Molecular Model Systems Research Articles

How Molecules Became Signs

To explore how molecules became signs I will ask: “What sort of process is necessary and sufficient to treat a molecule as a sign?” This requires focusing on the interpreting system and its interpretive competence. To avoid assuming any properties that need to be explained I develop what I consider to be a simplest possible molecular model system which only assumes known physics and chemistry but nevertheless exemplifies the interpretive properties of interest. Three progressively more complex variants of this model of interpretive competence are developed that roughly parallel an icon-index-symbol hierarchic scaffolding logic. The implication of this analysis is a reversal of the current dogma of molecular and evolutionary biology which treats molecules like DNA and RNA as the original sources of biological information. Instead I argue that the structural characteristics of these molecules have provided semiotic affordances that the interpretive dynamics of viruses and cells have taken advantage of. These molecules are not the source of biological information but are instead semiotic artifacts onto which dynamical functional constraints have been progressively offloaded during the course of evolution.

Finite temperature quantum dynamics of complex systems: Integrating thermo‐field theories and tensor‐train methods

AbstractThis review provides the fundamental theoretical tools for the development of a complete wave‐function formalism for the study of time‐evolution of chemico‐physical systems at finite temperature. The methodology is based on the non‐equilibrium thermo‐field dynamics (NE‐TFD) representation of quantum mechanics, which is alternative to the commonly used density matrix representation. TFD concepts are extended and integrated with the tensor‐train (TT) numerical tools leading to a novel and powerful theoretical and computational framework for the study of complex quantum dynamical problems. In addition, NE‐TFD techniques are extended to enable the study of dissipative open systems via a new formulation of the hierarchical equations of motion (HEOM) fully integrated with TT methodologies. We demonstrate that the combination of the TFD machinery with computational advantages of TTs results in a powerful theoretical and computational framework for scrutinizing dynamics of complex multidimensional electron‐vibrational systems. We illustrate the validity and the computational advantages of the developed methodologies by applying them to the study of quantum coherence effects in the energy‐transfer processes in antenna systems, to the analysis of fingerprints of vibrational modes in electron‐transfer and charge‐transfer processes in various model and realistic multidimensional molecular systems, as well as to simulation of other fundamental models of physical chemistry.This article is categorized under: Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics Theoretical and Physical Chemistry > Statistical Mechanics

Direct comparison of amplitude and geometric measures of spectral inhomogeneity using phase-cycled 2D-IR spectroscopy.

Two-dimensional infrared (2D-IR) spectroscopy provides access to equilibrium dynamics with the extraction of the frequency-fluctuation correlation function (FFCF) from the measured spectra. Several different methods of obtaining the FFCF from experimental spectra, such as the center line slope (CLS), ellipticity, phase slope, and nodal line slope, all depend on the geometrical nature of the 2D line shape and necessarily require spectral extent in order to achieve a measure of the FFCF. Amplitude measures, on the other hand, such as the inhomogeneity index, rely only on signal amplitudes and can, in principle, be computed using just a single point in a 2D spectrum. With a pulse shaper-based 2D-IR spectrometer, in conjunction with phase cycling, we separate the rephasing and nonrephasing signals used to determine the inhomogeneity index. The same measured data provide the absorptive spectrum, needed for the CLS. Both methods are applied to two model molecular systems: tungsten hexacarbonyl (WCO6) and methylcyclopentadienyl manganese tricarbonyl [Cp'Mn(CO)3, MCMT]. The three degenerate IR modes of W(CO)6 lack coherent modulation or noticeable intramolecular vibrational redistribution (IVR) and are used to establish a baseline comparison. The two bands of the MCMT tripod complex include intraband coherences and IVR as well as likely internal torsional motion on a few-picosecond time scale. We find essentially identical spectral diffusion, but faster, non-equilibrium dynamics lead to differences in the FFCFs extracted with the two methods. The inhomogeneity index offers an advantage in cases where spectra are complex and energy transfer can mimic line shape changes due to frequency fluctuations.

