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Biology subjects

Syam, A.

Publications and source records attributed to Syam, A..

2 recordsLinked to original sources

Multiple Sclerosis Drug Fingolimod Exhibits Antibacterial Activity through Bacterial Membrane Permeabilization

Although receptor-mediated mechanisms account for the therapeutic action of numerous FDA-approved drugs, emerging evidence suggests that many of these therapeutics have off-target antimicrobial activities. One example is fingolimod, an immunomodulator used to treat multiple sclerosis, that has been reported to have antimicrobial effects associated with membrane permeabilization. Yet the molecular mechanism by which fingolimod alters bacterial membranes remains unknown. As a cationic amphiphilic drug (CAD), fingolimod is comprised of both hydrophobic and positively charged regions that can enable membrane interactions. We show that fingolimod compromises membrane integrity in E. coli and P. aeruginosa, contributing to its antimicrobial activity. To determine how fingolimod disrupts membrane integrity, we used planar lipid bilayer electrophysiology with phospholipid compositions mimicking E. coli membranes. Using gramicidin A channels as molecular biosensors, we show that fingolimod alters both mechanical properties and surface charge of lipid bilayers at concentrations that have antimicrobial effects. At higher concentrations, fingolimod directly permeabilizes lipid bilayers, as revealed by conductance measurements and Bilayer Overtone Analysis. Molecular dynamics simulations correlate fingolimods preference for pore-favoring curvature with its strong interactions with lipids and trans-leaflet translocation. These findings establish a molecular mechanism for fingolimods off-target activity and provide a starting point for understanding how some CAD structures can drive membrane-specific effects that compromise bacterial physiology. ImportanceMany commonly prescribed drugs, beyond their primary action via receptor targets, modify cell membranes. A mechanistic understanding of how these drugs interact with bacterial membranes will have a significant impact on drug design and on the evaluation of potential side effects. Furthermore, the emerging need for new antimicrobial drugs has led to increased interest in drug repurposing. Elucidating the molecular mechanisms of these compounds interactions with bacterial membranes can ultimately provide critical insights into redesigning existing drugs as antimicrobials and into identifying unintended membrane-related effects that may contribute to their therapeutic or off-target effects.

microbiology↗

Fast Phenotype Simulation for Genotype Representation Graphs

MotivationThe Genotype Representation Graph (GRG) [DeHaas et al., 2025] is a graph representation of whole genome polymorphisms, designed to encode the variant hard-call information in phased whole genomes. It encodes the geno-types as an extremely compact graph that can be traversed efficiently, enabling dynamic programming-style algorithms on applications such as genome-wide association studies that run faster on biobank-scale data than existing alternatives. To facilitate scalable statistical genetics, we present GrgPhenoSim, an extremely fast phenotype simulator for GRGs, suitable for simulating phenotypes on biobank-scale datasets. ResultsGrgPhenoSim contains all the primary functionalities of a phenotype simulator, uses a standardized output, and supports customized simulations. Grg-PhenoSim is dozens to hundreds of times faster than tstrait [Tagami et al., 2024], a fast ancestral recombination graph-based phenotype simulator, when the sample size ranges from thousands to hundreds of thousands samples. AvailabilityThe GrgPhenoSim library and use-case demonstrations are available at https://github.com/aprilweilab/grg_pheno_sim The documentation for GrgPhenoSim is hosted at https://grgl.readthedocs.io/en/latest/index.html

genetics↗