Structural basis for human Cav3.2 inhibition by selective antagonists.

The Cav3.2 subtype of T-type calcium channels has been targeted for developing analgesics and anti-epileptics for its role in pain and epilepsy. Here we present the cryo-EM structures of Cav3.2 alone and in complex with four T-type calcium channel selective antagonists with overall resolutions ranging from 2.8 Å to 3.2 Å. The four compounds display two binding poses. ACT-709478 and TTA-A2 both place their cyclopropylphenyl-containing ends in the central cavity to directly obstruct ion flow, meanwhile extending their polar tails into the IV-I fenestration. TTA-P2 and ML218 project their 3,5-dichlorobenzamide groups into the II-III fenestration and place their hydrophobic tails in the cavity to impede ion permeation. The fenestration-penetrating mode immediately affords an explanation for the state-dependent activities of these antagonists. Structure-guided mutational analysis identifies several key residues that determine the T-type preference of these drugs. The structures also suggest the role of an endogenous lipid in stabilizing drug binding in the central cavity.

Statistical Analysis of the Relationship between AETA Electromagnetic Anomalies and Local Earthquakes.

To verify the relationship between AETA (Acoustic and Electromagnetics to Artificial Intelligence (AI)) electromagnetic anomalies and local earthquakes, we have performed statistical studies on the electromagnetic data observed at AETA station. To ensure the accuracy of statistical results, 20 AETA stations with few data missing and abundant local earthquake events were selected as research objects. A modified PCA method was used to obtain the sequence representing the signal anomaly. Statistical results of superposed epoch analysis have indicated that 80% of AETA stations have significant relationship between electromagnetic anomalies and local earthquakes. These anomalies are more likely to appear before the earthquakes rather than after them. Further, we used Molchan's error diagram to evaluate the electromagnetic signal anomalies at stations with significant relationships. All area skill scores are greater than 0. The above results have indicated that AETA electromagnetic anomalies contain precursory information and have the potential to improve local earthquake forecasting.