CoChat
Sign Up
Cited by 5Click Chemistry and ApplicationsProtein Interaction Studies and Fluorescence AnalysisAdvanced Proteomics Techniques and Applications

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

CLICK-chemoproteomics and molecular dynamics simulation reveals pregnenolone targets and their binding conformations in Th2 cells

Open access
Roy, Sougata, Roy, Sudeep, Mahata, Bidesh, Pramanik, Jhuma, Hennrich, Marco L., Gavin, Anne-Claude, Teichmann, Sarah A.·2023·Frontiers in Immunology
DOI 10.3389/fimmu.2023.1229703PMC PMC10644475

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Pregnenolone (P5) is synthesized as the first bioactive steroid in the mitochondria from cholesterol. Clusters of differentiation 4 (CD4+) and Clusters of differentiation 8 (CD8+) immune cells synthesize P5 de novo ; P5, in turn, play important role in immune homeostasis and regulation. However, P5’s biochemical mode of action in immune cells is still emerging. We envisage that revealing the complete spectrum of P5 target proteins in immune cells would have multifold applications, not only in basic understanding of steroids biochemistry in immune cells but also in developing new therapeutic applications. We employed a CLICK-enabled probe to capture P5-binding proteins in live T helper cell type 2 (Th2) cells. Subsequently, using high-throughput quantitative proteomics, we identified the P5 interactome in CD4+ Th2 cells. Our study revealed P5’s mode of action in CD4+ immune cells. We identified novel proteins from mitochondrial and endoplasmic reticulum membranes to be the primary mediators of P5’s biochemistry in CD4+ and to concur with our earlier finding in CD8+ immune cells. Applying advanced computational algorithms and molecular simulations, we were able to generate near-native maps of P5–protein key molecular interactions. We showed bonds and interactions between key amino acids and P5, which revealed the importance of ionic bond, hydrophobic interactions, and water channels. We point out that our results can lead to designing of novel molecular therapeutics strategies.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fimmu.2023.1229703

