Dataset Information

PISA Assay of B1 antibiotic on Neisseria gonorrhoeae

ABSTRACT: Study on antibiotic B1 and for target identification and mode of action characterization on Neisseria gonorrhoeae Strain, using Proteome Integral Solubility Alteration (PISA) Assay

INSTRUMENT(S):

ORGANISM(S): Neisseria Gonorrhoeae

SUBMITTER: Massimiliano Gaetani

LAB HEAD: Massimiliano Gaetani

PROVIDER: PXD063107 | Pride | 2026-01-19

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20250226_nU5_Exp2_Amir_B1.msf	Msf
	20250226_nU5_Exp2_Amir_B2_01.raw	Raw
	20250226_nU5_Exp2_Amir_B2_02.raw	Raw
	20250226_nU5_Exp2_Amir_B2_03.raw	Raw
	20250226_nU5_Exp2_Amir_B2_04.raw	Raw

Items per page:

1 - 5 of 18

Publications

A generative deep learning approach to de novo antibiotic design.

Krishnan Aarti A Anahtar Melis N MN Valeri Jacqueline A JA Jin Wengong W Donghia Nina M NM Sieben Leif L Luttens Andreas A Zhang Yu Y Modaresi Seyed Majed SM Hennes Andrew A Fromer Jenna J Bandyopadhyay Parijat P Chen Jonathan C JC Rehman Danyal D Desai Ronak R Edwards Paige P Lach Ryan S RS Aschtgen Marie-Stéphanie MS Gaborieau Margaux M Gaetani Massimiliano M Palace Samantha G SG Omori Satotaka S Khonde Lutete L Moroz Yurii S YS Blough Bruce B Jin Chunyang C Loh Edmund E Grad Yonatan H YH Saei Amir Ata AA Coley Connor W CW Wong Felix F Collins James J JJ

Cell 20250814 21

The antimicrobial resistance crisis necessitates structurally distinct antibiotics. While deep learning approaches can identify antibacterial compounds from existing libraries, structural novelty remains limited. Here, we developed a generative artificial intelligence framework for designing de novo antibiotics through two approaches: a fragment-based method to comprehensively screen >10<sup>7</sup> chemical fragments in silico against Neisseria gonorrhoeae or Staphylococcus aureus, subsequently ...[more]

PMID: 40816267

Similar Datasets

Project description:Background: Despite current therapeutic treatments including surgery, chemotherapy, radiotherapy and recently immunotherapy, the mortality rate of lung cancer stays high. Regarding lung cancer, epigenetic modifications altering cell cycle, angiogenesis and programmed cancer cell death are therapeutic targets to combine with immunotherapy to improve treatment success. In a recent study, we uncovered a dual function of a molecule called QAPHA ((E)-3-(5-((2-cyanoquinolin-4-yl)(methyl)amino)-2-methoxyphenyl)-N-hydroxyacrylamide) as both a tubulin polymerization and HDAC inhibitors. Here, we investigate the impact of this novel dual inhibitor on the lung cancer immune response. Methods: To elucidate the mechanism of action of QAPHA, we conducted a chemical proteomics analysis. Using an in vivo mouse model of lung cancer (TC-1 tumor cells), we assessed the effects of QAPHA on tumor regression. Tumor infiltrating immune cells were characterize by flow cytometry. Results In this study, we first show that QAPHA can inhibit HDAC6, leading to upregulation of HSP90, cytochrome C and caspases, found by proteomic analysis. We also confirm that QAPHA induces immunogenic cell death (ICD) by upregulating HMGB1 in vitro and demonstrated its effectiveness as a vaccine in vivo. Remarkably, even at a low concentration (0.5mg/kg), QAPHA achieved complete tumor regression in approximately 60% of intratumorally treated mice, establishing a long-lasting anticancer immune response. Moreover, QAPHA treatment promoted infiltration of neutrophils in the treated mice, reflecting inflammatory cell death promoted. Very interestingly, we show that QAPHA is also able to upregulate MHC-II expression on TC-1 tumor cells in vitro and in vivo. This process participates to the recruitment of CD4+ NKG2D+ CRTAM+ Perforin+ T cells in tumor infiltrate, defined as cytotoxic CD4+ T cells (CD4+ CTL). Finally, we show that tumor regression is strongly correlated to MHC-II expression level on tumor cell and CD4+ CTL infiltrate. Conclusion Collectively, our findings shed light on the discovery of a new multi-target inhibitor able to induce ICD and MHC-II upregulation in TC-1 tumor cell. These two processes participate to enhance a specific CD4+ cytotoxic T cell-mediated anti-tumor response in vivo in our model of lung cancer. This breakthrough suggests the potential of QAPHA as a promising therapeutic agent for cancer treatment.