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Better Pathogen Targeting

Dr. Mona Minkara (center) with members of the COMBINE Lab at Northeastern University. The team combines molecular simulation and protein engineering to explore innate immune recognition and advance research in computational biophysics.
Led by Dr Mona Minkara, the Computational Modeling for Biointerface Engineering (COMBINE) Lab at Northeastern applies computational biophysics to decode molecular recognition at biological interfaces.

At the COMBINE Lab, researchers are uncovering how certain immune system proteins—called collectins—recognize and bind to sugars found on the surfaces of harmful microbes. These proteins, like surfactant protein D (SP-D), play a key role in our body’s first line of defense, especially in the lungs. By understanding how they interact with pathogens such as influenza and Pseudomonas aeruginosa, the team is helping design new proteins that could better target and neutralize these threats.

To do this, the lab uses advanced computer simulations to model how collectins behave in watery environments—just like inside the human body. In a recent study featured on the cover of the Journal of Chemical Information and Modeling, the team tested six different water models to see which best captured the subtle interactions between SP-D and a sugar molecule called trimannose. Their findings showed that newer, more physically accurate models (like OPC and TIP4P/2005) gave much better results than older ones still commonly used.

These insights are more than just technical improvements—they lay the groundwork for designing better treatments and drug delivery systems that rely on precise molecular targeting.

But the COMBINE Lab isn’t just pushing the boundaries of science—it’s also working to make that science more accessible. With support from the NIH and NSF, the team is developing multisensory tools that allow blind and visually impaired researchers to explore molecular structures through sound and touch. This work bridges chemistry, biophysics, and inclusive innovation, opening doors for more people to contribute to cutting-edge research.

By improving both the accuracy of molecular simulations and the accessibility of scientific tools, the COMBINE Lab is helping shape a future where science is both more powerful and more inclusive.

Dr. Mona Minkara
Assistant Professor of Bioengineering at Northeastern University and Affiliated Faculty in Chemistry & Chemical Biology.

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Investigating Mantle Flow Through Analyses of Earthquake Wave Propagation
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Avoiding Smash Hits
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Neurocognition at the Wu Tsai Institute, Yale
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
Building for Floods
Better Pathogen Targeting
Tracking Environmental Health Risks
AI for Cancer Diagnosis
Microplastic-Free by Design
Supporting Data-intensive Social Science
Sailing the Symbiosis Seascape
Wrangle Range Modeling
Shining a Light on Dark Matter
Grid Responsive Data Centers
Multifunctional 3D-Printed Materials
AI Pareidolia
Computing Hidden Health Threats from Heat
Staving off the Banana Apocalypse
CRISPR Mice, Smarter Science
Naval and Ocean Renewable Energy Hydrodynamics
AI That Speaks Human About Health
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