Research Interests - Macromolecular Structure, Function & Dynamics
Long-term research goals of the Dobbs group are to understand how proteins and nucleic acids achieve their functional three-dimensional structures and to elucidate mechanisms that determine recognition and regulate interactions among proteins, nucleic acids and other molecules in cells. We have used both computational and wet-lab experimental approaches to explore the structure and function of important macromolecular complexes, in close collaboration with several groups at ISU, Pennsyvania State University, University of Minnesota, the Mayo Clinic, and Harvard University.
Current areas of focus include: providing computational resources to improve efficacy of CRISPR-Cas9 and other designer nucleases for precision genome modification; predicting RNA-protein interactions and interaction networks; predicting and validating of structural and functional effects of mutations and SNPs in both proteins in ncRNAs; comparative genomics.
Recent Representative Publications
- Identification of a homogenous structural basis for oligomerization by retroviral Rev-like proteins. Umunnakwe CN, Dorman KS, Dobbs D, Carpenter S. Retrovirology. 2017; 14(1):40.
- Template-based protein-protein docking exploiting pairwise interfacial residue restraints. Xue LC, Rodrigues JPGLM, Dobbs D, Honavar V, Bonvin AMJJ. Briefings in Bioinformatics. 2017; 18(3):458-466.
- Sequence-Based Prediction of RNA-Binding Residues in Proteins. Walia RR, El-Manzalawy Y, Honavar VG, Dobbs D. Methods in Molecular Biology 2017; 1484:205-235.
- In Silico Prediction of Linear B-Cell Epitopes on Proteins. El-Manzalawy Y, Dobbs D, Honavar VG. Methods in Molecular Biology 2017; 1484:255-264.
- Computational Prediction of RNA-Protein Interactions. Mann CM, Muppirala UK, Dobbs D. Methods in Molecular Biology 2017; 1543:169-185.
- A Plasmodium-like virulence effector of the soybean cyst nematode suppresses plant innate immunity. Noon JB, Qi M, Sill DN, Muppirala U, Eves-van den Akker S, Maier TR, Dobbs D, Mitchum MG, Hewezi T, Baum TJ. The New Phytologist. 2016; 212(2):444-60.
- A motif-based method for predicting interfacial rsidues in both the RNA and protein components of protein-RNA complexes. Muppirala U, Lewis BA, Mann CM, Dobbs D. Pacific Symposium on Biocomputing. 2016; 21:445-455.
- Xue LC, Rodrigues JP, Dobbs D, Honavar V, Bonvin AM (2016) Template-based protein-protein docking exploiting pairwise interfacial residue restraints. Brief Bioinform. 2016 Mar 24. pii: bbw027. [Epub ahead of print]
- Dobbs D, Brenner SE, Honavar VG, Jernigan RL, Laederach A, Morris, Q (2016) Regulatory RNA. Pac Symp Biocomput. 21:429-32.
- Xue LC, Dobbs D, Bonvin AM, Honavar V (2015) Computational prediction of protein interfaces: A review of data driven methods. FEBS Lett. Nov 30;589(23):3516-26.
- Umunnakwe CN, Loyd H, Cornick K, Chavez JR, Dobbs D, Carpenter S (2014) Computational modeling suggests dimerization of equine infectious anemia virus Rev is required for RNA binding. Retrovirology Dec 23;11:115.
- Andorf CM, Kopylov M, Dobbs D, Koch KE, Stroupe ME, Lawrence CJ, Bass HW (2014) G-quadruplex (G4) motifs in the maize (Zea mays L.) genome are enriched at specific locations in thousands of genes coupled to energy status, hypoxia, low sugar, and nutrient deprivation. J Genet Genomics Dec 20;41(12):627-47.
- Walia, RR, Xue, LC, Wilkins, K, El-Manzalawy Y, Dobbs D, Honavar, V (2014) RNABindRPlus: A predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins. PLoS ONE 9(5): e97725.
- Xue LC, Jordan RA, El-Manzalawy Y, Dobbs D, Honavar V (2014) DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction. Proteins Feb;82(2):250-67.
- Muppirala, UK, Lewis,BA, Dobbs, D (2013) Computational tools for investigating RNA-protein interaction partners. J Comput Sci Syst Biol. 6(4):182-187
- Walia RR, Caragea C, Lewis BA, Towfic FG, Terribilini, M, El-Manzalawy, Y, Dobbs D, Honavar V (2012) Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinformatics 13, 89.
- Jordan RA, El-Manzalawy Y, Dobbs D, Honavar, V (2012) Predicting protein-protein interface residues using local surface structural similarity. BMC Bioinformatics 13, 41.
- Muppirala,UK, Honavar V, Dobbs D (2011) Predicting RNA-protein interactions using only sequence information. BMC Bioinformatics 12, 489.
- Xue, LC, Dobbs, D, Honavar, V (2011) HomPPI: a class of sequence homology based protein-protein interface prediction methods. BMC Bioinformatics 12, 244.
- Steczkiewicz K, Zimmermann MT, Kurcinski M, Lewis BA, Dobbs D, Kloczkowski A, Jernigan RL, Kolinski A, Ginalski K. (2011) Human telomerase model shows the role of the TEN domain in advancing the double helix for the next polymerization step. Proc Natl Acad Sci U S A Jun 7;108(23):9443-8.
- Sander JD, Dahlborg EJ, Goodwin MJ, Cade L, Zhang F, Cifuentes D, Curtin SJ, Blackburn JS, Thibodeau-Beganny S, Qi Y, Pierick CJ, Hoffman E, Maeder ML, Khayter C, Reyon D, Dobbs D, Langenau DM, Stupar RM, Giraldez AJ, Voytas DF, Peterson RT, Yeh JR, Joung JK. (2011) Selection-free zinc-finger-nuclease engineering by context-dependent assembly (CoDA). Nat Methods Jan;8(1):67-9.