Sefika Ozkan
Arizona State University Campus Immersion, AZ·Biophysics
DNA sequencing reveals huge numbers of mutations in human genes and viruses. A key problem is telling which ones matter.
- Fields
Biophysics
Biochemistry
Computer Science
- Topics
protein dynamics
molecular dynamics simulations
missense mutations
- Grants
- 1 known grant, through Aug 2027
What they work on
- Develop models that predict how much binding affinity changes when amino acids far from a protein's binding site are substituted, using molecular dynamics and force perturbation on the E. coli lactose repressor (LacI).
- Predict which pairs of distant, non-contacting substitutions have non-additive (epistatic) effects on binding, and test predictions experimentally with collaborators.
- Identify which long-distance positions control ligand specificity, and test the generality of the approach in PurR, the cAMP receptor protein and SARS-CoV-2 main protease (Mpro).
More about the research
Predictions are especially poor for missense mutations, which swap one amino acid in a protein, when the change sits far from the site where the protein binds its partner. Such distant changes can still alter function, and failing to predict them also limits protein design. This project builds computer models that predict how these long-range substitutions change protein binding.
Why it matters
Knowing which protein mutations change function matters for personalized medicine, protein engineering and tracking how viruses evolve. Better computational tools for predicting the effects of mutations far from binding sites could help researchers separate disease-relevant variants from harmless ones. They could also help engineers design proteins and help scientists anticipate changes in viral proteins such as the SARS-CoV-2 protease.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Ao Ma
University of Illinois Chicago, IL·Biophysics
Compute true reaction coordinates for ligand binding using energy flow theory and the generalized work functional method, then simulate natural, unbiased binding in HIV-1 protease and PDZ domains.
Ronald Levy
Temple University, PA·Biophysics
Determine the physical basis of epistasis, where one mutation's effect depends on others, in HIV integrase and capsid under different drugs, using molecular dynamics simulations and virus data to build drug-specific fitness landscapes.
Wen Zhu
Florida State University, FL·Biochemistry
Test whether mutations far from the active site impair asparagine synthetase (ASNS) by altering its protein motions, comparing normal enzyme with two variants linked to asparagine synthetase deficiency.
The school
Arizona State University Campus Immersion: 36 labs on PI Pages, $1.0B a year on research, 625 research doctorates a year.
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