Atomic Detail Research Articles

Tegument Protein pp150 Sequence-Specific Peptide Blocks Cytomegalovirus Infection.

Human cytomegalovirus (HCMV) tegument protein pp150 is essential for the completion of the final steps in virion maturation. Earlier studies indicated that three pp150nt (N-terminal one-third of pp150) conformers cluster on each triplex (Tri1, Tri2A and Tri2B), and extend towards small capsid proteins atop nearby major capsid proteins, forming a net-like layer of tegument densities that enmesh and stabilize HCMV capsids. Based on this atomic detail, we designed several peptides targeting pp150nt. Our data show significant reduction in virus growth upon treatment with one of these peptides (pep-CR2) with an IC50 of 1.33 μM and no significant impact on cell viability. Based on 3D modeling, pep-CR2 specifically interferes with the pp150–capsid binding interface. Cells pre-treated with pep-CR2 and infected with HCMV sequester pp150 in the nucleus, indicating a mechanistic disruption of pp150 loading onto capsids and subsequent nuclear egress. Furthermore, pep-CR2 effectively inhibits mouse cytomegalovirus (MCMV) infection in cell culture, paving the way for future animal testing. Combined, these results indicate that CR2 of pp150 is amenable to targeting by a peptide inhibitor, and can be developed into an effective antiviral.

Modeling DNA Opening in the Eukaryotic Transcription Initiation Complexes via Coarse-Grained Models.

Recently, the molecular mechanisms of transcription initiation have been intensively studied. Especially, the cryo-electron microscopy revealed atomic structure details in key states in the eukaryotic transcription initiation. Yet, the dynamic processes of the promoter DNA opening in the pre-initiation complex remain obscured. In this study, based on the three cryo-electron microscopic yeast structures for the closed, open, and initially transcribing complexes, we performed multiscale molecular dynamics (MD) simulations to model structures and dynamic processes of DNA opening. Combining coarse-grained and all-atom MD simulations, we first obtained the atomic model for the DNA bubble in the open complexes. Then, in the MD simulation from the open to the initially transcribing complexes, we found a previously unidentified intermediate state which is formed by the bottleneck in the fork loop 1 of Pol II: The loop opening triggered the escape from the intermediate, serving as a gatekeeper of the promoter DNA opening. In the initially transcribing complex, the non-template DNA strand passes a groove made of the protrusion, the lobe, and the fork of Rpb2 subunit of Pol II, in which several positively charged and highly conserved residues exhibit key interactions to the non-template DNA strand. The back-mapped all-atom models provided further insights on atomistic interactions such as hydrogen bonding and can be used for future simulations.

Physical Vapor Deposition Growth of Ultrathin Molybdenum Dioxide Nanosheets with Excellent Conductivity

A single crystal of 2D layered α‐MoO2 using a simple technique of physical vapor deposition (PVD) method is generated. By adjusting the growth temperature, the thickness of α‐MoO2 single crystals can be tuned to sub ten nanometers. High‐resolution transmission electron microscopy (HRTEM) images verified the atomic structural details of PVD grown orthorhombic MoO2 (α‐MoO2) nanosheet with high quality. Additionally, the unsaturated linear magnetic range (LMR) in the grown nanosheets is up to 5 T. Also, α‐MoO2 nanosheet with low defect displays excellent conductivity that is comparable to the metal silver. Thus, this new nanomaterial can show a promising application as a potential 2D conductor.

