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Matysiak Lab

Biomolecular Modeling Group


Principal Investigator

Silvina Matysiak, PhD

Associate Professor of Bioengineering
University of Maryland

Postdoctoral Fellow The University of Texas at Austin
PhD Rice University
BS Instituto Tecnologico de Buenos Aires


Photo of Silvin

Graduate Students

Abhilash Sahoo

BS/MS Indian Institute of Science Education and Research,  India


Project: Peptide aggregation

Aggregation of mis-folded proteins on cellular membranes into highly structured forms (amyloid fibrils) is observed in several neurodegenerative diseases like Alzheimer's, Parkinson's and Huntington's. However, the physicochemical forces leading to protein aggregation, specifically the protein-protein and protein-membrane interactions are yet to be fully understood. The multi-step pathway of protein polymerization into aggregates goes through several ephemeral oligomeric structures. The transient nature of these oligomeric intermediates makes experimental characterization extremely difficult. On the other hand, computational studies can provide detailed mechanistic insights about protein aggregation pathway's intermediate structures that are not accessible to wet-lab experiments. My research aims to capture the aggregation behavior of aberrant peptide sequences and it's dependence on environmental conditions through coarse grained molecular dynamics simulations.

Abhilash's photo

Hongcheng Xu

BS Nanjing Normal University, China


Project 1: Membrane peptide folding: Membrane peptide folding is an area not well explored experimentally because of the difficulties in crystallizing membrane proteins. On the other hand, computational methods have been developed to predict membrane structure fold but do not provide information about the driving forces behind membrane protein folding and how the presence of particular lipids can tune the emergence of different folding behavior. Also, membrane protein folding is inaccessible to atomistic molecular dynamics since ~μs simulations are needed to embrace a wider range of membrane processes. Up-to-date coarse-grained models have been used to study the insertion and self-assembly process of peptides with fixed secondary structure. Since the group's coarse-grained model can capture de novo folding, my research aim is to combine it with model membranes to explore the steps in membrane protein folding and how they can be tuned by changing the membrane composition.

Project 2: Hydrogels:  Hydrogels are water-filled 3D surfaces that are solid, responsive and programmable. My research aims at exploring how an hydrogel molecular structure affects its behavior. By using atomistic and coarse-grained simulations we are developing a multiscale model of chitosan to understand its self-assembly behavior.
Hongcheng's photo

Riya Samanta

BS/MS Indian Institute of Science Education and Research,  India


Project: Protein allostery
Protein allostery, also called action at distance where the signal from one site is transmitted to a second, distal site, to alter protein function is a fundamental process in biological systems. How does the information traverses between two faraway sites in a monoallosteric protein? I am currently working on BirA allostery and effects of point mutations in its activity, and applying network science concepts combined with an ensemble view of protein allostery to address this query. Improving the understanding on of the molecular mechanism of allostery, a regulatory mechanism used in very known biological processs will have impact in drug development.

Riya's photo

Undergraduate Students

Christopher Look



Dr. Anu Nagarajan        current position: Schrodinger


Dr. Sai Ganesan             current position: UCSF

Dr. Gregory Custer        current position: Air Force



Mattew Eckler                 current position: IBM

David Peeler                    current position: University of Washington

Michael McCutchen       current position: W.L. Gore

Sudi Jawahery                current position: University of California, Berkeley

Anastasiya Belyaeva     current position: MIT