Molecular Dynamics and Machine Learning Study of Adrenaline Dynamics in the Binding Pocket of GPCR.

G-protein coupled receptors (GPCRs) are the most prominent family of membrane proteins that serve as major targets for one-third of the drugs produced. A detailed understanding of the molecular mechanism of drug-induced activation and inhibition of GPCRs is crucial for the rational design of novel therapeutics. The binding of the neurotransmitter adrenaline to the ß2-adrenergic receptor (ß2AR) is known to induce a flight or fight cellular response, but much remains to be understood about binding-induced dynamical changes in ß2AR and adrenaline. In this article, we examine the potential of mean force (PMF) for the unbinding of adrenaline from the orthosteric binding site of ß2AR and the associated dynamics using umbrella sampling and molecular dynamics (MD) simulations. The calculated PMF reveals a global energy minimum, which corresponds to the crystal structure of ß2AR-adrenaline complex, and a meta-stable state in which the adrenaline is moved slightly deeper into the binding pocket with a different orientation compared to that in the crystal structure. The orientational and conformational changes in adrenaline during the transition between these two states and the underlying driving forces of this transition are also explored. Based on the clustering of MD configurations and machine learning-based statistical analyses of time series of relevant collective variables, the structures and stabilizing interactions of these two states of the ß2AR-adrenaline complex are also investigated.

The 3Dmol.js learning environment: a classroom response system for 3D chemical structures.

Classroom response systems are an important tool in many active learning pedagogies. They support real-time feedback on student learning and promote student engagement, even in large classrooms, by allowing instructors to solicit an answer to a question from all students and show the results. Existing classroom response systems are general purpose and not tailored to the specific needs of a chemistry classroom. In particular, it is not easy to deploy molecular representations except as static images. Here we present the 3Dmol.js learning environment, a classroom response system that uses the open source web-based 3Dmol.js JavaScript framework to provide interactive viewing and querying of 3D molecules. 3Dmol.js is available under a BSD 3-clause open source license, and the learning environment features are all available through http://3dmol.csb.pitt.edu/ without any software installation required.