AIMC Topic: Proteome
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DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation.
Nature communications
Nov 18, 2021
Phosphoproteomics integrating data-independent acquisition (DIA) enables deep phosphoproteome profiling with improved quantification reproducibility and accuracy compared to data-dependent acquisition (DDA)-based phosphoproteomics. DIA data mining he...
Proteome-Informed Machine Learning Studies of Cocaine Addiction.
The journal of physical chemistry letters
Nov 9, 2021
No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate molecular mechanisms of cocaine addiction, involving synergistic interactions among proteins upstrea...
pValid 2: A deep learning based validation method for peptide identification in shotgun proteomics with increased discriminating power.
Journal of proteomics
Nov 2, 2021
Tandem mass spectrometry has been the principal method in shotgun proteomics for peptide and protein identification. However, incorrect identifications reported by proteome search engines are still unknown, and further validation methods are needed. ...
The AlphaFold Database of Protein Structures: A Biologist's Guide.
Journal of molecular biology
Oct 29, 2021
AlphaFold, the deep learning algorithm developed by DeepMind, recently released the three-dimensional models of the whole human proteome to the scientific community. Here we discuss the advantages, limitations and the still unsolved challenges of the...
DeepLC can predict retention times for peptides that carry as-yet unseen modifications.
Nature methods
Oct 28, 2021
The inclusion of peptide retention time prediction promises to remove peptide identification ambiguity in complex liquid chromatography-mass spectrometry identification workflows. However, due to the way peptides are encoded in current prediction mod...
Time-resolved in vivo ubiquitinome profiling by DIA-MS reveals USP7 targets on a proteome-wide scale.
Nature communications
Sep 13, 2021
Mass spectrometry (MS)-based ubiquitinomics provides system-level understanding of ubiquitin signaling. Here we present a scalable workflow for deep and precise in vivo ubiquitinome profiling, coupling an improved sample preparation protocol with dat...
Highly accurate protein structure prediction for the human proteome.
Nature
Jul 22, 2021
Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues i...
A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins.
Journal of proteome research
Jul 8, 2021
Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to pre...
Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.
Life science alliance
Jun 24, 2021
SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that...
A deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites.
Scientific reports
Jun 15, 2021
Protein phosphorylation, which is one of the most important post-translational modifications (PTMs), is involved in regulating myriad cellular processes. Herein, we present a novel deep learning based approach for organism-specific protein phosphoryl...
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