Unravelling the nature of intra-molecular hydrogen bonds in curcumin using in-situ low temperature spectroscopic studies

Curcumin, described as a wonder drug owing to various medicinal, viz. anticancer, antiviral, anti-inflammatory etc., properties, can also be seen as a model molecular system to study strong intra-molecular OH----O hydrogen bonds which govern its physico-chemical properties. The study of these hydrogen bonds is important to understand its binding characteristics. Here, we present systematic in-situ variable temperature studies of curcumin in the range 350–75 K using infrared spectroscopy to analyse the effects of external stresses on molecular structure and hydrogen bonding network. The results have been well supported by Raman spectroscopic studies. Our studies show striking difference in the nature of the two intra-molecular hydrogen bonds, generally considered equivalent, which form at the edges of the molecule. Also, the strongest intra-molecular hydrogen bond involving the enol group, present at the centre of the molecule, depicts a remarkable temperature induced strengthening upon cooling. The studies further indicate that the compound does not show any drastic structural transition in the measured temperature range. However, subtle spectral changes associated with reorientations of the hydrogen bonds are noticed across 210 K. These results will be useful to predict reaction pathways during chemical complexation of curcumin.

A Novel Biofilm Model System to Visualise Conjugal Transfer of Vancomycin Resistance by Environmental Enterococci.

Enterococci and biofilm-associated infections are a growing problem worldwide, given the rise in antibiotic resistance in environmental and clinical settings. The increasing incidence of antibiotic resistance and its propagation potential within enterococcal biofilm is a concern. This requires a deeper understanding of how enterococcal biofilm develops, and how antibiotic resistance transfer takes place in these biofilms. Enterococcal biofilm assays, incorporating the study of antibiotic resistance transfer, require a system which can accommodate non-destructive, real-time experimentation. We adapted a Gene Frame® combined with fluorescence microscopy as a novel non-destructive platform to study the conjugal transfer of vancomycin resistance in an established enterococcal biofilm.A multi-purpose fluorescent in situ hybridisation (FISH) probe, in a novel application, allowed the identification of low copy number mobile elements in the biofilm. Furthermore, a Hoechst stain and ENU 1470 FISH probe identified Enterococcus faecium transconjugants by excluding Enterococcus faecalis MF06036 donors. Biofilm created with a rifampicin resistant E. faecalis (MW01105Rif) recipient had a transfer efficiency of 2.01 × 10−3; double that of the biofilm primarily created by the donor (E. faecalis MF06036). Conjugation in the mixed enterococcal biofilm was triple the efficiency of donor biofilm. Double antibiotic treatment plus lysozyme combined with live/dead imaging provided fluorescent micrographs identifying de novo enterococcal vancomycin resistant transconjugants inside the biofilm. This is a model system for the further study of antibiotic resistance transfer events in enterococci. Biofilms promote the survival of enterococci and reduce the effectiveness of drug treatment in clinical settings, hence giving enterococci an advantage. Enterococci growing in biofilms exchange traits by means of horizontal gene transfer, but currently available models make study difficult. This work goes some way to providing a non-destructive, molecular imaging-based model system for the detection of antibiotic resistance gene transfer in enterococci.

Chloropentaphenyldisiloxane—Model Study on Intermolecular Interactions in the Crystal Structure of a Monofunctionalized Disiloxane

Small functional siloxane units have gained great interest as molecular model systems for mimicking more complex silicate structures both in nature and in materials chemistry. The crystal structure of chloropentaphenyldisiloxane, which was synthesized for the first time, was elucidated by single-crystal X-ray diffraction analysis. The molecular crystal packing was studied in detail using state-of-the-art Hirshfeld surface analysis together with a two-dimensional fingerprint mapping of the intermolecular interactions. It was found that the phenyl C–H bonds act as donors for both weak C–H···π and C–H···Cl hydrogen bond interactions. The influence of intramolecular Si–O–Si bond parameters on the acceptor capability of functional groups in intermolecular hydrogen bond interactions is discussed.

A beginner's guideline for low‐cost 3D printing of macromolecules usable for teaching and demonstration

The structure and function of biomolecules relationship is the hallmark of biochemistry, molecular biology, and life sciences in general. Physical models of macromolecules give students the possibility to manipulate these structures in three dimensions, developing a sense of spatiality and a better understanding of key aspects such as atom size and shape, bond lengths and symmetry. Several molecular model systems were developed specifically to represent particular classes or groups of molecules and hence lack the flexibility of a universal solution. Three-dimensional printing could nevertheless provide such a universal solution, as it can be used to create physical models of biomolecular structures based on the teacher's or demonstrator's needs and requirements. Here, insulin was used as a model molecule and several depiction and printing parameters were tested in order to highlight the technical limitations of the approach. In the end, a set of settings that worked is provided which could serve as a starting point for anyone wishing to print his or her own custom macromolecular model on the cheap.

