K
Kenneth A. Johnson
Researcher at University of Texas at Austin
Publications - 250
Citations - 18132
Kenneth A. Johnson is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Polymerase & DNA polymerase. The author has an hindex of 72, co-authored 250 publications receiving 17043 citations. Previous affiliations of Kenneth A. Johnson include National Institutes of Health & Yale University.
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The Original Michaelis Constant: Translation of the 1913 Michaelis–Menten Paper
TL;DR: This reanalysis of Michaelis and Menten's data using modern computational methods revealed an unanticipated rigor and precision in the original publication and uncovered a sophisticated, comprehensive analysis that has been overlooked in the century since their work was published.
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Conformational Coupling in DNA Polymerase Fidelity
TL;DR: This paradigm provides the theoretical basis for further investigation of the structural basis for fidelity by pointing to the essential elements of the polymerization reaction that need to be examined in order to evaluate active-site-directed mutants of polymerases to test appropriate structure/function relationships.
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Mechanism of inhibition of HIV-1 reverse transcriptase by nonnucleoside inhibitors
TL;DR: The data suggest that an inhibitor combining the functionalities of a nonnucleoside inhibitor and a nucleotide analog could bind very tightly and specifically to reverse transcriptase and could be effective in the treatment of AIDS.
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Pre-steady-state kinetic analysis of processive DNA replication including complete characterization of an exonuclease-deficient mutant.
TL;DR: These studies provide the first complete and self-consistent thermodynamic descriptions of DNA polymerase and establish the basis for quantitative assessment of the reactions contributing to its extraordinary fidelity.
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Global Kinetic Explorer: A new computer program for dynamic simulation and fitting of kinetic data
TL;DR: A new dynamic kinetic simulation program that allows multiple data sets to be fit simultaneously to a single model based on numerical integration of the rate equations describing the reaction mechanism is described.