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 67

  1. Shih, 2011, Regulation of steroid production: analysis of Cyp11a1 promoter, Mol Cell Endocrinol, 336, 10.1016/j.mce.2010.12.017 · DOI
  2. Payne, 2004, Overview of steroidogenic enzymes in the pathway from cholesterol to active steroid hormones, Endocr Rev, 25, 10.1210/er.2003-0030 · DOI · Paper page
  3. Legacki, 2017, Equine fetal adrenal, gonadal and placental steroidogenesis, Reproduction, 154, 10.1530/REP-17-0239 · DOI
  4. Weng, 2016, Nongenomic actions of neurosteroid pregnenolone and its metabolites, Steroids, 111, 10.1016/j.steroids.2016.01.017 · DOI
  5. Mayo, 2001, Pregnenolone sulfate and aging of cognitive functions: behavioral, neurochemical, and morphological investigations, Hormones Behav, 40, 10.1006/hbeh.2001.1677 · DOI
  6. Mellon, 2007, Neurosteroid regulation of central nervous system development, Pharmacol Ther, 116, 10.1016/j.pharmthera.2007.04.011 · DOI · Paper page
  7. Marx, 2014, Proof-of-concept randomized controlled trial of pregnenolone in schizophrenia, Psychopharmacol (Berl), 231, 10.1007/s00213-014-3673-4 · DOI
  8. Grigoryev, 2000, Pregnenolone stimulates LNCaP prostate cancer cell growth via the mutated androgen receptor, J Steroid Biochem Mol Biol, 75, 1, 10.1016/S0960-0760(00)00131-X · DOI
  9. Trabert, 2021, Association of endogenous pregnenolone, progesterone, and related metabolites with risk of endometrial and ovarian cancers in postmenopausal women: the B~FIT cohort, Cancer Epidemiol Biomarkers Prev, 30, 10.1158/1055-9965.EPI-21-0669 · DOI
  10. Xiao, 2014, Pregnenolone, a cholesterol metabolite, induces glioma cell apoptosis via activating extrinsic and intrinsic apoptotic pathways, Oncol Lett, 8, 10.3892/ol.2014.2147 · DOI
  11. Murugan, 2019, The neurosteroid pregnenolone promotes degradation of key proteins in the innate immune signaling to suppress inflammation, J Biol Chem, 294, 10.1074/jbc.RA118.005543 · DOI
  12. Weng, 2013, Pregnenolone activates CLIP-170 to promote microtubule growth and cell migration, Nat Chem Biol, 9, 10.1038/nchembio.1321 · DOI
  13. Hamasaki, 2014, Pregnenolone functions in centriole cohesion during mitosis, Chem Biol, 21, 10.1016/j.chembiol.2014.11.005 · DOI
  14. Mahata, 2014, Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis, Cell Rep, 7, 10.1016/j.celrep.2014.04.011 · DOI
  15. Jia, 2013, Steroidogenic enzyme Cyp11a1 regulates Type 2 CD8+ T cell skewing in allergic lung disease, PNAS, 110, 10.1073/pnas.1216671110 · DOI
  16. Luckheeram, 2012, CD4+T cells: differentiation and functions, Clin Dev Immunol, 2012, 925135, 10.1155/2012/925135 · DOI · Paper page
  17. Kennedy, 2008, Multiple roles for CD4+ T cells in anti-tumor immune responses, Immunol Rev, 222, 10.1111/j.1600-065X.2008.00616.x · DOI
  18. Chen, 2012, An essential role for the Th2-type response in limiting tissue damage during helminth infection, Nat Med, 18, 10.1038/nm.2628 · DOI
  19. Liu, 2010, B cells have distinct roles in host protection against different nematode parasites, J Immunol, 184, 10.4049/jimmunol.0902879 · DOI
  20. Roy, 2021, CLICK-enabled analogues reveal pregnenolone interactomes in cancer and immune cells, iScience, 24, 102485, 10.1016/j.isci.2021.102485 · DOI
  21. Fu, 2018, Insights into the molecular mechanisms of protein-ligand interactions by molecular docking and molecular dynamics simulation: A case of oligopeptide binding protein, Comput Math Methods Med, 2018, 3502514, 10.1155/2018/3502514 · DOI
  22. Du, 2016, Insights into protein–ligand interactions: mechanisms, models, and methods, Int J Mol Sci, 17, 144, 10.3390/ijms17020144 · DOI
  23. Venkatachalam, 2003, LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites, J Mol Graph Model, 21, 289, 10.1016/S1093-3263(02)00164-X · DOI
  24. Osterberg, 2002, Automated docking to multiple target structures: incorporation of protein mobility and structural water heterogeneity in AutoDock, Proteins, 46, 34, 10.1002/prot.10028 · DOI · Paper page
  25. Rarey, 1996, A fast flexible docking method using an incremental construction algorithm, J Mol Biol, 261, 10.1006/jmbi.1996.0477 · DOI
  26. Jain, 2003, Surflex: Fully automatic flexible molecular docking using a molecular similarity-based search engine, J Med Chem, 46, 499, 10.1021/jm020406h · DOI
  27. Jones, 1997, Development and validation of a genetic algorithm for flexible docking, J Mol Biol, 267, 10.1006/jmbi.1996.0897 · DOI · Paper page
  28. Schapira, 2003, Nuclear hormone receptor targeted virtual screening, J Med Chem, 46, 10.1021/jm0300173 · DOI
  29. Friesner, 2004, Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy, J Med Chem, 47, 10.1021/jm0306430 · DOI · Paper page
  30. McGann, 2003, Gaussian docking functions, Biopolymers, 68, 76, 10.1002/bip.10207 · DOI
  31. Corbeil, 2012, Variability in docking success rates due to dataset preparation, J Comput Aided Mol Des, 26, 10.1007/s10822-012-9570-1 · DOI · Paper page
  32. Zhao, 2013, Discovery of ZAP70 inhibitors by high-throughput docking into a conformation of its kinase domain generated by molecular dynamics, Bioorg Med Chem Lett, 23, 10.1016/j.bmcl.2013.08.009 · DOI
  33. Trott, 2010, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, J Comput Chem, 31, 10.1002/jcc.21334 · DOI · Paper page
  34. Ruiz-Carmona, 2014, rDock: A fast, versatile and open source program for docking ligands to proteins and nucleic acids, PloS Comput Biol, 10, 10.1371/journal.pcbi.1003571 · DOI
  35. Allen, 2015, DOCK 6: impact of new features and current docking performance, J Comput Chem, 36, 10.1002/jcc.23905 · DOI
  36. Vallée, 2014, Pregnenolone can protect the brain from cannabis intoxication, Science, 343, 10.1126/science.1243985 · DOI
