Protein residue networks
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Non-canonical residues, caps, crosslinks, and nicks are important to many functions of DNAs, RNAs, proteins, and complexes. However, we do not fully understand how networks of such non-canonical macromolecules generate behavior. One barrier is our limited formats for describing macromolecules.
21p viarchimedes 26-01-2022 7 0 Download
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Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation.
11p viwyoming2711 16-12-2020 14 1 Download
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Weighted and un-weighted protein residue networks can predict key functional residues in proteins based on the closeness centrality C and betweenness centrality B values for each residue. A static snapshot of the protein structure, and a cutoff distance, are used to define edges between the network nodes.
11p vikentucky2711 24-11-2020 18 1 Download
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Proteins adapt to environmental conditions by changing their shape and motions. Characterising protein conformational dynamics is increasingly recognised as necessary to understand how proteins function. Given a conformational ensemble, computational tools are needed to extract in a systematic way pertinent and comprehensive biological information.
16p vioklahoma2711 19-11-2020 18 2 Download
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The post-genomic era with its wealth of sequences gave rise to a broad range of protein residueresidue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap.
9p vioklahoma2711 19-11-2020 6 1 Download
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Deep learning is one of the most powerful machine learning methods that has achieved the state-ofthe-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition.
13p viflorida2711 30-10-2020 11 2 Download
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Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categorized as sequence-based or 3D-structure-based methods.
12p vicoachella2711 27-10-2020 9 0 Download
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Protein ubiquitination occurs when the ubiquitin protein binds to a target protein residue of lysine (K), and it is an important regulator of many cellular functions, such as signal transduction, cell division, and immune reactions, in eukaryotes.
10p vicoachella2711 27-10-2020 12 0 Download
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Recurrent neural network(RNN) is a good way to process sequential data, but the capability of RNN to compute long sequence data is inefficient. As a variant of RNN, long short term memory(LSTM) solved the problem in some extent. Here we improved LSTM for big data application in protein-protein interaction interface residue pairs prediction based on the following two reasons.
11p vicolorado2711 23-10-2020 23 0 Download
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Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands.
12p vicolorado2711 22-10-2020 13 0 Download
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In this paper we address the problem of extracting features relevant for predicting protein±protein interaction sites from the three-dimensional structures of protein complexes. Our approach is based on information about evolutionary con-servation and surface disposition. We implement a neural network based system, which uses a cross validation proce-dure and allows the correct detection of 73% of the residues involved in protein interactions in a selected database comprising 226 heterodimers.
6p research12 29-04-2013 29 2 Download
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Although allostery plays a central role in driving protein–DNA interac-tions, the physical basis of such cooperative behavior remains poorly understood. In the present study, using isothermal titration calorimetry in conjunction with site-directed mutagenesis, we provide evidence that an intricate network of energetically-coupled residues within the basic regions of the Jun-Fos heterodimeric transcription factor accounts for its allosteric binding to DNA.
15p cosis54 05-01-2013 33 2 Download