A bone preservation protocol that enables evaluation of osseointegration of implants with micro- and nanotextured surfaces

Development of surface treatments has enabled secure attachment of dental implants in less than 1 month. Consequently, it is necessary to characterize accurately the osseointegration of the implant surface in the region of the bone-implant contact (BIC). We developed a method for sample preparation that preserves both bone and BIC to permit analysis of the contact interface. We prepared eight nanotextured implants and implanted them in rabbit tibias. After healing for 30 days, outcomes were analyzed using both our bone preservation protocol and routine decalcification followed by preparation of histological sections stained by hematoxylin and eosin (H & E). Pull-out tests for implant osseointegration were performed after healing. Non-implanted samples of rabbit mandible were used as a control for assessing organic and mineralized bone characteristics and bone structure. Our bone preservation protocol enabled evaluation of many of the same bone characteristics as histological sections stained with H & E. Our protocol enables analysis of implant samples, implant surfaces and osseointegration without risk of BIC damage.     

Model-free Analysis of Protein Dynamics: Assessment of Accuracy and Model Selection Protocols Based on Molecular Dynamics Simulation

The popular model-free approach to analyze NMR relaxation measurements has been examined using artificial amide (15)N relaxation data sets generated from a 10 nanosecond molecular dynamics trajectory of a dihydrofolate reductase ternary complex in explicit water. With access to a detailed picture of the underlying internal motions, the efficacy of model-free analysis and impact of model selection protocols on the interpretation of NMR data can be studied. In the limit of uncorrelated global tumbling and internal motions, fitting the relaxation data to the model-free models can recover a significant amount of quantitative information on the internal dynamics. Despite a slight overestimation, the generalized order parameter is quite accurately determined. However, the model-free analysis appears to be insensitive to the presence of nanosecond time scale motions with relatively small magnitude. For such cases, the effective correlation time can be significantly underestimated. As a result, proteins appear to be more rigid than they really are. The model selection protocols have a major impact on the information one can reliably obtain. The commonly employed protocol based on step-up hypothesis testing has severe drawbacks of oversimplification and underfitting. The consequences are that the order parameter is more severely overestimated and the correlation time more severely underestimated. Instead, model selection based on Bayesian Information Criteria (BIC), recently introduced to the model-free analysis by d'Auvergne and Gooley (2003), provides a better balance between bias and variance. More appropriate models can be selected, leading to improved estimate of both the order parameter and correlation time. In addition, the computational cost is significantly reduced and subjective parameters such as the significance level are unnecessary.     

Structure-based phylogeny of polyene macrolide antibiotic glycosyltransferases

Antibiotic glycosyltransferases (AGts) attach unusual deoxy-sugars to aglycons so antibiotics can exert function. It has been reported that polyene macrolide (PEM) AGts have different evolutionary origin when compared with other polyketide AGts, and our previous analysis have suggested that they could be results of horizontal gene transfer (HGT) from eukaryotes. In this paper, we compared the structures of PEM AGts with structures of eukaryotes and other AGts, and then built models of the representative PEM AGts and GT-1 glycosyltransferases. We also constructed the Neighbor-Joining (NJ) trees based on the normalized Root Mean Square (RMS) distance, the Bayesian tree guided by structural alignments, and carried out analysis on several key conserved residues in PEM AGts. The NJ tree showed a close relationship between PEM AGts and eukaryotic glycosyltransferases, and Bayesian tree further supported their affinity with UDP-glucuronosyltransferases (UGTs). Analysis on key conserved residues showed that PEM AGts may have similar interaction mechanism such as in the formation of hydrogen bonds as eukaryotic glycosyltransferases. Using structure-based phylogenetic approaches, this study further supported that PEM AGts were the result of HGT between prokaryotes and eukaryotes.     

ATPase and Protease Domain Movements in the Bacterial AAA+ Protease FtsH Are Driven by Thermal Fluctuations

AAA+ proteases are essential players in cellular pathways of protein degradation. Elucidating their conformational behavior is key for understanding their reaction mechanism and, importantly, for elaborating our understanding of mutation-induced protease deficiencies. Here, we study the structural dynamics of the Thermotoga maritima AAA+ hexameric ring metalloprotease FtsH (TmFtsH). Using a single-molecule Förster resonance energy transfer approach to monitor ATPase and protease inter-domain conformational changes in real time, we show that TmFtsH—even in the absence of nucleotide—is a highly dynamic protease undergoing sequential transitions between five states on the second timescale. Addition of ATP does not influence the number of states or change the timescale of domain motions but affects the state occupancy distribution leading to an inter-domain compaction. These findings suggest that thermal energy, but not chemical energy, provides the major driving force for conformational switching, while ATP, through a state reequilibration, introduces directionality into this process. The TmFtsH A359V mutation, a homolog of the human pathogenic A510V mutation of paraplegin (SPG7) causing hereditary spastic paraplegia, does not affect the dynamic behavior of the protease but impairs the ATP-coupled domain compaction and, thus, may account for protease malfunctioning and pathogenesis in hereditary spastic paraplegia.     

Performance of several variable-selection methods applied to real ecological data

I evaluated the predictive ability of statistical models obtained by applying seven methods of variable selection to 12 ecological and environmental data sets. Cross-validation, involving repeated splits of each data set into training and validation subsets, was used to obtain honest estimates of predictive ability that could be fairly compared among methods. There was surprisingly little difference in predictive ability among five methods based on multiple linear regression. Stepwise methods performed similarly to exhaustive algorithms for subset selection, and the choice of criterion for comparing models (Akaike's information criterion, Schwarz's Bayesian information criterion or F statistics) had little effect on predictive ability. For most of the data sets, two methods based on regression trees yielded models with substantially lower predictive ability. I argue that there is no 'best' method of variable selection and that any of the regression-based approaches discussed here is capable of yielding useful predictive models.     

Multi-timescale dynamics study of FKBP12 along the rapamycin-mTOR binding coordinate

Drugs can affect function in proteins by modulating their flexibility. Despite this possibility, there are very few studies on how drug binding affects the dynamics of target macromolecules. FKBP12 (FK506 binding protein 12) is a prolyl cis-trans isomerase and a drug target. The immunosuppressant drug rapamycin exerts its therapeutic effect by serving as an adaptor molecule between FKBP12 and the cell proliferation regulator mTOR (mammalian target of rapamycin). To understand the role of dynamics in rapamycin-based immunosuppression and to gain insight into the role of dynamics in the assembly of supramolecular complexes, we used ¹⁵N, ¹³C, and ²H NMR spin relaxation to characterize FKBP12 along the binding coordinate that leads to cell cycle arrest. We show that sequential addition of rapamycin and mTOR leads to incremental rigidification of the FKBP12 backbone on the picosecond-nanosecond timescale. Both binding events lead to perturbation of main-chain and side-chain dynamics at sites distal to the binding interfaces, suggesting tight coupling interactions dispersed throughout the FKBP12-rapamycin interface. Binding of the first molecule, rapamycin, quenches microsecond-millisecond motions of the FKBP12 80's loop. This loop provides much of the surface buried at the protein-protein interface of the ternary complex, leading us to assert that preorganization upon rapamycin binding facilitates binding of the second molecule, mTOR. Widespread microsecond-millisecond motions of the backbone persist in the drug-bound enzyme, and we provide evidence that these slow motions represent coupled dynamics of the enzyme and isomerization of the bound drug. Finally, the pattern of microsecond-millisecond dynamics reported here in the rapamycin complex is dramatically different from the pattern in the complex with the structurally related drug FK506. This raises the important question of how two complexes that are highly isomorphic based on high-resolution static models have such different flexibilities in solution.