Conventional Molecular Dynamics Research Articles

Rational Discovery of Microtubule-Stabilizing Peptides.

Microtubule (MT) stabilization is an attractive pharmacological strategy to hamper the progress of neurodegenerative diseases. In this regard, seeking peptides with MT-stabilizing properties has awoken great interest. This work reports the rational discovery of two structurally related MT-stabilizing octapeptides using a combination of protein-peptide docking, conventional molecular dynamics, Gaussian accelerated molecular dynamics (GaMD), and tubulin polymerization assays. FASTA sequences for ∼1000 peptides were crafted from single and double mutants of davunetide (NAP) and docked against the Taxol (TX) site on an octameric MT model representing a portion of the MT wall. Docked peptides were rescored after MM minimization and binding free energy refinement through single-point MM/GBSA calculations. The 60 best-ranked peptides were subjected to 50 ns MD simulations on peptide-MT complexes at the terminal TX site in the octameric Tau-MT model resulting in 11 complexes with occupancies greater than 99% and peptide-protein binding free energies less than -40 kcal/mol. Selected peptides were then examined through 300 ns GaMD simulations in complexes containing two identical ligands at the terminal and intermediate TX sites in the Tau-MT model to account for the differential association of MT-binding peptides to different regions of the MT structure. Six candidates showed a favorable MT-binding potential based on the analysis of interaction frequencies and relative mobilities of the complex components, suggesting a pivotal role of Arg278, Gln281, and Arg369 residues for peptides recognition. Four candidates were predicted to preserve an adequate balance of longitudinal and lateral interactions between tubulin dimers in peptide-MT complexes such that MT-stabilizing effects could be expected. MT polymerization experiments confirmed that four peptides (HAPVSIHQ, NYPVSIHQ, NWPVSIWQ, HAPVSIIQ) exhibit MT-stabilizing activity in vitro with NWPVSIWQ (P43) and HAPVSIIQ (P52) being the most active. Tryptophan quenching assays verified that P43 and P52 bind to nonpolymeric tubulin, whereas viability experiments on HEK cells confirmed their safety to pursue future pharmacological studies. The results herein presented are valuable to making progress in the rational design of MT-stabilizing peptides.

Melatonin Inhibits hIAPP Oligomerization by Preventing β-Sheet and Hydrogen Bond Formation of the Amyloidogenic Region Revealed by Replica-Exchange Molecular Dynamics Simulation.

The pathogenesis of type 2 diabetes (T2D) is highly related to the abnormal self-assembly of the human islet amyloid polypeptide (hIAPP) into amyloid aggregates. To inhibit hIAPP aggregation is considered a promising therapeutic strategy for T2D treatment. Melatonin (Mel) was reported to effectively impede the accumulation of hIAPP aggregates and dissolve preformed fibrils. However, the underlying mechanism at the atomic level remains elusive. Here, we performed replica-exchange molecular dynamics (REMD) simulations to investigate the inhibitory effect of Mel on hIAPP oligomerization by using hIAPP20–29 octamer as templates. The conformational ensemble shows that Mel molecules can significantly prevent the β-sheet and backbone hydrogen bond formation of hIAPP20–29 octamer and remodel hIAPP oligomers and transform them into less compact conformations with more disordered contents. The interaction analysis shows that the binding behavior of Mel is dominated by hydrogen bonding with a peptide backbone and strengthened by aromatic stacking and CH–π interactions with peptide sidechains. The strong hIAPP–Mel interaction disrupts the hIAPP20–29 association, which is supposed to inhibit amyloid aggregation and cytotoxicity. We also performed conventional MD simulations to investigate the influence and binding affinity of Mel on the preformed hIAPP1–37 fibrillar octamer. Mel was found to preferentially bind to the amyloidogenic region hIAPP20–29, whereas it has a slight influence on the structural stability of the preformed fibrils. Our findings illustrate a possible pathway by which Mel alleviates diabetes symptoms from the perspective of Mel inhibiting amyloid deposits. This work reveals the inhibitory mechanism of Mel against hIAPP20–29 oligomerization, which provides useful clues for the development of efficient anti-amyloid agents.

