Dataset Information

IDPM: an online database for ion distribution in protein molecules.

ABSTRACT: BACKGROUND:Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of 'ion-amino acid' pairing interaction and share the information with a publicly available database. RESULTS:The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in 'ion-amino acid' interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/ . CONCLUSION:The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures.

SUBMITTER: Xiang X

PROVIDER: S-EPMC5857119 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

IDPM: an online database for ion distribution in protein molecules.

Xiang Xilun X Liu Haiguang H

BMC bioinformatics 20180316 1

<h4>Background</h4>Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino ...[more]

PMID: 29548284

Similar Datasets

Project description:BACKGROUND: Human protein-protein interaction (PPIs) data are the foundation for understanding molecular signalling networks and the functional roles of biomolecules. Several human PPI databases have become available; however, comparisons of these datasets have suggested limited data coverage and poor data quality. Ongoing collection and integration of human PPIs from different sources, both experimentally and computationally, can enable disease-specific network biology modelling in translational bioinformatics studies. RESULTS: We developed a new web-based resource, the Human Annotated and Predicted Protein Interaction (HAPPI) database, located at http://bio.informatics.iupui.edu/HAPPI/. The HAPPI database was created by extracting and integrating publicly available protein interaction databases, including HPRD, BIND, MINT, STRING, and OPHID, using database integration techniques. We designed a unified entity-relationship data model to resolve semantic level differences of diverse concepts involved in PPI data integration. We applied a unified scoring model to give each PPI a measure of its reliability that can place each PPI at one of the five star rank levels from 1 to 5. We assessed the quality of PPIs contained in the new HAPPI database, using evolutionary conserved co-expression pairs called "MetaGene" pairs to measure the extent of MetaGene pair and PPI pair overlaps. While the overall quality of the HAPPI database across all star ranks is comparable to the overall qualities of HPRD or IntNetDB, the subset of the HAPPI database with star ranks between 3 and 5 has a much higher average quality than all other human PPI databases. As of summer 2008, the database contains 142,956 non-redundant, medium to high-confidence level human protein interaction pairs among 10,592 human proteins. The HAPPI database web application also provides ..." should be "The HAPPI database web application also provides hyperlinked information of genes, pathways, protein domains, protein structure displays, and sequence feature maps for interactive exploration of PPI data in the database. CONCLUSION: HAPPI is by far the most comprehensive public compilation of human protein interaction information. It enables its users to fully explore PPI data with quality measures and annotated information necessary for emerging network biology studies.

Project description:Background: Date palm (Phoenix dactylifera L.) is a cultivated woody plant with agricultural and economic importance in many countries around the world. With the advantages of next generation sequencing technologies, genome sequences for many date palm cultivars have been released recently. Short sequence repeat (SSR) and single nucleotide polymorphism (SNP) can be identified from these genomic data, and have been proven to be very useful biomarkers in plant genome analysis and breeding. Results: Here, we first improved the date palm genome assembly using 130X of HiSeq data generated in our lab. Then 246,445 SSRs (214,901 SSRs and 31,544 compound SSRs) were annotated in this genome assembly; among the SSRs, mononucleotide SSRs (58.92%) were the most abundant, followed by di- (29.92%), tri- (8.14%), tetra- (2.47%), penta- (0.36%), and hexa-nucleotide SSRs (0.19%). The high-quality PCR primer pairs were designed for most (174,497; 70.81% out of total) SSRs. We also annotated 6,375,806 SNPs with raw read depth?3 in 90% cultivars. To further reduce false positive SNPs, we only kept 5,572,650 (87.40% out of total) SNPs with at least 20% cultivars support for downstream analyses. The high-quality PCR primer pairs were also obtained for 4,177,778 (65.53%) SNPs. We reconstructed the phylogenetic relationships among the 62 cultivars using these variants and found that they can be divided into three clusters, namely North Africa, Egypt - Sudan, and Middle East - South Asian, with Egypt - Sudan being the admixture of North Africa and Middle East - South Asian cultivars; we further confirmed these clusters using principal component analysis. Moreover, 34,346 SSRs and 4,177,778 SNPs with PCR primers were assigned to shared cultivars for cultivar classification and diversity analysis. All these SSRs, SNPs and their classification are available in our database, and can be used for cultivar identification, comparison, and molecular breeding. Conclusion:DRDB is a comprehensive genomic resource database of date palm. It can serve as a bioinformatics platform for date palm genomics, genetics, and molecular breeding. DRDB is freely available at http://drdb.big.ac.cn/home.

Dataset Information

IDPM: an online database for ion distribution in protein molecules.

Publications

IDPM: an online database for ion distribution in protein molecules.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets