GrantLab Grant Lab Logo

Research Overview

Research in the Grant Lab applies bioinformatics to important questions in cell biology, molecular biology, biophysics and biochemistry. This includes investigating molecular mechanism of kinesin motors and the microtubule cytoskeleton; signal transduction through G proteins, membrane receptors and channels; the evolution of functional specialization in large protein superfamilies; and characterizing the atomistic basis of protein allosteric mechanisms.


GeneralApproach

Our general approach is to develop and apply state-of-the-art computational techniques at multiple levels that can be coupled to a wide range of biochemical and biophysical experiments. This includes:

  • Bioinformatic analysis to probe sequence-structure-function relationships;
  • Molecular dynamics to investigate essential conformational changes;
  • Brownian dynamics for diffusional protein-protein and protein-ligand encounters;
  • Computer-aided drug design for discovering novel therapeutics; and
  • Genome informatics for mapping SNPs and disease associated variants to structural dynamic consequences and potential functional effects.


Major Contributions

In this way we have gained a number of unique insights and made important contributions. This includes the development of a new class of allosteric Ras & Rho molecular switch inhibitors (1, 2), reporting the first rationally designed faster velocity kinesin motors (3) , demonstrating for the first time that kinesin processivity can be modulated by rational mutation of the motor domain (4), discovery of key atomistic determinants of allosteric activation in G proteins (5), successfully predicting the mechanism of a major immunologically mediated adverse drug reaction (6), discovery of disease associated mutations and post-translational modifications that can tune kinesin protein function (7), and development of the Bio3D software package used by thousands of researchers and students around the world (8-10).

Collectively, this broad body of work demonstrates the power of applying a bioinformatics informed approach to biology. Our research goals are to advance these efforts to further facilitate the fields of protein design and drug discovery.


Selected References

  1. Grant, B. J., S. Lukman, H. J. Hocker, J. Sayyah, J. H. Brown, J. A. McCammon, and A. A. Gorfe. 2011. Novel allosteric sites on Ras for lead generation. PLoS One 6:e25711.

  2. Ortiz-Sanchez, J. M., S. E. Nichols, J. Sayyah, J. H. Brown, J. A. McCammon, and B. J. Grant. 2012. Identification of potential small molecule binding pockets on Rho family GTPases. PLoS One 7:e40809.

  3. Grant, B. J., D. M. Gheorghe, W. Zheng, M. Alonso, G. Huber, M. Dlugosz, J. A. McCammon, and R. A. Cross. 2011. Electrostatically biased binding of kinesin to microtubules. PLoS Biol 9:e1001207.

  4. Scarabelli, G., V. Soppina, X. Q. Yao, J. Atherton, C. A. Moores, K. J. Verhey, and B. J. Grant. 2015. Mapping the Processivity Determinants of the Kinesin-3 Motor Domain. Biophys J 109:1537-1540.

  5. Yao, X. Q., R. U. Malik, N. W. Griggs, L. Skjaerven, J. R. Traynor, S. Sivaramakrishnan, and B. J. Grant. 2016. Dynamic Coupling and Allosteric Networks in the alpha Subunit of Heterotrimeric G Proteins. J Biol Chem 291:4742-4753.

  6. Ostrov, D. A., B. J. Grant, Y. A. Pompeu, J. Sidney, M. Harndahl, S. Southwood, C. Oseroff, S. Lu, J. Jakoncic, C. A. de Oliveira, L. Yang, H. Mei, L. Shi, J. Shabanowitz, A. M. English, A. Wriston, A. Lucas, E. Phillips, S. Mallal, H. M. Grey, A. Sette, D. F. Hunt, S. Buus, and B. Peters. 2012. Drug hypersensitivity caused by alteration of the MHC-presented self-peptide repertoire. Proc Natl Acad Sci U S A 109:9959-9964.

  7. Muretta, J., B. J. Reddy, G. Scarabelli, B. J. Grant, S. P. Gross, and S. S. Rosenfeld. 2016. Allosterically tuning the mechanochemical properties of kinesin-5 via mutations and post translational modifications. In preparation.

  8. Grant, B. J., A. P. Rodrigues, K. M. ElSawy, J. A. McCammon, and L. S. Caves. 2006. Bio3D: an R package for the comparative analysis of protein structures. Bioinformatics 22:2695-2696.

  9. Skjaerven, L., X. Q. Yao, G. Scarabelli, and B. J. Grant. 2014. Integrating protein structural dynamics and evolutionary analysis with Bio3D. BMC Bioinformatics 15:399.

  10. Skjaerven, L., S. Jariwala, X. Q. Yao, and B. J. Grant. 2016. Online interactive analysis of protein structure ensembles with Bio3D-web. Bioinformatics 2016;32(22):3510-3512.

Additional Grant Lab Publications →