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
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.
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