The KPC-2 carbapenemase enzyme is responsible for drug resistance in the majority of carbapenem-resistant gram-negative bacterial infections in the United States. A better understanding of what permits KPC-2 to hydrolyze carbapenem antibiotics and how this might be inhibited is thus of fundamental interest and great practical importance to development of better anti-infectives. By correlating molecular dynamics simulations with experimental enzyme kinetics, we have identified conformational changes that control KPC-2’s ability to hydrolyze carbapenem antibiotics. Related beta-lactamase enzymes can interconvert between catalytically permissive and catalytically nonpermissive forms of an acylenzyme intermediate critical to drug hydrolysis. Using molecular dynamics simulations, we identify a similar equilibrium in KPC-2 and analyze the determinants of this conformational change. Because the conformational dynamics of KPC-2 are complex and sensitive to allosteric changes, we develop an information-theoretic approach to identify key determinants of this change. We measure unbiased estimators of the reaction coordinate between catalytically permissive and nonpermissive states, perform information-theoretic feature selection and, using restrained molecular dynamics simulations, validate the protein conformational changes predicted to control catalytically permissive geometry. We identify two binding-pocket residues that control the conformational transitions between catalytically active and inactive forms of KPC-2. Mutations to one of these residues, Trp105, lower the stability of the catalytically permissive state in simulations and have reduced experimental kcat values that show a strong linear correlation with the simulated catalytically permissive state lifetimes. This understanding can be leveraged to predict the drug resistance of further KPC-2 mutants and help design inhibitors to combat extreme drug resistance.

p66Shc is an oxidoreductase that responds to cell stress by translocating to mitochondria, where p66Shc produces pro-apoptotic reactive oxygen species (ROS). This study identifies ROS-active p66Shc as a monomer that produces superoxide anion independent of metal ions, inhibits cytochrome c peroxidase, and is regulated by environmental condition-induced structural changes. p66Shc anti-apoptotic functions, including: cytochrome c reduction, increased electron transport chain activity, and caspase cascade inhibition were also discovered. This study also demonstrates that p66Shc is a stress-dependent rheostat of apoptosis, regulated by p66Shc-mortalin complexes. These complexes decrease pro-apoptotic ROS production, without blocking p66Shc-mediated cytochrome c reduction. However, stress disrupts p66Shc-mortalin interactions, promoting apoptosis. Tipping p66Shc apoptotic balance toward anti-apoptotic functions by genetic knockdown or p66Shc-selective ROS inhibition decreased pro-apoptotic effects and improved outcomes in zebrafish myocardial infarction models, representing a potential new myocardial infarction treatment with promising results.

TheoryA more complex formulation of bias-resampling ensemble refinement (BRER) may be used to perform more advanced sampling. Rather than draw each conformation x from the previous conformational estimate "#$ , a history is maintained of k refinement rounds, so that the conformation x is drawn from the union of "#$ , "#& , … , "#( . The conformational estimate " is then obtained as before: the conformations are updated using a biased MD simulation such that the updated estimate $…" will optimally reproduce *++, ( ). Just as with the formulation provided in the main text, over the course of multiple rounds of refinement, the conformational estimate { } should yield a distribution 2 ( ) that converges on *++, ( ). Methods Molecular dynamics simulations Setup and equilibration of syntaxin-1aIn order to best demonstrate the ability of our method to sample backbone conformational change and rare conformational states, we started all simulations of syntaxin-1a from its closed state. We obtained an initial structure of closed syntaxin by extracting the soluble domain from the crystal structure of syntaxin in complex with Munc-18 (PDB ID 3C98) 1 . The system was solvated with approximately 90,000 TIP3P water molecules and ions were added to obtain a system with 150 mM NaCl and no net charge. Simulations were run in Gromacs 2 using the CHARMM36 3 force field. The system was energy minimized using the steepest-descent integrator for 5000 steps or until the largest force was less than 500 kJ/mol/nm 2 , whichever came first. A brief 100 ps equilibration was run using NPT conditions using the velocity-rescaling thermostat 4 at 310 K with a 2-ps time constant and pressure maintained at 1 bar using the Parrinello-Rahman barostat 5 with a 10-ps time constant. Covalent bonds were constrained using LINCS, and long-range electrostatics were treated using Particle Mesh Ewald 6 . For each set of ensemble simulations, we generated 50 identical replicas from the equilibrated structure and used these replicas as initial states for production runs. Production simulationsAll production simulations were run under the same NPT conditions described above. DEER-derived distance distributions were smoothed with a Gaussian filter. The smoothing parameter σ was chosen to reflect the experimental uncertainty in the fine modes of the DEER-derived distance distributions, 2 Å for all three distributions. Histograms were calculated using 1 Å bins. These distributions were then incorporated into MD simulation using each of three ensemble methods, detailed below. Production simulations were carried out using 50 ensemble members and 5 μs of simulation data were collected for each refinement method except EBMetaD. The reason for this exception is described in "EBMetaD simulations." Simulations were run using Gromacs 2 and the gmxapi Python API 7 , which permits introduction of user-defined biasing potentials. BRER simulationsTo sample the syntaxin conformational ensemble, we performed five iterations of BRER for each of 50 ensemble members. Each iteratio...

Highly flexible proteins present a special challenge for structure determination because they are multi-structured yet not disordered, so their conformational ensembles are essential for understanding function. Because spectroscopic measurements of multiple conformational populations often provide sparse data, experiment selection is a limiting factor in conformational refinement. A molecular simulations- and information-theory based approach to select which experiments best refine conformational ensembles has been developed. This approach was tested on three flexible proteins. For proteins where a clear mechanistic hypothesis exists, experiments that test this hypothesis were systematically identified. When available data did not yield such mechanistic hypotheses, experiments that significantly outperform structure-guided approaches in conformational refinement were identified. This approach offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

p66Shc is a widely expressed protein that governs a variety of cardiovascular pathologies by generating, and exacerbating, pro-apoptotic ROS signals. Here, we review p66Shc’s connections to reactive oxygen species, expression, localization, and discuss p66Shc signaling and mitochondrial functions. Emphasis is placed on recent p66Shc mitochondrial function discoveries including structure/function relationships, ROS identity and regulation, mechanistic insights, and how p66Shc-cyt c interactions can influence p66Shc mitochondrial function. Based on recent findings, a new p66Shc mitochondrial function model is also put forth wherein p66Shc acts as a rheostat that can promote or antagonize apoptosis. A discussion of how the revised p66Shc model fits previous findings in p66Shc-mediated cardiovascular pathology follows.