Modified Protein-Water Interactions in CHARMM36m for Thermodynamics and Kinetics of Proteins in Dilute and Crowded Solutions.

Proper balance between protein-protein and protein-water interactions is vital for atomistic molecular dynamics (MD) simulations of globular proteins as well as intrinsically disordered proteins (IDPs). The overestimation of protein-protein interactions tends to make IDPs more compact than those in experiments. Likewise, multiple proteins in crowded solutions are aggregated with each other too strongly. To optimize the balance, Lennard-Jones (LJ) interactions between protein and water are often increased about 10% (with a scaling parameter, λ = 1.1) from the existing force fields. Here, we explore the optimal scaling parameter of protein-water LJ interactions for CHARMM36m in conjunction with the modified TIP3P water model, by performing enhanced sampling MD simulations of several peptides in dilute solutions and conventional MD simulations of globular proteins in dilute and crowded solutions. In our simulations, 10% increase of protein-water LJ interaction for the CHARMM36m cannot maintain stability of a small helical peptide, (AAQAA)3 in a dilute solution and only a small modification of protein-water LJ interaction up to the 3% increase (λ = 1.03) is allowed. The modified protein-water interactions are applicable to other peptides and globular proteins in dilute solutions without changing thermodynamic properties from the original CHARMM36m. However, it has a great impact on the diffusive properties of proteins in crowded solutions, avoiding the formation of too sticky protein-protein interactions.

Atomic Mechanisms of Transthyretin Tetramer Dissociation Studied by Molecular Dynamics Simulations.

The dissociation of the transthyretin (TTR) tetramer into a monomer is closely related to various TTR amyloidoses in humans. While the tetramer dissociation has been reported to be the rate-limiting step for TTR aggregation, few details are known about the mechanism. Here, molecular dynamics (MD) simulations were performed by combining conventional MD and biased metadynamics to investigate the mechanism for the wild-type (WT) and mutant (T119M) structures. Both were found to have a great deal in common. Conventional MD simulations reveal that interfacial hydrophobic interactions contribute significantly to stabilize the tetramer. Interfacial residues including L17, V20, L110, and V121 with close contacts form a hydrophobic channel. Metadynamics simulations indicate that the mouth opening of the hydrophobic channel is the first and the most difficult step for dissociation. Interactions of V20 between opposing dimers lock four monomers into the tetramer, and disruption of the interactions is found to be involved in the final step. During the dissociation, an increasing extent of solvation was observed by calculating the radial distribution functions of water around interfacial hydrophobic residues, suggesting that water plays a role in driving the tetramer dissociation. Moreover, compared to T119, residue M119 has a longer side chain that extends into the hydrophobic channel, making solvation more difficult, consistent with a higher energy barrier for dissociation of the T119M tetramer. This result provides a good explanation for the protective role of the T119M mutation. Overall, this study can provide atomic-level insights to better understand the pathogenesis of TTR amyloidosis and guide rational drug design in the future.

A New Transfer Free Energy Based Implicit Solvation Model for the Description of Disordered and Folded Proteins.

Most biological events occur on time scales that are difficult to access using conventional all-atom molecular dynamics simulations in explicit solvent. Implicit solvent techniques offer a promising solution to this problem, alleviating the computational cost associated with the simulation of large systems and accelerating the sampling compared to explicit solvent models. The substitution of water molecules by a mean field, however, introduces simplifications that may penalize accuracy and impede the prediction of certain physical properties. We demonstrate that existing implicit solvent models developed using a transfer free energy approach, while satisfactory at reproducing the folding behavior of globular proteins, fare less well in characterizing the conformational properties of intrinsically disordered proteins. We develop a new implicit solvent model that maximizes the degree of accuracy for both disordered and folded proteins. We show, by comparing the simulation outputs to experimental data, that in combination with the a99SB-disp force field, the implicit solvent model can describe both disordered (aβ40, PaaA2, and drkN SH3) and folded ((AAQAA)3, CLN025, Trp-cage, and GTT) peptides. Our implicit solvent model permits a computationally efficient investigation of proteins containing both ordered and disordered regions, as well as the study of the transition between ordered and disordered protein states.