High Temporal and Spectral Resolution of Stimulated X-Ray Raman Signals with Stochastic Free-Electron-Laser Pulses

The chaotic nature of x-ray free-electron-laser pulses is a major bottleneck that has limited the joint temporal and spectral resolution of spectroscopic measurements. We show how to use the stochastic x-ray field statistics to overcome this difficulty by correlation signals averaged over independent pulse realizations. No control is required over the spectral phase of the pulse, enabling immediate application with existing, noisy x-ray free-electron-laser pulses. The proposed stimulated Raman technique provides the broad observation bandwidth and high time-frequency resolution needed for the observation of elementary molecular events. A model is used to simulate chaotic free-electron-laser pulses and calculate their correlation properties. The resulting joint temporal/spectral resolution is exemplified for a molecular model system with time-dependent frequencies and for the RNA base Uracil passing through a conical intersection. Ultrafast coherences, which represent a direct signature of the nonadiabatic dynamics, are resolved. The detail and depth of physical information accessed by the proposed stochastic signal are virtually identical to those obtained by phase-controlled pulses.

Waypoint Graph Generation with Growing Neural Gases for Pathfinding Applications in Molecular Dynamics Simulations

Path planning is a fundamental problem in the fields of autonomous robotics and molecular simulation. A large body of algorithms developed for vision-based robotic motion planning have been successfully applied to molecular pathfinding problems. We present the application of one such technique, the growing neural gas (GNG), an unsupervised machine learning procedure that estimates the optimal topological discretization of a collective variable space of arbitrary dimensionality. The GNG constructs an undirected graph representation of a probability density by utilizing a Hebb-like competitive learning rule, where individual neurons compete to represent different regions of the input space by moving and replicating in response to random samples drawn from the target density. The nodes of the resulting graph correspond to waypoint molecular states and its edges represent the potential transitions between states. Recent developments in autoencoder- and flow-based generative learning procedures have facilitated the unsupervised sampling and discovery of key collective variables in molecular systems, along which free energy differences can be calculated. Applying the GNG to such multidimensional free energy profiles allows for rapid generation of waypoint graphs within the collective variable space, which can be subsequently refined to determine optimal transition paths between selected states of interest. This proposed pipeline enables the unsupervised estimation of minimum free-energy transition paths from an initial molecular structure. We demonstrate our procedure on toy Gaussian-well systems and model molecular systems such as alanine tripeptide and show that the GNG can be a powerful tool for feature space discretization and path planning applications in molecular dynamics simulations.

Aphanius fasciatus: a molecular model of scoliosis?

Observational study of Killifish with spinal deformities OBJECTIVE: To evaluate the morphology and molecular biology of Aphanius fasciatus with severe spine deformities. Idiopathic Scoliosis affects 3% of the population and is an abnormal three-dimensional curvature of the spine with unknown cause. The lack of a model system with naturally occurring spinal curvatures has hindered research on the etiology of IS. The Mediterranean killifish Aphanius fasciatus, collected from the coast of Sfax (Tunisia), which has an inborn skeletal deformity was chosen. We used morphologic features to evaluate the severity of scoliosis according to the different types and performed a biochemical analysis using factors previously studied in humans (estradiol, melatonin and Insulin Growth Factor 1 "IGF-1"). We have detected relevant molecular deviations that occur in Killifish deformities and the fish with severe scoliosis are smaller and less old than the ones with milder scolioses. Furthermore, a significant change in levels of ovarian estradiol, liver IGF-1 and brain melatonin was noted between deformed and normal fish. Aphanius fasciatus could be used as a molecular model system to study the etiology of IS in humans as the characterization of the Aphanius fasciatus scoliosis syndrome has revealed morphological and biochemical parallels to IS. However, it is important to note the limitations of the proposed model, including the short lifespan of the fish. III.

Mo3 S13 ]2- as a Model System for Hydrogen Evolution Catalysis by MoSx : Probing Protonation Sites in the Gas Phase by Infrared Multiple Photon Dissociation Spectroscopy.

Materials based on molybdenum sulfide are known as efficient hydrogen evolution reaction (HER) catalysts. As the binding site for H atoms on molybdenum sulfides for the catalytic process is under debate, [HMo3S13]− is an interesting molecular model system to address this question. Herein, we probe the [HMo3S13]− cluster in the gas phase by coupling Fourier‐transform ion‐cyclotron‐resonance mass spectrometry (FT‐ICR MS) with infrared multiple photon dissociation (IRMPD) spectroscopy. Our investigations show one distinct S−H stretching vibration at 2450 cm−1. Thermochemical arguments based on DFT calculations strongly suggest a terminal disulfide unit as the H adsorption site.

