Professor of Chemistry and Chemical and Biomolecular Engineering
"Anyone who has ever struggled to fold a roadmap should have an extra measure of respect for protein molecules, which fold up all on their own and practically put themselves away in the glove box" - (by Brian Hayes, from a paper published on American Scientist, 1998)
Virtually all biological activities are regulated by proteins. Combined in diverse cellular assemblies that vary with cell cycle, tissue type and in response to external stimuli, proteins constitute the nanomachines of biology. Understanding how proteins move and interact with neighboring molecules is necessary for solving critical puzzles in molecular biology, as for instance the so called "protein misfolding diseases" such as Alzheimer's and certain types of cancers. Yet, our understanding of protein mechanisms at the molecular level is still in its relative infancy. Research has long focused on grasping the "sequence-to-structure" relationship, but structure can only give a cursory understanding of a protein's function.
Filling the sizeable gaps in our knowledge of protein dynamics and function (or malfunction) is increasingly crucial in the nanotechnology era. The possibility now exists of engineering bio-nano conjugates which promise novel therapies, such as tunable nanoparticles designed to interact with certain proteins to ablate tumor tissue. These opportunities can be fully exploited only if technological progress is paired with a major step forward in our understanding of the detailed physical and chemical factors regulating protein mechanisms (encompassing dynamics, folding, interactions, and assembly) and consequently in our ability to model and predict these processes.
The study of protein dynamics and interactions at the molecular level of detail still poses outstanding challenges both for theory and experiment. No single technique can at present span the whole range of typical time and length scales relevant for a protein biological function. New theoretical and computational approaches need to be developed in order to address this challenge. It is our belief that this goal can be achieved by reconciling biological and biochemical approaches with a physical and mathematical perspective of the problem.
The results of Clementi's research group in the past few years have paved the way to create a new theoretical scaffold, blending
theory, simulation and experiment to address the characterization of protein systems at multiple length and time scales.
Please visit our group web page to find more information on the ongoing research projects: http://leonardo.rice.edu/~cecilia
Interdisciplinary training on theoretical physics,
physical chemistry and biochemistry, molecular biology and biophysics.
PhD in Theoretical Physics (Statistical Mechanics),
postdoctoral experience as a LJIS fellow (La Jolla Interfaces in Science
- Burroughs Wellcome program)
working on a project across the Physics department and the Chemistry and Biochemistry departments.
Current research and educational activities lie at the interface of Physical Chemistry, Theoretical Physics, Computer Science and Molecular Biology.
M. Praprotnik, S. Matysiak, L. Delle Site, K. Kremer, C. Clementi "Adaptive resolution simulation of liquid water" [Erratum to document cited in CA147:529061], J.Phys.: Condens. Matter, 21, 499801/1 (2009)
S. Matysiak, C. Clementi "Characterization of protein folding landscapes by coarse-grained models incorporating experimental data", Coarse-Graining of Condensed Phase and Biomolecular Systems, G. A. Voth Ed, Taylor & Francis/CRC press, Chapter 11 (2009): 157-170
A. Davtyan, N. P. Schaefer, W. Zheng, C. Clementi, P. G. Wolynes, G. A. Papoian Protein Structure Prediction Using Coarse-Grained Physical Potentials and Bioinformatically Based Local Structure Biasing. J. Phys. Chem. B, 116 2012: 8494-8503
P.J. Ledbetter, C. Clementi A new perspective on transition states: chi(1) separatrix. J. Chem. Phys., 135 2011: 044116-1:044116-13
W. Zheng, B. Qi, M. A. Rohrdanz, A. Caflisch, A. R. Dinner, C. Clementi Delineation of folding pathways of a beta-sheet miniprotein. J. Phys. Chem. B, 115 2011: 13065-13074
M. A. Rohrdanz, W. Zheng, M. Maggioni, C. Clementi Determination of reaction coordinates via locally scaled diffusion map. J. Chem. Phys., 134 2011: 124116
W. Zheng, M. A. Rohrdanz, M. Maggioni, C. Clementi Polymer reversal rate calculated via locally scaled diffusion map. J. Chem. Phys., 134 2011: 144109
P. Das, T. A. Frewen, I. G. Kevrekidis, C. Clementi Think Globally, Move Locally: Coarse Graining of Effective Free Energy Surfaces. Lecture Notes in Computational Science and Engineering, 35 2011
H. Stamati, C. Clementi, L. E. Kavraki Application of nonlinear dimensionality reduction to characterize the conformational landscape of small peptides. Proteins Struct. Funct. Bioinf., 78 2010: 223-235
B. P. Lambeth, Jr., C. Junghans, K. Kremer, C. Clementi, L. Delle Site Communication: On the locality of Hydrogen bond networks at hydrophobic interfaces. J. Chem. Phys., 133 2010: 221101
A. Shehu, L. E. Kavraki, C. Clementi Multiscale characterization of protein conformational ensembles. Proteins: Structure, Function and Bioinformatics , 76 2009: 837-851
J. A. Hegler, J. Latzer, A. Shehu, C. Clementi, P. G. Wolynes Restriction vs. guidance: Fragment assembly and associative memory Hamiltonians for protein structure prediction. Proc. Natl. Acad. Sci. USA, 106 2009: 15302-15307
S. Matysiak, C. Clementi Characterization of Protein-Folding Landscapes by Coarse-Grained Models Incorporating Experimental Data. Coarse-graining in Condensed Phase and Biomolecular Systems 2008: 157-170
C. Clementi Coarse-Grained Models of Protein Folding. Curr. Opin. Struct. Biol., 18 2008: 10-15
S. Matysiak C. Clementi Mapping Folding Energy Landscapes with Theory and Experiment. Arc. Biochem. Biophys., 469 2008: 29-33
S. Matysiak, C. Clementi, M. Praprotnik, K. Kremer, L. delle Site Modeling diffusive dynamics in adaptive resolution simulation of liquid water. J. Chem. Phys., 128 2008: 024503
A. Shehu, L. E. Kavraki, C. Clementi Unfolding the Fold of Cyclic Systeine-rich Peptides. Protein Sci., 17 2008: 482-493
Plaku, E., Stamati, H., Clementi, C. & Kavraki, L.E. Fast and Reliable Analysis of Molecular Motion Using Proximity Relations and Dimensionality Reduction. Proteins, 67 2007: 897-907
Heath, A.P., Kavraki, L.E. & Clementi, C. From Coarse-Grain to All-Atom: Toward Multiscale Analysis of Protein Landscapes. Proteins, 68 2007: 646-661
Shehu, A., Kavraki, L.E. & Clementi, C. On the Characterization of Protein Native State Ensembles. Biophysical Journal, 92 2007: 1503-1511
Mossa, A. & Clementi, C. Supersymmetric Langevin equation to explore free energy landscapes. Phys. Rev. E, 75 2007: 046707
P. Das, M. Moll, H. Stamati, L. E. Kavraki, and C. Clementi Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction. Proc. Natl. Acad. Sci. USA, 103 2006: 9885-9890