Understanding a malaria protein to spot and prevent drug resistance
Leveraging PfCRT Structure to Discern Function and Predict Emergence of Drug-Resistant Malaria
['FUNDING_R01'] · COLUMBIA UNIVERSITY HEALTH SCIENCES · NIH-11458279
This project uses detailed 3D pictures and computer models of a malaria parasite protein to better spot how drug resistance appears so treatments for people with malaria remain effective.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | COLUMBIA UNIVERSITY HEALTH SCIENCES (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-11458279 on ClinicalTrials.gov |
What this research studies
Researchers are focusing on a protein in the deadliest malaria parasite that lets it resist common drugs. They mapped the protein in high detail and combine lab tests, gene-editing of parasites, advanced imaging, and computer simulations including molecular dynamics and machine learning to see how drugs interact with the protein. The team runs experiments in artificial membranes and in modified parasites to connect lab findings with how the parasite behaves. By linking structural, biochemical, and computational results, they aim to predict which mutations could cause new forms of drug resistance.
Who could benefit from this research
Good fit: Ideal participants would be people in malaria-endemic areas or patients whose infections fail standard antimalarial drugs and who can provide parasite samples through collaborating clinics.
Not a fit: People without Plasmodium falciparum infection or those with other non-falciparum malaria types are unlikely to receive direct benefit from this project.
Why it matters
Potential benefit: If successful, this work could help detect and stop drug-resistant malaria earlier and guide development of more effective antimalarial medicines.
How similar studies have performed: Previous structural and laboratory studies have successfully identified mechanisms of malaria drug resistance, though using structural data and machine learning together to predict emergence is relatively novel.
Where this research is happening
NEW YORK, UNITED STATES
- COLUMBIA UNIVERSITY HEALTH SCIENCES — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: MANCIA, FILIPPO — COLUMBIA UNIVERSITY HEALTH SCIENCES
- Study coordinator: MANCIA, FILIPPO
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.