35 research outputs found
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Resolving the energy paradox of chaperone/usher-mediated fibre assembly
Periplasmic chaperone/usher machineries are used for assembly of filamentous adhesion organelles of Gram-negative pathogens in a process that has been suggested to be driven by folding energy. Structures of mutant chaperone-subunit complexes revealed a final folding transition (condensation of the subunit hydrophobic core) on the release of organelle subunit from the chaperone-subunit pre-assembly complex and incorporation into the final fibre structure. However, in view of the large interface between chaperone and subunit in the pre-assembly complex and the reported stability of this complex, it is difficult to understand how final folding could release sufficient energy to drive assembly. In the present paper, we show the X-ray structure for a native chaperone-fibre complex that, together with thermodynamic data, shows that the final folding step is indeed an essential component of the assembly process. We show that completion of the hydrophobic core and incorporation into the fibre results in an exceptionally stable module, whereas the chaperone-subunit preassembly complex is greatly destabilized by the high-energy conformation of the bound subunit. This difference in stabilities creates a free energy potential that drives fibre formation
Single Mutation Induced H3N2 Hemagglutinin Antibody Neutralization: A Free Energy Perturbation Study
Potent inhibitors of the Plasmodium falciparum enzymes plasmepsin I and II devoid of cathepsin D inhibitory activity.
The hemoglobin-degrading aspartic proteases plasmepsin I (Plm I) and plasmepsin II (Plm II) of the malaria parasite Plasmodium falciparum have lately emerged as putative drug targets. A series of C(2)-symmetric compounds encompassing the 1,2-dihydroxyethylene scaffold and a variety of elongated P1/P1' side chains were synthesized via microwave-assisted palladium-catalyzed coupling reactions. Binding affinity calculations with the linear interaction energy method and molecular dynamics simulations reproduced the experimental binding data obtained in a Plm II assay with very good accuracy. Bioactive conformations of the elongated P1/P1' chains were predicted and agreed essentially with a recent X-ray structure. The compounds exhibited picomolar to nanomolar inhibition constants for the plasmepsins and no measurable affinity to the human enzyme cathepsin D. Some of the compounds also demonstrated significant inhibition of parasite growth in cell culture. To the best of our knowledge, these plasmepsin inhibitors represent the most selective reported to date and constitute promising lead compounds for further optimization
Are automated molecular dynamics simulations and binding free energy calculations realistic tools in lead optimization? An evaluation of the linear interaction energy (LIE) method
An extensive evaluation of the linear interaction energy (LIE) method for the prediction of binding affinity of docked compounds has been performed, with an emphasis on its applicability in lead optimization. An automated setup is presented, which allows for the use of the method in an industrial setting. Calculations are performed for four realistic examples, retinoic acid receptor γ, matrix metalloprotease 3, estrogen receptor α, and dihydrofolate reductase, focusing on different aspects of the procedure. The obtained LIE models are evaluated in terms of the root-mean-square (RMS) errors from experimental binding free energies and the ability to rank compounds appropriately. The results are compared to the best empirical scoring function, selected from a set of 10 scoring functions. In all cases, good LIE models can be obtained in terms of free-energy RMS errors, although reasonable ranking of the ligands of dihydrofolate reductase proves difficult for both the LIE method and scoring functions. For the other proteins, the LIE model results in better predictions than the best performing scoring function. These results indicate that the LIE approach, as a tool to evaluate docking results, can be a valuable asset in computational lead optimization programs. © 2006 American Chemical Society