Biology subjects

Khan, F. M.

Publications and source records attributed to Khan, F. M..

4 recordsLinked to original sources

bioRxiv2026

Characterizing the endopeptidase activity of Candida albicans Gpi8, a crucial subunit of the GPI transamidase

GPI-anchored proteins are crucial cell surface proteins with diverse, organism-specific functions, in eukaryotes. They are produced when the GPI transamidase (GPIT), a five-subunit membrane-bound enzyme complex, attaches a pre-formed GPI anchor to the C-terminal end of nascent proteins on the lumenal face of the endoplasmic reticulum. This process requires the removal of a C-terminal signal sequence (SS) on the substrate protein by the action of an endopeptidase subunit of the GPIT, Gpi8/ PIG-K. Using an AMC-tagged peptide in a cell free (post-mitochondrial fraction) assay, this manuscript studies the steady state kinetics of enzymatic cleavage of the substrate by GPIT of the human pathogenic fungus, C. albicans. We show that Mn+2 enhances activity by improving substrate binding but plays no direct role in substrate cleavage per se. Molecular dynamics simulations suggest that the divalent cation binds at a site away from the active site but provides compactness and stability to Gpi8. It also enables a conformation in which a flexible loop (219-244 residues) in the vicinity of the catalytic pocket is able to interact with and position the scissile bond for cleavage by Cys202. Steady state kinetics also indicate that peptides of lengths 7-mer to 9-mer are better bound than 4-mer or 15-mer peptide substrates. A bulky residue at the site of cleavage reduces the catalytic activity of the GPIT. This is the first detailed steady state kinetics study on the endopeptidase activity of a GPIT from any organism.

biochemistry↗

bioRxiv2025

Integrative network modeling of colorectal cancer reveals diagnostic signatures and therapeutic targets

Emerging evidence suggests that the interplay between multiple signaling pathways and the immune microenvironment influences tumorigenesis in cancers such as colorectal cancer (CRC). To gain an in-depth understanding of CRC mechanisms and identify novel therapeutic targets, we constructed a molecular interaction map (MIM) integrating key signaling pathways from cancer cells and immune cells within the tumor microenvironment. This map comprises 218 molecules and 328 interactions, curated using PubMed references and official gene symbols. We dynamically simulated the MIM for individual pathways and combinations via stimulus-response and perturbation analyses, calibrating the model with two CRC datasets: GSE1323 (primary tumor-to-metastasis progression) and GSE8671 (normal mucosa-to-adenoma progression), which served as experimental conditions. Simulations revealed distinct disease signatures for GSE1323, including (1) simultaneous activation of TNF/TNFRSF1A,B and EGF/EGFR with inactivation of ERE/ESR, and (2) simultaneous activation of TNF/TNFRSF1A,B and TLR4 with inactivation of ERE/ESR. For GSE8671, the signature was simultaneous activation of TNF/TNFRSF1A,B and TLR4. In silico perturbation analysis identified potent anti-cancer effects from concurrent inhibition of MAPK3 and STAT3 (GSE1323), and ELK1/ATF2 and STAT3 or MAPK14 and STAT3 (GSE8671), significantly reducing epithelial-mesenchymal transition (EMT), proliferation, and inflammation while increasing apoptosis. Disease signatures and therapeutic targets were validated using patient data through Kaplan-Meier survival analysis and machine learning. This integrative model recapitulates cancer biology, predicts biomarkers and therapeutic targets, and is extensible to other immunogenic cancers.

systems biology↗

bioRxiv2025

Antifungal therapeutic potential of Candida albicans Fun30: screening and validation of novel inhibitors against Candida albicans

WHO has listed Candida albicans as a fungal pathogen of priority. With the increasing incidence of C. albicans infection and limited treatment strategies, the identification of new drug targets and inhibitor molecules is of global concern. ATP-dependent chromatin remodelling proteins play a crucial role in regulating gene expression. Fun30 from C. albicans (CaFun30) mediates DNA end-resection during DNA double-strand break repair. It also transcriptionally co-regulates the expression of DNA damage response genes and genes involved in white-opaque switching. The gene is not essential for viability; however, the null mutant shows increased sensitivity to genotoxic agents. We hypothesised that the protein could be a potential therapeutic target against C. albicans. The structural model of CaFun30 was generated using homology modelling. Screening of a small molecule library identified 10 potential molecules, of which F1853-0039 was found as the lead inhibitor candidate. In vitro studies showed that the molecule had an MIC in the micromolar range against C. albicans with minimal effect on human THP-1 cells. Finally, coculture experiments showed that the inhibitor molecule prevented the formation of hyphae of C. albicans upon infecting THP-1 cells leading us to conclude that CaFun30 could potentially be developed as a therapeutic target against C. albicans.

pharmacology and toxicology↗

bioRxiv2022

A Clinically Useful and Biologically Informative Genomic Classifier for Papillary Thyroid Cancer

Clinical management of papillary thyroid cancer depends on estimations of prognosis. Standard care, which relies on prognostication based on clinicopathologic features, is inaccurate. We applied a machine learning algorithm (HighLifeR) to 502 cases annotated by The Cancer Genome Atlas Project to derive an accurate molecular prognostic classifier. Unsupervised analysis of the 82 genes that were most closely associated with recurrence after surgery enabled identification of three unique molecular subtypes. One subtype had a high recurrence rate, an immunosuppressed microenvironment, and enrichment of the EZH2-HOTAIR pathway. Two other unique molecular subtypes with a lower rate of recurrence were identified, including one subtype with a paucity of BRAFV600E mutations and a high rate of RAS mutations. The genomic risk classifier, in addition to tumor size and lymph node status, enabled effective prognostication that outperformed the American Thyroid Association clinical risk stratification. The genomic classifier we derived can potentially be applied preoperatively to direct clinical decision-making. Distinct biological features of molecular subtypes also have implications regarding sensitivity to radioactive iodine, EZH2 inhibitors, and immune checkpoint inhibitors.

cancer biology↗