assessment for improving protein tertiary structure prediction

Motivation: Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well.

Results: Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM’s outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling.

Availability and implementation: The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/.

Contact: chengji@missouri.edu

A theoretical investigation of DNA dynamics and desolvation kinetics for zinc finger proteinZif268

Background

Transcription factors, regulating the expression inventory of a cell, interact with its respective DNA subjugated by a specific recognition pattern, which if well exploited may ensure targeted genome engineering. The mostly widely studied transcription factors are zinc finger proteins that bind to its target DNA via direct and indirect recognition levels at the interaction interface. Exploiting the binding specificity and affinity of the interaction between the zinc fingers and the respective DNA can help in generating engineered zinc fingers for therapeutic applications. Experimental evidences lucidly substantiate the effect of indirect interaction like DNA deformation and desolvation kinetics, in empowering ZFPs to accomplish partial sequence specificity functioning around structural properties of DNA. Exploring the structure-function relationships of the existing zinc finger-DNA complexes at the indirect recognition level can aid in predicting the probable zinc fingers that could bind to any target DNA. Deformation energy, which defines the energy required to bend DNA from its native shape to its shape when bound to the ZFP, is an effect of indirect recognition mechanism. Water is treated as a co-reactant for unfurling the affinity studies in ZFP-DNA binding equilibria that takes into account the unavoidable change in hydration that occurs when these two solvated surfaces come into contact.

Results

Aspects like desolvation and DNA deformation have been theoretically investigated based on simulations and free energy perturbation data revealing a consensus in correlating affinity and specificity as well as stability for ZFP-DNA interactions. Greater loss of water at the interaction interface of the DNA calls for binding with higher affinity, eventually distorting the DNA to a greater extent accounted by the change in major groove width and DNA tilt, stretch and rise.

Conclusion

Most prediction algorithms for ZFPs do not account for water loss at the interface. The above findings may significantly affect these algorithms. Further the sequence dependent deformation in the DNA upon complexation with our prototype as well as preference of bases at the 2^nd and 3^rd position of the repeating triplet provide an absolutely new insight about the indirect interactions undergoing a change that have not been probed yet.

Protein structure refinement via molecular-dynamics simulations: What works and what does not?

Protein structure refinement during CASP11 by the Feig group was described. Molecular dynamics simulations were used in combination with an improved selection and averaging protocol. On average, modest refinement was achieved with some targets improved significantly. Analysis of the CASP submission from our group focused on refinement success versus amount of sampling, refinement of different secondary structure elements and whether refinement varied as a function of which group provided initial models. The refinement of local stereochemical features was examined via the MolProbity score and an updated protocol was developed that can generate high-quality structures with very low MolProbity scores for most starting structures with modest computational effort. Proteins 2016; 84(Suppl 1):282-292. © 2015 Wiley Periodicals, Inc.

Study on the interaction of artificial and natural food colorants with human serum albumin: A computational point of view

Due to the high amount of artificial food colorants present in infants' diets, their adverse effects have been of major concern among the literature. Artificial food colorants have been suggested to affect children's behavior, being hyperactivity the most common disorder. In this study we compare binding affinities of a group of artificial colorants (sunset yellow, quinoline yellow, carmoisine, allura red and tartrazine) and their natural industrial equivalents (carminic acid, curcumin, peonidin-3-glucoside, cyanidin-3-glucoside) to human serum albumin (HSA) by a docking approach and further refinement through atomistic molecular dynamics simulations. Due to the protein-ligand conformational interface complexity, we used collective variable driven molecular dynamics to refine docking predictions and to score them according to a hydrogen-bond criterion. With this protocol, we were able to rank ligand affinities to HSA and to compare between the studied natural and artificial food additives. Our results show that the five artificial colorants studied bind better to HSA than their equivalent natural options, in terms of their H-bonding network, supporting the hypothesis of their potential risk to human health.

