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Eukaryotic translation initiation begins with assembly of a 43S preinitiation complex. First, methionylated initiator methionine transfer RNA (Met-tRNAi(Met)), eukaryotic initiation factor (eIF) 2, and guanosine triphosphate form a ternary complex (TC). The TC, eIF3, eIF1, and eIF1A cooperatively bind to the 40S subunit, yielding the 43S preinitiation(More)
Hepatitis C virus (HCV) and classical swine fever virus (CSFV) messenger RNAs contain related (HCV-like) internal ribosome entry sites (IRESs) that promote 5'-end independent initiation of translation, requiring only a subset of the eukaryotic initiation factors (eIFs) needed for canonical initiation on cellular mRNAs. Initiation on HCV-like IRESs relies on(More)
DNA-binding proteins (DNA-BPs) play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Attempts have been made to identify DNA-BPs based on their sequence and structural information with moderate accuracy. Here we develop a machine learning protocol for the prediction of DNA-BPs where the(More)
MOTIVATION The rapid accumulation of single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), brings the opportunities and needs to understand and predict their disease association. Currently published attributes are limited, the detailed mechanisms governing the disease association of a SAP remain(More)
Membrane-binding peripheral proteins play important roles in many biological processes, including cell signaling and membrane trafficking. Unlike integral membrane proteins, these proteins bind the membrane mostly in a reversible manner. Since peripheral proteins do not have canonical transmembrane segments, it is difficult to identify them from their amino(More)
Annotation of the functional sites on the surface of a protein has been the subject of many studies. In this regard, the search for attributes and features characterizing these sites is of prime consequence. Here, we present an implementation of a kernel-based machine learning protocol for identifying residues on a DNA-binding protein form the interface(More)
Because of the relatively large gap of knowledge between number of protein sequences and protein structures, the ability to construct a computational model predicting structure from sequence information has become an important area of research. The knowledge of a protein's structure is crucial in understanding its biological role. In this work, we present a(More)
Nucleic acid-binding proteins are involved in a great number of cellular processes. Understanding the mechanisms underlying these proteins first requires the identification of specific residues involved in nucleic acid binding. Prediction of NA-binding residues can provide practical assistance in the functional annotation of NA-binding proteins. Predictions(More)
DNA-binding proteins perform vital functions related to transcription, repair and replication. We have developed a new sequence-based machine learning protocol to identify DNA-binding proteins. We compare our method with an extensive benchmark of previously published structure-based machine learning methods as well as a standard sequence alignment(More)
During protein synthesis, elongation of the polypeptide chain by each amino acid is followed by a translocation step in which mRNA and transfer RNA (tRNA) are advanced by one codon. This crucial step is catalyzed by elongation factor G (EF-G), a guanosine triphosphatase (GTPase), and accompanied by a rotation between the two ribosomal subunits. A mutant of(More)