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Zhou, H.-X.

Publications and source records attributed to Zhou, H.-X..

At least 37 records · Page 2Linked to original sources

A Common Pathway for Detergent-Assisted Oligomerization of Aβ42

Amyloid beta (A{beta}) aggregation is a slow process without seeding or assisted nucleation. Sodium dodecyl sulfate (SDS) micelles stabilize A{beta}42 small oligomers (in the dimer-tetramer range); subsequent SDS removal leads to a 150-kD A{beta}42 oligomer. Dodecylphosphorylcholine (DPC) micelles also stabilize an A{beta}42 tetramer. Here we characterize the detergent-assisted oligomerization pathway by solid-state NMR spectroscopy and molecular dynamics simulations. SDS and DPC-induced oligomers have the same structure, implying a common oligomerization pathway. An antiparallel {beta}-sheet formed by the C-terminal region, the only stable structure in SDS and DPC micelles, is directly incorporated into the 150-kD oligomer. Three Gly residues (at positions 33, 37, and 38) create holes that are filled by the SDS and DPC hydrocarbon tails, thereby turning a potentially destabilizing feature into a stabilizing factor. These observations have implications for endogenous A{beta} aggregation at cellular interfaces.

biophysics↗

Dimeric Transmembrane Structure of the SARS-CoV-2 E Protein

The SARS-CoV-2 E protein is a transmembrane (TM) protein with its N-terminus exposed on the external surface of the virus. Here, the TM structure of the E protein is characterized by oriented sample and magic angle spinning solid-state NMR in lipid bilayers and refined by molecular dynamics simulations. This protein has been found to be a pentamer, with a hydrophobic pore that appears to function as an ion channel. We identified only a symmetric helix-helix interface, leading to a dimeric structure that does not support channel activity. The two helices have a tilt angle of only 6{degrees}, resulting in an extended interface dominated by Leu and Val sidechains. While residues Val14-Thr35 are almost all buried in the hydrophobic region of the membrane, Asn15 lines a water-filled pocket that potentially serves as a drug-binding site. The E and other viral proteins may adopt different oligomeric states to help perform multiple functions.

biophysics↗

Atomistic Modeling of Liquid-Liquid Phase Equilibrium Explains Dependence of Critical Temperature on γ-Crystallin Sequence

Liquid-liquid phase separation of protein solutions has regained heightened attention for its biological importance and pathogenic relevance. Coarse-grained models are limited when explaining residue-level effects on phase equilibrium. Here we report phase diagrams for {gamma}-crystallins using atomistic modeling. The calculations were made possible by combining our FMAP method for computing chemical potentials and Brownian dynamics simulations for configurational sampling of dense protein solutions, yielding the binodal and critic temperature (Tc). We obtain a higher Tc for a known high-Tc {gamma}-crystallin, {gamma}F, than for a low-Tc paralog, {gamma}B. The difference in Tc is corroborated by a gap in second virial coefficient. Decomposition of inter-protein interactions reveals one amino-acid substitution between {gamma}B and {gamma}F, from Ser to Trp at position 130, as the major contributor to the difference in Tc. This type of analysis enables us to link phase equilibrium to amino-acid sequence and to design mutations for altering phase equilibrium.

biophysics↗

Magnesium ions mediate ligand binding and conformational transition of the SAM/SAH riboswitch

The SAM/SAH riboswitch binds S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) with similar affinities. Mg2+ is generally known to stabilize RNA structures by neutralizing phosphates, but how it contributes to ligand binding and conformational transition is understudied. Here, extensive molecular dynamics simulations (totaling 120 s) identified over 10 inner-shell Mg2+ ions in the SAM/SAH riboswitch. Six of them line the two sides of a groove to widen it and thereby pre-organize the riboswitch for ligand entry. They also form outer-shell coordination with the ligands and stabilize an RNA-ligand hydrogen bond, which effectively diminish the selectivity between SAM and SAH. One Mg2+ ion unique to the apo form maintains the Shine-Dalgarno sequence in an autonomous mode and thereby facilitates its release for ribosome binding. Mg2+ thus plays vital roles in SAM/SAH riboswitch function.

biophysics↗

Predicting the Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

biophysics↗

Structural Model for Self-Limiting β-strand Arrangement Within an Alzheimer's Amyloid-β Oligomer

Previous reports revealed that sodium dodecyl sulfate near its critical micelle concentration can drive the assembly of A{beta}42 along an oligomeric pathway. This pathway produces a 150 kDa peptide oligomer (approximately 32 peptide molecules or protomers) that does not aggregate further into amyloid fibrils. Solid-state nuclear magnetic resonance (NMR) spectroscopy revealed structural features distinguishing the 150 kDa oligomer from fibrils. A puzzling feature was the coexistence of parallel and antiparallel {beta}-sheets within the oligomer structure. Here we present new atomic-level structural constraints obtained via solid-state NMR spectroscopy, benefitting from improved resolution via sample concentration by ultracentrifugation. In addition, two-dimensional cryo-electron microscopy (cryo-EM) reconstruction revealed a 4-fold symmetric shape. We propose a structural model to rationalize the solid-sate NMR- and cryo-EM-derived structural constraints. This model has a hollow square cylinder shape, with antiparallel {beta}-sheets formed by residues 33-39 lining the inner walls and parallel {beta}-sheets formed by residues 11-22 lining the outer walls. Within successive layers, the outer {beta}-strands on each side of the square cylinder alternate between two forms: one within a U-shaped protomer and another within L-shaped protomer. Molecular dynamics simulations show that, when the oligomer model is embedded in a lipid membrane, ions permeate through the central pore, with cation selectivity. The model further motivates an assembly pathway-based interpretation that may explain why the 150 kDa oligomer does not undergo further aggregation into amyloid fibrils. Significance StatementA{beta} oligomers are thought to be the most toxic species in Alzheimers disease. Their sizes range from 2 to [~]50 protomers. Most published experimental data on A{beta} oligomers indicate that they, like fibrils, are composed of {beta}-sheets, but it is a mystery why any {beta}-sheet aggregate would exist as a stable oligomer without undergoing further aggregation into fibrils. Here, structural constraints from solid-state NMR and cryo-EM led us to an oligomer model with a hollow square cylinder shape capable of conducting ions when embedded in a lipid membrane. Based on the model, we argue that geometric frustration may distinguish the assembly pathway that produces this oligomer from fibril-forming assembly pathways.

biochemistry↗

Why Does Synergistic Activation of WASP, but Not N-WASP, by Cdc42 and PIP2 Require Cdc42 Prenylation?

Human WASP and N-WASP are homologous proteins that require the binding of multiple regulators, including the acidic lipid PIP2 and the small GTPase Cdc42, to relieve autoinhibition before they can stimulate the initiation of actin polymerization. Autoinhibition involves intramolecular binding of the C-terminal acidic and central motifs to an upstream basic region and GTPase binding domain. Little is known about how a single intrinsically disordered protein, WASP or N-WASP, binds multiple regulators to achieve full activation. Here we used molecular dynamics simulations to characterize the binding of WASP and N-WASP with PIP2 and Cdc42. In the absence of Cdc42, both WASP and N-WASP strongly associate with PIP2-containing membranes, through their basic region and also possibly through a tail portion of the N-terminal WH1 domain. The basic region also participates in Cdc42 binding, especially for WASP; consequently Cdc42 binding significantly compromises the ability of the basic region in WASP, but not N-WASP, to bind PIP2. PIP2 binding to the WASP basic region is restored only when Cdc42 is prenylated at the C-terminus and tethered to the membrane. This distinction in the activation of WASP and N-WASP may contribute to their different functional roles.

