Mohan Babu

This paper uses MM-TPP to show that cholesteryl hemisuccinate broadly stabilizes membrane proteins across different systems and membrane mimetics.

This paper introduces Peptergents, a detergent-free method for native membrane proteomics that preserves protein structure and function, enabling better analysis of membrane proteins and their interactions.

This paper uses membrane-mimetic proteomics to show that AD-related membrane proteome changes are enriched in APP mice, and M1 receptor activation selectively affects disease-altered membrane networks.

This study compares seven membrane proteomic workflows, finding that solid-phase methods capture more total proteins while membrane mimetics enrich membrane proteins, with Peptidisc excelling in detecting dysregulated membrane proteins in diseased liver.

This study generates CHCHD2 T61I mutant mice to model Parkinson's disease, finding mitochondrial dysfunction and metabolic shifts towards glycolysis.

This study shows GlpG protease is essential for type 1 pili assembly in E. coli, affecting biofilm formation and bacterial fitness.

The paper maps DNA binding of 139 E. coli TFs using ChIP-Seq and trains BoltzNet, a neural network that predicts TF binding energy from DNA sequence, validated with biophysical experiments.

This study identifies YibN as a functional interactor of YidC, showing it enhances membrane protein insertion and lipid production in bacteria.

This paper introduces MM-TPP, a method to map membrane protein-ligand interactions using Peptidisc and thermal proteome profiling, showing it detects specific ligand effects on ABC transporters and GPCRs better than detergent-based TPP.

This study identifies dysregulated membrane proteins in liver disease using peptidisc-based proteomics in mice, highlighting lipid metabolism and xenobiotic processing pathways.

This study uses a chemical-genetic approach to analyze resistance determinants of E. coli to 15 AMPs, revealing cross-resistance and collateral sensitivity patterns.

The paper identifies two yeast genes, ITT1 and RPS1A, whose deletion increases heavy metal sensitivity by affecting URE2 mRNA translation.

This study predicts human-Zika virus protein-protein interactions and designs synthetic peptides to disrupt these interactions as potential anti-Zika virus therapeutics.