Efflux dynamics of the antiseizure drug, levetiracetam, through the P-glycoprotein channel revealed by advanced comparative molecular simulations

Understanding the precise mechanistic details of the possible binding and transport of antiseizure medications (ASMs) through the P-glycoprotein (P-gp) efflux pump is essential to find strategies for the treatment of patients with epilepsy resistant to ASMs. In the present work, conventional molecular dynamics, binding free energy calculations, steered molecular dynamics and umbrella sampling were applied to study the interactions of levetiracetam and brivaracetam with P-gp and their possible egress path from the binding site. Comparative results for the control drugs, zosuquidar and verapamil, confirmed their established P-gp inhibitory activity. Brivaracetam, a non-substrate of P-gp, demonstrated stronger static and dynamic interactions with the exporter protein, than levetiracetam. The potential of mean force calculations indicated that the energy barriers through the ligand export were the lowest for levetiracetam, suggesting the drug as a P-gp substrate with facile passage through the transporter channel. Our findings also stressed the contribution of nonpolar interactions with P-gp channel lining as well as with membrane lipid molecules to hamper the ASM efflux by the transmembrane exporter. Appropriate structural engineering of the ASMs is thus recommended to address drug-resistant epilepsy.

Gaussian Accelerated Molecular Dynamics in OpenMM.

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

Structural Validation by the G-Factor Properly Regulates Boost Potentials Imposed in Conformational Sampling of Proteins.

Free energy landscapes (FELs) of proteins are indispensable for evaluating thermodynamic properties. Molecular dynamics (MD) simulation is a computational method for calculating FELs; however, conventional MD simulation frequently fails to search a broad conformational subspace due to its accessible timescale, which results in the calculation of an unreliable FEL. To search a broad subspace, an external bias can be imposed on a protein system, and biased sampling tends to cause a strong perturbation that might collapse the protein structures, indicating that the strength of the external bias should be properly regulated. This regulation can be challenging, and empirical parameters are frequently employed to impose an optimal bias. To address this issue, several methods regulate the external bias by referring to system energies. Herein, we focused on protein structural information for this regulation. In this study, a well-established structural indicator (the G-factor) was used to obtain structural information. Based on the G-factor, we proposed a scheme for regulating biased sampling, which is referred to as a G-factor-based external bias limiter (GERBIL). With GERBIL, the configurations were structurally validated by the G-factor during biased sampling. As an example of biased sampling, an accelerated MD (aMD) simulation was adopted in GERBIL (aMD-GERBIL), whereby the aMD simulation was repeatedly performed by increasing the strength of the boost potential. Furthermore, the configurations sampled by the aMD simulation were structurally validated by their G-factor values, and aMD-GERBIL stopped increasing the strength of the boost potential when the sampled configurations were regarded as low-quality (collapsed) structures. This structural validation is regarded as a "Brake" of the boost potential. For demonstrations, aMD-GERBIL was applied to globular proteins (ribose binding and maltose-binding proteins) to promote their large-amplitude open-closed transitions and successfully identify their domain motions.