biophysics↗

Partial Mimicry of the Microtubule Binding of Tau by Its Membrane Binding

Tau, as typical of intrinsically disordered proteins (IDPs), binds to multiple targets including microtubules and acidic membranes. The latter two surfaces are both highly negatively charged, raising the prospect of mimicry in their binding by tau. The tau-microtubule complex was recently determined by cryo-EM. Here we used molecular dynamics simulations to characterize the dynamic binding of tau K19 to an acidic membrane. This IDP can be divided into three repeats, each containing an amphipathic helix. The three amphipathic helices, along with flanking residues, tether the protein to the membrane interface. The separation between and membrane positioning of the amphipathic helices in the simulations are validated by published EPR data. The membrane contact probabilities of individual residues in tau show both similarities to and distinctions from native contacts with microtubules. In particular, a Lys that is conserved among the repeats forms similar interactions with membranes and with microtubules, as does a conserved Val. This partial mimicry facilitates both the membrane anchoring of microtubules by tau and the transfer of tau from membranes to microtubules.

biophysics↗

An Arg/Ala-Rich Helix in the N-Terminal Region of M. tuberculosis FtsQ Anchors FtsZ to Membranes

Mycobacteria tuberculosis (Mtb) inflicts a quarter of the worldwide population. Most drugs for treating tuberculosis target cell growth and division. With rising drug resistance, it becomes ever more urgent to better understand Mtb cell division. This process begins with the formation of the Z-ring via polymerization of FtsZ and anchoring of the Z-ring to the inner membrane. Here, by combining solution and solid-state NMR spectroscopy with molecular dynamics simulations and other techniques, we show that the transmembrane protein FtsQ is a membrane anchor of the Mtb Z-ring. In the otherwise disordered N-terminal cytoplasmic region of FtsQ (residues 1-99), a 29-residue, Arg/Ala-rich -helix is formed that interacts with upstream acidic residues in solution and with acidic lipids at the membrane surface. The same helix also binds to the GTPase domain of FtsZ, with enormous implications for drug binding and Z-ring formation including its curvature.

biophysics↗

Membrane Tethering of SepF, a Membrane Anchor for the Mycobacterium tuberculosis Z-ring

Bacterial cell division begins with the formation of the Z-ring via polymerization of FtsZ and the localization of Z-ring beneath the inner membrane through membrane anchors. In Mycobacterium tuberculosis (Mtb), SepF is one such membrane anchor, but our understanding of the underlying mechanism is very limited. Here we used molecular dynamics simulations to characterize how SepF itself, a water-soluble protein, tethers to acidic membranes that mimic the Mtb inner membrane. In addition to an amphipathic helix (residues 1-12) at the N-terminus, membrane binding also occurs through two stretches of positively charged residues (Arg27-Arg 37 and Arg95-Arg107) in the long linker preceding the FtsZ-binding core domain (residues 128-218). The additional interactions via the disordered linker stabilize the membrane tethering of SepF, and keep the core domain of SepF and hence the attached Z-ring close to the membrane. The resulting membrane proximity of the Z-ring in turn enables its interactions with and thus recruitment of two membrane proteins, FtsW and CrgA, at the late stage of cell division.

biophysics↗

SpiDec: Computing Binodals and Interfacial Tension of Biomolecular Condensates From Simulations of Spinodal Decomposition

Phase separation of intrinsically disordered proteins (IDPs) is a phenomenon associated with many essential cellular processes, but a robust method to compute the binodal from molecular dynamics simulations of IDPs modeled at the all-atom level in explicit solvent is still elusive, due to the difficulty in preparing a suitable initial dense configuration and in achieving phase equilibration. Here we present SpiDec as such a method, based on spontaneous phase separation via spinodal decomposition that produces a dense slab when the system is initiated at a homogeneous, low density. After illustrating the method on four model systems, we apply SpiDec to a tetrapeptide modeled at the all-atom level and solvated in TIP3P water. The concentrations in the dense and dilute phases agree qualitatively with experimental results and point to binodals as a sensitive property for force-field parameterization. SpiDec may prove useful for the accurate determination of the phase equilibrium of IDPs. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/496322v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@118b545org.highwire.dtl.DTLVardef@124e03eorg.highwire.dtl.DTLVardef@1fe3c5forg.highwire.dtl.DTLVardef@2dbc77_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins

For intrinsically disordered proteins (IDPs), a pressing question is how sequence codes for function. Dynamics serves as a crucial link, reminiscent of the role of structure in sequence-function relations of structured proteins. To define general rules governing sequence-dependent backbone dynamics, we carried out long molecular dynamics simulations of eight IDPs. Blocks of residues exhibiting large amplitudes in slow dynamics are rigidified by local inter-residue interactions or secondary structures. A long region or an entire IDP can be slowed down by long-range contacts or secondary- structure packing. On the other hand, glycines promote fast dynamics and either demarcate rigid blocks or facilitate multiple modes of local and long-range inter-residue interactions. The sequence-dependent backbone dynamics endows IDPs with versatile response to binding partners, with some blocks recalcitrant while others readily adapting to intermolecular interactions.

biophysics↗

Artificial Intelligence Guided Conformational Mining of Intrinsically Disordered Proteins

Artificial intelligence recently achieved the breakthrough of predicting the three-dimensional structures of proteins. The next frontier is presented by intrinsically disordered proteins (IDPs), which, representing 30% to 50% of proteomes, readily access vast conformational space. Molecular dynamics (MD) simulations are promising in sampling IDP conformations, but only at extremely high computational cost. Here, we developed generative autoencoders that learn from short MD simulations and generate full conformational ensembles. An encoder represents IDP conformations as vectors in a reduced-dimensional latent space. The mean vector and covariance matrix of the training dataset are calculated to define a multivariate Gaussian distribution, from which vectors are sampled and fed to a decoder to generate new conformations. The ensembles of generated conformations cover those sampled by long MD simulations and are validated by small-angle X-ray scattering profile and NMR chemical shifts. This work illustrates the vast potential of artificial intelligence in conformational mining of IDPs.

biophysics↗

Multiphase Organization Is a Second Phase Transition Within Multi-Component Biomolecular Condensates

We present a mean-field theory for the multiphase organization of multi-component biomolecular condensates and validate the theory by molecular dynamics simulations of model mixtures. A first phase transition results in the separation of the dense phase from the bulk phase. In a second phase transition, the components in the dense phase demix to localize in separate regions that attach to each other. The second phase transition occurs when the strength of cross-species attraction goes below the mean strength of the self-attraction of the individual species and reaches a critical value. At a given strength of cross-species attraction, both of the phase transitions can be observed by decreasing temperature, leading first to phase separation and then to demixing of the dense phase. The theory and simulations establish the disparity in strength between self and cross-species attraction as a main driver for the multiphase organization of multi-component biomolecular condensates. TOC GRAPHICS O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/460104v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@e17fdcorg.highwire.dtl.DTLVardef@9168deorg.highwire.dtl.DTLVardef@7c07bcorg.highwire.dtl.DTLVardef@e0077d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Preferential interactions of a crowder protein with the specific binding site of a native protein complex

The crowded cellular environments provide ample opportunities for proteins to interact with bystander macromolecules, yet direct evidence, let alone residue-specific information, for such nonspecific binding is rare. Here, by combining NMR spectroscopy and atomistic modeling, we investigated how crowders influence the association equilibrium and kinetics of two protein partners, EIN and HPr. Ficoll-70 increases the EIN-HPr binding affinity whereas bovine serum albumin (BSA) decreases the affinity. The opposite effects of the two crowders are quantitatively explained by atomistic modeling, which shows that the stabilizing effect of Ficoll-70 arises from volume exclusion favoring the bound state. In contrast, the destabilizing effect of BSA arises from preferential soft interactions with the free state; notably, BSA has favorable electrostatic interactions with positively charged HPr residues within the EIN-binding site. Some of the residues from this site indeed experience significant chemical shift perturbation when titrated with BSA, while the relaxation rates of HPr backbone amides exhibit overall elevation. Furthermore, relaxation dispersion data indicate that Ficoll-70 and BSA both slow down the EIN-HPr association rate, but change the dissociate rate in opposite directions. The observations on kinetics are accounted for by two effects of the crowders: increasing the solution microviscosity and reshaping the EIN-HPr interaction energy surface. The kind of preferential interactions between BSA and HPr that leads to competition with EIN should be prevalent in cellular environments. Our NMR results and atomistic modeling provide benchmarks, at both qualitative and quantitative levels, for the effects of crowded cellular environments on protein-protein specific interactions. Significance StatementAlthough nonspecific binding of crowder macromolecules with functional proteins is likely prevalent in vivo, direct evidence is rare. Here we present NMR characterizations showing that bovine serum albumin preferentially interacts with a specific binding site on HPr, leading to competition with the latters partner EIN. The preferential interactions result in destabilization of the EIN-HPr native complex and speedup of its dissociation, contrary to expectations from excluded-volume and viscosity effects. Atomistic modeling of macromolecular crowding rationalizes the experimental observations, and provides qualitative and quantitative insight into the influences of the crowded cellular environment on protein-protein specific interactions. Our work also has implications for evolution, regarding how nonspecific binding can be either minimized or exploited for gaining new functions.