Structural anomalies in a published NMR-derived structure of IRAK-M

Signaling by Toll-Like Receptors and the Interleukin-1 Receptor (IL1-R) involves intracellular binding of MyD88, followed by assembly of IL1-R Associated Kinases (IRAKs) into the so-called Myddosome. Using NMR, Nechama et al. determined the structure of the IRAK-M death domain monomer (PDBid: 5UKE). With this structure, they performed a docking study to model the location of IRAK-M in the Myddosome. Based on this, they present a molecular basis for selectivity of IRAK-M towards IRAK1 over IRAK2 binding. When we attempted to use 5UKE as a homology modeling template, we noticed that our 5UKE-based models had structural issues, such as disallowed torsion angles and solvent exposed tryptophans. We therefore analyzed the NMR ensemble of 5UKE using structure validation tools and we compared 5UKE with homologous high-resolution X-ray structures. We identified several structural anomalies in 5UKE, including packing issues, frayed helices and improbable side chain conformations. We used Yasara to build a homology model, based on two high resolution death domain crystal structures, as an alternative model for the IRAK-M death domain (atomic coordinates, modeling details and validation are available at https://swift.cmbi.umcn.nl/gv/service/5uke/). Our model agrees better with known death domain structure information than 5UKE and also with the chemical shift data that was deposited for 5UKE.

Lessons Learned from Responsive Molecular Dynamics Studies of the COVID-19 Virus.

Over the past 18 months, the need to perform atomic detail molecular dynamics simulations of the SARS-CoV-2 virion, its spike protein, and other structures related to the viral infection cycle has led biomedical researchers worldwide to urgently seek out all available biomolecular structure information, appropriate molecular modeling and simulation software, and the necessary computing resources to conduct their work. We describe our experiences from several COVID-19 research collaborations and the challenges they presented in terms of our molecular modeling software development and support efforts, our laboratory's local computing environment, and our scientists' use of non-traditional HPC hardware platforms such as public clouds for large scale parallel molecular dynamics simulations.

The role of the 'sphingoid motif' in shaping the molecular interactions of sphingolipids in biomembranes.

Sphingolipids can be differentiated from other membrane lipids by the distinctive chemistry of the sphingoid long chain base (LCB), which is generated by the condensation of an amino acid (normally but not always serine) and a fatty acyl CoA (normally palmitoyl CoA) by the pyridoxal phosphate-dependent enzyme, serine palmitoyl transferase (SPT). The first five carbon atoms of the sphingoid LCB, herein defined as the 'sphingoid motif', are largely responsible for the unique chemical and biophysical properties of sphingolipids since they can undergo a relatively large number (compared to other lipid species) of molecular interactions with other membrane lipids, via hydrogen-bonding, charge-pairing, hydrophobic and van der Waals interactions. These interactions are responsible, for instance, for the association of sphingolipids with cholesterol in the membrane lipid bilayer. Here, we discuss some of the unique properties of this sphingoid motif, and in addition to outlining how this structural motif drives intra-bilayer interactions, discuss the atomic details of the interactions with two critical players in the biosynthetic pathway, namely SPT, and the ceramide transport protein, CERT. In the former, the selectivity of sphingolipid synthesis relies on a hydrogen bond interaction between Lys379 of SPTLC2 and the l-serine sidechain hydroxyl moiety. In the latter, the entire sphingoid motif is stereoselectively recognized by a hydrogen-bonding network involving all three sphingoid motif heteroatoms. The remarkable selectivity of these interactions, and the subtle means by which these interactions are modified and regulated in eukaryotic cells raises a number of challenging questions about the generation of these proteins, and of their interactions with the sphingoid motif in evolutionary history.

Investigation of glutathione as a natural antioxidant and multitarget inhibitor for Alzheimer’s disease: Insights from molecular simulations

Glutathione (GSH) is the most plentiful nonprotein thiol-containing substance in all kinds of cells, and plays crucial roles in the antioxidant defense system and maintaining redox homeostasis in neurons. Extensive microscopic molecular simulations with atomistic details were performed to examine GSH interaction with three proteins involved in β-Amyloid formation (BACE-1, GSK-3β, AChE). The results show that the binding of GSH to AChE is vertical and from the side of Cys residue, while for BACE-1 it was relatively horizontal. The simultaneous study of MSD and interaction energies proved that due to the stronger interaction between GSH and the active-site of BACE-1, GSH shows the least mobility in the BACE-1 containing system, also due to no binding to GSK-3β, it shows the most mobility in this system. Analyzing the radius of gyration and the molecule's inner angle showed that GSH adopts folded and extended structures in interaction with BACE-1 and AChE, respectively. Estimating binding free energy using MMPBSA calculations proved that GSH binding to BACE-1 (-16.98 kJ/mol) is thermodynamically more favorable than AChE (-8.27 kJ/mol). Contributions of active-site residues in binding free energies revealed that GSH binding into BACE-1 and AChE was controlled more dynamically and thermodynamically, respectively. Cavity size analysis showed that the accessible volume of cavities for GSH in BACE-1 and AChE is sufficient for binding. Furthermore, “adjacent pocket” and “breathing motion” types were suggested for AChE and BACE-1, respectively.

