Prediction of protein tertiary structure using PROFESY, a novel method based on fragment assembly and conformational space annealing.
A novel method for ab initio prediction of protein tertiary structures, PROFESY (PROFile Enumerating SYstem), is proposed. This method utilizes the secondary structure prediction information of a query sequence and the fragment assembly procedure based on global optimization. Fifteen-residue-long fragment libraries are constructed using the secondary structure prediction method PREDICT, and fragments in these libraries are assembled to generate full-length chains of a query protein. Tertiary structures of 50 to 100 conformations are obtained by minimizing an energy function for proteins, using the conformational space annealing method that enables one to sample diverse low-lying local minima of the energy. We apply PROFESY for benchmark tests to proteins with known structures to demonstrate its feasibility. In addition, we participated in CASP5 and applied PROFESY to four new-fold targets for blind prediction. The results are quite promising, despite the fact that PROFESY was in its early stages of development. In particular, PROFESY successfully provided us the best model-one structure for the target T0161.

title: Microcanonical origin of the maximum entropy principle for open systems.
abstract: There are two distinct approaches for deriving the canonical ensemble. The canonical ensemble either follows as a special limit of the microcanonical ensemble or alternatively follows from the maximum entropy principle. We show the equivalence of these two approaches by applying the maximum entropy formulation to a closed universe consisting of an open system plus bath. We show that the target function for deriving the canonical distribution emerges as a natural consequence of partial maximization of the entropy over the bath degrees of freedom alone. By extending this mathematical formalism to dynamical paths rather than equilibrium ensembles, the result provides an alternative justification for the principle of path entropy maximization as well.

title: Protein loop modeling by using fragment assembly and analytical loop closure.
abstract: Protein loops are often involved in important biological functions such as molecular recognition, signal transduction, or enzymatic action. The three dimensional structures of loops can provide essential information for understanding molecular mechanisms behind protein functions. In this article, we develop a novel method for protein loop modeling, where the loop conformations are generated by fragment assembly and analytical loop closure. The fragment assembly method reduces the conformational space drastically, and the analytical loop closure method finds the geometrically consistent loop conformations efficiently. We also derive an analytic formula for the gradient of any analytical function of dihedral angles in the space of closed loops. The gradient can be used to optimize various restraints derived from experiments or databases, for example restraints for preferential interactions between specific residues or for preferred backbone angles. We demonstrate that the current loop modeling method outperforms previous methods that employ residue-based torsion angle maps or different loop closure strategies when tested on two sets of loop targets of lengths ranging from 4 to 12.

title: A derivation of the master equation from path entropy maximization.
abstract: The master equation and, more generally, Markov processes are routinely used as models for stochastic processes. They are often justified on the basis of randomization and coarse-graining assumptions. Here instead, we derive nth-order Markov processes and the master equation as unique solutions to an inverse problem. We find that when constraints are not enough to uniquely determine the stochastic model, an nth-order Markov process emerges as the unique maximum entropy solution to this otherwise underdetermined problem. This gives a rigorous alternative for justifying such models while providing a systematic recipe for generalizing widely accepted stochastic models usually assumed to follow from the first principles.

title: Measures for the assessment of fuzzy predictions of protein secondary structure.
abstract: Many of the recent secondary structure prediction methods incorporate the idea of fuzzy set theory, where instead of assigning a definite secondary structure to a query residue, probability for the residue being in each of the conformational states is estimated. Moreover, continuous assignment of conformational states to the experimentally observed protein structures can be performed in order to reflect inherent flexibility. Although various measures have been developed for evaluating performances of secondary structure prediction methods, they depend only on the most probable secondary structures. They do not assess the accuracy of the probabilities produced by fuzzy prediction methods, and they cannot incorporate information contained in continuous assignments of conformational states to observed structures. Three important measures for evaluating performance of a secondary structure prediction algorithm, Q score, Segment OVerlap (SOV) measure, and the k-state correlation coefficient (Corr), are deformed into fuzzy measures F score, Fuzzy OVerlap (FOV) measure, and the fuzzy correlation coefficient (Forr), so that the new measures not only assess probabilistic outputs of fuzzy prediction methods, but also incorporate information from continuous assignments of secondary structure. As an example of application, prediction results of four fuzzy secondary structure prediction methods, PSIPRED, PROFking, SABLE, and PREDICT, are assessed using the new fuzzy measures.

title: Protein structure prediction based on fragment assembly and parameter optimization.
abstract: We propose a novel method for ab-initio prediction of protein tertiary structures based on the fragment assembly and global optimization. Fifteen residue long fragment libraries are constructed using the secondary structure prediction method PREDICT, and fragments in these libraries are assembled to generate full-length chains of a query protein. Tertiary structures of 50 to 100 conformations are obtained by minimizing an energy function for proteins, using the conformational space annealing method that enables one to sample diverse low-lying local minima of the energy. Then in order to enhance the performance of the prediction method, we optimize the linear parameters of the energy function, so that the native-like conformations become energetically more favorable than the non-native ones for proteins with known structures. We test the feasibility of the parameter optimization procedure by applying it to the training set consisting of three proteins: the 10-55 residue fragment of staphylococcal protein A (PDB ID 1bdd), a designed protein betanova, and 1fsd.