biophysics↗

Binding Free energy Decomposition and Multiple Unbinding Paths of Buried Ligands in a PreQ1 Riboswitch

Riboswitches are naturally occurring RNA elements that control bacterial gene expression by binding to specific small molecules. They serve as important models for RNA-small molecule recognition and have also become a novel class of targets for developing antibiotics. Here, we carried out conventional and enhanced-sampling molecular dynamics (MD) simulations, totaling 141.5 s, to characterize the determinants of binding free energies and unbinding paths for the cognate and synthetic ligands of a PreQ1 riboswitch. Binding free energy analysis showed that two triplets of nucleotides U6-C15-A29 and G5-G11-C16, contribute the most to the binding of the cognate ligands, by hydrogen bonding and by base stacking, respectively. Mg2+ ions are essential in stabilizing the binding pocket. For the synthetic ligands, the hydrogen-bonding contributions of the U6-C15-A29 triplet are significantly compromised, and the bound state resembles the apo state in several respects, including the disengagement of the C15-A14-A13 and A32-G33 base stacks. The bulkier synthetic ligands lead to significantly loosening of the binding pocket, including extrusion of the C15 nucleobase and a widening of the C15-C30 groove. Enhanced-sampling simulations further revealed that the cognate and synthetic ligands unbind in almost opposite directions. Our work offers new insight for designing riboswitch ligands.

biophysics↗

A Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening

Virtual screening is receiving renewed attention in drug discovery, but progress is hampered by challenges on two fronts: handling the ever increasing sizes of libraries of drug-like compounds, and separating true positives from false positives. Here we developed a machine learning-enabled pipeline for large-scale virtual screening that promises breakthroughs on both fronts. By clustering compounds according to molecular properties and limited docking against a drug target, the full library was trimmed by 10-fold; the remaining compounds were then screened individually by docking; and finally a dense neural network was trained to classify the hits into true and false positives. As illustration, we screened for inhibitors against RPN11, the deubiquitinase subunit of the proteasome and a drug target for breast cancer. TOC Graphic O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biophysics↗

Removing Thermostat Distortions of Protein Dynamics in Constant-Temperature Molecular Dynamics Simulations

Molecular dynamics simulations are widely used to determine equilibrium and dynamic properties of proteins. Nearly all simulations nowadays are carried out at constant temperature, with a Langevin thermostat among the most widely used. Thermostats distort protein dynamics, but whether or how such distortions can be corrected has long been an open question. Here we show that constant-temperature simulations with a Langevin thermostat dilate protein dynamics and present a correction scheme to remove the dynamic distortions. Specifically, ns-scale time constants for overall rotation are dilated significantly but sub-ns time constants for internal motions are dilated modestly, while all motional amplitudes are unaffected. The correction scheme involves contraction of the time constants, with the contraction factor a linear function of the time constant to be corrected. The corrected dynamics of eight proteins are validated by NMR data for rotational diffusion and for backbone amide and side-chain methyl relaxation. The present work demonstrates that, even for complex systems like proteins with dynamics spanning multiple timescales, one can predict how thermostats distort protein dynamics and remove such distortions. The correction scheme will have wide applications, facilitating force-field parameterization and propelling simulations to be on par with NMR and other experimental techniques in determining dynamic properties of proteins. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/447619v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1aa72e8org.highwire.dtl.DTLVardef@15e0a4eorg.highwire.dtl.DTLVardef@f6c41borg.highwire.dtl.DTLVardef@c4e8e8_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