Unveiling the Gating Mechanism of CRAC Channel: A Computational Study

Partial Water Intrusion and Extrusion in Hydrophobic Nanopores for Thermomechanical Energy Dissipation

Forced wetting (intrusion) and spontaneous dewetting (extrusion) of hydrophobic/lyophobic nanoporous materials by water/nonwetting liquid are of great importance for a broad span of technological and natural systems such as shock-absorbers, molecular springs, separation, chromatography, ion channels, nanofluidics, and many more. In most of these cases, the process of intrusion-extrusion is not complete due to the stochastic nature of external stimuli under realistic operational conditions. However, understanding of these partial processes is limited, as most of the works are focused on an idealized complete intrusion-extrusion cycle. In this work, we show an experimental system operating under partial intrusion/extrusion conditions and present a simple model that captures its main features. We rationalize these operational conditions in terms of the pore entrance and cavity size distributions of the material, which control the range of intrusion/extrusion pressures.

Hydrophobically gated memristive nanopores for neuromorphic applications

Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor and construct a synaptic device capable of learning and forgetting. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.

What keeps nanopores boiling

The liquid-to-vapor transition can occur under unexpected conditions in nanopores, opening the door to fundamental questions and new technologies. The physics of boiling in confinement is progressively introduced, starting from classical nucleation theory, passing through nanoscale effects, and terminating with the material and external parameters that affect the boiling conditions. The relevance of boiling in specific nanoconfined systems is discussed, focusing on heterogeneous lyophobic systems, chromatographic columns, and ion channels. The current level of control of boiling in nanopores enabled by microporous materials such as metal organic frameworks and biological nanopores paves the way to thrilling theoretical challenges and to new technological opportunities in the fields of energy, neuromorphic computing, and sensing.

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.