A comparative in silico study to detect the effect of food-additives on metabolic protein and its perturbations compensated by osmolytes

Since its inception, food additive has been an integral part of the food processing industry with various commercial roles. Besides its advantages, various studies have already highlighted its long-term adverse effects on human health. However, in terms of protein structures and functions, the innate mechanism that triggers these effects has not been elucidated in previously reported studies. Our work takes an in silico approach to delve into structural implications resulting from these additives with three well studied metabolic proteins-lysozyme, bovine serum albumin (BSA) and ribonuclease A. Three classes of food additives- synthetic color, preservatives, and phosphate-containing, are taken here to understand their effects on the aforementioned metabolic proteins. Conventional molecular docking and dynamics (MD) studies reveal that these additives induce significant structural perturbations. Among them, carmoisine brings about the most secondary structural changes for lysozyme and ribonuclease A, whereas sodium tripolyphosphate affects BSA the most. To restore the secondary structural loss, we further examine the roles of osmolytes through cross-docking and higher timescale MD simulations. These studies unravel that application of osmolytes like raffinose and trehalose triggers structural restoration for BSA, lysozyme and ribonuclease A, and highlight their roles as co-formulants to alleviate the adverse effects of food additives.

Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials.

Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede the proper sampling of the free energy landscapes when using conventional molecular dynamics simulations. One such method is variationally enhanced sampling (VES), which is based on a variational principle where a bias potential in the space of some chosen slow degrees of freedom, or collective variables, is constructed by minimizing a convex functional. In practice, the bias potential is taken as a linear expansion in some basis function set. So far, primarily basis functions delocalized in the collective variable space, like plane waves, Chebyshev, or Legendre polynomials, have been used. However, there has not been an extensive study of how the convergence behavior is affected by the choice of the basis functions. In particular, it remains an open question if localized basis functions might perform better. In this work, we implement, tune, and validate Daubechies wavelets as basis functions for VES. The wavelets construct orthogonal and localized bases that exhibit an attractive multiresolution property. We evaluate the performance of wavelet and other basis functions on various systems, going from model potentials to the calcium carbonate association process in water. We observe that wavelets exhibit excellent performance and much more robust convergence behavior than all other basis functions, as well as better performance than metadynamics. In particular, using wavelet bases yields far smaller fluctuations of the bias potential within individual runs and smaller differences between independent runs. Based on our overall results, we can recommend wavelets as basis functions for VES.

Notoginsenoside R1 Regulates Ischemic Myocardial Lipid Metabolism by Activating the AKT/mTOR Signaling Pathway.

Ischemic heart diseases are responsible for more than one-third of all deaths worldwide. Radix notoginseng is widely used to treat ischemic heart disease in China and other Asian countries, and notoginsenoside R1 (NGR1) is its characteristic and large-amount ingredient. However, the potential molecular mechanisms of NGR1 in improving ischemic heart diseases are unclear. In this study, we combined pharmacological evaluation with network pharmacology, myocardial proteomics, and conventional molecular dynamics (MD) simulation to explore the cardio-protection mechanisms of NGR1. Our results revealed that NGR1 improved the echocardiographic, tissue pathological, and serum biochemical perturbations in myocardial ischemic rats. The network pharmacology studies indicated that NGR1 mainly regulated smooth muscle cell proliferation, vasculature development, and lipid metabolism signaling, especially in the PI3K/AKT pathway. Myocardial proteomics revealed that the function of NGR1 was focused on regulating metabolic and energy supply processes. The research combined reverse-docked targets with differential proteins and demonstrated that NGR1 modulated lipid metabolism in ischemic myocardia by interacting with mTOR and AKT. Conventional MD simulation was applied to investigate the influence of NGR1 on the structural stabilization of the mTOR and AKT complex. The results suggested that NGR1 can strengthen the affinity stabilization of mTOR and AKT. Our study first revealed that NGR1 enhanced the affinity stabilization of mTOR and AKT, thus promoting the activation of the AKT/mTOR pathway and improving lipid metabolic abnormity in myocardial ischemic rats.

Molecular Dynamics Simulation Investigation of the Binding and Interaction of the EphA6-Odin Protein Complex.

