Clinical risk factors (CRFs), either alone or in combination with bone mineral density, are used to determine the fracture risk for clinical assessment and to determine intervention thresholds. Because fracture risk is strongly affected by ethnicity and population-specific differences, we sought to identify Korean-specific CRFs for fracture, in combination with quantitative ultrasound (qUS) measurements of the radius and tibia. A total of 9351 subjects (4732 men and 4619 women) aged 40 to 69 years were followed for a mean of 46.3 AE 2.2 months. We obtained CRF information using a standardized questionnaire and measured anthropometric variables. Speed of sound at the radius (SoSR) and tibia (SoST) were measured by qUS. Fracture events were recorded using a questionnaire, and a height-loss threshold was used as an indicator of vertebral fracture. Relative risks were calculated by Cox regression analysis. A total of 195 subjects (61 men and 134 women) suffered low-trauma fractures. Older age, lower body mass index (BMI), and previous fracture history were positively associated with fracture risk in both sexes. Decreased hip circumference, lack of regular exercise, higher alcohol intake, menopause, and osteoarthritis history were further independent CRFs for fracture in women. However, neither SoSR nor SoST was independently associated with fracture risk. In this study, we identified the major Korean-specific CRFs for fracture and found that smaller hip circumference was a novel risk factor. This information will allow optimal risk-assessment targeting Koreans for whom treatment would provide the greatest benefit. ß

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We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods.

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase.

An accurate scoring function that can select near-native structure models from a pool of alternative models is key for successful protein structure prediction. For the Critical Assessment of Techniques for protein Structure Prediction (CASP) 11, we have built a protocol of protein structure prediction that has novel coarse-grained scoring functions for selecting decoys as the heart of its pipeline. The score named PRESCO (Protein Residue Environment SCOre) developed recently by our group evaluates the native-likeness of local structural environment of residues in a structure decoy considering positions and the depth of side-chains of spatially neighboring residues. We also introduced a helix interaction potential as an additional scoring function for selecting decoys. The best models selected by PRESCO and the helix interaction potential underwent structure refinement, which includes side-chain modeling and relaxation with a short molecular dynamics simulation. Our protocol was successful, achieving the top rank in the free modeling category with a significant margin of the accumulated Z-score to the subsequent groups when the top 1 models were considered.

No abstract

We developed a new representation of local amino acid environments in protein structures called the Side-chain Depth Environment (SDE). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side-chain centroid of the residue. SDEs are general enough that similar SDEs are found in protein structures with globally different folds. Using SDEs, we developed a procedure called PRESCO (Protein Residue Environment SCOre) for selecting native or near-native models from a pool of computational models. The procedure searches similar residue environments observed in a query model against a set of representative native protein structures to quantify how native-like SDEs in the model are. When benchmarked on commonly used computational model datasets, our PRESCO compared favorably with the other existing scoring functions in selecting native and near-native models.

Progress during the past decade in non‐linear dynamics and instability theory has provided useful tools for understanding spatio‐temporal pattern formation. Procedures which apply principle component analysis (using the Karhunen–Loeve decomposition technique) to the multichannel electroencephalograph (EEG) time series have been developed. This technique shows localized changes of cortical functioning; it identifies increases and decreases of the activity of localized cortical regions over time while the subject performs a simple task or test. It can be used to demonstrate the change in cortical dynamics in response to a continuous challenge. Using 16 EEG electrodes, the technique provides spatio‐temporal information not obtained with power spectrum analysis, and includes the weighted information given with omega complexity. As an application, we performed a pattern analysis of sleep‐deprived human EEG data in 20 healthy young men. Electroencephalograph recordings were performed on subjects for <2 min, with eyes closed after normal sleep and after 24 h of experimentally‐induced sleep deprivation. The significant changes in the eigenvector components indicated the relative changes of local activity in the brain with progressive sleep deprivation. A sleep deprivation effect was observed, which was hemispherically correlated but with opposite directional dynamics. These changes were seen in the temporo‐parietal regions bilaterally. The application of the technique showed that the simple test task was performed with a limited unilateral hemispheric involvement at baseline, but needed a much larger cortical participation with decreased frontal activity and increased coherence and bilateral hemispheric involvement. The calculations performed demonstrated that the same weighted changes as those obtained with omega complexity were shown, but the technique had the added advantage of showing the localized directional changes of the principle eigenvector at each studied electrode, pointing out the cortical localized region affected by the sleep deprivation and toward which direction the environmental challenge induced the spatial change. This methodology may allow the evaluation of changes in local dynamics in brain activity in normal and pathological conditions.