In the News
Rui Huang Awarded Marvin D. Rausch Fellowship
Rui Huang (Rotello lab) research: Bioorthogonal catalysis offers a unique strategy to modulate biological processes through the in situ generation of therapeutic agents. However, the direct application of bioorthogonal transition metal catalysts (TMCs) in complex media poses numerous challenges due to issues of limited biocompatibility, poor water solubility, and catalyst deactivation in biological environments. In the Rotello lab, these issues can be addressed by integrating TMCs into polymers to generate bioorthogonal “polyzymes”. Polyzymes are able to activate imaging and therapeutic agents from their inactive precursors, creating on-demand “drug factories''. Through the engineering of host polymer structures, I have synthesized a series of polyzymes that are biodegradable, biostable, and/or stimuli responsive. The therapeutic potential of polyzymes has been demonstrated in vitro for the treatment of both bacterial biofilms and cancers, with enhanced efficacy and reduced side effects.
Ahsan Ausaf Ali Receives Paul Hatheway Terry Scholarship
Ahsan Ausaf Ali (You Group) received the Paul Hatheway Terry Scholarship in recognition of excellence in research. Research: The cell membrane is a very important component of cells which plays a critical role in cell signaling and cell-cell communication. Since the cell membrane is fluidic in nature, molecules in it such as lipids and proteins are generally free to associate and dissociate resulting in short lived dynamic interactions. Such short-lived interactions are important because they allow the membrane to modulate the formation signaling platforms in response to specific stimuli. Unfortunately, visualizing these transient interactions has proved to be challenging due to their fast nature and the complex heterogenous composition of membranes. In my research, we use short DNA tags to label certain lipids on the cell membrane which allows us to stabilize these short-lived interactions for long enough so that they may be imaged and quantified. This was achieved by developing a “DNA Zipper” probe where DNA hybridization between different lipid-DNA conjugates may “zip” two transiently interacting probes together to various degrees depending on the DNA sequence chosen. From our experiments we were able to visualize various lipid-lipid interactions and observe their relative strength. We further used our DNA Zipper probe to investigate and visualize the heterogeneity of the cell membrane and its role in several important biological processes including immune cell activation and the progression of cancer. Our current goal is to apply our DNA Zipper to membrane proteins as an approach to quantify transient protein interactions and screen various small molecules which may impact these interactions.
AI Ranks Synthesizability of Materials Showing Promise for Carbon Capture
The journal Digital Discovery published a study from an international research team including UMass Amherst chemistry professor Scott Auerbach that applied artificial intelligence (AI) to a long-standing problem in materials science – identifying structures within massive computer-generated databases that are good candidates for actual fabrication. Auerbach and coworkers focused their study on hypothetical zeolites, which show promise for capturing carbon dioxide emissions.
Zeolites are nanoporous crystals that have been utilized for more than 6 decades in a number of industrial processes, particularly in refining petroleum and separating chemical mixtures. While much effort has been put into identifying and synthesizing new zeolites for modern needs such as producing clean biofuels and capturing carbon dioxide, success has been largely theoretical. While massive databases of hypothetical zeolites have been generated containing millions of new framework structures, none has been made in the lab.
“This problem, which is known as the ‘zeolite conundrum,’ has severely limited the pace of the clean energy transition,” said Auerbach. “Finding the few hypothetical zeolites that can actually be synthesized in the lab is like finding a needle in a gigantic haystack.”
Auerbach and coworkers – Michele Ceriotti and Benjamin Helfrecht at the Swiss Federal Institute of Technology (EPFL) in Lausanne, and Rocio Semino and Giovanni Pireddu at the Sorbonne University in Paris – developed an algorithm called the “sorting hat” that uses artificial intelligence and machine learning to distinguish between the 255 already-synthesized zeolites and more than 300,000 hypothetical framework structures. They created a short list of hypothetical zeolites that are so similar to real ones that they are “misclassified” by the sorting hat as real materials – making them good candidates for actual synthesis.
“Ours is the first study to apply AI to the zeolite conundrum, “ said Auerbach. “All the previous studies are biased by preconceived ideas about what makes real zeolites real – we wanted to move away from such bias.”