Significant Refinement of Protein Structure Models Using a Residue-Specific Force Field

An important application of all-atom explicit-solvent molecular dynamics (MD) simulations is the refinement of protein structures from low-resolution experiments or template-based modeling. A critical requirement is that the native structure is stable with the force field. We have applied a recently developed residue-specific force field, RSFF1, to a set of 30 refinement targets from recent CASP experiments. Starting from their experimental structures, 1.0 μs unrestrained simulations at 298 K retain most of the native structures quite well except for a few flexible terminals and long internal loops. Starting from each homology model, a 150 ns MD simulation at 380 K generates the best RMSD improvement of 0.85 Å on average. The structural improvements roughly correlate with the RMSD of the initial homology models, indicating possible consistent structure refinement. Finally, targets TR614 and TR624 have been subjected to long-time replica-exchange MD simulations. Significant structural improvements are generated, with RMSD of 1.91 and 1.36 Å with respect to their crystal structures. Thus, it is possible to achieve realistic refinement of protein structure models to near-experimental accuracy, using accurate force field with sufficient conformational sampling.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Induction and activation of latent transforming growth factor-β1 are carried out by two distinct domains of pregnancy-specific glycoprotein 1 (PSG1)

Pregnancy-specific glycoproteins (PSGs) are a family of Ig-like proteins secreted by specialized placental cells. The PSG1 structure is composed of a single Ig variable region-like N-terminal domain and three Ig constant region-like domains termed A1, A2, and B2. Members of the human and murine PSG family have been shown to induce anti-inflammatory cytokines from monocytes and macrophages and to stimulate angiogenesis. We recently showed that recombinant forms of PSG1 (PSG1-Fc and PSG1-His) and PSG1 purified from the serum of pregnant women are associated with the immunoregulatory cytokine TGF-β1 and activated latent TGF-β1. Here, we sought to examine the requirement of specific PSG1 domains in the activation of latent TGF-β1. Plasmon surface resonance studies showed that PSG1 directly bound to the small latent complex and to the latency-associated peptide of TGF-β1 and that this binding was mediated through the B2 domain. Furthermore, the B2 domain alone was sufficient for activating the small latent complex. In separate experiments, we found that the PSG1-mediated induction of TGF-β1 secretion in macrophages was dependent on the N-terminal domain. Mutagenesis analysis revealed that four amino acids (LYHY) of the CC' loop of the N-terminal domain were required for induction of latent TGF-β1 secretion. Together, our results show that two distinct domains of PSG1 are involved in the regulation of TGF-β1 and provide a mechanistic framework for how PSGs modulate the immunoregulatory environment at the maternal-fetal interface for successful pregnancy outcome.

On the importance of the distance measures used to train and test knowledge-based potentials for proteins

Knowledge-based potentials are energy functions derived from the analysis of databases of protein structures and sequences. They can be divided into two classes. Potentials from the first class are based on a direct conversion of the distributions of some geometric properties observed in native protein structures into energy values, while potentials from the second class are trained to mimic quantitatively the geometric differences between incorrectly folded models and native structures. In this paper, we focus on the relationship between energy and geometry when training the second class of knowledge-based potentials. We assume that the difference in energy between a decoy structure and the corresponding native structure is linearly related to the distance between the two structures. We trained two distance-based knowledge-based potentials accordingly, one based on all inter-residue distances (PPD), while the other had the set of all distances filtered to reflect consistency in an ensemble of decoys (PPE). We tested four types of metric to characterize the distance between the decoy and the native structure, two based on extrinsic geometry (RMSD and GTD-TS*), and two based on intrinsic geometry (Q* and MT). The corresponding eight potentials were tested on a large collection of decoy sets. We found that it is usually better to train a potential using an intrinsic distance measure. We also found that PPE outperforms PPD, emphasizing the benefits of capturing consistent information in an ensemble. The relevance of these results for the design of knowledge-based potentials is discussed.

