Proteomics Standards Initiative at Twenty Years: Current Activities and Future Work.

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

The ProteomeXchange consortium at 10 years: 2023 update.

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

Proteomics Standards Initiative's ProForma 2.0: Unifying the Encoding of Proteoforms and Peptidoforms.

It is important for the proteomics community to have a standardized manner to represent all possible variations of a protein or peptide primary sequence, including natural, chemically induced, and artifactual modifications. The Human Proteome Organization Proteomics Standards Initiative in collaboration with several members of the Consortium for Top-Down Proteomics (CTDP) has developed a standard notation called ProForma 2.0, which is a substantial extension of the original ProForma notation developed by the CTDP. ProForma 2.0 aims to unify the representation of proteoforms and peptidoforms. ProForma 2.0 supports use cases needed for bottom-up and middle-/top-down proteomics approaches and allows the encoding of highly modified proteins and peptides using a human- and machine-readable string. ProForma 2.0 can be used to represent protein modifications in a specified or ambiguous location, designated by mass shifts, chemical formulas, or controlled vocabulary terms, including cross-links (natural and chemical) and atomic isotopes. Notational conventions are based on public controlled vocabularies and ontologies. The most up-to-date full specification document and information about software implementations are available at http://psidev.info/proforma.

Universal Spectrum Identifier for mass spectra.

Mass spectra provide the ultimate evidence to support the findings of mass spectrometry proteomics studies in publications, and it is therefore crucial to be able to trace the conclusions back to the spectra. The Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories. USI enables greater transparency of spectral evidence, with more than 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.

The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics.

The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) has standardized data submission and dissemination of mass spectrometry proteomics data worldwide since 2012. In this paper, we describe the main developments since the previous update manuscript was published in Nucleic Acids Research in 2017. Since then, in addition to the four PX existing members at the time (PRIDE, PeptideAtlas including the PASSEL resource, MassIVE and jPOST), two new resources have joined PX: iProX (China) and Panorama Public (USA). We first describe the updated submission guidelines, now expanded to include six members. Next, with current data submission statistics, we demonstrate that the proteomics field is now actively embracing public open data policies. At the end of June 2019, more than 14 100 datasets had been submitted to PX resources since 2012, and from those, more than 9 500 in just the last three years. In parallel, an unprecedented increase of data re-use activities in the field, including 'big data' approaches, is enabling novel research and new data resources. At last, we also outline some of our future plans for the coming years.

Assembling the Community-Scale Discoverable Human Proteome.

The increasing throughput and sharing of proteomics mass spectrometry data have now yielded over one-third of a million public mass spectrometry runs. However, these discoveries are not continuously aggregated in an open and error-controlled manner, which limits their utility. To facilitate the reusability of these data, we built the MassIVE Knowledge Base (MassIVE-KB), a community-wide, continuously updating knowledge base that aggregates proteomics mass spectrometry discoveries into an open reusable format with full provenance information for community scrutiny. Reusing >31 TB of public human data stored in a mass spectrometry interactive virtual environment (MassIVE), the MassIVE-KB contains >2.1 million precursors from 19,610 proteins (48% larger than before; 97% of the total) and doubles proteome coverage to 6 million amino acids (54% of the proteome) with strict library-scale false discovery controls, thereby providing evidence for 430 proteins for which sufficient protein-level evidence was previously missing. Furthermore, MassIVE-KB can inform experimental design, helps identify and quantify new data, and provides tools for community construction of specialized spectral libraries.

ProteinExplorer: A Repository-Scale Resource for Exploration of Protein Detection in Public Mass Spectrometry Data Sets.

High-throughput tandem mass spectrometry has enabled the detection and identification of over 75% of all proteins predicted to result in translated gene products in the human genome. In fact, the galloping rate of data acquisition and sharing of mass spectrometry data has led to the current availability of many tens of terabytes of public data in thousands of human data sets. The systematic reanalysis of these public data sets has been used to build a community-scale spectral library of 2.1 million precursors for over 1 million unique sequences from over 19,000 proteins (including spectra of synthetic peptides). However, it has remained challenging to find and inspect spectra of peptides covering functional protein regions or matching novel proteins. ProteinExplorer addresses these challenges with an intuitive interface mapping tens of millions of identifications to functional sites on nearly all human proteins while maintaining provenance for every identification back to the original data set and data file. Additionally, ProteinExplorer facilitates the selection and inspection of HPP-compliant peptides whose spectra can be matched to spectra of synthetic peptides and already includes HPP-compliant evidence for 107 missing (PE2, PE3, and PE4) and 23 dubious (PE5) proteins. Finally, ProteinExplorer allows users to rate spectra and to contribute to a community library of peptides entitled PrEdict (Protein Existance dictionary) mapping to novel proteins but whose preliminary identities have not yet been fully established with community-scale false discovery rates and synthetic peptide spectra. ProteinExplorer can be now be accessed at https://massive.ucsd.edu/ProteoSAFe/protein_explorer_splash.jsp .

