The Crystallography and Computational Biosciences (CCB) Shared Resource serves as a portal for access to:
- Expertise, consultation and state-of-the-art instrumentation for X-ray crystallography and structure modeling and refinement; and
- Computational resources and expertise to handle the development of structural and force field models, deployment of quantum mechanical calculations, virtual screening of compound libraries, and molecular dynamics studies. Among other computational resources, CCBSR has access to supercomputing capabilities of the Wake Forest DEAC cluster. A key feature of CCBSR is expertise in virtual screening for small molecules, which complements recent high-throughput screening partnerships between SRs at WFBCCC and other academic centers in North Carolina.
The CCB meets the growing needs for structure determination and computational analysis of protein and DNA/RNA structure, function and dynamics for a diverse array of projects ranging from basic science questions to drug design.
The Crystallography and Computational Biosciences Core supports areas of basic science research with an emphasis on biological processes related to cancer such as:
- Cell signaling
- Transcriptional regulation
- DNA damage and repair
- Lipid metabolism
Basic science research to understand the normal and pathophysiological function of proteins and their interactions with a myriad of biological partners and functional modifiers (e.g., other proteins, DNA, RNA, cofactors, drugs, post-translational modifications, mutations) is the foundation on which to build all progress towards these objectives. We provide access to cutting-edge modeling and simulation methods. The information from these complementary approaches can be used to develop novel therapies.
The CCB also provides support for ongoing projects and the development of new projects through the collection of preliminary data for funding applications.
Below is a workflow overview in the CCBSR: progression from project prioritization and initial development to advanced development and translation.
1. Wu D, Salsbury FR, Jr. Simulations suggest double sodium binding induces unexpected conformational changes in thrombin. J Mol Model 2022;28:120
2. Hemphill WO, Simpson SR, Liu M, Salsbury FR, Jr., Hollis T, Grayson JM, et al. TREX1 as a Novel Immunotherapeutic Target. Front Immunol 2021;12:660184
3. Xiao J, Salsbury FR. Na(+)-binding modes involved in thrombin's allosteric response as revealed by molecular dynamics simulations, correlation networks and Markov modeling. Phys Chem Chem Phys 2019;21:4320-30
4. Xiao J, Melvin RL, Salsbury FR, Jr. Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning. J Biomol Struct Dyn 2019;37:982-99
5. Loberg MA, Hurtig JE, Graff AH, Allan KM, Buchan JA, Spencer MK, et al. Aromatic Residues at the Dimer-Dimer Interface in the Peroxiredoxin Tsa1 Facilitate Decamer Formation and Biological Function. Chem Res Toxicol 2019;32:474-83
6. Forshaw TE, Holmila R, Nelson KJ, Lewis JE, Kemp ML, Tsang AW, et al. Peroxiredoxins in Cancer and Response to Radiation Therapies. Antioxidants (Basel) 2019;8
7. Rogers LC, Davis RR, Said N, Hollis T, Daniel LW. Blocking LPA-dependent signaling increases ovarian cancer cell death in response to chemotherapy. Redox Biol 2018;15:380-6
8. Melvin RL, Xiao J, Godwin RC, Berenhaut KS, Salsbury FR, Jr. Visualizing correlated motion with HDBSCAN clustering. Protein Sci 2018;27:62-75
9. Melvin RL, Xiao J, Berenhaut KS, Godwin RC, Salsbury FR. Using correlated motions to determine sufficient sampling times for molecular dynamics. Phys Rev E 2018;98:023307
10. Mauney CH, Perrino FW, Hollis T. Identification of Inhibitors of the dNTP Triphosphohydrolase SAMHD1 Using a Novel and Direct High-Throughput Assay. Biochemistry 2018;57:6624-36
11. Mauney CH, Hollis T. SAMHD1: Recurring roles in cell cycle, viral restriction, cancer, and innate immunity. Autoimmunity 2018;51:96-110
12. Guragain M, Jennings-Gee J, Cattelan N, Finger M, Conover MS, Hollis T, et al. The Transcriptional Regulator BpsR Controls the Growth of Bordetella bronchiseptica by Repressing Genes Involved in Nicotinic Acid Degradation. J Bacteriol 2018;200
13. Godwin RC, Macnamara LM, Alexander RW, Salsbury FR, Jr. Structure and Dynamics of tRNA(Met) Containing Core Substitutions. ACS Omega 2018;3:10668-78
14. Bolduc JA, Nelson KJ, Haynes AC, Lee J, Reisz JA, Graff AH, et al. Novel hyperoxidation resistance motifs in 2-Cys peroxiredoxins. J Biol Chem 2018;293:11901-12
15. Akter S, Fu L, Jung Y, Conte ML, Lawson JR, Lowther WT, et al. Chemical proteomics reveals new targets of cysteine sulfinic acid reductase. Nat Chem Biol 2018;14:995-1004