A conformational analysis of mouse Nalp3 domain structures by molecular dynamics simulations, and binding site analysis

Scrutinizing various nucleotide-binding oligomerization domain (NOD)-like receptor (NLR) genes in higher eukaryotes is very important for understanding the intriguing mechanism of the host defense against pathogens. The nucleotide-binding domain (NACHT), leucine-rich repeat (LRR), and pyrin domains (PYD)-containing protein 3 (Nalp3), is an intracellular innate immune receptor and is associated with several immune system related disorders. Despite Nalp3's protective role during a pathogenic invasion, the molecular features and structural organization of this crucial protein is poorly understood. Using comparative modeling and molecular dynamics simulations, we have studied the structural architecture of Nalp3 domains, and characterized the dynamic and energetic parameters of adenosine triphosphate (ATP) binding in NACHT, and pathogen-derived ligands muramyl dipeptide (MDP) and imidazoquinoline with LRR domains. The results suggested that walker A, B and extended walker B motifs were the key ATP binding regions in NACHT that mediate self-oligomerization. The analysis of the binding sites of MDP and imidazoquinoline revealed LRR 7-9 to be the most energetically favored site for imidazoquinoline interaction. However, the binding free energy calculations using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method indicated that MDP is incompatible for activating the Nalp3 molecule in its monomeric form, and suggest its complex interaction with NOD2 or other NLRs accounts for MDP recognition. The high binding affinity of ATP with NACHT was correlated to the experimental data for human NLRs. Our binding site prediction for imidazoquinoline in LRR warrants further investigation via in vivo models. This is the first study that provides ligand recognition in mouse Nalp3 and its spatial structural arrangements.

Site-specific antibody-drug conjugation through an engineered glycotransferase and a chemically reactive sugar

Conjugation of small molecule drugs to specific sites on the antibody molecule has been increasingly used for the generation of relatively homogenous preparations of antibody-drug conjugates (ADCs) with physicochemical properties similar or identical to those of the naked antibody. Previously a method for conjugation of small molecules to glycoproteins through existing glycans by using an engineered glycotransferase and a chemically reactive sugar as a handle was developed. Here, for the first time, we report the use of this method with some modifications to generate an ADC from a monoclonal antibody, m860, which we identified from a human naïve phage display Fab library by panning against the extracellular domain of human HER2. M860 bound to cell surface-associated HER2 with affinity comparable to that of Trastuzumab (Herceptin), but to a different epitope. The m860ADC was generated by enzymatically adding a reactive keto-galactose to m860 using an engineered glycotransferase and conjugating the reactive m860 to aminooxy auristatin F. It exhibited potent and specific cell-killing activity against HER2 positive cancer cells, including trastuzumab-resistant breast cancer cells. This unique ADC may have utility as a potential therapeutic for HER2 positive cancers alone or in combination with other drugs. Our results also validate the keto-galactose/engineered glycotransferase method for generation of functional ADCs, which could potentially also be used for preparation of ADCs targeting other disease markers.

Is atomic rearrangement of type IV PHA synthases responsible for increased PHA production?

BACKGROUND

Type IV PHA synthase is a key enzyme responsible for catalyzing the formation of non-toxic, biocompatible, and biodegradable short-chain-length polyhydroxyalkanoates (scl-PHA) under the growth-limiting conditions in the members of the genus Bacillus.

RESULTS

The comparative in vitro and in silico analysis of the phaC subunit of type IV PHA synthases among Bacillus cereus FA11, B. cereus FC11, and B. cereus FS1 was done in our study to determine its structural and functional properties. Conserved domain analysis demonstrated that phaC subunit belongs to the alpha/beta (α/β) hydrolase fold. The catalytic triad comprising of cysteine (Cys), histidine (His), and aspartate (Asp) was found to be present at the active site. A shorter inter-atomic distance was found between the carboxyl (-COO) group of Asp and amino (NH2) group of His. Furthermore, slightly long inter-atomic distances between sulfhydryl (SH) group of Cys and NH2 group of His may be pointing toward the broader substrate specificity of type IV PHA synthases. However, a shorter distance between the SH group of Cys and NH2 group of His in case of B. cereus FC11 leads to a higher enzymatic activity and maximum PHA yield (49.26%).