The molecular mechanism of electroporation: Changes in the hydrogen bonds

Electroporation has many technological applications in drug delivery and gene transfection. However, the molecular mechanism of electroporation is unknown. Thus, we propose for the first time that hydrogen bonds play a key role during electroporation based on molecular dynamics and quantum chemistry methods. The electric field affects the hydrogen-bonded network in the membrane system, which induces water molecules to pass through the membrane. Our findings reveal the mechanism of electroporation in atomic details and may have a potential application in controlling the permeability of cell membranes.

Multiscale Simulations to Study the Atomic Structure of Solid Electrolyte Interfaces

The Solid Electrolyte Interface (SEI) is the "most important but least understood" area of research in batteries. A deeper understanding of the atomic structure of SEI can provide a theoretical basis for the development of high energy density batteries. Based on the available experimental results, four generations of SEI models have been developed. However, the above-mentioned SEI models lack atomic details and cannot reasonably explain important experimental phenomena and guide experimental synthesis. Quantum chemistry (QM)-based multi-scale theoretical simulations are a powerful tool to study the atomic structure of interfaces. The authors' group has developed a series of computational methods for SEI simulations in recent years,1 including the Hybrid ab initio molecular dynamics combined with reactive force fields (HAIR)2, the Kinetic Monte Carlo method for simulating lithium dendrite Kinetic Monte Carlo (KMC) method for simulating the growth of lithium dendrites, etc. Applying these methods, we have performed detailed theoretical simulations of the formation of the SEI interface and achieved some milestones, including (1) elucidation of the important initial decomposition reaction mechanism of solute and solvent (Fig. 1a);2 (2) revealing the formation process and structure of the initial inorganic LiF layer of SEI (Fig. 1b);3 (3) resolving the SEI solid-solid phase transition in all-solid-state batteries (Fig. 1b).4 The above theoretical simulation progress provides important theoretical guidance for the development of high energy density and high safety batteries, such as Li-Metal batteries, Li-Sulfur batteries, and all-solid-state batteries. Currently, the Battery open source package developed by the group has implemented most of the above functions.Reference[1] Cheng T; Jaramillo-Botero A; An Q; Ilyin DV; Naserifar S; Goddard WA*;Proc. Natl. Acad. Sci. U.S.A. 2019, 116, 18193.[2] Liu Y; Yu PP; Wu Y; Yang H; Miao X; Huai LY; Goddard WA*; Cheng T*; J. Phys. Chem. Lett. 2021, 12, 1300.[3] Liu Y; Sun QT; Yu PP; Wu Y; Xu L; Yang H; Xie M; Cheng T*; Goddard III WA; J. Phys. Chem. Lett. 2021,12, 2922.[4] Cheng T; Merinov BV*; Morozov S; Goddard WA; ACS Energy Lett. 2017, 2, 1454. Figure 1

Toward revealing atomic deformation mechanics in lithium disilicate and β‐quartz containing glass‐ceramics

