Statistical Thermodynamics & Molecular Simulations (STMS) Seminar Series: Prof. Jian Qin (Stanford), Mr. Jonathan Zajac (Minnesota)
These seminar series are aimed at providing a virtual platform for sharing scientific research in the area of statistical mechanics, molecular simulations, and computational materials science. Since early 2020, the coronavirus pandemic has disrupted many large in-person scientific gatherings, including conferences and department seminars. STMS is aimed at filling this gap, and provide a venue for dissemination of research findings and exchange of ideas in the age of COVID. This model is being currently used by several other scientific communities, and can potentially continue even beyond the pandemic if successful.
Each seminar will be a 60-minute event and will comprise of a long-form (30-minute) talk by a principal investigator or a senior research scientists from academia or industry and a short-form (15-minute) presentation by a graduate student or a postdoc. The remainder of the event will be dedicated to Q&A (10 minutes for the PI, 5 minutes for the student/postdoc). Long-form speakers will be chosen by the STMS Organizing Committee, while we encourage suggestions from the community at large. Student and postdoctoral speakers can either be nominated by their advisors or can self-nominate themselves by sending a CV to the organizers. During 2022 we expect to hold two seminar per month, and the events will take place in the last two Fridays of each month, from 10:45 AM-12:00 PM Eastern Standard Time (EST):
This event's talks:
Crossover between mean-field and critical scalings near the gel point
Prof. Jian Qin (Stanford University)
Abstract: Gelation of linear precursor chains via random crosslinking is accompanied by the formation of finite clusters. The number and size distributions of the clusters have been predicted by the Flory-Stockmayer mean-field theory, which neglects the formation of loops. The theory breaks down in the close vicinity of the gel point, and its predictions are replaced with a set of critical scaling exponents. We explore the crossover between the mean-field and critical scaling by conducting coarse grained simulations for a mixture of reversibly crosslinked precursors and clusters. Molecular weights, backbone stiffness, and monomer bulkiness of the precursors are tuned systematically. The simulated radii of gyration of clusters exhibits distinct behaviors, which collapse onto a master curve upon normalization by an emergent length scale, thermal blob. The thermal blob measures the magnitude of the excluded volume interaction, which mainly depends on the extent of inter-chain overlap. The master curve reveals a surprisingly gradual crossover between the mean-field and critical regimes and indicates that majority of the crosslinked systems of experimental interests fall within the critical regime.
Speaker Bio: Jian Qin is an Associate Professor in the Department of Chemical Engineering at Stanford University. He received B.S. and M.S. degrees in Materials Science from Tsinghua University, and his Ph.D. from University of Minnesota under the supervision of Profs. David Morse and Frank Bates. Following postdoctoral fellowships at Pennsylvania State University, with Prof. Scott Milner, and The University of Chicago, with Prof. Juan de Pablo, he joined Stanford University as a Terman Faculty Fellow in 2016. His research focuses on theoretical study of morphological and rheological behavior of polymeric fluids, electrostatic interactions in structured electrolytes, and surface charge polarization. He has held the Kadanoff-Rice Fellowship and has been recognized by the 3M Non-Tenured Faculty Award, the Hellman Faculty Award, the NSF CAREER Award, the ACS PMSE Arthur Doolittle Award, the ACS PMSE Young Investigator Award, the Tau Beta Pi (Stanford) Teaching Honor Roll, and the APS Dillon Medal.
Protein-solvent shape complementarity as a unifying feature of excipient-driven protein stability
Mr. Jonathan Zajac (University of Minnesota)
Abstract: Proteins are marginally stable macromolecules prone to denaturation when exposed to environmental stressors. This susceptibility burdens the development, storage, and transportation of most biological therapeutics. Biological formulations are thus generally accompanied with excipients – such as amino acids and sugars – that stabilize the native state of proteins. While empirically excipient effects are known, the molecular features that drive stability remain unclear. To establish a molecular picture of excipient mechanisms, we have utilized molecular dynamics simulations to explore the effects of a diverse range of excipient solutions on miniprotein folding/unfolding equilibria. We observe that the choice of excipient has profound impacts on the shape complementarity between solvent and protein interaction networks, which in turn alters miniprotein temperature stability. These results bring into focus key molecular motifs that act as determinants of stability and provide insights towards protein folding manipulation via small molecule additives. Such findings have significant implications in biologics development, including vaccines, gene therapy products, and therapeutic proteins.
Speaker Bio: Jonathan is a 4th year Ph.D. candidate at the University of Minnesota, Department of Chemistry, and works with Professor Sapna Sarupria. He graduated from the University of Wisconsin – Eau Claire in 2020, where he worked with Dr. Sudeep Bhattacharyya on QM/MM simulations of oxidoreductases, as well as with Dr. David Jewett in the field of behavioral pharmacology. Currently, his thesis work is focused on using molecular simulations to elucidate mechanisms of additive-mediated stabilization towards the design of temperature-stable vaccines.