“Looking into the Soft Matter Landscape Through Computational Microscope”
The Center for Theoretical Biological Physics presents Seminar Speaker:
Research Staff Scientist and Technical Lead
Data Science and Cognitive Computing Department
IBM Thomas J. Watson Research Center
“Looking into the Soft Matter Landscape Through
Tuesday, October 17, 2017
12:30 – 1:30 PM
BRC, 10th Floor, Room 1060 A/B
Multi-scale molecular modeling techniques are becoming indispensable tools for designing and characterizing soft matter systems, such as proteins, nucleic acids, polymers, and surfactants. In this talk, I will first discuss molecular simulations at different resolution, which explain critical role of nanoscale hydration in determining the structure, assembly, and function of proteins and polymers. Our results reveal how the interplay between different molecular factors defines the wetting state, which, in turn, dictates the stability of a biological protein structure.
I will next explain a recently developed coarse-grained model of a solvated polymer system, with the goal of exploring the effect of hydrophobicity on the (P, T) landscape of a protein as well as of a surfactant. We show emergence of alternatively interaction pattern at non-physiological conditions, as the hydrophobicity starts to weaken.
In the remaining part of the talk, I will discuss a combined simulation-experimental approach toward optimized DNA biosensor design. While studying DNA hybridization on surface, our approach reveals presence of conformational heterogeneities corresponding to partially hybridized structures on the surface, which results in false positives and false negatives during sequence detection. We propose a solution of this problem by customizing the sensor surface area according to the molecular dimension, which will increase the diagnostic accuracy of hybridization-based DNA sequence detection methods. In summary, the results discussed in this talk will demonstrate the usefulness and efficiency of molecular simulation techniques in understanding the complex structure-function relationship of soft materials.
Dr. Payel Das is a Research Staff Member in the AI, Blockcain, and Quantum Solutions Department at the IBM Thomas J Watson Research Center. Her research focuses on the development of physics-based modeling and machine learning techniques for understanding complex systems, with applications in chemistry, biology, and neuroscience. Das received her PhD degree from Rice University in 2007 and then did a post-doctoral fellowship at the Computational Biology Center, IBM T J Watson Research Center.
She has co-authored over 30 peer-reviewed publications and several patent disclosures, given dozens of invited talks at several university colloquiums, department seminars, top rated conferences, and workshops. She has been selected as the editorial advisory board member of the ACS Central Science journal. Das is the recipient of IBM Outstanding Technical Achievement Award, two IBM Research Division Awards, one IBM Eminence and Excellence Award, and one IBM Invention Achievement Award.
An Official Seminar of the Ph.D. Program in Systems, Synthetic and Physical Biology at Rice University
For more information, visit: https://events.rice.edu/#!view/event/event_id/1028
BioScience Research Collaborative (BRC), 10th Floor, Room 1060 A/B
6500 Main St, Houston, TX 77030