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Three USF Professors Receive Excellence in Innovation Award October 14, 2016 The award is presented to faculty members for exceptional achievement in technological innovation and entrepreneurial success TAMPA, Fla. – Three USF faculty professors received the 2016 Excellence in Innovation Award for exceptional achievement in innovation and research. Norma Alcantar, Svitlana Garbuzova-Davis, and H. Lee Woodcock were presented with the award, along with a $2,000 check and a plaque of recognition, by USF Provost Ralph Wilcox and Dr. Paul R. Sanberg, senior vice president for research, innovation and economic development and president of the National Academy of Inventors (NAI). The awards were presented as part of the eighth annual meeting and luncheon of the USF Chapter of the National Academy of Inventors, held Oct. 10, 2016, in the USF Research Park on the university’s Tampa campus. “These outstanding inventors represent the commitment of our inventive faculty to translating their research into innovations and patents that benefit society and make a difference in people's lives,” said Sanberg. “USF continues to drive economic development, creating and working with our private and public partners to bring economic growth, and jobs for our graduates and citizens to Tampa Bay.”
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The COMP Division is excited to announce the OpenEye Award winners for the San Francisco ACS meeting (fall 2014). Please visit the COMP award winners and the other excellent COMP posters at the COMP Poster Session on Tuesday, August 12, 2014 from 6pm to 8pm at a location to be determined.
How the walls come crumbling down: Elucidating mechanisms of cellulose-active enzymes using molecular simulation. Gregg T Beckham, National Renewable Energy Laboratory, National Bioenergy Center, Golden, Colorado Quantum fluctuations in hydrogen bond networks: from atmospheric science to enzyme catalysis. Thomas E Markland, Department of Chemistry, Stanford University, Stanford, California Affordable multiscale free energy simulations: A novel method that efficiently connects low level sampling to QM/MM via Non-Boltzmann Bennett reweighting. Henry Lee Woodcock, University of South Florida, Department of Chemistry, Tampa, Florida Targeting membrane interfaces for computer-aided drug design and drug delivery applications. Zoe Cournia, Biomedical Research Foundation of the Academy of Athens, Pharmacology, Athens, Greece T.C. Owen Outstanding Undergraduate Research Award http://chemistry.usf.edu/annualawards/FionaKearns.aspx I have been involved in undergraduate research at the University of South Florida since my second semester in my freshman year. I have worked in a natural-products “traditional” organic wet-lab as well as most of my time has been spent in the computational lab. Under the guidance and direction of Dr. H. Lee Woodcock and graduate mentor Dr. Sai Lakshmana Vankayala, I have been involved in two prior computational projects and we are soon beginning another. Since I began in the Woodcock lab, I have learned many computational techniques including basics in bioinformatics, docking studies and binding mode analyses (with Schrodinger), MD Simulations (in CHARMM) and QM/MM (using QChem). The research I have been involved in is fascinating! In the spirit of interdisciplinary research: we have used computational techniques to solve an ecological chemistry problem posed by Dr. Bill J. Baker (natural products chemist). In another work, I have used computational methods to model the interaction of hydroxyurea and catalase to release nitric oxide. The purpose in this work is to understand how hydroxyurea functions as a treatment for sickle-cell disease. Using conclusions from this work we will propose analogs to hydroxyurea that are likely to be more efficient treatments for sickle-cell. As a junior now, I feel I have been incredibly fortunate to have such diverse opportunities for undergraduate research at USF. Furthermore, I feel so lucky that I have found a group of advisors—both faculty and graduate students—that are a dedicated support system; because of them, I have been able to experience a world of research in many fascinating and challenging areas including one of the fastest growing areas of chemistry. It is my dream to earn my Ph.D. in chemistry and continue research in computational chemistry. I hope to, in the future, use computational techniques as well as experimental techniques to understand protein folding and reaction mechanisms, or design and optimize pharmaceuticals and pesticides, or design alternative energy resources, or possibly model and understand metal organic materials for optimizing properties. Though it is hard to say now what areas of chemistry I will become entwined with in the future, I know for sure that I am headed for a career in chemistry research. Over the past eight years, I've accumulated quite the academic profile. My first five years were spent at Pennsylvania State University studying mathematics with a focus on graduate studies, and eventually added on medical physics. Although I learned a lot during my time there, I wanted to work in a field that combined all areas of my education and allowed me to work with theoretical concepts in practical applications. I decided to test the waters with some graduate physics courses, along with Physical Chemistry I at the University of South Florida in 2012. After completing the semester, I decided to pursue a B.S. degree in chemistry. I enrolled in Physical Chemistry II the following semester and met Dr. H Lee Woodcock, who sparked my interests in use of computational methods in chemistry and offered me a place in his research lab. The focus of my work is a multifaceted approach to free energy simulation using Quantum Mechanical/Molecular Mechanical (QM/MM) interface calculations which allow for the speed of Molecular methods and high level energetics of Quantum methods. My research strikes the perfect balance between theoretical considerations and practical applications. Currently I implement a novel method of combining QM/MM reweighting scheme with Bennett’s Acceptance ratio for free energy computation, the Non-Boltzmann Bennett (NBB). Dr. Woodcock, two of his colleagues at the NIH and University of Vienna, and I recently had our paper on the method and it’s efficiency officially accepted by The Journal of Chemical Theory and Computation, with publication soon to follow. Overall, work I do in methodology requires combining logical structure, managing a database of over ~500k files, bash scripting, and error handling. Software I use for the MM end is Harvard’s CHARMM Molecular Dynamics program, and Q-Chem for the QM evaluations. Data analysis is performed with Python scripts that I code personally. Chemistry is by far the perfect overlap of all the areas I’ve studied. The dualistic nature of computational research gives me the freedom to delve into tedious and abstract ideas, or apply methods to investigate systems of interest. The mathematics background I have has proven to be invaluable for approaching problems from every conceivable angle, and finding the simplest and most effective methods to solving them. I hope to secure a PhD in Computational Chemistry, and eventually work in academia to research and teach the future generations what fortran 90 is, since it will probably still be used. Overall I hope to provide ways for experimentalist to develop novel processes that are only elucidated by use of computation. I firmly believe that modern chemistry is going to take a turn where the computational will dictate the experimental, due to the cost effective and nearly limitless use of modern simulation software. |