After filtering their results by additional criteria, including the potential for stabilizing them during synthesis, the researchers proposed three leading hypothetical candidates for synthesis. Their analysis also categorized real zeolites into four compositional classes or “houses.” This partitioning into houses allowed the researchers to propose chemical compositions to pursue in the laboratory for making the hypothetical zeolites – like recipes for synthesis.
“As is the case for many synthetic tasks, making zeolites is a form of art, guided by experience, chemical intuition and serendipity,” the researchers said. “The zeolite sorting hat introduces data-driven techniques and rational design into the process of selecting candidates that we hope will accelerate the rate of discovery that will in turn, will improve the predictive capabilities of the model in a positive feedback mechanism that will progressively take the guesswork out of zeolite synthesis.”
Faculty Search - Assistant Professor in Chemistry - DNA/RNA/Biologics
Kittilstved Selected as UMass ADVANCE Faculty Fellow
The University of Massachusetts Amherst believes that a culturally diverse campus is integral to academic excellence and that our students, faculty, and staff should reflect the diverse world in which we live. Recognizing and valuing the wide range of voices and perspectives in all spheres of the academic enterprise, we are committed to policies that promote inclusiveness, social justice, and respect for all.
“Fostering an environment that protects intellectual exploration, advances mutual respect, and promotes inclusivity is critical to the mission of the university.” — Chancellor Kumble R. Subbaswamy
The UMass Office of Diversity Equity and Inclusion supports these efforts with resources, events, campus climate initiatives, podcasts, and more.
Building Bridges is a campus initiative that seeks to draw on the power of solidarity and creative expression to bring people together across race, religion, class, immigration status, gender, sexual orientation, age, ability, nationality and more.
Rotello Receives the Arthur C. Cope Scholar Award
An interdisciplinary team of UMass Amherst researchers had their recently published article chosen as a “hot” article in the journal Physical Chemistry Chemical Physics. The team, led by chemistry professor Scott Auerbach and chemical engineering professor Wei Fan, reported breakthrough computer simulations confirmed by experiments showing faster crystallization of nanoporous catalysts known as zeolites.
“Understanding how to make zeolites, and how to make them faster, is incredibly important. Zeolites are the most used synthetic catalysts on planet earth, and they show great potential for making green fuels and capturing carbon dioxide – both critical for battling climate change,” said Dr. Auerbach.
The team also includes lead author Dr. Cecilia Bores, a former postdoctoral fellow at UMass Amherst and now a physics professor at Union College, as well as chemical engineering PhD student Song Luo and undergraduate researchers J. David Lonergan, Eden Richardson, and Alexander Engstrom.
“Simulating zeolite crystallization is one of the grand challenges in materials science because the process can take days to weeks, so our simulations have to efficiently model very slow assembly processes,” said Dr. Bores. She continued, “The key to our work is capturing only the essential aspects of zeolite bonding and intentionally omitting some interactions between particles that would only slow down the simulation.”
Also critical to the work are experimental tests confirming that the simulation predictions are correct. Such experiments, carried out by Fan and Luo, involve using additives called “structure directing agents” to help steer the crystallization. Fan and Luo confirmed the prediction that using multiple structure directing agents that match the different nanopore sizes within a zeolite can speed up crystallization, by as much as a factor of three.
“Learning how faster zeolite crystallization occurs by using several structure directing agents is a real breakthrough for my lab,” said Dr. Fan. “We spend countless hours trying to fabricate new zeolites, so being able to speed up the process can lead to much faster discovery of new and useful materials.”
The team plans to continue the research, which is funded by the Department of Energy’s program in Synthesis and Processing Science, by applying artificial intelligence to analyze the simulated crystallization trajectories to identify key steps that lead to crystals, and by testing those predictions using advanced experimental methods such as Raman spectroscopy.
“Being able to combine computer simulations with experiments so seamlessly is critical to this research,” said Dr. Auerbach. “Our collaboration with Wei Fan and his team has been fantastic. As we like to say: ‘Without Wei, there’s no way!’”