Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Jennifer M. Bui is active.

Publication


Featured researches published by Jennifer M. Bui.


Structure | 2008

A coupled equilibrium shift mechanism in calmodulin-mediated signal transduction.

Jörg Gsponer; John Christodoulou; Andrea Cavalli; Jennifer M. Bui; Barbara Richter; Christopher M. Dobson; Michele Vendruscolo

Summary We used nuclear magnetic resonance data to determine ensembles of conformations representing the structure and dynamics of calmodulin (CaM) in the calcium-bound state (Ca2+-CaM) and in the state bound to myosin light chain kinase (CaM-MLCK). These ensembles reveal that the Ca2+-CaM state includes a range of structures similar to those present when CaM is bound to MLCK. Detailed analysis of the ensembles demonstrates that correlated motions within the Ca2+-CaM state direct the structural fluctuations toward complex-like substates. This phenomenon enables initial ligation of MLCK at the C-terminal domain of CaM and induces a population shift among the substates accessible to the N-terminal domain, thus giving rise to the cooperativity associated with binding. Based on these results and the combination of modern free energy landscape theory with classical allostery models, we suggest that a coupled equilibrium shift mechanism controls the efficient binding of CaM to a wide range of ligands.


Proceedings of the National Academy of Sciences of the United States of America | 2006

Protein complex formation by acetylcholinesterase and the neurotoxin fasciculin-2 appears to involve an induced-fit mechanism.

Jennifer M. Bui; J. Andrew McCammon

Specific, rapid association of protein complexes is essential for all forms of cellular existence. The initial association of two molecules in diffusion-controlled reactions is often influenced by the electrostatic potential. Yet, the detailed binding mechanisms of proteins highly depend on the particular system. A complete protein complex formation pathway has been delineated by using structural information sampled over the course of the transformation reaction. The pathway begins at an encounter complex that is formed by one of the apo forms of neurotoxin fasciculin-2 (FAS2) and its high-affinity binding protein, acetylcholinesterase (AChE), followed by rapid conformational rearrangements into an intermediate complex that subsequently converts to the final complex as observed in crystal structures. Formation of the intermediate complex has also been independently captured in a separate 20-ns molecular dynamics simulation of the encounter complex. Conformational transitions between the apo and liganded states of FAS2 in the presence and absence of AChE are described in terms of their relative free energy profiles that link these two states. The transitions of FAS2 after binding to AChE are significantly faster than in the absence of AChE; the energy barrier between the two conformational states is reduced by half. Conformational rearrangements of FAS2 to the final liganded form not only bring the FAS2/AChE complex to lower energy states, but by controlling transient motions that lead to opening or closing one of the alternative passages to the active site of the enzyme also maximize the ligands inhibition of the enzyme.


Biophysical Journal | 2003

The Dynamics of Ligand Barrier Crossing inside the Acetylcholinesterase Gorge

Jennifer M. Bui; Richard H. Henchman; J. Andrew McCammon

The dynamics of ligand movement through the constricted region of the acetylcholinesterase gorge is important in understanding how the ligand gains access to and is released from the active site of the enzyme. Molecular dynamics simulations of the simple ligand, tetramethylammonium, crossing this bottleneck region are conducted using umbrella potential sampling and activated flux techniques. The low potential of mean force obtained is consistent with the fast reaction rate of acetylcholinesterase observed experimentally. From the results of the activated dynamics simulations, local conformational fluctuations of the gorge residues and larger scale collective motions of the protein are found to correlate highly with the ligand crossing.


Biophysical Journal | 2009

Analysis of Sub-τc and Supra-τc Motions in Protein Gβ1 Using Molecular Dynamics Simulations

Jennifer M. Bui; Jörg Gsponer; Michele Vendruscolo; Christopher M. Dobson

The functions of proteins depend on the dynamical behavior of their native states on a wide range of timescales. To investigate these dynamics in the case of the small protein Gbeta1, we analyzed molecular dynamics simulations with the model-free approach of nuclear magnetic relaxation. We found amplitudes of fast timescale motions (sub-tau(c), where tau(c) is the rotational correlation time) consistent with S(2) obtained from spin relaxation measurements as well as amplitudes of slow timescale motions (supra-tau(c)) in quantitative agreement with S(2) order parameters derived from residual dipolar coupling measurements. The slow timescale motions are associated with the large variations of the (3)J couplings that follow transitions between different conformational substates. These results provide further characterization of the large structural fluctuations in the native states of proteins that occur on timescales longer than the rotational correlation time.


Journal of Computational Chemistry | 2016

Free energies of solvation in the context of protein folding: Implications for implicit and explicit solvent models

Alexander Cumberworth; Jennifer M. Bui; Jörg Gsponer

Implicit solvent models for biomolecular simulations have been developed to use in place of more expensive explicit models; however, these models make many assumptions and approximations that are likely to affect accuracy. Here, the changes in free energies of solvation upon folding ΔΔGsolv of several fast folding proteins are calculated from previously run μs–ms simulations with a number of implicit solvent models and compared to the values needed to be consistent with the explicit solvent model used in the simulations. In the majority of cases, there is a significant and substantial difference between the ΔΔGsolv values calculated from the two approaches that is robust to the details of the calculations. These differences could only be remedied by selecting values for the model parameters—the internal dielectric constant for the polar term and the surface tension coefficient for the nonpolar term—that were system‐specific or physically unrealistic. We discuss the potential implications of our findings for both implicit and explicit solvent simulations.


Journal of the American Chemical Society | 2004

Acetylcholinesterase: enhanced fluctuations and alternative routes to the active site in the complex with fasciculin-2.

Jennifer M. Bui; and Kaihsu Tai; J. Andrew McCammon


Biophysical Journal | 2005

The entropic cost of protein-protein association: a case study on acetylcholinesterase binding to fasciculin-2.

David D. L. Minh; Jennifer M. Bui; Chia-en A. Chang; Tushar Jain; Jessica M. J. Swanson; J. Andrew McCammon


Biophysical Journal | 2006

Conformational Transitions in Protein-Protein Association: Binding of Fasciculin-2 to Acetylcholinesterase

Jennifer M. Bui; Zoran Radić; Palmer Taylor; J. Andrew McCammon


Angewandte Chemie | 2008

Identification of Aggregation-Prone Elements by Using Interaction-Energy Matrices†

Jennifer M. Bui; Andrea Cavalli; Jörg Gsponer


Archive | 2009

Analysis of Sub-tc and Supra-tc Motions in Protein Gb1 Using Molecular Dynamics Simulations

Jennifer M. Bui; Michele Vendruscolo; Christopher M. Dobson

Collaboration


Dive into the Jennifer M. Bui's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jörg Gsponer

Laboratory of Molecular Biology

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

David D. L. Minh

Argonne National Laboratory

View shared research outputs
Researchain Logo
Decentralizing Knowledge