The long-standing problem of constructing protein structure alignments is of central importance in computational biology. The main goal is to provide an alignment of residue correspondences, in order to identify homologous residues across chains. A critical next step of this is the alignment of protein complexes and their interfaces.
View Article and Find Full Text PDFIdentification of extracellular ligand-receptor interactions is important for drug design and the treatment of diseases. Difficulties in detecting these interactions using high-throughput experimental techniques motivate the development of computational prediction methods. We propose a novel threading algorithm, LTHREADER, which generates accurate local sequence-structure interface alignments and integrates various statistical scores and experimental binding data to predict interactions within ligand-receptor families.
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December 2007
Identification of ligand-receptor interactions is important for drug design and treatment of diseases. Difficulties in detecting these interactions using high-throughput experimental techniques motivate the development of computational prediction methods. We propose a novel threading algorithm, LTHREADER, which generates accurate local sequence-structure alignments and integrates statistical and energy scores to predict interactions within ligand-receptor families.
View Article and Find Full Text PDFTopologically modeled amorphized silica structures have been refined using a molecular dynamics simulation technique. Several metastable structures with substantially different medium-range connectivities, as characterized by primitive ring statistics, were obtained. Whereas the total correlation function is insensitive to these differences, the first step diffraction peak derived from energy-filtered electron diffraction shows a promising correlation to medium-range structure.
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