Results 51 to 60 of about 1,631,952 (291)
Multistage Combination Classifier Augmented Model for Protein Secondary Structure Prediction
Frontiers in Genetics, 2022 In the field of bioinformatics, understanding protein secondary structure is very important for exploring diseases and finding new treatments. Considering that the physical experiment-based protein secondary structure prediction methods are time ...
Xu Zhang +6 more
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Protein-RNA interactions: a structural analysis [PDF]
, 2001 A detailed computational analysis of 32 protein-RNA complexes is presented. A number of physical and chemical properties of the intermolecular interfaces are calculated and compared with those observed in protein-double-stranded DNA and protein-single ...
Berman, HM +4 more
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BCL::Score--knowledge based energy potentials for ranking protein models represented by idealized secondary structure elements. [PDF]
PLoS ONE, 2012 The topology of most experimentally determined protein domains is defined by the relative arrangement of secondary structure elements, i.e. α-helices and β-strands, which make up 50-70% of the sequence.
Nils Woetzel +5 more
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Protein Secondary Structure Prediction
International Journal of Innovative Technology and Exploring Engineering, 2019 Proteins are made up of basic units called amino acids which are held together by bonds namely hydrogen and ionic bond. The way in which the amino acids are sequenced has been categorized into two dimensional and three dimensional structures. The main advantage of predicting secondary structure is to produce tertiary structure likelihoods that are in ...
Priyanka B V +5 more
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Protein secondary structure prediction in different structural classes [PDF]
Protein Engineering Design and Selection, 1998 Information about the secondary structure of a protein can be helpful in understanding its native folded state. In previous work, it was shown that the medium-range interactions predominate in all-alpha class and the long-range interactions predominate in all-beta class proteins.
M M, Gromiha, S, Selvaraj
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The Caenorhabditis elegans DPF‐3 and human DPP4 have tripeptidyl peptidase activity
FEBS Letters, EarlyView.The dipeptidyl peptidase IV (DPPIV) family comprises serine proteases classically defined by their ability to remove dipeptides from the N‐termini of substrates, a feature that gave the family its name. Here, we report the discovery of a previously unrecognized tripeptidyl peptidase activity in DPPIV family members from two different species.
Aditya Trivedi, Rajani Kanth Gudipati
wiley +1 more source
MASSP3: A System for Predicting Protein Secondary Structure
EURASIP Journal on Advances in Signal Processing, 2006 A system that resorts to multiple experts for dealing with the problem of predicting secondary structures is described, whose performances are comparable to those obtained by other state-of-the-art predictors.
Armano Giuliano +2 more
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NMR analysis of synthetic human serum albumin alpha-helix 28 identifies structural distortion upon amadori modification [PDF]
, 2005 The non-enzymatic reaction between reducing sugars and long-lived proteins in vivo results in the formation of glycation and advanced glycation end products, which alter the properties of proteins including charge, helicity, and their tendency to ...
Howard, Mark J. +1 more
core +1 more source
Molecular bases of circadian magnesium rhythms across eukaryotes
FEBS Letters, EarlyView.Circadian rhythms in intracellular [Mg2+] exist across eukaryotic kingdoms. Central roles for Mg2+ in metabolism suggest that Mg2+ rhythms could regulate daily cellular energy and metabolism. In this Perspective paper, we propose that ancestral prokaryotic transport proteins could be responsible for mediating Mg2+ rhythms and posit a feedback model ...
Helen K. Feord, Gerben van Ooijen
wiley +1 more source
Secondary structure specific simpler prediction models for protein backbone angles
BMC Bioinformatics, 2022 Motivation Protein backbone angle prediction has achieved significant accuracy improvement with the development of deep learning methods. Usually the same deep learning model is used in making prediction for all residues regardless of the categories of ...
M. A. Hakim Newton +3 more
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