CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field

158

The transmembrane protein 16 (TMEM16) family of membrane proteins includes both lipid scramblases and ion channels involved in olfaction, nociception, and blood coagulation. The crystal structure of the fungal Nectria haematococca TMEM16 (nhTMEM16) scramblase suggested a putative mechanism of lipid transport, whereby polar and charged lipid headgroups move through the low-dielectric environment of the membrane by traversing a hydrophilic groove on the membrane-spanning surface of the protein. Here, we use computational methods to explore the membrane-protein interactions involved in lipid scrambling. Fast, continuum membrane-bending calculations reveal a global pattern of charged and hydrophobic surface residues that bends the membrane in a large-amplitude sinusoidal wave, resulting in bilayer thinning across the hydrophilic groove. Atomic simulations uncover two lipid headgroup-interaction sites flanking the groove. The cytoplasmic site nucleates headgroup-dipole stacking interactions that form a chain of lipid molecules that penetrate into the groove. In two instances, a cytoplasmic lipid interdigitates into this chain, crosses the bilayer, and enters the extracellular leaflet, and the reverse process happens twice as well. Continuum membrane-bending analysis carried out on homology models of mammalian homologs shows that these family members also bend the membrane-even those that lack scramblase activity. Sequence alignments show that the lipid-interaction sites are conserved in many family members but less so in those with reduced scrambling ability. Our analysis provides insight into how large-scale membrane bending and protein chemistry facilitate lipid permeation in the TMEM16 family, and we hypothesize that membrane interactions also affect ion permeation.TMEM16 | lipid scrambling | continuum membrane models | simulation | anoctamin T he compositional asymmetry between the leaflets of the plasma membrane influences the signaling properties of cells. Scramblases are a class of proteins that disrupt membrane asymmetry by facilitating the transfer of phospholipids from one leaflet to the other in an energy-independent manner. These transmembrane proteins play a role in events such as coagulation of the blood and cellular apoptosis by transporting phosphatidylserine (PS) from the inner leaflet to the outer leaflet of the plasma membrane (1). In particular, transmembrane protein 16 (TMEM16) family members have gained recent attention for their role in phospholipid scrambling in platelets and fungi. The TMEM16 family members have diverse functions. For example, TMEM16A and -B are calcium-activated chloride channels, TMEM16F is a nonspecific cation channel and scramblase, and the fungal Aspergillus fumigatus TMEM16 is another dual scramblase/ion channel (2-6).The structure of the Nectria haematococca TMEM16 (nhTMEM16) membrane protein revealed a possible mechanism for phospholipid conduction across the membrane (Fig. 1A) (7). The protein forms a dimer, and each subunit has a hydrophilic groove composed of polar...

Section: Methodsmentioning

confidence: 99%

“…All simulations were run in the isothermal-isobaric (NPT) ensemble with Amber on GPUs using the CHARMM36 force field (45,46). The membrane simulation protocol follows closely recent published standards (44). Each system 1 simulation was run for 120 ns each, whereas system 2 simulations were run for 400 ns.…”

Section: Methodsmentioning

confidence: 99%

Atomistic insight into lipid translocation by a TMEM16 scramblase

Bethel

Grabe

2016

158

“…Results were validated for WT NIS with explicit water and a POPC membrane using GROMACS 5.0 (72,73). The initial water molecules and the bilayer were built using the web-based automated builder CHARMM-GUI (74)(75)(76). The protein model used was the same as that used in the implicit solvent simulation.…”

Section: Methodsmentioning

confidence: 99%

“…The equilibrated system was extended into a 100-ns-long MD production simulation using a Nose-Hoover thermostat. The LINear Constant Solvent (LINCS) algorithm was used to constrain bonds, and the Particle Mesh Ewald algorithm was used to treat long-range electrostatic interactions during equilibration of the system and MD production runs (72)(73)(74)(75)(76)(77).…”

Section: Methodsmentioning

confidence: 99%

Na ⁺ coordination at the Na2 site of the Na ⁺ /I ⁻ symporter

Ferrandino

Nicola

Sánchez

et al. 2016

The sodium/iodide symporter (NIS) mediates active I− transport in the thyroid—the first step in thyroid hormone biosynthesis—with a 2 Na+: 1 I− stoichiometry. The two Na+ binding sites (Na1 and Na2) and the I− binding site interact allosterically: when Na+ binds to a Na+ site, the affinity of NIS for the other Na+ and for I− increases significantly. In all Na+-dependent transporters with the same fold as NIS, the side chains of two residues, S353 and T354 (NIS numbering), were identified as the Na+ ligands at Na2. To understand the cooperativity between the substrates, we investigated the coordination at the Na2 site. We determined that four other residues—S66, D191, Q194, and Q263—are also involved in Na+ coordination at this site. Experiments in whole cells demonstrated that these four residues participate in transport by NIS: mutations at these positions result in proteins that, although expressed at the plasma membrane, transport little or no I−. These residues are conserved throughout the entire SLC5 family, to which NIS belongs, suggesting that they serve a similar function in the other transporters. Our findings also suggest that the increase in affinity that each site displays when an ion binds to another site may result from changes in the dynamics of the transporter. These mechanistic insights deepen our understanding not only of NIS but also of other transporters, including many that, like NIS, are of great medical relevance.

“…Periodic boundary conditions were applied in all directions. Each system of protein, water, and counter ion was prepared using CHARMM-GUI (57,58), which generates a series of GROMACS inputs for subsequent MD simulations.…”

Section: Methodsmentioning

confidence: 99%

Sequence-, structure-, and dynamics-based comparisons of structurally homologous CheY-like proteins

Maisuradze

Yin

et al. 2017

We recently introduced a physically based approach to sequence comparison, the property factor method (PFM). In the present work, we apply the PFM approach to the study of a challenging set of sequences-the bacterial chemotaxis protein CheY, the N-terminal receiver domain of the nitrogen regulation protein NT-NtrC, and the sporulation response regulator Spo0F. These are all response regulators involved in signal transduction. Despite functional similarity and structural homology, they exhibit low sequence identity. PFM sequence comparison demonstrates a statistically significant qualitative difference between the sequence of CheY and those of the other two proteins that is not found using conventional alignment methods. This difference is shown to be consonant with structural characteristics, using distance matrix comparisons. We also demonstrate that residues participating strongly in native contacts during unfolding are distributed differently in CheY than in the other two proteins. The PFM result is also in accord with dynamic simulation results of several types. Molecular dynamics simulations of all three proteins were carried out at several temperatures, and it is shown that the dynamics of CheY are predicted to differ from those of NT-NtrC and Spo0F. The predicted dynamic properties of the three proteins are in good agreement with experimentally determined B factors and with fluctuations predicted by the Gaussian network model. We pinpoint the differences between the PFM and traditional sequence comparisons and discuss the informatic basis for the ability of the PFM approach to detect physical differences between these sequences that are not apparent from traditional alignment-based comparison.amino acid physical properties | protein fluctuations | all-atom simulations