Protein-protein interaction plays an important role in the development of almost all cells. Elucidating the dynamic binding and affinity of a protein-protein complex is essential for understanding the biological functions of proteins. EphA6 and Odin proteins are members of the Eph (erythropoietin-producing hepatocyte) receptor family and the Anks (ankyrin repeat and sterile α motif domain-containing) family, respectively. Odin significantly functions in regulating endocytosis, degradation, and stability of EphA receptors. In this work, the key residues of the interaction interface were determined through a hydrogen bond, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and dynamic correlation analysis of the conventional molecular dynamics (MD) simulations. The calculated standard binding free energy, -7.92 kcal/mol, between EphA6 and Odin is quite consistent with the experimental measurement value, -8.73 kcal/mol. By the combination of several MD simulation techniques, our investigation of the binding process reveals the detailed representative characteristics of the entire binding pathway at the molecular level. Based on the obtained potential of the mean force (PMF) curve, the analysis of the simulation trajectories shows that the residue Arg1013 in the receptor EphA6 is responsible for capturing Asp739 and Asp740 in the ligand Odin during the initial stage of binding. In the later stage of binding, the hydrogen bonds and salt bridges between a series of residues Lys973, Leu1007, Gly1009, His1010, and Arg1012 in the receptor and residues Leu735, Asn736, Asp739, Asp740, and Asp753 in the ligand mainly contribute to the stability of the protein complex. In addition, the specific change process of the receptor-ligand-binding mode is also clarified during the binding process. Our present simulation will promote a deep understanding of the protein-protein interaction, and the identified key interresidue interaction will be theoretical guidance for the design of protein drugs.

Fast evaluation technique for the shear viscosity and ionic conductivity of electrolyte solutions

With the growing need to obtain ideal materials for various applications, there is an increasing interest in computational methods to rapidly and accurately search for materials. Molecular dynamics simulation is one of the successful methods used to investigate liquid electrolytes with high transport properties applied in lithium-ion batteries. However, further reduction in computational cost is required to find a novel material with the desired properties from a large number of combinations. In this study, we demonstrate an effective fast evaluation technique for shear viscosity and ionic conductivity by molecular dynamics simulation for an exhaustive search of electrolyte materials with high transport properties. The proposed model was combined with a short-time correlation function of the stress tensor and empirical relationships to address the issues of inefficient and uncertain evaluation by conventional molecular dynamics methods. Because we focus on liquid electrolytes consisting of organic solvents and lithium salts, our model requires dissociation ratio and effective diffusion size of lithium salts. Our method is applied to search for the compositional combinations of electrolytes with superior transport properties even at low temperatures. These results correlate well with experimental results.

Integrative Modeling, Molecular Mechanics, and Molecular Dynamics Evaluation of Genomics Variants in KMT2C (MLL3), a Gene Involved in Kleefstra Syndrome Type 2

Kleefstra Syndrome (KS) is a genetic, neurodevelopmental disorder characterized by intellectual disability, infantile hypotonia, severe expressive language delay, and characteristic facial appearance, with a spectrum of other distinct clinical manifestations. Pathogenic mutations in the epigenetic modifier, type 2 lysine methyltransferase (KMT2C), are attributed to cause KS core features in individuals who are Euchromatic Histone Lysine Methyltransferase 1, EHMT1, mutation negative. These individuals are designated as having KS type 2. In this study, we made use of multidimensional approaches, including conventional genomic bioinformatics, molecular modeling, molecular mechanics, and molecular dynamics simulations, to understand and enhance the annotation and potential mechanisms by which disease‐associated missense variants affect KMT2C function. In addition, we report a scoring system based on statistical integration and modeling of data derived from the structure and dynamics of KMT2C, which allows us to classify germline variants into SV (Structural Variants), DV (Dynamic Variants), SDV (Structural and Dynamic Variant), and VUS (Variant of Uncertain Significance). Moreover, these scores of disease‐associated variants reflect alterations in molecular fitness when compared with tolerated, benign variants, used as controls. Thus, these studies provide data that is more refined, both structurally and functionally for each variant, compared to current annotation tools used in human genomics databases and reveal mechanisms for their dysfunction not predictable from clinical genomic methods alone. This new knowledge extends our understanding of molecular mechanisms underlying the dysfunction of KS type 2‐associated genomic mutations. Lastly, by identifying KMT2C mutation‐specific druggable conformations, this study builds the trajectory toward the future development of small molecules to ameliorate the symptoms of this disease.

