RESUMEN
The elevator transport mechanism is one of the handful of canonical mechanisms by which transporters shuttle their substrates across the semi-permeable membranes that surround cells and organelles. Studies of molecular function are naturally guided by evolutionary context, but until now this context has been limited for elevator transporters because established evolutionary classification methods have organized them into several apparently unrelated families. Through comprehensive examination of the pertinent structures available in the Protein Data Bank, we show that 62 elevator transporters from 18 families share a conserved architecture in their transport domains consisting of 10 helices connected in 8 topologies. Through quantitative analysis of the structural similarity, structural complexity, and topologically-corrected sequence similarity among the transport domains, we provide compelling evidence that these elevator transporters are all homologous. Using our analysis, we have constructed a phylogenetic tree to enable quantification and visualization of the evolutionary relationships among elevator transporters and their families. We also report several examples of functional features that are shared by elevator transporters from different families. Our findings shed new light on the elevator transport mechanism and allow us to understand it in a far deeper and more nuanced manner.
RESUMEN
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
RESUMEN
Citrate, α-ketoglutarate and succinate are TCA cycle intermediates that also play essential roles in metabolic signaling and cellular regulation. These di- and tricarboxylates are imported into the cell by the divalent anion sodium symporter (DASS) family of plasma membrane transporters, which contains both cotransporters and exchangers. While DASS proteins transport substrates via an elevator mechanism, to date structures are only available for a single DASS cotransporter protein in a substrate-bound, inward-facing state. We report multiple cryo-EM and X-ray structures in four different states, including three hitherto unseen states, along with molecular dynamics simulations, of both a cotransporter and an exchanger. Comparison of these outward- and inward-facing structures reveal how the transport domain translates and rotates within the framework of the scaffold domain through the transport cycle. Additionally, we propose that DASS transporters ensure substrate coupling by a charge-compensation mechanism, and by structural changes upon substrate release.
Asunto(s)
Transportadores de Ácidos Dicarboxílicos/metabolismo , Proteínas de Escherichia coli/metabolismo , Escherichia coli/metabolismo , Microscopía por Crioelectrón , Cristalografía por Rayos X , Lactobacillus acidophilus/metabolismo , Simulación de Dinámica MolecularRESUMEN
Membrane transporters are key gatekeeper proteins at cellular membranes that closely control the traffic of materials. Their function relies on structural rearrangements of varying degrees that facilitate substrate translocation across the membrane. Characterizing these functionally important molecular events at a microscopic level is key to our understanding of membrane transport, yet challenging to achieve experimentally. Recent advances in simulation technology and computing power have rendered molecular dynamics (MD) simulation a powerful biophysical tool to investigate a wide range of dynamical events spanning multiple spatial and temporal scales. Here, we review recent studies of diverse membrane transporters using computational methods, with an emphasis on highlighting the technical challenges, key lessons learned, and new opportunities to illuminate transporter structure and function.
Asunto(s)
Microscopía por Crioelectrón , Proteínas de Transporte de Membrana/metabolismo , Simulación de Dinámica Molecular , Transporte Biológico , Cristalografía por Rayos X , Proteínas de Transporte de Membrana/química , Conformación ProteicaRESUMEN
Biological membranes and their diverse lipid constituents play key roles in a broad spectrum of cellular and physiological processes. Characterization of membrane-associated phenomena at a microscopic level is therefore essential to our fundamental understanding of such processes. Due to the semi-fluid and dynamic nature of lipid bilayers, and their complex compositions, detailed characterization of biological membranes at an atomic scale has been refractory to experimental approaches. Computational modeling and simulation offer a highly complementary toolset with sufficient spatial and temporal resolutions to fill this gap. Here, we review recent molecular dynamics studies focusing on the diversity of lipid composition of biological membranes, or aiming at the characterization of lipid-protein interaction, with the overall goal of dissecting how lipids impact biological roles of the cellular membranes.