Computational biophysics · AI · Experiments
Uncovering the molecular features driving neurodegenerative diseases
We combine AI and physics-based modeling, molecular simulations, and biophysical/biochemical experiments to uncover the molecular mechanisms, transition states, and critical seed structures that drive neurodegenerative protein aggregation.
Research directions
From molecular mechanism to molecular design.
Our work connects physics-based simulation with modern AI methods and targeted experiments.
Tau, Amyloid-β & α-Synuclein
Molecular mechanisms of nucleation, oligomerization, fibril formation, and disease-associated structural polymorphism.
Explore →02Molecular Dynamics
Atomistic MD, enhanced sampling, free-energy methods, and conformational ensemble analysis.
Explore →03AI Protein & Ligand Design
AI-guided design of proteins and peptides that recognize or modulate disease-relevant molecular states.
Explore →04Experimental Validation
Biochemical and biophysical assays to test computational predictions and designed molecules.
Explore →Our approach
Physics + artificial intelligence + experiment
Protein aggregation is a multiscale problem. We study it by combining detailed molecular models with computational design and experiments.
Our goal is not only to describe aggregate structures, but to identify the transient molecular states and interactions that initiate disease-relevant assembly.
Read about our research →Opportunities
Interested in joining the Sari Lab?
We welcome inquiries from postdoctoral researchers, graduate students, undergraduates, and collaborators interested in computational and experimental biophysics.
View opportunities