Chen Research Group
Computational Biochemistry & Biophysics

Our general interest is in theoretical and computational study of biomolecular structure, dynamics and function, with particular emphasis on modeling weakly stable proteins and understanding their roles in important biological processes such as regulation of transcription and translation, signal transduction and disease-related protein misfolding. Our research is currently supported by NSF, through grants MCB 0952514 (2010-15), CNS 1006860 (2011-14) and CHE 1265821 (2013-17), NIH, through GM 074096 (2010-14), GM107487 (2014-19) and several local and state funding agencies including the Johnson Center for Basic Cancer Research. More specifically, we are currently focusing on the following areas.

1. Implicit treatment of solvent

De novo simulation of large conformational changes of proteins such as folding remains one of the greatest challenges in computational biology. A critical bottleneck is accurate and efficient description of the solvent environment. Implicit treatment of solvent arguably provides an optimal balance between description of the essential physics and computational feasibility. The basic idea is to capture the mean influence of water on the solute via direct estimation of the solvation free energy. Important approximations need to be made in order to estimate the solvation free energy without extensively sampling all water degrees of freedom. In particular, it is generally assumed that water dynamics is much faster than peptide conformational diffusion, such that the solvent can be effectively described as a continuum medium. As such, only the solute is represented microscopically, and the system size is reduced about 10-fold. The latest implicit solvent models often decompose the total solvation free energy into nonpolar and electrostatic contributions, which increases the accuracy and enhances the ability to describe the conformational dependence of solvation. Important advances have been made in recent years for accurate calculation of the solvation free energy on the fly with only a modest computational overhead, such as using the generalized Born (GB) theory. A critical remaining limitation is in the treatment of nonpolar solvation, where the popular surface area-based models are insufficient in describing the conformational dependence of nonpolar solvation. A key focus of our research is to develop better nonpolar solvation models, through studying key physical properties of nonpolar solvation, devising efficient numerical methods to model these properties, and consistently optimizing the solvation model together with the underlying protein force field.

2. Intrinsically disordered proteins

(Coupled binding and folding of ACTR of p160 nuclear
hormone receptor and NCBD of CBP/p300 transcriptional
coactivator. Demarest et al., Nature 2002)
Intrinsically disordered proteins (IDPs) are an important newly recognized class of functional proteins that rely on a lack of stable structures for function. They are highly abundant, play fundamental roles in biology, and are extensively involved in human diseases. The heterogeneous and dynamical nature of IDPs, however, presents substantial challenges for detailed characterization using experiment alone. This difficulty represents a unique and exciting opportunity for modeling to make crucial contributions. At the same time, IDPs also pose substantial new challenges that push the limits of both the force field accuracy and conformational sampling capability. Implicit solvent is arguably the best choice for de novo simulation of IDPs with a necessary balance between accuracy and speed. One of the key motivations of developing better implicit solvent protein force fields (see above) is actually to understand the structure, interaction and control of IDPs. At this stage, we are mainly interested in understanding the nature of the unbound states of a set of model regulatory IDPs and the molecular mechanisms of their interaction with specific substrates. We rely on close collaborations with NMR experimentalists for reliable interpretation and critical validation of simulation.

3. Coupled folding, assembly and membrane insertion of helical peptides

The precise mechanisms of spontaneous insertion and self-assembly of peptides in membrane remain poorly understood at molecular level. This limitation is related to both (1) a lack of suitable molecular modeling tools for simulating such complex processes and (2) difficulty in designing model peptides to systematically investigate various factors under controlled conditions. So-called coarse-grained approaches can extend the accessible time scales by several orders of magnitude while capturing the essence of underlying physical interactions. In particular, increasing amount of experimental evidence, as well as theoretical considerations, has accumulated to argue that peptides generally fold or refold upon membrane insertion and that coupling of folding, insertion and assembly is essential for the actions of membrane-inserting proteins in biology. There is a need to develop a new generation of CG protein-lipid force fields that is efficient yet realistic enough to enable direct simulation of coupled peptide folding during membrane insertion and self-assembly. At the same time, we are exploiting model peptide systems that allow specific questions to be formulated and addressed simultaneously by experiment and simulation. In particular, M2GlyR-derived channel-forming peptides designed by the Tomich lab (see below) possess a set of unique properties that make them an ideal platform for understanding membrane insertion of helical peptides.

4. Modeling and design of synthetic peptide channels

(A short molecular dynamics simulation of
a designed peptide channel in POPC bilayer)
In close collaboration with the Tomich lab in Biochemistry Department, our long-term goal is to design, develop and implement the use of ion-selective, synthetic channel-forming peptides. A primary application for such technology will be the treatment of loss-of-function ion channel diseases such as cystic fibrosis. The Tomich lab has derived a series of pore-forming peptides from the second transmembrane helix of glycine receptor (M2GlyR) alpha1 subunit with many desired properties (solubility, monomeric, spontaneous insertion, large conductance, etc). A final remaining barrier is a lack of sufficient anion selectivity. We are currently exploiting peptide synthesis, biological testing, structural analysis and computer modeling to understand the structural and physicochemical properties responsible for modulating anion selectivity. Given the challenges of structural characterization of membrane proteins, our strategy is to combine molecular modeling, solution NMR and various (low-resolution) structural restraints to build our "best-guess" structural models of these synthetic channels. Subsequent molecular simulations will provide important insights for rationale design of novel sequences with desired characteristics.

5. New simulation and conformational sampling methods

Successful biomolecular simulations hinge on both the quality of the empirical force field employed and the ability to sufficiently sample functionally relevant conformational spaces. Brute-force molecular dynamic simulations have very limited ability to probe biologically relevant processes, which often occur at time scales much longer what is accessible by such simulations. Development of nontrivial sampling techniques is one of the most actively research areas in biomolecular modeling. This is also an important focus of our research. For example, we extensively explore so-called replica exchange enhanced sampling in our peptide simulations. Much remains to be learned about the actual efficacy of replica exchange and how to improve it. We are also interested in exploring so-called internal coordinate molecular dynamics that reduces the number of the degrees of freedom and allows larger molecular dynamics time steps. Such simulation technique has found usage in NMR structure calculation and refinement, flexible protein-ligand docking, etc.

Want to find out more about our research? Check out our latest publications, or, simply drop by if you can! We are in 34 Chalmers Hall.

| 34 Chalmers Hall | Biochemistry & Molecular Biophysics | Kansas State University