A lesson for the maestro of the replication fork: Targeting the protein‐binding interface of proliferating cell nuclear antigen for anticancer therapy

The proliferating cell nuclear antigen (PCNA) has emerged as a promising candidate for the development of novel cancer therapeutics. PCNA is a nononcogenic mediator of DNA replication that regulates a diverse range of cellular functions and pathways through a comprehensive list of protein-protein interactions. The hydrophobic binding pocket on PCNA offers an opportunity for the development of inhibitors to target various types of cancers and modulate protein-protein interactions. In the present study, we explored the binding modes and affinity of molecule I1 (standard molecule) with the previously suggested dimer interface pocket and the hydrophobic pocket present on the frontal side of the PCNA monomer. We also identified potential lead molecules from the library of in-house synthesized 3-methylenisoindolin-1-one based molecules to inhibit the protein-protein interactions of PCNA. Our results were based on robust computational methods, including molecular docking, conventional, steered, and umbrella sampling molecular dynamics simulations. Our results suggested that the standard inhibitor I1 interacts with the hydrophobic pocket of PCNA with a higher affinity than the previously suggested binding site. Also, the proposed molecules showed better or comparable binding free energies as calculated by the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach and further validated by enhanced umbrella sampling simulations. In vitro and in vivo methods could test the computationally suggested molecules for advancement in the drug discovery pipeline.

Practical Protocols for Efficient Sampling of Kinase-Inhibitor Binding Pathways Using Two-Dimensional Replica-Exchange Molecular Dynamics.

Molecular dynamics (MD) simulations are increasingly used to study various biological processes such as protein folding, conformational changes, and ligand binding. These processes generally involve slow dynamics that occur on the millisecond or longer timescale, which are difficult to simulate by conventional atomistic MD. Recently, we applied a two-dimensional (2D) replica-exchange MD (REMD) method, which combines the generalized replica exchange with solute tempering (gREST) with the replica-exchange umbrella sampling (REUS) in kinase-inhibitor binding simulations, and successfully observed multiple ligand binding/unbinding events. To efficiently apply the gREST/REUS method to other kinase-inhibitor systems, we establish modified, practical protocols with non-trivial simulation parameter tuning. The current gREST/REUS simulation protocols are tested for three kinase-inhibitor systems: c-Src kinase with PP1, c-Src kinase with Dasatinib, and c-Abl kinase with Imatinib. We optimized the definition of kinase-ligand distance as a collective variable (CV), the solute temperatures in gREST, and replica distributions and umbrella forces in the REUS simulations. Also, the initial structures of each replica in the 2D replica space were prepared carefully by pulling each ligand from and toward the protein binding sites for keeping stable kinase conformations. These optimizations were carried out individually in multiple short MD simulations. The current gREST/REUS simulation protocol ensures good random walks in 2D replica spaces, which are required for enhanced sampling of inhibitor dynamics around a target kinase.

Probing the competitive inhibitor efficacy of frog-skin alpha helical AMPs identified against ACE2 binding to SARS-CoV-2 S1 spike protein as therapeutic scaffold to prevent COVID-19.

