Computational identification of microbial phosphorylation sites by the enhanced characteristics of sequence information

Phosphorylation sites are hyperabundant in the eukaryotic disordered proteome, suggesting that conformational fluctuations play a major role in determining to what extent a kinase interacts with a particular substrate. In biophysical terms, substrate selectivity may be determined not just by the structural–chemical complementarity between the kinase and its protein substrates but also by the free energy difference between the conformational ensembles that are, or are not, recognized by the kinase. To test this hypothesis, we developed a statistical-thermodynamics-based informatics framework, which allows us to probe for the contribution of equilibrium fluctuations to phosphorylation, as evaluated by the ability to predict Ser/Thr/Tyr phosphorylation sites in the disordered proteome. Essential to this framework is a decomposition of substrate sequence information into two types: vertical information encoding conserved kinase specificity motifs and horizontal information encoding substrate conformational equilibrium that is embedded, but often not apparent, within position-specific conservation patterns. We find not only that conformational fluctuations play a major role but also that they are the dominant contribution to substrate selectivity. In fact, the main substrate classifier distinguishing selectivity is the magnitude of change in local compaction of the disordered chain upon phosphorylation of these mostly singly phosphorylated sites. In addition to providing fundamental insights into the consequences of phosphorylation across the proteome, our approach provides a statistical-thermodynamic strategy for partitioning any sequence-based search into contributions from structural–chemical complementarity and those from changes in conformational equilibrium.

Download Full-text

Computational identification of condition-specific miRNA targets based on gene expression profiles and sequence information

BMC Bioinformatics ◽

10.1186/1471-2105-10-s1-s34 ◽

2009 ◽

Vol 10 (S1) ◽

Cited By ~ 8

Author(s):

Je-Gun Joung ◽

Zhangjun Fei

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Sequence Information ◽

Mirna Targets ◽

Computational Identification

Download Full-text

DeepPPSite: A deep learning-based model for analysis and prediction of phosphorylation sites using efficient sequence information

Analytical Biochemistry ◽

10.1016/j.ab.2020.113955 ◽

2021 ◽

Vol 612 ◽

pp. 113955

Author(s):

Saeed Ahmed ◽

Muhammad Kabir ◽

Muhammad Arif ◽

Zaheer Ullah Khan ◽

Dong-Jun Yu

Keyword(s):

Deep Learning ◽

Sequence Information ◽

Phosphorylation Sites ◽

Efficient Sequence

Download Full-text

Computational Identification of Phosphorylation Sites around Nuclear Localization Signal Sequence Reveals New Insight into Genes Associated With Human Diseases

JOURNAL OF BIOINFORMATICS AND PROTEOMICS REVIEW ◽

10.15436/2381-0793.16.1217 ◽

2017 ◽

Vol 3 (1) ◽

pp. 1-5

Author(s):

Jianjun Hu ◽

Keyword(s):

Nuclear Localization ◽

Nuclear Localization Signal ◽

Signal Sequence ◽

Human Diseases ◽

Phosphorylation Sites ◽

Nuclear Localization Signal Sequence ◽

Localization Signal ◽

Computational Identification ◽

Insight Into

Download Full-text

Hidden dynamic signatures drive substrate selectivity in the disordered phosphoproteome

10.1101/866558 ◽

2019 ◽

Author(s):

Min-Hyung Cho ◽

James O. Wrabl ◽

James Taylor ◽

Vincent J. Hilser

Keyword(s):

High Performance ◽

Conformational Dynamics ◽

Phosphorylation Site ◽

Energy Difference ◽

Disordered Proteins ◽

Statistical Thermodynamic ◽

Sequence Information ◽

Substrate Selectivity ◽

Phosphorylation Sites ◽

Information Encoding

AbstractPhosphorylation sites are hyper-abundant in the disordered proteins of eukaryotes, suggesting that conformational dynamics (or heterogeneity) may play a major role in determining to what extent a kinase interacts with a particular substrate. In biophysical terms, substrate selectivity may be determined not just by the structural and chemical complementarity between the kinase and its protein substrates, but also by the free energy difference between the conformational ensembles that are recognized by the kinase and those that are not. To test this hypothesis, we developed an informatics framework based on statistical thermodynamics, which allows us to probe for dynamic contributions to phosphorylation, as evaluated by the ability to predict Ser/Thr/ Tyr phosphorylation sites in the disordered proteome. Essential to this framework is a decomposition of substrate sequence information into two types: vertical information encoding conserved kinase specificity motifs and horizontal (distributed) information encoding substrate conformational dynamics that are embedded, but often not apparent, within position specific conservation patterns. We find not only that conformational dynamics play a major role, but that they are the dominant contribution to substrate selectivity. In fact, the main substrate classifier distinguishing selectivity is the magnitude of change in compaction of the disordered chain upon phosphorylation. Thus, in addition to providing fundamental insights into the underlying mechanistic consequences of phosphorylation across the entire proteome, our approach provides a novel statistical thermodynamic strategy for partitioning any sequence-based search into contributions from direct chemical and structural complementarity and those from changes in conformational dynamics. Using this framework, we developed a high-performance open-source phosphorylation site predictor, PHOSforUS, which is freely available at https://github.com/bxlab/PHOSforUS.

