- Antibiotics Pharmacokinetics and Efficacy
- Gastroesophageal reflux and treatments
- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- Chemical Reactions and Isotopes
- Spectroscopy and Quantum Chemical Studies
- Ion Transport and Channel Regulation
- Advanced Proteomics Techniques and Applications
- Cell Image Analysis Techniques
- Nanopore and Nanochannel Transport Studies
- Machine Learning in Materials Science
- Aldose Reductase and Taurine
- Drug Transport and Resistance Mechanisms
- Methane Hydrates and Related Phenomena
- Quantum, superfluid, helium dynamics
- Metabolism and Genetic Disorders
- Fuel Cells and Related Materials
- Lipid Membrane Structure and Behavior
- Cancer therapeutics and mechanisms
- Pancreatic function and diabetes
- Influenza Virus Research Studies
- Radioactive element chemistry and processing
- Adipose Tissue and Metabolism
Chicago Institute for Psychoanalysis
2024-2025
University of Chicago
1998-2025
University of Maryland, College Park
2025
This study investigated the role of intracellular free Ca2+ concentration ([Ca2+]i) in apoptosis MIN6 cells, an insulin secreting cell line, and mouse islets. Thapsigargin, inhibitor sarcoendoplasmic reticulum Ca2+-ATPases (SERCA), caused a time- concentration-dependent decrease viability cells increase DNA fragmentation nuclear chromatin staining changes characteristic apoptosis. Two structurally distinct SERCA inhibitors, cyclopiazonic acid 2,5-di-[t-butyl]-1,4-hydroquinone also apoptosis,...
Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable currently access these routinely, traditional molecular dynamics feature fixed bonding arrangements that cannot account for changes in the system's topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, implemented Rapid Approach Proton Transport Other Reactions (RAPTOR) software package LAMMPS code, offers...
Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time- scales is a challenging task. Ab initio methods are unable currently access these timescales routinely, traditional molecular dynamics feature fixed bonding arrangements that cannot account for changes in the system’s topology. The Mul- tiscale Reactive Molecular Dynamics (MS-RMD) method, implemented Rapid Approach Proton Transport Other Reactions (RAPTOR) software package LAMMPS...
We introduce AlphaFold2-RAVE (af2rave), an open-source Python package that integrates machine learning-based structure prediction with physics-driven sampling to generate alternative protein conformations efficiently. Protein structures are not static but exist as ensembles of conformations, many which functionally relevant yet challenging resolve experimentally. While deep learning models like AlphaFold2 can predict structural ensembles, they lack explicit physical validation. af2rave...
The model multi-drug efflux pump from Escherichia coli , EmrE, can perform multiple types of transport leading to different biological outcomes, conferring resistance some drug substrates and enhancing susceptibility others. While transporters have traditionally been classified as antiporters, symporters, or uniporters, there is growing recognition that may exhibit mixed modalities. This raises new questions about the regulation mechanisms these transporters. Here we show C-terminal tail...
The model multi-drug efflux pump from Escherichia coli , EmrE, can perform multiple types of transport leading to different biological outcomes, conferring resistance some drug substrates and enhancing susceptibility others. While transporters have traditionally been classified as antiporters, symporters, or uniporters, there is growing recognition that may exhibit mixed modalities. This raises new questions about the regulation mechanisms these transporters. Here we show C-terminal tail...
We introduce AlphaFold2-RAVE (af2rave), an open-source Python package that integrates machine learning-based structure prediction with physics-driven sampling to generate alternative protein conformations efficiently. Protein structures are not static but exist as ensembles of conformations, many which functionally relevant yet challenging resolve experimentally. While deep learning models like AlphaFold2 can predict structural ensembles, they lack explicit physical validation. af2rave...
Quantum Mechanics/Molecular Mechanics (QM/MM) can describe chemical reactions in molecular dynamics (MD) simulations at a much lower cost than ab initio MD. Still, it is prohibitively expensive for many systems of interest because such usually require long sufficient statistical sampling. Additional MM degrees freedom are often slow and numerous but secondary interest. Coarse-graining (CG) well-known to be able speed up sampling through both reduction simulation the ability accelerate...
Influenza B viruses have cocirculated during most seasonal flu epidemics and can cause significant human morbidity mortality due to their rapid mutation, emerging drug resistance, severe impact on vulnerable populations. The influenza M2 proton channel (BM2) plays an essential role in viral replication, but the mechanisms behind its symmetric conductance involvement of a second histidine (His27) cluster remain unclear. Here we performed membrane-enabled continuous constant-pH molecular...
The model multi-drug efflux pump from Escherichia coli, EmrE, can perform multiple types of transport leading to different biological outcomes, conferring resistance some drug substrates and enhancing susceptibility others. While transporters have traditionally been classified as antiporters, symporters, or uniporters, there is growing recognition that may exhibit mixed modalities. This raises new questions about the regulation mechanisms these transporters. Here we show C-terminal tail EmrE...