Pharmaceutical Sciences
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/29938
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Browsing Pharmaceutical Sciences by Author "Emmitte, Kyle"
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Item Discovery of Small Molecule Slack Inhibitors for the Treatment of MMPSI: SAR Development in the Eastern Region of Hit Compound VU0606170(2020) Mishra, Nigam; Spitznagel, Brittany; Weaver, C.; Emmitte, Kyle; Tran, Elizabeth; Qunies, Alshaima'aIntroduction: Malignant Migrating Partial Seizures of Infancy (MMPSI) is a severe form of epilepsy without effective treatments. Slack channels are sodium-activated potassium channels, which are critical regulators of electrical activity in the CNS. MMPSI has been linked to gain-of-function mutations of Slack channels. Objective: To develop small molecule selective Slack inhibitors through an iterative hit optimization library synthesis approach to identify lead compounds for development into MMPSI therapeutics. Methods: Classical and state-of-the-art synthetic chemistry techniques including microwave assisted organic synthesis and flow chemistry were employed. Purification was by automated liquid chromatography. Bruker Fourier 300HD and Agilent 6230 time-of-flight LC/MS were utilized to obtain NMR and HRMS, respectively. Inhibitory activity of Slack was measured utilizing a Thallium flux assay in HEK293 cells stably expressing either WT or Slack mutants. Results: SAR studies developed around hit compound VU0606170 revealed that a 2,5-di-substitution pattern on the eastern phenyl ring was optimal for Slack activity. Compounds were identified that are selective for the A934T Slack variant versus WT. Modifications to the linker portion led to a loss of Slack activity. Lastly, in vitro DMPK studies with selected compounds revealed high clearance, high protein binding, and good permeability. Conclusion: SAR was identified for Slack activity, mutant selectivity, and DMPK properties around the eastern portion of VU0606170. These findings are presently being combined with SAR obtained from other regions of the molecule in search of compounds with improved potency and a more favorable DMPK profile.Item Discovery of Small Molecule Slack Inhibitors for the Treatment of MMPSI: SAR Development in the Western and Central Region of Hit Compound VU0606170(2020) Qunies, Alshaima'a; Acuna, Valeria; Acebo, Jonathan; Spitznagel, Brittany; Weaver, C.; Emmitte, Kyle; Mishra, NigamIntroduction: Malignant Migrating Partial Seizures of Infancy (MMPSI) is a severe and pharmacoresistant form of epilepsy. Slack channels are sodium-activated potassium channels that regulate essential electrical activity in the CNS. Gain-of-function mutations in Slack channels have been linked to MMPSI. Objective: To develop small molecule selective inhibitors of Slack employing a library synthesis based iterative hit optimization approach to discover leads for development into MMPSI therapeutics. Methods: Classical and state-of-the-art synthetic chemistry techniques including microwave assisted organic synthesis and flow chemistry were employed. Purification was by automated liquid chromatography. Bruker Fourier 300HD and Agilent 6230 time-of-flight LC/MS were utilized to obtain NMR and HRMS, respectively. Inhibitory activity of Slack was measured utilizing a Thallium flux assay in HEK293 cells stably expressing either WT or Slack mutants. Results: SAR studies around hit compound VU0606170 identified a chiral-methyl analog in piperizine core as optimal for potency. Other new core analogs were less potent than their piperazine counterparts. Several western urea and amide analogs were prepared, and a few moderately potent compounds were identified. Replacement of sulfamide linkers with a sulfonamide gave encouraging results. Lastly, invitro DMPK studies with selected compounds revealed high clearance, high protein binding, and good permeability. Conclusion: SAR was identified for Slack activity, mutant selectivity, and DMPK properties around the western and central region of VU0606170. Presently, synthesis of analogs that combine optimal functional groups from the entire chemotype are underway with a goal of improving potency and DMPK properties.Item Using Artificial Intelligence Algorithms to Develop Target-specific Ligands(2020) Emmitte, Kyle; Hayatshahi, Sayyed; Liu, Jin; Escobedo, Daniel; Li, Leo; Yang, YanmingPurpose: Pharmaceutical research has recently taken advantage of the rapid advancement in artificial intelligence (AI). The purpose of this study is to use AI to facilitate target-specific ligands development in drug discovery. Here, we used a machine learning algorithm to identify target-specific features of compounds to the metabotropic G-protein coupled receptors 2 and 3 (mGlu2 and mGlu3), which have been targeted for treatment of CNS disorders. Methods: A convolutional neural network (CNN) with 3 hidden layers was made using Tensorflow. We obtained data sets of 315 mGlu2 and 118 mGlu3 compounds and split them into testing and training sets. 75% of each data set was used for training and the remaining was used for testing. We fed the data sets into the CNN and ran the program over 100 iterations with each data set. Results: The neural network was able to differentiate between mGlu2 and mGlu3 compounds in the testing data set with up to a 99.1% accuracy. Visualization of the hidden layers revealed areas in the 2D images that the CNN viewed as important to distinguish the compounds. These identified chemical features can be considered as the target-specific features of the compounds. Conclusions: The neural network is able to differentiate mGlu2 and mGlu3 compounds by 2D representation alone and provide insight to distinguish target-specific features of the compounds through hidden layer visualization. Further testing through cross validation and introduction of a control data set with compounds that bind to neither receptor is needed.