AbstractThe mechanics of glass‐ceramics subjected to sharp contact or other loading conditions remain elusive, even after being commercialized in many industrial applications. We present work herein to reveal atomic details of such deformations that are otherwise extremely difficult to probe experimentally for a lithium disilicate (LS2) and β‐quartz containing glass‐ceramics via molecular dynamics simulations. Specifically, the materials are comprised of LS2 and β‐quartz nanocrystals in a residual glass matrix. Regardless of the deformation mechanism, whether it be nanoindentation or crack propagation for samples with pre‐existing flaws, we observe that the LS2 nanocrystal itself undergoes substantial deformation, either by activating dislocations, forming an amorphization zone, or by initiating microcracks at glass‐crystal interfaces or weak crystallographic planes. In contrast, the β‐quartz nanocrystal is not easily deformed and remains almost intact with minimal plastic deformation, thereby forcing shear flow and crack propagation pathways to predominately occur in the residual glass and/or at interfaces. The dramatic difference between the crystalline phases also manifests itself in the deformation mode of interfaces under pure shear loading, in which shear bands preferably occur at the LS2‐glass interfaces, while cavities form at the β‐quartz‐glass interfaces. These observations significantly advance our understanding of glass‐ceramics and pave ways to exploit the understanding for more applications.

Pro219 is an electrostatic color determinant in the light-driven sodium pump KR2

Color tuning in animal and microbial rhodopsins has attracted the interest of many researchers, as the color of their common retinal chromophores is modulated by the amino acid residues forming the chromophore cavity. Critical cavity amino acid residues are often called “color switches”, as the rhodopsin color is effectively tuned through their substitution. Well-known color switches are the L/Q and A/TS switches located in the C and G helices of the microbial rhodopsin structure respectively. Recently, we reported on a third G/P switch located in the F helix of the light-driven sodium pumps of KR2 and JsNaR causing substantial spectral red-shifts in the latter with respect to the former. In order to investigate the molecular-level mechanism driving such switching function, here we present an exhaustive mutation, spectroscopic and computational investigation of the P219X mutant set of KR2. To do so, we study the changes in the absorption band of the 19 possible mutants and construct, semi-automatically, the corresponding hybrid quantum mechanics/molecular mechanics models. We found that the P219X feature a red-shifted light absorption with the only exception of P219R. The analysis of the corresponding models indicate that the G/P switch induces red-shifting variations via electrostatic interactions, while replacement-induced chromophore geometrical (steric) distortions play a minor role. However, the same analysis indicates that the P219R blue-shifted variant has a more complex origin involving both electrostatic and steric changes accompanied by protonation state and hydrogen bond networks modifications. These results make it difficult to extract simple rules or formulate theories for predicting how a switch operates without considering the atomistic details and environmental consequences of the side chain replacement.

Pore-Bound Water at the Key Residue Histidine 37 in Influenza A M2.

Atomic details of structured water molecules are indispensable to understand the thermodynamics of important biological processes including the proton conduction mechanism of the M2 protein. Despite the expectation of structured water molecules based on crystal structures of Influenza A M2, only two water populations have been observed by NMR in reconstituted lipid bilayer samples. These are the bulk‐ and lipid‐associated water populations typically seen in membrane samples. Here, we detect a bound water molecule at a chemical shift of 11 ppm, located near the functional histidine 37 residue in the M2 conductance domain, which comprises residues 18 to 60. Combining 100 kHz magic‐angle spinning NMR, dynamic nuclear polarization and density functional theory calculations, we show that the bound water forms a hydrogen bond to the δ1 nitrogen of histidine 37.

Structural Dynamics and Electronic Properties of Semiconductor Quantum Dots: Computational Insights

Semiconductor quantum dots (QDs) exhibit exciting photophysical properties for a wide variety of applications in the field of energy conversion, lighting, and more recently quantum communication. The photophysics underpinning these applications at ambient conditions strongly depends on atomistic details of their dynamic surface. Neutral organic ligands used in surface passivation play a critical role in determining the structural and optoelectronic properties of these QDs. Small sizes and irregular atomic arrangements make these QD surface–ligand interfaces challenging to explore at the atomistic level. Here, we combine several computational simulation techniques to study thermally induced geometrical fluctuations in stable cadmium selenide (CdSe) QDs with and without ligand passivation. We find that structural fluctuations of surface atoms significantly depend on passivating molecules. The bulky and strongly binding ligands such as phosphine oxides induce a higher extent of interfacial dynamics. Though these stoichiometric QDs do not possess any permanent in-gap states, significant thermal distortion of QD–ligand interfaces can induce fluctuating defectlike states near band edges. Such vibronic dynamics in these QDs also modifies band-edge state positions on sub-picosecond timescale, impacting their functional properties. Our results further suggest that primary amine ligands are optimal choices for QD passivation. These insights may be helpful to make design principles for screening and optimizing passivating ligands best suited for various QD applications, such as for quantum communication technologies.

AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function.

AlphaFold 2 (AF2) was the star of CASP14, the last biannual structure prediction experiment. Using novel deep learning, AF2 predicted the structures of many difficult protein targets at or near experimental resolution. Here, we present our perspective of why AF2 works and show that it is a very sophisticated fold recognition algorithm that exploits the completeness of the library of single domain PDB structures. It has also learned local side chain packing rearrangements that enable it to refine proteins to high resolution. The benefits and limitations of its ability to predict the structures of many more proteins at or close to atomic detail are discussed.

Molecular Dynamics Insight into the Lipid II Recognition by Type A Lantibiotics: Nisin, Epidermin, and Gallidermin

Lanthionine-containing peptides (lantibiotics) have been considered as pharmaceutical candidates for decades, although their clinical application has been restricted. Most lantibiotics kill bacteria via targeting and segregating of the cell wall precursor—membrane-inserted lipid II molecule—in some cases accompanied by pores formation. Nisin-like lantibiotics specifically bind to pyrophosphate (PPi) moiety of lipid II with their structurally similar N-terminal thioether rings A and B. Although possessing higher pore-forming capability, nisin, in some cases, is 10-fold less efficient in vivo as compared to related epidermin and gallidermin peptides, differing just in a few amino acid residues within their target-binding regions. Here, using molecular dynamics simulations, we investigated atomistic details of intermolecular interactions between the truncated analogues of these peptides (residues 1–12) and lipid II mimic (dimethyl pyrophosphate, DMPPi). The peptides adopt similar conformation upon DMPPi binding with backbone amide protons orienting into a single center capturing PPi moiety via simultaneous formation of up to seven hydrogen bonds. Epidermin and gallidermin adopt the complex-forming conformation twice as frequent as nisin does, enhancing the binding by the lysine 4 side chain. Introduction of the similar residue to nisin in silico improves the binding, providing ideas for further design of prototypic antibiotics.

Structures of the human cholecystokinin receptors bound to agonists and antagonists.

Cholecystokinin receptors, CCKAR and CCKBR, are important neurointestinal peptide hormone receptors and play a vital role in food intake and appetite regulation. Here, we report three crystal structures of the human CCKAR in complex with different ligands, including one peptide agonist and two small-molecule antagonists, as well as two cryo-electron microscopy structures of CCKBR-gastrin in complex with Gi2 and Gq, respectively. These structures reveal the recognition pattern of different ligand types and the molecular basis of peptide selectivity in the cholecystokinin receptor family. By comparing receptor structures in different conformational states, a stepwise activation process of cholecystokinin receptors is proposed. Combined with pharmacological data, our results provide atomic details for differential ligand recognition and receptor activation mechanisms. These insights will facilitate the discovery of potential therapeutics targeting cholecystokinin receptors.

Molecular Dynamics and Machine Learning in Catalysts

Given the importance of catalysts in the chemical industry, they have been extensively investigated by experimental and numerical methods. With the development of computational algorithms and computer hardware, large-scale simulations have enabled influential studies with more atomic details reflecting microscopic mechanisms. This review provides a comprehensive summary of recent developments in molecular dynamics, including ab initio molecular dynamics and reaction force-field molecular dynamics. Recent research on both approaches to catalyst calculations is reviewed, including growth, dehydrogenation, hydrogenation, oxidation reactions, bias, and recombination of carbon materials that can guide catalyst calculations. Machine learning has attracted increasing interest in recent years, and its combination with the field of catalysts has inspired promising development approaches. Its applications in machine learning potential, catalyst design, performance prediction, structure optimization, and classification have been summarized in detail. This review hopes to shed light and perspective on ML approaches in catalysts.

