A Massively Parallel Screen of 5'UTR Mutations Identifies Variants Impacting Translation and Protein Production in Neurodevelopmental Disorder Genes.

mutations cause a variety of neurodevelopmental disorders including autism. Recent whole genome sequencing from individuals with autism has shown that many mutations also occur in untranslated regions (UTRs) of genes, but it is difficult to predict from sequence alone which mutations are functional, let alone causal. Therefore, we developed a high throughput assay to screen the transcriptional and translational effects of 997 variants from 5'UTR patient mutations.

Incorporating physics to overcome data scarcity in predictive modeling of protein function: A case study of BK channels.

Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation.

Evaluation of gliovascular functions of Aqp4 readthrough isoforms.

Aquaporin-4 (AQP4) is a water channel protein that links astrocytic endfeet to the blood-brain barrier (BBB) and regulates water and potassium homeostasis in the brain, as well as the glymphatic clearance of waste products that would otherwise potentiate neurological diseases. Recently, translational readthrough was shown to generate a C-terminally extended variant of AQP4, known as AQP4x, that preferentially localizes around the BBB through interaction with the scaffolding protein α-syntrophin, and loss of AQP4x disrupts waste clearance from the brain. To investigate the function of AQP4x, we generated a novel mouse AQP4 line (AllX) to increase relative levels of the readthrough variant above the ~15% of AQP4 in the brain of wildtype (WT) mice.

Incorporating physics to overcome data scarcity in predictive modeling of protein function: a case study of BK channels.

Unlabelled: Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation.

Aqp4 stop codon readthrough facilitates amyloid-β clearance from the brain.

Alzheimer's disease is initiated by the toxic aggregation of amyloid-β. Immunotherapeutics aimed at reducing amyloid beta are in clinical trials but with very limited success to date. Identification of orthogonal approaches for clearing amyloid beta may complement these approaches for treating Alzheimer's disease.

Electro-mechanical coupling of KCNQ channels is a target of epilepsy-associated mutations and retigabine.

KCNQ2 and KCNQ3 form the M-channels that are important in regulating neuronal excitability. Inherited mutations that alter voltage-dependent gating of M-channels are associated with neonatal epilepsy. In the homolog KCNQ1 channel, two steps of voltage sensor activation lead to two functionally distinct open states, the intermediate-open (IO) and activated-open (AO), which define the gating, physiological, and pharmacological properties of KCNQ1.

Calmodulin acts as a state-dependent switch to control a cardiac potassium channel opening.

Calmodulin (CaM) and phosphatidylinositol 4,5-bisphosphate (PIP) are potent regulators of the voltage-gated potassium channel KCNQ1 (K7.1), which conducts the cardiac current. Although cryo-electron microscopy structures revealed intricate interactions between the KCNQ1 voltage-sensing domain (VSD), CaM, and PIP, the functional consequences of these interactions remain unknown.

A PIP substitute mediates voltage sensor-pore coupling in KCNQ activation.

KCNQ family K channels (KCNQ1-5) in the heart, nerve, epithelium and ear require phosphatidylinositol 4,5-bisphosphate (PIP) for voltage dependent activation. While membrane lipids are known to regulate voltage sensor domain (VSD) activation and pore opening in voltage dependent gating, PIP was found to interact with KCNQ1 and mediate VSD-pore coupling. Here, we show that a compound CP1, identified in silico based on the structures of both KCNQ1 and PIP, can substitute for PIP to mediate VSD-pore coupling.

Structure and physiological function of the human KCNQ1 channel voltage sensor intermediate state.

Voltage-gated ion channels feature voltage sensor domains (VSDs) that exist in three distinct conformations during activation: resting, intermediate, and activated. Experimental determination of the structure of a potassium channel VSD in the intermediate state has previously proven elusive. Here, we report and validate the experimental three-dimensional structure of the human KCNQ1 voltage-gated potassium channel VSD in the intermediate state.

Two-stage electro-mechanical coupling of a K channel in voltage-dependent activation.

In voltage-gated potassium (K) channels, the voltage-sensing domain (VSD) undergoes sequential activation from the resting state to the intermediate state and activated state to trigger pore opening via electro-mechanical (E-M) coupling. However, the spatial and temporal details underlying E-M coupling remain elusive. Here, utilizing K7.

ML277 specifically enhances the fully activated open state of KCNQ1 by modulating VSD-pore coupling.

Upon membrane depolarization, the KCNQ1 potassium channel opens at the intermediate (IO) and activated (AO) states of the stepwise voltage-sensing domain (VSD) activation. In the heart, KCNQ1 associates with KCNE1 subunits to form I channels that regulate heart rhythm. KCNE1 suppresses the IO state so that the I channel opens only to the AO state.