Detection of Hydrophobic Clusters in Molecular Dynamics Protein Unfolding Simulations Using Association Rules

Azevedo, Paulo J.; Silva, Cândida G.; Rodrigues, Joaquim Rui; Loureiro-Ferreira, Nuno; Brito, Rui M. M.

doi:10.1007/11573067_33

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…After ubiquitin recognizes the substrate, its dynamics, and structure get altered which may expose these hydrophobic residues to solvent and form hydrophobic clusters. This may lead to collapse of the protein structure and aids in unfolding on its own to enter the narrow cavity of 26S proteosomal complex …”

Section: Resultsmentioning

confidence: 99%

Sequence and structure‐based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

Kumar

Vellaichamy

2019

Proteins

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Ubiquitination is an important post‐translational event responsible for half‐life and turnover of proteins inside the cell. Proteins are ubiquitinated by forming an iso‐peptide bond between their lysine residue and C‐terminal glycine residue of ubiquitin leading to rapid degradation of proteins by 26S proteosome complex. Deregulation of ubiquitination is manifested by aberrant expression of E3‐ligase activity or mutation in the surroundings of ubiquitination sites. Many new experimentally validated ubiquitinated lysines have been recently identified that motivated the study of the environments surrounding the ubiquitinated lysines. With the help of known ubiquitinated proteins, here we present a comprehensive study of sequence and spatial environment of ubiquitination sites of human and yeast proteins. To identify position‐specific features, this work distinguishes the spatial environments as proximity and distal regions. Certain amino acids specific to these regions, well differentiate the ubiquitination sites from non‐ubiquitination sites are revealed. Additionally, amino acid signatures that contribute for protein disordered regions and solvent accessibility of amino acids are found to be contributing factors in ubiquitination sites. These results suggest that the ubiquitination site environment of the substrate determines the recognition and unfolding of substrate to facilitate the entry into 26S proteosomal complex. We believe that these findings will help in better prediction of ubiquitination sites using the sequence and spatial information.

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Section: Resultsmentioning

confidence: 99%

Sequence and structure‐based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

Kumar

Vellaichamy

2019

Proteins

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“…The Solvent Accessible Surface Area (SASA) is one example of such properties that are important to study in order to understand the cause of the disorder and consequent manifestation. This analysis is performed by means of simulation from Molecular Dynamics (MD) unfolding of TTR [11]. The dataset is constituted by 127 time series of 10000 points each, corresponding to the variation of the SASA in each of the 127 aminoacids of the protein during a period of 10 nanoseconds (ns): one point per picosecond (ps) of simulation.…”

Section: Protein Unfoldingmentioning

confidence: 99%

Multiresolution Motif Discovery in Time Series

Castro¹,

Azevedo

2010

Proceedings of the 2010 SIAM International Conference on Data Mining

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Time series motif discovery is an important problem with applications in a variety of areas that range from telecommunications to medicine. Several algorithms have been proposed to solve the problem. However, these algorithms heavily use expensive random disk accesses or assume the data can fit into main memory. They only consider motifs at a single resolution and are not suited to interactivity. In this work, we tackle the motif discovery problem as an approximate Top-K frequent subsequence discovery problem. We fully exploit state of the art iSAX representation multiresolution capability to obtain motifs at different resolutions. This property yields interactivity, allowing the user to navigate along the Top-K motifs structure. This permits a deeper understanding of the time series database. Further, we apply the Top-K space saving algorithm to our frequent subsequences approach. A scalable algorithm is obtained that is suitable for data stream like applications where small memory devices such as sensors are used. Our approach is scalable and disk-efficient since it only needs one single pass over the time series database. We provide empirical evidence of the validity of the algorithm in datasets from different areas that aim to represent practical applications.

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“…formatting data according to Weka's ARFF structure [9], or the format of the CAREN association algorithm [10]. Such tasks usually required the data summary calculated earlier, and could be used to deliver data transformed and formatted to servers ready for processing with data mining algorithms.…”

Section: Figmentioning

confidence: 99%

Grid Computing Solutions for Distributed Repositories of Protein Folding and Unfolding Simulations

Swain

Ostropytskyy

Silva

et al. 2008

Computational Science – ICCS 2008

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Abstract. The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories -this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

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Detection of Hydrophobic Clusters in Molecular Dynamics Protein Unfolding Simulations Using Association Rules

Cited by 8 publications

References 11 publications

Sequence and structure‐based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

Sequence and structure‐based characterization of ubiquitination sites in human and yeast proteins using Chou's sample formulation

Multiresolution Motif Discovery in Time Series

Grid Computing Solutions for Distributed Repositories of Protein Folding and Unfolding Simulations

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