Toward Convergence in Free Energy Calculations for Protein Conformational Changes: A Case Study on the Thin Gate of Mhp1 Transporter.

It has been challenging to obtain reliable free energies for protein conformational changes from all-atom molecular dynamics simulations, despite the availability of many enhanced sampling techniques. To alleviate the difficulties associated with the enormous complexity of the conformational space, here we propose a few practical strategies for such calculations, including (1) a stringent method to examine convergence by comparing independent simulations starting from different initial coordinates, (2) adoption of multistep schemes in which the complete conformational change consists of multiple transition steps, each sampled using a distinct reaction coordinate, and (3) application of boundary restraints to simplify the conformational space. We demonstrate these strategies on the conformational changes between the outward-facing and outward-occluded states of the Mhp1 membrane transporter, obtaining the equilibrium thermodynamics of the relevant metastable states, the kinetic rates between these states, and the reactive trajectories that reveal the atomic details of spontaneous transitions. Our approaches thus promise convergent and reliable calculations to examine intuition-based hypotheses and to eventually elucidate the underlying molecular mechanisms of reversible conformational changes in complex protein systems.

Accurate and Transferable Reactive Molecular Dynamics Models from Constrained Density Functional Theory.

Chemical reactions constitute the central feature of many liquid, material, and biomolecular processes. Conventional molecular dynamics (MD) is inadequate for simulating chemical reactions given the fixed bonding topology of most force fields, while modeling chemical reactions using ab initio molecular dynamics is limited to shorter time and length scales given its high computational cost. As such, the multiscale reactive molecular dynamics method provides one promising alternative for simulating complex chemical systems at atomistic detail on a reactive potential energy surface. However, the parametrization of such models is a key barrier to their applicability and success. In this work, we present reactive MD models derived from constrained density functional theory that are both accurate and transferable. We illustrate the features of these models for proton dissociation reactions of amino acids in both aqueous and protein environments. Specifically, we present models for ionizable glutamate and lysine that predict accurate absolute pKa values in water as well as their significantly shifted pKa in staphylococcal nuclease (SNase) without any modification of the models. As one outcome of the new methodology, the simulations show that the deprotonation of ionizable residues in SNase can be closely coupled with side chain rotations, which is a concept likely generalizable to many other proteins. Furthermore, the present approach is not limited to only pKa prediction but can enable the fully atomistic simulation of many other reactive systems along with a determination of the key aspects of the reaction mechanisms.

Solvent-Assisted Li-Ion Transport and Structural Heterogeneity in Fluorinated Battery Electrolytes.

The electrolytes diluted with fluorinated solvents show promising properties toward better battery technology than existing ones. The transport of Li ions in these fluorinated electrolytes is essential to access the performance of a battery. It is believed that the transport of the Li ion in these electrolytes occurs through polar solvents in the matrix of nonpolar solvent molecules. The atomistic details of this mechanism are yet to be proved using the dynamics of these mixtures. In this study, we performed classical molecular dynamics simulations at various temperatures to probe this mechanism through the structure and dynamics of electrolytes at the atomic level. Here, we have shown that the polar fluorinated solvents assist the Li-ion transport in a region of nonpolar solvent. Highly polar molecules also solvate the Li ion at a lower temperature. The nonpolar solvent solvates the Li ion weakly as compared to others. The calculated values of the ionic conductivity from the Green-Kubo relation provide a better match than that from an experimental conductivity meter. Furthermore, we probed the heterogeneity in the dynamics of the electrolytes by calculating the non-Gaussian parameter. We also show that the transport mechanism of the Li ion in diluted concentrated electrolytes is different than a few of the other reported electrolytes. We have also calculated the ion-pair and ion-cage lifetimes to see the most and least lived ion/ion-solvent pairs. The mechanism given from the present study may help to design the fluorinated electrolytes for Li-ion batteries.