23 research outputs found

    Evolution of the Potential Energy Landscape with Static Pulling Force for Two Model Proteins

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    The energy landscape is analyzed for off-lattice bead models of protein L and protein G as a function of a static pulling force. Two different pairs of attachment points (pulling directions) are compared in each case, namely, residues 1/56 and 10/32. For the terminal residue pulling direction 1/56, the distinct global minimum structures are all extended, aside from the compact geometry that correlates with zero force. The helical turns finally disappear at the highest pulling forces considered. For the 10/32 pulling direction, the changes are more complicated, with a variety of competing arrangements for beads outside the region where the force is directly applied. These alternatives produce frustrated energy landscapes, with low-lying minima separated by high barriers. The calculated folding pathways in the absence of force are in good agreement with previous work. The N-terminal hairpin folds first for protein L and the C-terminal hairpin for protein G, which exhibits an intermediate. However, for a relatively low static force, where the global minimum retains its structure, the folding mechanisms change, sometimes dramatically, depending on the protein and the attachment points. The scaling relations predicted by catastrophe theory are found to hold in the limit of short path lengths

    Calculating the Bimolecular Rate of Protein–Protein Association with Interacting Crowders

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    We have recently introduced a method termed Poisson–Boltzmann semianalytical method (PB-SAM) for solving the linearized Poisson–Boltzmann equation for large numbers of arbitrarily shaped dielectric cavities with controlled precision. In this work we extend the applicability of the PB-SAM approach by deriving force and torque expressions that fully account for mutual polarization in both the zero- and first-order derivatives of the surface charges, that can now be embedded into a Brownian dynamics scheme to look at electrostatic-driven mesoscale assembly and kinetics. We demonstrate the capabilities of the PB-SAM approach by simulating the protein concentration effects on the bimolecular rate of association of barnase and barstar, under periodic boundary conditions and evaluated through mean first passage times. We apply PB-SAM to the pseudo-first-order reaction rate conditions in which either barnase or barstar are in great excess relative to the other protein (124:1). This can be considered a specific case in which the PB-SAM approach can be applied to crowding conditions in which crowders are not inert but can form interactions with other molecules

    Mechanism of Nucleation and Growth of Aβ40 Fibrils from All-Atom and Coarse-Grained Simulations

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    In this work, we characterize the nucleation and elongation mechanisms of the “diseased” polymorph of the amyloid-β 40 (Aβ40) fibril using an off-lattice coarse-grained (CG) protein model. After determining the nucleation size and subsequent stable protofibrillar structure from the CG model, validated with all-atom simulations, we consider the “lock and dock” and “activated monomer” fibril elongation mechanisms for the protofibril by statistical additions of a monomer drawn from four different ensembles of the free Aβ40 peptide to grow the fibril. Our CG model shows that the dominant mechanism for fibril elongation is the lock and dock mechanism across all monomer ensembles, even when the monomer is in the activated form. Although our CG model finds no thermodynamic difference between the two fibril elongation mechanisms, the activated monomer is found to be kinetically faster by a factor of 2 for the “locking” step compared with all other structured or unstructured monomer ensembles

    The Importance of the Scaffold for <i>de Novo</i> Enzymes: A Case Study with Kemp Eliminase

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    We report electric field values relevant to the reactant and transition states of designed Kemp eliminases KE07 and KE70 and their improved variants from laboratory directed evolution (LDE), using atomistic simulations with the AMOEBA polarizable force field. We find that the catalytic base residue contributes the most to the electric field stabilization of the transition state of the LDE variants of the KE07 and KE70 enzymes, whereas the electric fields of the remainder of the enzyme and solvent <i>disfavor</i> the catalytic reaction in both cases. By contrast, we show that the electrostatic environment plays a large and stabilizing role for the naturally occurring enzyme ketosteroid isomerase (KSI). These results suggest that LDE is ultimately a limited strategy for improving <i>de novo</i> enzymes since it is largely restricted to optimization of chemical positioning in the active site, thus yielding a ∟3 order magnitude improvement over the uncatalyzed reaction, which we suggest may be an absolute upper bound estimate based on LDE applied to comparable <i>de novo</i> Kemp eliminases and other enzymes like KSI. Instead <i>de novo</i> enzymatic reactions could more productively benefit from optimization of the electrostatics of the protein scaffold in early stages of the computational design, utilizing electric field optimization as guidance
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