The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition.

The ProteomeXchange (PX) Consortium of proteomics resources (http://www.proteomexchange.org) was formally started in 2011 to standardize data submission and dissemination of mass spectrometry proteomics data worldwide. We give an overview of the current consortium activities and describe the advances of the past few years. Augmenting the PX founding members (PRIDE and PeptideAtlas, including the PASSEL resource), two new members have joined the consortium: MassIVE and jPOST. ProteomeCentral remains as the common data access portal, providing the ability to search for data sets in all participating PX resources, now with enhanced data visualization components.We describe the updated submission guidelines, now expanded to include four members instead of two. As demonstrated by data submission statistics, PX is supporting a change in culture of the proteomics field: public data sharing is now an accepted standard, supported by requirements for journal submissions resulting in public data release becoming the norm. More than 4500 data sets have been submitted to the various PX resources since 2012. Human is the most represented species with approximately half of the data sets, followed by some of the main model organisms and a growing list of more than 900 diverse species. Data reprocessing activities are becoming more prominent, with both MassIVE and PeptideAtlas releasing the results of reprocessed data sets. Finally, we outline the upcoming advances for ProteomeXchange.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra.

Tandem mass spectrometry (MS/MS) experiments yield multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra they generate. We propose a spectral archives approach that clusters MS/MS datasets, representing similar spectra by a single consensus spectrum. Spectral archives extend spectral libraries by analyzing both identified and unidentified spectra in the same way and maintaining information about peptide spectra that are common across species and conditions. Thus archives offer both traditional library spectrum similarity-based search capabilities along with new ways to analyze the data. By developing a clustering tool, MS-Cluster, we generated a spectral archive from ∼1.18 billion spectra that greatly exceeds the size of existing spectral repositories. We advocate that publicly available data should be organized into spectral archives rather than be analyzed as disparate datasets, as is mostly the case today.

Catalytic mechanism of the inverting N-acetylglucosaminyltransferase I: DFT quantum mechanical model of the reaction pathway and determination of the transition state structure.

The complex N-glycan structures on glycoproteins play important roles in cell adhesion and recognition events in metazoan organisms. A critical step in the biosynthetic pathway leading from high mannose to these complex structures includes the transfer of N-acetylglucosamine (GlcNAc) to a mannose residue by the inverting N-acetylglucosaminyltransferase I (GnT-I). The catalytic mechanism of this enzymatic reaction is explored herein using DFT quantum chemical methods. The computational model used to follow the reaction is based on the X-ray crystallographic structure of GnT-I and contains 127 atoms that represent fragments of residues critical for the substrate binding and catalysis. The mechanism of the catalytic reaction was monitored by means of a 2D potential energy map calculated as a function of predefined reaction coordinates at the B3LYP/6-31G** level. This potential energy surface revealed one transition state associated with a reaction pathway following a concerted mechanism. The reaction barrier was estimated, and the structure of the transition state was characterized at the B3LYP/6-311++G**// B3LYP/6-31G** level.

On the reaction pathways and determination of transition-state structures for retaining alpha-galactosyltransferases.

The catalytic mechanism of retaining glycosyltransferases is not yet completely understood, but one possible mechanism, by analogy with retaining glycosidases, is a double-displacement mechanism via a covalent glycosyl-enzyme intermediate (CGE). We have investigated various reaction pathways for this mechanism using non-empirical quantum mechanical methods. Because a double-displacement mechanism presumes a reaction happening in two steps, we have used predefined reaction coordinates to calculate the potential energy surface describing each step of the mechanism. By investigating several potential candidates to act as a catalytic base, this study attempts to shed some light on the unclear mechanism of the second step of the reaction. All intermediates and transition states on the reaction pathways were characterized using basis sets up to the DFT/B3LYP/6-311++G**//DFT/B3LYP/6-31G* level. Reaction pathways and structural changes were compared with the results previously obtained for inverting glycosyltransferases. The outcome of this study indicates, that among the reaction models investigated, the energetically favorable one is also the most plausible given the existing experimental data. This model requires the presence of only one catalytic acid in the active site with the UDP functioning as a general base in the second step of the reaction. This mechanism is in agreement with both kinetic data in the literature and the description of X-ray structures of retaining glycosyltransferases solved up to today.

