Matysiak, Silvina

Silvina Matysiak
Assistant Professor
2212 Jeong H. Kim Engineering Building
Research Interests: 
  • Protein folding, misfolding and aggregation
  • Allosteric regulation of proteins
  • Biological transport
  • Biomolecular recognition
  • Role of water in biology
  • Multiscale simulation methods
  • Ph.D., Rice University, 2007

Current Research

Proteins are the nanomachines of biology. They possess a well-defined functional native conformation that is stable within a limited range of temperatures, pressures, and solvent conditions. This well-defined native structure is determined entirely by the protein's amino acid sequence, but a detailed understanding of how sequence determines structure remains elusive. Furthermore, several diseases including Alzheimer's and Parkinson's are associated with the formation of amyloid fibrils by self-assembly of misfolded proteins. Proteins are not static structures; in order to function, they have to move within their energy landscape, so a detailed characterization of the folding landscape is critical and would aid in the design of new proteins for a variety of applications, including pharmaceuticals, enzyme catalysis and biomaterials.

Free energy landscape of mutated protein S6 exhibiting the competition between protein folding and misfoldingFree energy landscape of mutated protein S6 exhibiting the competition between protein folding and misfolding.

The study of biomolecular dynamics poses outstanding challenges both for theory and experiment. From the bio-chemical perspective, proteins, DNA, and RNA are giant molecules, comprised of thousands of atoms, and interacting with thousands of water molecules. Solvation/ desolvation strongly affect biomolecular folding transitions and almost all binding and docking events in biomolecular systems. Characteristic time-scales in protein systems span 16 orders of magnitude, from vibrations to highly cooperative structural transitions. Linking these vastly different time and length scales is a grand challenge in computational bioengineering. Our research activity is centered on the application of statistical mechanics techniques, molecular modeling and simulation to the study of biomolecular dynamics, folding, assembly and function.

Because of the multiple time and length scales intrinsically coexisting in biomolecular systems, in the past few decades the field has evolved through parallel lines, focusing at different resolutions. No single technique can at present span the whole range of typical time and length scales relevant for a protein's biochemical function. In order to significantly advance our understanding of the fundamental principles shaping protein mechanisms we are developing new coarse-grained and multi-resolution models and techniques that can overcome the computational impasse. Our line of research has the potential to build computational models to assist molecular design for a variety of applications ranging from drug design to the engineering of novel functional materials.

Fischell Department of Bioengineering
University of Maryland, College Park