  37. Murakami, 2000, Pregnenolone binds to microtubule-associated protein 2 and stimulates microtubule assembly, Proc Natl Acad Sci U.S.A., 97, 10.1073/pnas.97.7.3579 · DOI
  38. Kleiner, 2017, & Sieber, S. A. A whole proteome inventory of background photocrosslinker binding, Angewandte Chemie Int Edition, 56, 10.1002/anie.201605993 · DOI
  39. Mzhavia, 1999, Cloning, expression, and characterization of human metalloprotease 1: a novel member of the pitrilysin family of metalloendoproteases, DNA Cell Biol, 18, 10.1089/104454999315268 · DOI
  40. Tonazzi, 2021, The mitochondrial carnitine acyl-carnitine carrier (SLC25A20): molecular mechanisms of transport, role in redox sensing and interaction with drugs, Biomolecules, 11, 521, 10.3390/biom11040521 · DOI
  41. Mastorodemos, 2009, Human GLUD1 and GLUD2 glutamate dehydrogenase localize to mitochondria and endoplasmic reticulum, Biochem Cell Biol, 87, 10.1139/O09-008 · DOI
  42. Mahata, 2020, Tumors induce de novo steroid biosynthesis in T cells to evade immunity, Nat Commun, 11, 3588, 10.1038/s41467-020-17339-6 · DOI
  43. Angajala, 2018, Diverse roles of mitochondria in immune responses: novel insights into immuno-metabolism, Front Immunol, 9, 10.3389/fimmu.2018.01605 · DOI
  44. Jiang, 2021, Endoplasmic reticulum quality control in immune cells, Front Cell Dev Biol, 9, 10.3389/fcell.2021.740653 · DOI
  45. Gao, 2014, CLUH regulates mitochondrial biogenesis by binding mRNAs of nuclear-encoded mitochondrial proteins, J Cell Biol, 207, 10.1083/jcb.201403129 · DOI
  46. Yang, 2014, Glutamine oxidation maintains the TCA cycle and cell survival during impaired mitochondrial pyruvate transport, Mol Cell, 56, 10.1016/j.molcel.2014.09.025 · DOI · Paper page
  47. Matias, 2021, Regulatory T cell differentiation is controlled by αKG-induced alterations in mitochondrial metabolism and lipid homeostasis, Cell Rep, 37, 109911, 10.1016/j.celrep.2021.109911 · DOI
  48. Smith, 2019, Glutamate dehydrogenase, a complex enzyme at a crucial metabolic branch point, Neurochem Res, 44, 10.1007/s11064-017-2428-0 · DOI
  49. Michaelis, 2011, Neuronal glud1 (Glutamate dehydrogenase 1) over-expressing mice: increased glutamate formation and synaptic release, loss of synaptic activity, and adaptive changes in genomic expression, Neurochem Int, 59, 10.1016/j.neuint.2011.03.003 · DOI
  50. Chakraborty, 2021, Revisiting steroidogenesis and its role in immune regulation with the advanced tools and technologies, Genes Immun, 22, 10.1038/s41435-021-00139-3 · DOI
  51. Hughes, 2014, Ultrasensitive proteome analysis using paramagnetic bead technology, Mol Syst Biol, 10, 757, 10.15252/msb.20145625 · DOI
  52. Franken, 2015, Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry, Nat Protoc, 10, 10.1038/nprot.2015.101 · DOI
  53. Ritchie, 2015, limma powers differential expression analyses for RNA-sequencing and microarray studies, Nucleic Acids Res, 43, 10.1093/nar/gkv007 · DOI · Paper page
  54. Huber, 2002, Variance stabilization applied to microarray data calibration and to the quantification of differential expression, Bioinformatics, 18, S96, 10.1093/bioinformatics/18.suppl_1.S96 · DOI · Paper page
  55. Strimmer, 2008, fdrtool: a versatile R package for estimating local and tail area-based false discovery rates, Bioinformatics, 24, 10.1093/bioinformatics/btn209 · DOI
  56. Varadi, 2022, AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models, Nucleic Acids Res, 50, 10.1093/nar/gkab1061 · DOI · Paper page
  57. Labute, 2008, The generalized Born/volume integral implicit solvent model: estimation of the free energy of hydration using London dispersion instead of atomic surface area, J Comput Chem, 29, 10.1002/jcc.20933 · DOI
  58. Das, 2018, Dihydroactinidiolide, a natural product against Aβ25-35 induced toxicity in Neuro2a cells: Synthesis, in silico and in vitro studies, Bioorg Chem, 81, 10.1016/j.bioorg.2018.08.037 · DOI
  59. Vijayalakshmi, 2013, Exploration of the binding of DNA binding ligands to Staphylococcal DNA through QM/MM docking and molecular dynamics simulation, J Biomol Struct Dyn, 31, 10.1080/07391102.2012.706080 · DOI
  60. Patidar, 2016, Virtual screening approaches in identification of bioactive compounds akin to delphinidin as potential HER2 inhibitors for the treatment of breast cancer, Asian Pac J Cancer Prev, 17, 10.7314/APJCP.2016.17.4.2291 · DOI
  61. Suryanarayanan, 2015, Assessment of dual inhibition property of newly discovered inhibitors against PCAF and GCN5 through in silico screening, molecular dynamics simulation and DFT approach, J Recept Signal Transduct Res, 35, 10.3109/10799893.2014.956756 · DOI
  62. Reddy, 2013, Identification of potential HIV-1 integrase strand transfer inhibitors: in silico virtual screening and QM/MM docking studies, SAR QSAR Environ Res, 24, 10.1080/1062936X.2013.772919 · DOI
  63. Salgado-Moran, 2013, Docking studies of binding of ethambutol to the C-terminal domain of the arabinosyltransferase from Mycobacterium tuberculosis, J Chem, 2013, 10.1155/2013/601270 · DOI
  64. Pradiba, 2018, Structural insights into the binding mode of flavonols with the active site of matrix metalloproteinase-9 through molecular docking and molecular dynamic simulations studies, J Biomol Struct Dyn, 36, 10.1080/07391102.2017.1397058 · DOI
  65. Stourac, 2019, Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport, Nucleic Acids Res, 47, 10.1093/nar/gkz378 · DOI
  66. Dehouck, 2009, Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0, Bioinformatics, 25, 10.1093/bioinformatics/btp445 · DOI
  67. Perez-Riverol, 2019, The PRIDE database and related tools and resources in 2019: improving support for quantification data, Nucleic Acids Res, 47, 10.1093/nar/gky1106 · DOI

