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Kevin E. B. Parkes

Researcher at Scripps Research Institute

Publications -  7
Citations -  159

Kevin E. B. Parkes is an academic researcher from Scripps Research Institute. The author has contributed to research in topics: QM/MM & Dipole. The author has an hindex of 6, co-authored 7 publications receiving 155 citations.

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Criteria for confirming sequence periodicity identified by Fourier transform analysis: application to GCR2, a candidate plant GPCR?

TL;DR: Application of the Fourier transform algorithm to the G CR2 family revealed strongly predicted seven fold periodicity in hydrophobicity, suggesting why GCR2 has been reported to be a GPCR, despite negative indications in most transmembrane prediction algorithms.
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Assessing the role of polarization in docking.

TL;DR: A strategy for including ligand and protein polarization in docking that is based on the conversion of induced dipoles to induced charges is described and the options for implementing polarization within a purely classical docking framework are discussed.
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Toward a consistent treatment of polarization in model QM/MM calculations.

TL;DR: From the water dimer calculations, it is concluded that the induced charge approach is consistent with medium sized basis set calculations whereas the induced dipole approach is inconsistent with large basis set Calculations.
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The effect of MM polarization on the QM/MM transition state stabilization: application to chorismate mutase

TL;DR: The feasibility of including MM polarization into hybrid quantum mechanics/molecular mechanics calculations has been demonstrated using the method of induced charges, indicating that MM polarization may in principle have a significant effect on enzyme rate enhancement and mechanism.
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Closed loop folding units from structural alignments: experimental foldons revisited.

TL;DR: This work determined the locations of the closed loops in 37 pairs of proteins and obtained excellent agreement with previously published closed loops, indicating that the closed loop hypothesis may provide a useful framework for analyzing such experimental data.