The Periodic Tabloid

Professor Giselle Reye’s team at Pfizer has been named the 2023 recipient of a 2023 American Chemical Society Award. Recipients will be honored at the awards ceremony on Tuesday, March 28, 2023, in conjunction with the ACS Spring 2023 meeting in Indianapolis. 

ACS Award for Team Innovation, sponsored by ACS Corporation Associates, Sean O. Bowser, Adam R. Brown, Nga Do, Shane Eisenbeis, Aran K. Hubbell, Ruizhi “Richard” Li, Matthew M. Marchewka, Ryan S. O’Neill, Giselle P. Reyes, Frank Riley, Philipp Roosen, John F. Sagal, Omar A. Salman, Karen Sutherland, Qi “Tony” Yan, Ming Zeng, Pfizer

Please join us in congratulating Professor Reyes on this momentous achievement!

https://cen.acs.org/people/awards/ACS-2023-National-Award-winners/100/i32

It is our pleasure to announce that, in recognition of his career achievements, Dr. Michael Calter has been appointed to the endowed Beach Professorship of Chemistry, established in 1880.

Please join us in congratulating Dr. Calter!

Michael A. Calter received his BS from University of Vermont and his PhD from Harvard University. His work is in synthetic organic chemistry, for which he has received numerous grants from the National Institutes of Health (NIH). His research has been published in the top organic chemistry journals, and he serves as referee, reviewer, and panel member for several journals and funding agencies including Journal of the American Chemical Society and Journal of Organic Chemistry. He has consistently achieved teaching excellence in the sophomore-level organic chemistry sequence and he received the 2015 Binswanger Prize for Excellence in Teaching.

“Electrochemistry as a Design Tool for Colloidal Syntheses of Polyhedral Metal Nanoparticles”

The funded work will use real-time electrochemical measurements to probe the growth of noble metal nanoparticles and to provide enhanced chemical understanding of how to predictively and controllably produce metal nanoparticles with well-defined shapes. The ability to tune the function of noble metal nanoparticles by tailoring not only their composition but also their shape makes them especially promising for applications in catalysis, particularly for improving the sustainable usage of energy resources and enabling the generation of sustainable fuels. However, the chemical environment under which these materials are made is complex and involves multiple competing parameters. As a result, it can be challenging to understand precisely how these materials form and, consequently, how to design methods for producing the new materials required for various applications. Electrochemistry provides a powerful means by which to address this challenge, and involves the measurement of current and voltage to understand chemical reactions, as well as the application of a current or voltage to drive chemical processes. An electrochemical approach that integrates both of these methods will be used to gain understanding of the chemical reactions involved in metal nanoparticle growth while they are happening and with a level of detail and insight that is not possible using existing methods. This research will establish core chemical principles to inform the deliberate, predictive design of new metal nanomaterials to meet the increasingly complex needs of emerging applications. Graduate, undergraduate, and high school students who are involved in this research will be prepared for future careers at the interface of chemistry, materials science, and chemical engineering. The project will also contribute to enhancing participation in science and research by developing publicly available resources to increase the accessibility of undergraduate science for students who are the first in their family to pursue this course of study.

“Protein Structure Refinement with Ensemble-Based Scoring of Experimental Restraints”

Experimental data has been critical for protein structure determination with the Rosetta biomolecular modeling software. However, a key limitation in the way Rosetta handles that data is that a single structure must satisfy all data simultaneously. This in stark contrast to the physical reality that experimental data is derived from an ensemble of different protein conformations. The single structure approximation can therefore introduce artifacts and inaccuracies in the resulting protein structure models. The proposed work will develop computer code in Rosetta that enables scoring and optimization of multiple conformations simultaneously with experimental restraints or other score terms that are based on the entire ensemble and not a single structure alone.

We expect this will enable Rosetta to extract dynamics information from experimental data sources that explicitly capture structural heterogeneity. Such techniques include nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), X-ray crystallography, electron microscopy (EM), X-ray scattering (SAXS), cross-linking mass spectroscopy (XLMS), etc. The accuracy of several of those techniques is limited by the lack of explicit atomic modeling of the ensemble of states the chemical labels or cross linkers can take, which could also be addressed with the proposed ensemble scoring methodology.