In COVID-19 infection, the SARS-CoV-2 spike protein S1 interacts to the ACE2 receptor of human host, instigating the viral infection. To examine the competitive inhibitor efficacy of broad spectrum alpha helical AMPs extracted from frog skin, a comparative study of intermolecular interactions between viral S1 and AMPs was performed relative to S1-ACE2p interactions. The ACE2 binding region with S1 was extracted as ACE2p from the complex for ease of computation. Surprisingly, the Spike-Dermaseptin-S9 complex had more intermolecular interactions than the other peptide complexes and importantly, the S1-ACE2p complex. We observed how atomic displacements in docked complexes impacted structural integrity of a receptor-binding domain in S1 through conformational sampling analysis. Notably, this geometry-based sampling approach confers the robust interactions that endure in S1-Dermaseptin-S9 complex, demonstrating its conformational transition. Additionally, QM calculations revealed that the global hardness to resist chemical perturbations was found more in Dermaseptin-S9 compared to ACE2p. Moreover, the conventional MD through PCA and the torsional angle analyses indicated that Dermaseptin-S9 altered the conformations of S1 considerably. Our analysis further revealed the high structural stability of S1-Dermaseptin-S9 complex and particularly, the trajectory analysis of the secondary structural elements established the alpha helical conformations to be retained in S1-Dermaseptin-S9 complex, as substantiated by SMD results. In conclusion, the functional dynamics proved to be significant for viral Spike S1 and Dermaseptin-S9 peptide when compared to ACE2p complex. Hence, Dermaseptin-S9 peptide inhibitor could be a strong candidate for therapeutic scaffold to prevent infection of SARS-CoV-2.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00894-022-05117-8.

In Silico Investigation on KAR Signaling Reveals the Significant Dynamic Change of Its Receptor's Structure.

Karrikins (KARs) have been identified as a class of smoke-derived plant growth regulators widely functioning among angiosperms. However, little is known about the mechanism by which these molecules trigger the relevant signal transduction. In this research, conventional molecular dynamics simulations were used to investigate the dynamical behavior of the apo- and holo-forms of the KAR receptor KAI2. The results show that the dynamic binding conformation of KAR1 in the active site is not completely consistent with that in the static crystal and is largely affected by the residue segment of the receptor, Tyr150-Asn180. The binding of the ligand with KAI2 changes the distribution of the electrostatic potential near the active site and drives the conformational transition of the Tyr150-Asn180 segment with strong internal positive correlation. A "dual induction" signaling mechanism is proposed in view of the present calculations. Our work paves way for in-depth understanding of the KAR signal transduction mechanism and sheds light on further experimental and theoretical exploration.

Hydrodynamically Controlled Self-Organization in Mixtures of Active and Passive Colloids.

Active particles are known to exhibit collective behavior and induce structure in a variety of soft-matter systems. However, many naturally occurring complex fluids are mixtures of active and passive components. The authors examine how activity induces organization in such multi-component systems. Mixtures of passive colloids and colloidal micromotors are investigated and it is observed that even a small fraction of active particles induces reorganization of the passive components in an intriguing series of phenomena. Experimental observations are combined with large-scale simulations that explicitly resolve the near- and far-field effects of the hydrodynamic flow and simultaneously accurately treat the fluid-colloid interfaces. It is demonstrated that neither conventional molecular dynamics simulations nor the reduction of hydrodynamic effects to phoretic attractions can explain the observed phenomena, which originate from the flow field that is generated by the active colloids and subsequently modified by the aggregating passive units. These findings not only offer insight into the organization of biological or synthetic active-passive mixtures, but also open avenues to controlling the behavior of passive building blocks by means of small amounts of activeparticles.

Small angle symmetry splitting of helicene-based molecular wires on pyrolytic graphite

Synthesis of inherently chiral materials and investigation of their self-assembly into molecular wires or 2D crystals belongs to hot topics in nanotechnology. Here we report an inherent splitting of orientational symmetry of 10–500 nm long molecular wires assembled from 3 nm chiral helicene-based macrocycles on atomically flat HOPG surface. The symmetry splitting of molecular wire orientation by a small angle of (6.5 ± 0.5)° is attributed to interaction of individual helicene-based macrocycle with HOPG. There is a good correlation between experimental AFM data and theoretical simulations using ReaxFF force field and Lennard-Jones (L-J) potential. In particular the new 1000 times faster computational method based on L-J potential and sequential addition of molecules is able to simulate formation of molecular wires and emergence of their symmetry splitting, which was not possible to do by conventional molecular dynamics. The method is also sensitive to chirality of the studied molecules; enantiomers and racemates placed on HOPG form different arrangements. This opens new possibilities for simulations of large molecular systems.