CONCLUSION

The in silico study verifies that the close proximity between SH group of Cys and NH2 group of His in phaC subunit of type IV PHA synthases can be crucial for synthesis of scl-PHA. However, the catalytic activity of type IV PHA synthases declines as the distance between the sulfur (S) atom of the SH group of Cys and the nitrogen (N) atom of NH2 group of His increases.

Evaluation of unrestrained replica-exchange simulations using dynamic walkers in temperature space for protein structure refinement

A central problem of computational structural biology is the refinement of modeled protein structures taken from either comparative modeling or knowledge-based methods. Simulations are commonly used to achieve higher resolution of the structures at the all-atom level, yet methodologies that consistently yield accurate results remain elusive. In this work, we provide an assessment of an adaptive temperature-based replica exchange simulation method where the temperature clients dynamically walk in temperature space to enrich their population and exchanges near steep energetic barriers. This approach is compared to earlier work of applying the conventional method of static temperature clients to refine a dataset of conformational decoys. Our results show that, while an adaptive method has many theoretical advantages over a static distribution of client temperatures, only limited improvement was gained from this strategy in excursions of the downhill refinement regime leading to an increase in the fraction of native contacts. To illustrate the sampling differences between the two simulation methods, energy landscapes are presented along with their temperature client profiles.

Confirmation of warfarin resistance of naturally occurring VKORC1 variants by coexpression with coagulation factor IX and in silico protein modelling

BACKGROUND

VKORC1 has been identified some years ago as the gene encoding vitamin K epoxide reductase (VKOR) - the target protein for coumarin derivates like warfarin or phenprocoumon. Resistance against warfarin and other coumarin-type anticoagulants has been frequently reported over the last 50 years in rodents due to problems in pest control as well as in thrombophilic patients showing variable response to anticoagulant treatment. Many different mutations have already been detected in the VKORC1 gene leading to warfarin resistance in rats, mice and in humans. Since the conventional in vitro dithiothreitol (DTT)-driven VKOR enzymatic assay often did not reflect the in vivo status concerning warfarin resistance, we recently developed a cell culture-based method for coexpression of VKORC1 with coagulation factor IX and subsequent measurement of secreted FIX in order to test warfarin inhibition in wild-type and mutated VKORC1.

RESULTS

In the present study, we coexpressed wild-type factor IX with 12 different VKORC1 variants which were previously detected in warfarin resistant rats and mice. The results show that amino acid substitutions in VKORC1 maintain VKOR activity and are associated with warfarin resistance. When we projected in silico the amino acid substitutions onto the published three-dimensional model of the bacterial VKOR enzyme, the predicted effects matched well the catalytic mechanism proposed for the bacterial enzyme.

CONCLUSIONS

The established cell-based system for coexpression of VKORC1 and factor IX uses FIX activity as an indicator of carboxylation efficiency. This system reflects the warfarin resistance status of VKORC1 mutations from anticoagulant resistant rodents more closely than the traditional DTT-driven enzyme assay. All mutations studied were also predicted to be involved in the reaction mechanism.

Physics-based protein structure refinement through multiple molecular dynamics trajectories and structure averaging

We used molecular dynamics (MD) simulations for structure refinement of Critical Assessment of Techniques for Protein Structure Prediction 10 (CASP10) targets. Refinement was achieved by selecting structures from the MD-based ensembles followed by structural averaging. The overall performance of this method in CASP10 is described, and specific aspects are analyzed in detail to provide insight into key components. In particular, the use of different restraint types, sampling from multiple short simulations versus a single long simulation, the success of a quality assessment criterion, the application of scoring versus averaging, and the impact of a final refinement step are discussed in detail.