Metadata

Authors
Roy, S., Roy, S., Mahata, B., Pramanik, J., Hennrich, M. L., Gavin, A.-C., & Teichmann, S. A.
Affiliations
  • Ashoka University (IN)
  • University of Cambridge (GB)
  • European Molecular Biology Laboratory (DE)
  • University of Geneva (CH)
Corresponding author
Roy, Sougata
ORCID
Venue
Frontiers in Immunology
Publisher
Frontiers Media SA
Published
2023-10-31
Volume
14
Pages
1229703-1229703
ISSN
1664-3224 (ISSN-L)
DOI
10.3389/fimmu.2023.1229703
PMC
PMC10644475
OpenAlex
W4388047184
Cited by
5
References
3
Citations by year
2026: 1 · 2025: 2 · 2024: 2
FWCI
0.51
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Immunology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Brno University of Technology Digital Library (Brno University of Technology) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
Funders
European Research Council
Topics
  • Physical Sciences › Chemistry › Organic Chemistry › Click Chemistry and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
pregnenolone, steroid binding proteins, Th2 cells, CD4+ T cells, mitochondrial proteins, endoplasmic reticulum proteins
MeSH terms
Carrier Proteins, Pregnenolone, Steroids, Th2 Cells, Molecular Dynamics Simulation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review