MAR 21, 2020 10:28 AM PDT

Modeling Mutations to Beat Drug Resistance

WRITTEN BY: Nouran Amin

Mutations in bacteria or even cancer cells can make them resistant to drug treatments—that means they no longer respond to it and thus continue their harm.

To address this issue, engineers at Penn State have modeled a way of predicting which mutations will occur in people to create an easier path for effective pharmaceuticals.

"Structure-based drug design works very well," said Justin Pritchard, assistant professor of biomedical engineering and holder of the Dorothy Foehr Huck and J. Lloyd Huck Early Career Entrepreneurial Professorship. "It is an amazing ecosystem of technology, but you still have to point it at a set of resistance mutations."

How can this happen? Well researchers know the drugs are developed to the structure of chemicals and their cell targets—however, once a mutation occurs, the cells ‘change’ making them resistant to drugs.

"We need to not just understand the biophysics," said Pritchard. "We also need to understand the evolutionary dynamics."

"If we take out the community aspect of transmission, we can study just the de novo, or 'from nothing,' generation of mutations," said Pritchard.

"We are trying to create a generalized approach to getting the numbers that we use in the models," said Pritchard. "To do this we did not 'fit' the model, but used data obtained from experiments and scaling."

Drug resistance is a critical problem when treating diseases caused by pathogens and cancers. In the study, researchers were curious to know what drives these mutations that lead to resistance.

Learn more about drug resistance:

 

 

"We are trying to create a generalized approach to getting the numbers that we use in the models," said Pritchard. "To do this we did not 'fit' the model, but used data obtained from experiments and scaling."

"We ran the model and it matched clinical data to a degree much better than I ever expected," said Pritchard. "We did this from first principles (basic assumptions)."

Findings of the study was published in Cell Reports.

"We shouldn't always focus on the strongest resistance mutation because there are other evolutionary forces that dictate what happens in the real world," said Pritchard. "Sometimes drug resistance relies on biased random events."

"The data are not quite as strong in the prostate and breast cancer setting," said Pritchard. "In non-small cell lung cancer we didn't see this effect at all."

"If we take out the community aspect of transmission, we can study just the de novo, or 'from nothing,' generation of mutations," said Pritchard.

Source: Science Daily

About the Author
  • Nouran earned her BS and MS in Biology at IUPUI and currently shares her love of science by teaching. She enjoys writing on various topics as well including science & medicine, global health, and conservation biology. She hopes through her writing she can make science more engaging and communicable to the general public.
You May Also Like
JUL 09, 2020
Technology
How Chatbots Can Help the Medical Community
JUL 09, 2020
How Chatbots Can Help the Medical Community
It is no secret that COVID-19 pandemic has touched our lives in so many ways. For health care providers, the burden has ...
AUG 13, 2020
Cardiology
Using Artificial Intelligence to Read Your ECG Results
AUG 13, 2020
Using Artificial Intelligence to Read Your ECG Results
An electrocardiogram (ECG) is a tool used to measure the heartbeat using an electrical current. By following the current ...
OCT 02, 2020
Clinical & Molecular DX
Detecting Dystonia in the Blink of an AI
OCT 02, 2020
Detecting Dystonia in the Blink of an AI
A team of scientists have created a diagnostic tool, powered by artificial intelligence (AI), that can pick up on the su ...
OCT 19, 2020
Clinical & Molecular DX
Making Capillary Electrophoresis Accessible for Any Lab
OCT 19, 2020
Making Capillary Electrophoresis Accessible for Any Lab
Analyzing nucleic acids through gel electrophoresis has been a staple of genetic research for decades. But using traditi ...
OCT 28, 2020
Cell & Molecular Biology
Mimicking Cells With a Microfluidic Chip
OCT 28, 2020
Mimicking Cells With a Microfluidic Chip
Cell culture models are one way for scientists to learn more about biology. But cells grow in large cultures that are of ...
NOV 15, 2020
Genetics & Genomics
Novel Cancer-Driving Genes are Discovered
NOV 15, 2020
Novel Cancer-Driving Genes are Discovered
Cells have to be able to divide so new ones can replenish cells that get worn out, dysfunctional, or that accumulate dam ...
Loading Comments...