title: Quantitative Imaging of Cerebral Blood Flow Velocity and Intracellular Motility using Dynamic Light Scattering–Optical Coherence Tomography
abstract: This paper describes a novel optical method for label-free quantitative imaging of cerebral blood flow (CBF) and intracellular motility (IM) in the rodent cerebral cortex. This method is based on a technique that integrates dynamic light scattering (DLS) and optical coherence tomography (OCT), named DLS–OCT. The technique measures both the axial and transverse velocities of CBF, whereas conventional Doppler OCT measures only the axial one. In addition, the technique produces a three-dimensional map of the diffusion coefficient quantifying nontranslational motions. In the DLS–OCT diffusion map, we observed high-diffusion spots, whose locations highly correspond to neuronal cell bodies and whose diffusion coefficient agreed with that of the motion of intracellular organelles reported in vitro in the literature. Therefore, the present method has enabled, for the first time to our knowledge, label-free imaging of the diffusion-like motion of intracellular organelles in vivo. As an example application, we used the method to monitor CBF and IM during a brief ischemic stroke, where we observed an induced persistent reduction in IM despite the recovery of CBF after stroke. This result supports that the IM measured in this study represent the cellular energy metabolism-related active motion of intracellular organelles rather than free diffusion of intracellular macromolecules.

title: Korean version of the Revised Caregiving Appraisal Scale: a translation and validation study.
abstract: This paper is a report of a study to examine the reliability and validity of a Korean version of the Revised Caregiving Appraisal Scale with Korean caregivers of older stroke survivors.



The Revised Caregiving Appraisal Scale was developed in the United States of America for an American English-speaking population to measure primary caregivers' appraisals of potential stressors and the efficacy of their coping efforts related to caregiving experiences.



Using the back-translation method, the instrument was translated into Korean. The Korean version of the Revised Caregiving Appraisal Scale was self-administered by 147 primary family caregivers recruited from three outpatient clinics and two home health agencies in Korea. The study was conducted in 2005.



In this sample, Cronbach's alpha for the total scale was 0.86. Reliability coefficients for each of the five subscales ranged from 0.40 to 0.85. Two subscales, burden and satisfaction, showed good reliability; one subscale, impact, showed marginally acceptable reliability; two subscales, mastery and demand, had low reliability. Principal components factor analysis of the Korean version of the Revised Caregiving Appraisal Scale yielded six factors. Except for the mastery domain, which was divided into two factors, the other factors were similar to those in the original scale.



The Korean version of the Revised Caregiving Appraisal Scale had adequate reliability and validity in a sample of Korean caregivers of stroke survivors. It can be used to assess the impact of caregiving and interventions on Korean caregiver attitudes. Further studies are needed with different categories of caregiver.

title: Receptor-activity modifying protein 1 expression is increased in the striatum following repeated L-DOPA administration in a 6-hydroxydopamine lesioned rat model of Parkinson's disease.
abstract: Abnormalities in signaling by G-protein coupled receptors (GPCRs) within the striatum are involved in the pathophysiology of Parkinson's disease (PD) and L-DOPA induced dyskinesia (LID). Receptor activity modifying proteins (RAMPs) are single transmembrane accessory proteins crucial for both trafficking and defining the phenotype of GPCRs. In the CNS, RAMP1 mRNA is predominantly expressed in striatum, cortex, and olfactory tubercles. In the present study, expression of RAMP1 mRNA is increased in the striatum (68-77%), following repeated L-DOPA administration, in the 6-hydroxydopamine-lesioned rat. These data are the first to describe regulation of RAMP1 expression in the CNS and suggest that changes in RAMP1 activity are involved in the pathophysiology of LID.

title: Motor neuronal protection by L-arginine prolongs survival of mutant SOD1 (G93A) ALS mice.
abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive paralysis due to motor neuron degeneration. Despite the fact that many different therapeutic strategies have been applied to prevent disease progression, no cure or effective therapy is currently available for ALS. We found that L-arginine protects cultured motor neurons from excitotoxic injury. We also found that L-arginine supplementation both prior to and after the onset of motor neuron degeneration in mtSOD1 (G93A) transgenic ALS mice significantly slowed the progression of neuropathology in lumbar spinal cord, delayed onset of motor dysfunction, and prolonged life span. Moreover, L-arginine treatment was associated with preservation of arginase I activity and neuroprotective polyamines in spinal cord motor neurons. Our findings show that L-arginine has potent in vitro and in vivo neuroprotective properties and may be a candidate for therapeutic trials in ALS.

title: Detection of E. coli in beach water within 1 hour using immunomagnetic separation and ATP bioluminescence.
abstract: The contamination of beach waters occurs from the discharge of storm water and sanitary sewer overflows containing faecal material. Additional faecal material derives from discharge of animals and waterfowl. In order to protect public from exposure to faecal-contaminated water, it is required to test enteric indicators in beach water. The problem is that the traditional culture-based methods cannot meet this goal because it takes too long (>24 h), so the results are not available until a day later. A rapid method for testing beach water for Escherichia coli within 1 h has been developed. Immunomagnetic separation (IMS) and ATP bioluminescence were used for selective capture and quantification, respectively. This rapid method was compared to the current method (m-TEC) using beach water samples. The beach samples were prefiltered with a 20 microm pore size filter in order to remove algae, plant debris and large particles. The results showed that the prefiltration step did not trap the bacteria which were present in the original water samples. The prefiltered water was then passed through a 0.45 microm pore size filter for concentration. The deposited bacteria were resuspended and then mixed with superparamagnetic polystyrene beads (diameter of 0.6 microm) that were coated with E. coli antibodies. After IMS, the quantification of the E. coli was done by ATP bioluminescence. The results obtained with IMS-ATP bioluminescence correlated well with the plate count method (Rsq = 0.93). The detection limit of the assay was about 20 CFU/100 mL, which is well below the US EPA limits for recreational water. The entire procedure can be completed in less than 1 hour. The necessary equipment is portable and was tested on-site.