A computationally directed screen identifying interacting coiled coils from Saccharomyces cerevisiae

Computational methods can frequently identify protein-interaction motifs in otherwise uncharacterized open reading frames. However, the identification of candidate ligands for these motifs (e.g., so that partnering can be determined experimentally in a directed manner) is often beyond the scope of current computational capabilities. One exception is provided by the coiled-coil interaction motif, which consists of two or more α helices that wrap around each other: the ligands for coiled-coil sequences are generally other coiled-coil sequences, thereby greatly simplifying the motif/ligand recognition problem. Here, we describe a two-step approach to identifying protein–protein interactions mediated by two-stranded coiled coils that occur in Saccharomyces cerevisiae. Coiled coils from the yeast genome are first predicted computationally, by using the multicoil program, and associations between coiled coils are then determined experimentally by using the yeast two-hybrid assay. We report 213 unique interactions between 162 putative coiled-coil sequences. We evaluate the resulting interactions, focusing on associations identified between components of the spindle pole body (the yeast centrosome).

Measuring the thickness of the human cerebral cortex from magnetic resonance images

Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test–retest studies, as well as by comparison of cross-subject regional thickness measures with published values.

An approach to three-dimensional structures of biomolecules by using single-molecule diffraction images

We describe an approach to the high-resolution three-dimensional structural determination of macromolecules that utilizes ultrashort, intense x-ray pulses to record diffraction data in combination with direct phase retrieval by the oversampling technique. It is shown that a simulated molecular diffraction pattern at 2.5-Å resolution accumulated from multiple copies of single rubisco biomolecules, each generated by a femtosecond-level x-ray free electron laser pulse, can be successfully phased and transformed into an accurate electron density map comparable to that obtained by more conventional methods. The phase problem is solved by using an iterative algorithm with a random phase set as an initial input. The convergence speed of the algorithm is reasonably fast, typically around a few hundred iterations. This approach and phasing method do not require any ab initio information about the molecule, do not require an extended ordered lattice array, and can tolerate high noise and some missing intensity data at the center of the diffraction pattern. With the prospects of the x-ray free electron lasers, this approach could provide a major new opportunity for the high-resolution three-dimensional structure determination of single biomolecules.