This proposal seeks funding for an NRSA Institutional Predoctoral Training Grant from the Molecular Biophysics Program of the National Institute for General Medical Sciences (NIGMS). This grant will support predoctoral training in Structural and Computational Biophysics (SCB) leading to a Ph.D. degree at Wake Forest University. The goal of the SCB Training Program is to bridge the gap in training between biomedical sciences and more basic quantitative sciences. The SCB training faculty is highly collaborative across departmental lines, and includes faculty members from Physics, Chemistry, Biochemistry, and Molecular Medicine. Students are trained in structural biology (X-ray and NMR), computational biology, proteomics, and biophysics. The major scientific themes of the SCB Training Program include the overlapping areas of DNA damage and repair, redox biology, and molecular signaling. The Program has a flexible curriculum that is designed to meet the individual needs of the students in the program, and includes a well-developed system of interdisciplinary seminars and tutorials to promote interaction among members of the program. In addition to the SCB training faculty, who will serve as mentors for Ph.D. students, we also have a well-established network of resource faculty that contribute to the training of graduate students through educational innovation, direction of Core Laboratories that are central to training in structural biology and biophysics, and provision of career advice and networking with biotechnology industries. We offer specific training in skills for a wide variety of potential careers for our Ph.D. graduates, including academic careers, careers in the biotechnology and pharmaceutical industries, as well as careers in the intellectual property arena. We have developed a pipeline in which Masters'degree students in Physics, Mathematics and Computer Science can obtain a certificate in Structural and Computational Biophysics that provides a transition into Ph.D. training in our program. Similarly, we have an excellent track record of engaging Ph.D. students in biological sciences in structural and computational research. We have an active program of recruiting students from ethnic groups that are underrepresented in science into our training program. Funding is requested for 4 predoctoral positions out of the steady state level of 25-30 students in the laboratories of the training faculty. These positions will be used to support students in the second year or beyond, at which time it will be apparent that their dissertation research is consistent with the goals of the Program. Support will be for a maximum of two years, after which the students will be supported by the research funding of their advisors or their own individual fellowships.
The Coalition for Bridging the Sciences, a group composed of representatives from 13 different scientific societies has identified the interface between the biomedical sciences and more quantitative basic sciences, such as mathematics, physics, and chemistry, as a major gap that represents substantial missed opportunities in our national research effort. The goal of the Structural and Computational Biophysics Training Program at Wake Forest University is to bridge this gap by bringing together faculty from the Departments of Physics, Chemistry, Biochemistry, and Medicine into an interdisciplinary program to train Ph.D. students. These students will go on to careers in academia, the biotechnology and pharmaceutical industries, and the intellectual property arena in which their interdisciplinary training can serve to fill this important national need.
| Godwin, Ryan C; Macnamara, Lindsay M; Alexander, Rebecca W et al. (2018) Structure and Dynamics of tRNAMet Containing Core Substitutions. ACS Omega 3:10668-10678 |
| Godwin, Ryan C; Gmeiner, William H; Salsbury Jr, Freddie R (2018) All-atom molecular dynamics comparison of disease-associated zinc fingers. J Biomol Struct Dyn 36:2581-2594 |
| Melvin, Ryan L; Xiao, Jiajie; Berenhaut, Kenneth S et al. (2018) Using correlated motions to determine sufficient sampling times for molecular dynamics. Phys Rev E 98:023307 |
| Xiao, Jiajie; Melvin, Ryan L; Salsbury Jr, Freddie R (2018) Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning. J Biomol Struct Dyn :1-18 |
| Melvin, Ryan L; Xiao, Jiajie; Godwin, Ryan C et al. (2018) Visualizing correlated motion with HDBSCAN clustering. Protein Sci 27:62-75 |
| Mauney, Christopher H; Perrino, Fred W; Hollis, Thomas (2018) Identification of Inhibitors of the dNTP Triphosphohydrolase SAMHD1 Using a Novel and Direct High-Throughput Assay. Biochemistry 57:6624-6636 |
| Berenhaut, Kenneth S; Barr, Peter S; Kogel, Alyssa M et al. (2018) Cluster-based network proximities for arbitrary nodal subsets. Sci Rep 8:14371 |
| Mauney, Christopher H; Hollis, Thomas (2018) SAMHD1: Recurring roles in cell cycle, viral restriction, cancer, and innate immunity. Autoimmunity 51:96-110 |
| Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C et al. (2017) An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins. PLoS Comput Biol 13:e1005284 |
| Melvin, Ryan L; Gmeiner, William H; Salsbury Jr, Freddie R (2017) All-Atom MD Predicts Magnesium-Induced Hairpin in Chemically Perturbed RNA Analog of F10 Therapeutic. J Phys Chem B 121:7803-7812 |
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