Allosteric regulation of the Hsp90 dynamics and stability by client recruiter cochaperones: protein structure network modeling

The fundamental role of the Hsp90 chaperone in supporting functional activity of diverse protein clients is anchored by specific cochaperones. A family of immune sensing client proteins is delivered to the Hsp90 system with the aid of cochaperones Sgt1 and Rar1 that act cooperatively with Hsp90 to form allosterically regulated dynamic complexes. In this work, functional dynamics and protein structure network modeling are combined to dissect molecular mechanisms of Hsp90 regulation by the client recruiter cochaperones. Dynamic signatures of the Hsp90-cochaperone complexes are manifested in differential modulation of the conformational mobility in the Hsp90 lid motif. Consistent with the experiments, we have determined that targeted reorganization of the lid dynamics is a unifying characteristic of the client recruiter cochaperones. Protein network analysis of the essential conformational space of the Hsp90-cochaperone motions has identified structurally stable interaction communities, interfacial hubs and key mediating residues of allosteric communication pathways that act concertedly with the shifts in conformational equilibrium. The results have shown that client recruiter cochaperones can orchestrate global changes in the dynamics and stability of the interaction networks that could enhance the ATPase activity and assist in the client recruitment. The network analysis has recapitulated a broad range of structural and mutagenesis experiments, particularly clarifying the elusive role of Rar1 as a regulator of the Hsp90 interactions and a stability enhancer of the Hsp90-cochaperone complexes. Small-world organization of the interaction networks in the Hsp90 regulatory complexes gives rise to a strong correspondence between highly connected local interfacial hubs, global mediator residues of allosteric interactions and key functional hot spots of the Hsp90 activity. We have found that cochaperone-induced conformational changes in Hsp90 may be determined by specific interaction networks that can inhibit or promote progression of the ATPase cycle and thus control the recruitment of client proteins.

Evaluation of predictions in the CASP10 model refinement category

Here we report on the assessment results of the third experiment to evaluate the state of the art in protein model refinement, where participants were invited to improve the accuracy of initial protein models for 27 targets. Using an array of complementary evaluation measures, we find that five groups performed better than the naïve (null) method—a marked improvement over CASP9, although only three were significantly better. The leading groups also demonstrated the ability to consistently improve both backbone and side chain positioning, while other groups reliably enhanced other aspects of protein physicality. The top-ranked group succeeded in improving the backbone conformation in almost 90% of targets, suggesting a strategy that for the first time in CASP refinement is successful in a clear majority of cases. A number of issues remain unsolved: the majority of groups still fail to improve the quality of the starting models; even successful groups are only able to make modest improvements; and no prediction is more similar to the native structure than to the starting model. Successful refinement attempts also often go unrecognized, as suggested by the relatively larger improvements when predictions not submitted as model 1 are also considered. Proteins 2014; 82(Suppl 2):98–111.

Princeton_TIGRESS: protein geometry refinement using simulations and support vector machines

Protein structure refinement aims to perform a set of operations given a predicted structure to improve model quality and accuracy with respect to the native in a blind fashion. Despite the numerous computational approaches to the protein refinement problem reported in the previous three CASPs, an overwhelming majority of methods degrade models rather than improve them. We initially developed a method tested using blind predictions during CASP10 which was officially ranked in 5th place among all methods in the refinement category. Here, we present Princeton_TIGRESS, which when benchmarked on all CASP 7,8,9, and 10 refinement targets, simultaneously increased GDT_TS 76% of the time with an average improvement of 0.83 GDT_TS points per structure. The method was additionally benchmarked on models produced by top performing three-dimensional structure prediction servers during CASP10. The robustness of the Princeton_TIGRESS protocol was also tested for different random seeds. We make the Princeton_TIGRESS refinement protocol freely available as a web server at http://atlas.princeton.edu/refinement. Using this protocol, one can consistently refine a prediction to help bridge the gap between a predicted structure and the actual native structure.

