The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipidprotein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Leucine/isoleucine side chain polymers are of interest due to their hydrophobicity and reported role in the formation of α-helical structures. The synthesis and reversible addition-fragmentation chain transfer (RAFT) polymerization of amino acid-based chiral monomers, namely Boc-L-leucine methacryloyloxyethyl ester (Boc-L-Leu-HEMA, 1a), Boc-L-leucine acryloyloxyethyl ester (Boc-L-Leu-HEA, 1b), Boc-L-isoleucine methacryloyloxyethyl ester (Boc-L-Ile-HEMA, 1c), and Boc-L-isoleucine acryloyloxyethyl ester (Boc-L-Ile-HEA, 1d), are reported. The controlled nature of the polymerization of the said chiral monomers in N, N-dimethylformamide (DMF) at 70 °C is evident from the formation of narrow polydisperse polymers, the molecular weight controlled by the monomer/chain transfer agent (CTA) molar ratio and the linear relationship between molecular weight and monomer conversion. The resulting well-defined polymers were used as macro-CTAs to prepare corresponding diblock copolymers by RAFT polymerization of methyl (meth)acrylate monomers. Deprotection of Boc groups in the homopolymers and block copolymers under acidic conditions produced cationic, pH-responsive polymers with primary amine moieties at the side chains. The optical activity of the homopolymers and block copolymers were studied using circular dichroism (CD) spectroscopy and specific rotation measurements. The self-assembling nature of the block copolymers to produce highly ordered structures was illustrated through dynamic light scattering (DLS) and atomic force microscopy (AFM) studies. The side chain amine functionality instills pH-responsive behavior, which makes these cationic polymers attractive candidates for drug delivery applications, as well as for conjugation of biomolecules.

K v 7 channels are enriched at the axonal plasma membrane where their voltage-dependent potassium currents suppress neuronal excitability. Mutations in K v 7.2 and K v 7.3 subunits cause epileptic encephalopathy (EE), yet the underlying pathogenetic mechanism is unclear. Here, we used novel statistical algorithms and structural modeling to identify EE mutation hotspots in key functional domains of K v 7.2 including voltage sensing S4, the pore loop and S6 in the pore domain, and intracellular calmodulin-binding helix B and helix B-C linker. Characterization of selected EE mutations from these hotspots revealed that L203P at S4 induces a large depolarizing shift in voltage dependence of K v 7.2 channels and L268F at the pore decreases their current densities. While L268F severely reduces expression of heteromeric channels in hippocampal neurons without affecting internalization, K552T and R553L mutations at distal helix B decrease calmodulin-binding and axonal enrichment. Importantly, L268F, K552T, and R553L mutations disrupt current potentiation by increasing phosphatidylinositol 4,5-bisphosphate (PIP 2), and our molecular dynamics simulation suggests PIP 2 interaction with these residues. Together, these findings demonstrate that each EE variant causes a unique combination of defects in K v 7 channel function and neuronal expression, and suggest a critical need for both prediction algorithms and experimental interrogations to understand pathophysiology of K v 7-associated EE. Epilepsy is the second most prominent neurological disease (www.epilepsy.com), in which excessive electrical activity within networks of neurons in the brain manifests clinically as recurrent unprovoked seizures 1. Recent discoveries of epilepsy-related genes in multiple laboratories and through large consortia have revealed a diverse array of proteins that may contribute to epileptogenesis 1,2. Among these proteins, neuronal KCNQ/K v 7 potassium (K +) channels have been implicated in epilepsy since mutations in the principle subunits, KCNQ2/K v 7.2 and KCNQ3/K v 7.3, cause Benign Familial Neonatal Epilepsy (BFNE [MIM: 121200]) and Epileptic Encephalopathy (EE [MIM: 613720]) (RIKEE database www.rikee.org). Neuronal K v 7 channels are mainly composed of heterotetramers of K v 7.2 and K v 7.3 3 , which show overlapping distribution in the hippocampus and cortex 4. They generate slowly activating and non-inactivating voltage-dependent K + currents that contribute to resting membrane potential, prevent repetitive and burst firing of action potentials (APs), and modulate AP threshold 3,5-7 .They are enriched at the plasma membrane of axonal initial segments (AIS) and distal axons 8,9 , where APs initiate and propagate 10. Membrane phosphatidylinositol-4,5-bisphosphate (PIP 2) is required for K v 7 channels to open 3 , although its exact binding sites in K v 7.2 and K v 7.3

Glutamate is the most abundant excitatory neurotransmitter in the central nervous system, therefore its precise control is vital for maintaining normal brain function and preventing excitotoxicity 1 . Removal of extracellular glutamate is achieved by plasma membrane-bound transporters, which couple glutamate transport to sodium, potassium and pH gradients using an elevator mechanism [2][3][4][5] . Glutamate transporters also conduct chloride ions via a channel-like process that is thermodynamically uncoupled from transport [6][7][8] . However, the molecular mechanisms that allow these dual-function transporters to carry out two seemingly contradictory roles are unknown. Here we report the cryo-electron microscopy structure of a glutamate transporter homologue in an open-channel state, revealing an aqueous cavity that is formed during the transport cycle. Using functional studies and molecular dynamics simulations, we show that this cavity is an aqueous-accessible chloride permeation pathway gated by two hydrophobic regions, and is conserved across mammalian and archaeal glutamate transporters. Our findings provide insight into the mechanism by which glutamate transporters support their dual function and add a crucial piece of information to aid mapping of the complete transport cycle shared by the SLC1A transporter family.

An effective implementation of enhanced sampling algorithms for molecular dynamics simulations requires a priori knowledge of the approximate reaction coordinate describing the relevant mechanisms in the system. In this work, we focus on the recently developed artificial intelligence-based State Predictive Information Bottleneck (SPIB) approach and demonstrate how SPIB can learn such a reaction coordinate as a deep neural network even from undersampled trajectories. We exemplify its usefulness by achieving more than 40 times acceleration in simulating two model biophysical systems through well-tempered metadynamics performed by biasing along the SPIB-learned reaction coordinate. These include left-to right-handed chirality transitions in a synthetic helical peptide (Aib) 9 and permeation of a small benzoic acid molecule through a synthetic, symmetric phospholipid bilayer. In addition to significantly accelerating the dynamics and achieving back and forth movement between different metastable states, the SPIB-based reaction coordinate gives mechanistic insights into the processes driving these two important problems.