In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship.

One challenging aspect in the clinical development of molecularly targeted therapies, which represent a new and promising approach to treating cancers, has been the identification of a biologically active dose rather than a maximum tolerated dose. The goal of the present study was to identify a pharmacokinetic/pharmacodynamic relationship in preclinical models that could be used to help guide selection of a clinical dose. SU11248, a novel small molecule receptor tyrosine kinase inhibitor with direct antitumor as well as antiangiogenic activity via targeting the vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), KIT, and FLT3 receptor tyrosine kinases, was used as the pharmacological agent in these studies. In mouse xenograft models, SU11248 exhibited broad and potent antitumor activity causing regression, growth arrest, or substantially reduced growth of various established xenografts derived from human or rat tumor cell lines. To predict the target SU11248 exposure required to achieve antitumor activity in mouse xenograft models, we directly measured target phosphorylation in tumor xenografts before and after SU11248 treatment and correlated this with plasma inhibitor levels. In target modulation studies in vivo, SU11248 selectively inhibited Flk-1/KDR (VEGF receptor 2) and PDGF receptor beta phosphorylation (in a time- and dose-dependent manner) when plasma concentrations of inhibitor reached or exceeded 50-100 ng/ml. Similar results were obtained in a functional assay of VEGF-induced vascular permeability in vivo. Constant inhibition of VEGFR2 and PDGF receptor beta phosphorylation was not required for efficacy; at highly efficacious doses, inhibition was sustained for 12 h of a 24-h dosing interval. The pharmacokinetic/pharmacodynamic relationship established for SU11248 in these preclinical studies has aided in the design, selection, and evaluation of dosing regimens being tested in human trials.

SU6668 inhibits Flk-1/KDR and PDGFRbeta in vivo, resulting in rapid apoptosis of tumor vasculature and tumor regression in mice.

SU6668 is a small molecule inhibitor of the angiogenic receptor tyrosine kinases Flk-1/KDR, PDGFRbeta, and FGFR1. In mice, SU6668 treatment resulted in regression or growth arrest of all large established human tumor xenografts examined associated with loss of tumor cellularity. The events underlying loss of tumor cellularity were elucidated in detail in several tumor models. SU6668 treatment induced apoptosis in tumor microvessels within 6 h of the initiation of treatment. Dose-dependent decreases in tumor microvessel density were observed within 3 days of the first treatment. These changes were accompanied by decreased tumor cell proliferation and increased tumor cell apoptosis. Rapid increases in VEGF transcript levels were seen, consistent with the induction of tumor hypoxia. Using Western blot analyses, we determined that these in vivo antiangiogenic and proapoptotic effects of SU6668 occur at doses comparable to those required to inhibit Flk-1/KDR and PDGFRbeta phosphorylation in tumors. Potent, dose-dependent inhibition of Flk-1/KDR activity in vivo was independently demonstrated using vascular permeability as a readout. These data demonstrate that SU6668-induced inhibition of angiogenic receptor tyrosine kinase activity in vivo is associated with rapid vessel killing in tumors, leading to broad and potent antitumor effects.

Quantum mechanical and NMR spectroscopy studies on the conformations of the hydroxymethyl and methoxymethyl groups in aldohexosides.

The potential energy surfaces of the hydroxymethyl and methoxymethyl groups in methyl hexopyranosides have been extensively studied, employing quantum mechanical calculations and high resolution NMR data. The structure and energy of the C-5-C-6 rotamers were calculated at the B3LYP level of the density functional theory (DFT). For all, geometry optimizations were carried out for 264 conformers of 16 methyl D-gluco- and methyl D-galactopyranoside derivatives 1-16 at the B3LYP/6-31G** level. For all calculated minima, single-point calculations were performed at the B3LYP/6-311++G** level. Solvent effects were considered using a self-consistent reaction field method. Values of the vicinal coupling constants 3J(H-5-H-6R), 3J(H-5-H-6S), 3J(C-4-H-6R), and 3J(C-4-H-6S) for methyl D-glucopyranosides, methyl D-galactopyranosides and their 6-O-methyl derivatives 9-16 were measured in two solvents, methanol and water. The calculated gg, gt, and tg rotamer populations of the hydroxymethyl and methoxymethyl groups in 9-16 agreed well with experimental data. The results clearly showed that the population of gg, gt, and tg rotamers is sensitive to solvent effects. It was concluded that the preference of rotamers in 1-16 is due to the hydrogen bonding and solvent effects.