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Patel, K. R.

Publications and source records attributed to Patel, K. R..

2 recordsLinked to original sources

Discovery of Aminoglycosides as first in class, nanomolar inhibitors of Heptosyltransferase I

A clinically relevant inhibitor for Heptosyltransferase I (HepI) has been sought after for many years and while many have designed novel small-molecule inhibitors, these compounds lack the bioavailability and potency necessary for therapeutic use. Extensive characterization of the HepI protein has provided valuable insight into the dynamic motions necessary for catalysis that could be targeted for inhibition. With the help of molecular dynamic simulations, aminoglycoside antibiotics were shown to be putative inhibitors for HepI and in this study, they were experimentally determined to be the first in-class nanomolar inhibitors of HepI with the best inhibitor demonstrating a Ki of 600 +/- 90 nM. Detailed kinetic analyses were performed to determine the mechanism of inhibition while circular dichroism spectroscopy, intrinsic tryptophan fluorescence, docking, and MD simulations were used to corroborate kinetic experimental findings. Kinetic analysis methods include Lineweaver-Burk, Dixon, Cornish-Bowden and Mixed-Model of Inhibition which allowed for unambiguous assignment of inhibition mechanism for each inhibitor. In this study, we show that neomycin and kanamycin b are competitive inhibitors against the sugar acceptor substrate while tobramycin exhibits a mixed inhibitory effect and streptomycin is non-competitive. MD simulations also allowed us to suggest that the inhibitors bind tightly and inhibit catalytic dynamics due to a major desolvation penalty of the enzyme active site. While aminoglycosides have long been known as a class of potent antibiotics, they also have been scientifically shown to impact cell membrane stability, and we propose that inhibition of HepI contributes to this effect by disrupting lipopolysaccharide biosynthesis.

biochemistry↗

Single Cell-type Integrative Network Modeling IdentifiedNovel Microglial-specific Targets for the Phagosome inAlzheimer's disease

SummaryLate-Onset Alzheimer’s Disease (LOAD) results from a complex pathological process influenced by genetic variation, aging and environment factors. Genetic susceptibility factors indicate that myeloid cells such as microglia play a significant role in the onset of LOAD. Here, we developed a computational systems biology approach to construct probabilistic causal and predictive network models of genetic regulatory programs of microglial cells under LOAD diagnosis by integrating two independent brain transcriptome and genome-wide genotype datasets from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MAYO) studies in the AMP-AD consortium. From this network model, we identified and replicated novel microglial-specific master regulators predicted to modulate network states associated with LOAD. We experimentally validated three microglial master regulators (FCER1G, HCK and LAPTM5) in primary human microglia-like cells (MDMi) by demonstrating the molecular impact these master regulators have on modulating downstream genomic targets identified by our top-down/bottom-up method and the causal relations among the three key drivers. These master regulators are involved in phagocytosis, a process associated with LOAD. Thus, we propose three new master regulator (key driver) genes that emerged from our network analyses as robust candidates for further evaluation in LOAD therapeutic development efforts.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