Proteomics and Bioinformatics MultiOmics Applications towards New and Personalized Therapies Using Quantitative and Treatment-Specific Proteome Signatures, Quantitative Clinical End Points and Biomarkers Identification

Dear Colleagues,

Mass spectrometry (MS) based Proteomics involves the separation, identification, quantification and functional characterization of the entire protein profile of a given cell, tissue, and/or organism. Proteomics is used to study how proteins adapt and modify their expression as well as their function in a particular biological pathway or respond to a compound or treatment. Recent advances in MS have allowed proteomes to be studied in depth, with high throughput strategies and protocols producing long lists of proteins. Ergo, a boost of analytical DDA (Data Dependent Acquisition) and DIA (Data Independent Acquisition) methods for protein identification and quantification are being developed to increase the precision of methods which identify proteins within a sample. Recent high throughput chemical proteomics strategies can enable more biological replicates and provide orthogonal approaches for deconvolution of targets and MoA. The latest advances in bioinformatics have also been applied to proteomics data allowing the output to be analysed and relevant biological information to be specifically deconvoluted.

This issue is focused to original research that uses bioinformatics, mass spectrometry and proteomics tools integrated with multi-omics framework(s) aimed to the study of properties and interactions of proteins, protein structure and post-translational modifications, binding site and epitope identification, biomarker discovery in the context of human diseases.
Moreover, papers with focus on life threatening and rare haematological human diseases and repurposing strategies aided by proteomics and bioinformatics approaches are of particular interest.
This issue aims to provide the scientific community from bench scientists to clinicians a direct translational approach from basic science to meaningful explorative or actual end points of clinical trials of rare and life threatening diseases.

Dr. Piero Ricchiuto
Dr. Massimiliano Gaetani
Guest Editors

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• biomarker identification
• target deconvolution
• mechanism of action
• off-targets
• rare disease
• hematological disease
• life-threatening disease
• chemical proteomics
• personalized therapies
• clinical exploratory end points
• multi-omics tools
• good practices in clinical proteomics
• application of AI & Bayesian models in quantitative proteomics
• F.A.I.R. data