Functional characterization of genetic enzyme variations in human lipoxygenases

Mammalian lipoxygenases play a role in normal cell development and differentiation but they have also been implicated in the pathogenesis of cardiovascular, hyperproliferative and neurodegenerative diseases. As lipid peroxidizing enzymes they are involved in the regulation of cellular redox homeostasis since they produce lipid hydroperoxides, which serve as an efficient source for free radicals. There are various epidemiological correlation studies relating naturally occurring variations in the six human lipoxygenase genes (SNPs or rare mutations) to the frequency for various diseases in these individuals, but for most of the described variations no functional data are available. Employing a combined bioinformatical and enzymological strategy, which included structural modeling and experimental site-directed mutagenesis, we systematically explored the structural and functional consequences of non-synonymous genetic variations in four different human lipoxygenase genes (ALOX5, ALOX12, ALOX15, and ALOX15B) that have been identified in the human 1000 genome project. Due to a lack of a functional expression system we resigned to analyze the functionality of genetic variations in the hALOX12B and hALOXE3 gene. We found that most of the frequent non-synonymous coding SNPs are located at the enzyme surface and hardly alter the enzyme functionality. In contrast, genetic variations which affect functional important amino acid residues or lead to truncated enzyme variations (nonsense mutations) are usually rare with a global allele frequency<0.1%. This data suggest that there appears to be an evolutionary pressure on the coding regions of the lipoxygenase genes preventing the accumulation of loss-of-function variations in the human population.

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Non-synonymous coding variations in human lipoxygenases are mostly rare with a global allele frequency <1%.

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Common ALOX SNPs are mainly localized on the enzyme surface and hardly effect the enzyme functionality.

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hALOX15B Ala416Asp is a newly discovered loss-of-function mutation in the hALOX gene family while inactivity seems to be caused by severe structural alterations.

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Our data indicate that there is evolutionary pressure on these redox enzymes preventing the accumulation of loss-of-function variations in the human population.

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1000 Genome database is a useful tool to analyze the distribution and functionality of variations in genes of interest.

H-bond refinement for electron transfer membrane-bound protein-protein complexes: cytochrome c oxidase and cytochrome c552

In this study we propose a protocol to evaluate membrane-bound cytochrome c oxidase-cytochrome c552 docking candidates. An initial rigid docking algorithm generates docking poses of the cytochrome c oxidase-cytochrome c552, candidates are then aggregated into a 512-DPPC membrane model and solvated in explicit solvent. Molecular dynamic simulations are performed to induce conformational changes to membrane-bound protein complexes. Lastly each protein-protein complex is optimized in terms of its hydrogen bond network, evaluated energetically and ranked. The protocol is directly applicable to other membrane-protein complexes, such as protein-ligand systems.

i3Drefine software for protein 3D structure refinement and its assessment in CASP10

Protein structure refinement refers to the process of improving the qualities of protein structures during structure modeling processes to bring them closer to their native states. Structure refinement has been drawing increasing attention in the community-wide Critical Assessment of techniques for Protein Structure prediction (CASP) experiments since its addition in 8^th CASP experiment. During the 9^th and recently concluded 10^th CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed. Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement. In order to alleviate this need, we developed a completely automated and computationally efficient protein 3D structure refinement method, i3Drefine, based on an iterative and highly convergent energy minimization algorithm with a powerful all-atom composite physics and knowledge-based force fields and hydrogen bonding (HB) network optimization technique. In the recent community-wide blind experiment, CASP10, i3Drefine (as ‘MULTICOM-CONSTRUCT’) was ranked as the best method in the server section as per the official assessment of CASP10 experiment. Here we provide the community with free access to i3Drefine software and systematically analyse the performance of i3Drefine in strict blind mode on the refinement targets issued in CASP10 refinement category and compare with other state-of-the-art refinement methods participating in CASP10. Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics. Executable version of i3Drefine is freely available at http://protein.rnet.missouri.edu/i3drefine/.

GalaxyRefine: Protein structure refinement driven by side-chain repacking

The quality of model structures generated by contemporary protein structure prediction methods strongly depends on the degree of similarity between the target and available template structures. Therefore, the importance of improving template-based model structures beyond the accuracy available from template information has been emphasized in the structure prediction community. The GalaxyRefine web server, freely available at http://galaxy.seoklab.org/refine, is based on a refinement method that has been successfully tested in CASP10. The method first rebuilds side chains and performs side-chain repacking and subsequent overall structure relaxation by molecular dynamics simulation. According to the CASP10 assessment, this method showed the best performance in improving the local structure quality. The method can improve both global and local structure quality on average, when used for refining the models generated by state-of-the-art protein structure prediction servers.