Download Full-text

PROSPECT: A web server for predicting protein histidine phosphorylation sites

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720020500183 ◽

2020 ◽

Vol 18 (04) ◽

pp. 2050018 ◽

Cited By ~ 1

Author(s):

Zhen Chen ◽

Pei Zhao ◽

Fuyi Li ◽

André Leier ◽

Tatiana T. Marquez-Lago ◽

...

Keyword(s):

Mammalian Cells ◽

Cell Metabolism ◽

Web Server ◽

Acid Group ◽

Sequence Information ◽

Phosphorylation Sites ◽

Amino Acid Group ◽

The One ◽

Histidine Phosphorylation ◽

User Friendly

Background: Phosphorylation of histidine residues plays crucial roles in signaling pathways and cell metabolism in prokaryotes such as bacteria. While evidence has emerged that protein histidine phosphorylation also occurs in more complex organisms, its role in mammalian cells has remained largely uncharted. Thus, it is highly desirable to develop computational tools that are able to identify histidine phosphorylation sites. Result: Here, we introduce PROSPECT that enables fast and accurate prediction of proteome-wide histidine phosphorylation substrates and sites. Our tool is based on a hybrid method that integrates the outputs of two convolutional neural network (CNN)-based classifiers and a random forest-based classifier. Three features, including the one-of-K coding, enhanced grouped amino acids content (EGAAC) and composition of k-spaced amino acid group pairs (CKSAAGP) encoding, were taken as the input to three classifiers, respectively. Our results show that it is able to accurately predict histidine phosphorylation sites from sequence information. Our PROSPECT web server is user-friendly and publicly available at http://PROSPECT.erc.monash.edu/ . Conclusions: PROSPECT is superior than other pHis predictors in both the running speed and prediction accuracy and we anticipate that the PROSPECT webserver will become a popular tool for identifying the pHis sites in bacteria.

Download Full-text

Specificity determinants of phosphoprotein phosphatases controlling kinetochore functions

Essays in Biochemistry ◽

10.1042/ebc20190065 ◽

2020 ◽

Vol 64 (2) ◽

pp. 325-336 ◽

Cited By ~ 1

Author(s):

Dimitriya H. Garvanska ◽

Jakob Nilsson

Keyword(s):

Spindle Assembly Checkpoint ◽

Activity Level ◽

Phosphorylation Sites ◽

Binding Affinities ◽

Mitotic Kinases ◽

Anaphase Onset ◽

Phosphoprotein Phosphatases ◽

Linear Motifs ◽

Temporal And Spatial ◽

Kinetochore Function

Abstract Kinetochores are instrumental for accurate chromosome segregation by binding to microtubules in order to move chromosomes and by delaying anaphase onset through the spindle assembly checkpoint (SAC). Dynamic phosphorylation of kinetochore components is key to control these activities and is tightly regulated by temporal and spatial recruitment of kinases and phosphoprotein phosphatases (PPPs). Here we focus on PP1, PP2A-B56 and PP2A-B55, three PPPs that are important regulators of mitosis. Despite the fact that these PPPs share a very similar active site, they target unique ser/thr phosphorylation sites to control kinetochore function. Specificity is in part achieved by PPPs binding to short linear motifs (SLiMs) that guide their substrate specificity. SLiMs bind to conserved pockets on PPPs and are degenerate in nature, giving rise to a range of binding affinities. These SLiMs control the assembly of numerous substrate specifying complexes and their position and binding strength allow PPPs to target specific phosphorylation sites. In addition, the activity of PPPs is regulated by mitotic kinases and inhibitors, either directly at the activity level or through affecting PPP–SLiM interactions. Here, we discuss recent progress in understanding the regulation of PPP specificity and activity and how this controls kinetochore biology.

Download Full-text