Antimicrobial effects of syndiotactic polypeptides

We present design and antibacterial studies of stereochemically diversified antimicrobial peptides against multidrug-resistant bacterial pathogens. Syndiotactic polypeptides are polymers of alternating L and D amino acids with LDLD or DLDL backbone stereochemical sequence, which can form stable gramicidin like helical conformations. We designed, synthesized and characterized eight model molecular systems with varied electrostatic fingerprints, modulated through calibrated sequence positioning. Six out of eight model systems showed very impressive antimicrobial activity against three difficult to treat bacterial species, Gentamicin resistant MRSA, E. coli and Mycobacterium. More importantly, the designed LDLD peptides were equally potent in serum, an important drawback of poly L peptide sequences due to enzyme mediated degradation and ion sensitivity. Further, we tested the activity of the designed peptides against drug-resistant clinical isolates of Staphylococcus aureus and Escherichia coli. Molecular dynamics simulation studies suggest formation of an assembly of individual peptides, preceding the membrane interaction and deformation. The activity estimates are comparable with the available peptide based antimicrobials, and are also highly specific and less toxic as per standard estimates. Incorporation of D amino-acids can significantly expand the peptide design space, which can in turn manifest in future biomaterial designs, especially antimicrobials.

Chalcogen-Nitrogen Bond: Insights into a Key Chemical Motif

Chalcogen-nitrogen chemistry deals with systems in which sulfur, selenium, or tellurium is linked to a nitrogen nucleus. This chemical motif is a key component of different functional structures, ranging from inorganic materials and polymers, to rationally designed catalysts, to bioinspired molecules and enzymes. The formation of a selenium–nitrogen bond, typically occurring upon condensation of an amine and the unstable selenenic acid, often leading to intramolecular cyclizations, and its disruption, mainly promoted by thiols, are rather common events in organic Se-catalyzed processes. In this work, focusing on examples taken from selenium organic chemistry and biochemistry, the selenium–nitrogen bond is described, and its strength and reactivity are quantified using accurate computational methods applied to model molecular systems. The intermediate strength of the Se–N bond, which can be tuned to necessity, gives rise to significant trends when comparing it to the stronger S– and weaker Te–N bonds, reaffirming also in this context the peculiar and valuable role of selenium in chemistry and life.

Progress and prospect of single-molecular ClpX ATPase researching system-a mini-review.

ClpXP in Escherichia coli is a proteasome degrading protein substrates. It consists of one hexamer of ATPase (ClpX) and two heptamers of peptidase (ClpP). The ClpX binds ATP and translocates the substrate protein into the ClpP chamber by binding and hydrolysis of ATP. At single molecular level, ClpX harnesses cycles of power stroke (dwell and burst) to unfold the substrates, then releases the ADP and Pi. Based on the construction and function of ClpXP, especially the recent progress on how ClpX unfold protein substrates, in this mini-review, a currently proposed single ClpX molecular model system detected by optical tweezers, and its prospective for the elucidation of the mechanism of force generation of ClpX in its power stroke and the subunit interaction with each other, were discussed in detail.

Elucidating genetic divergence of silkworm (Bombyx mori) using internal transcribed Spacer1 (ITS1)

The silkworm Bombyx mori is one of the prominent molecular model system, being continuously evaluated through genetic approaches, since decades to better the best in silk production. DNA profiles provide reliable estimates of genetic diversity within and between genotypes. This is important both for the maintenance of genotypes as well as selection of parents for the development of elite hybrids. To ascertain genetic diversity and phylogenetic relationship among 23 bivoltine silkworm strains, DNA barcoding of ITS1 region and Mahalanobis D2 analysis was carried out. Neighbour-joining analysis grouped 23 strains into five clusters based on sequence variation of ITS1 region. Based on seven quantitative traits, the D2 values were obtained and the selected strains were grouped into three clusters using Tocher’s method. Cocoon yield by number (44.27%) and shell ratio (41.5%) recorded maximum contribution towards divergence. The clustering pattern revealed agreement for divergence as SKUAST-1 and SKUAST-22 formed an outgroup cluster at both molecular as well as genetic level. The current study clearly demonstrated that ITS1 sequences of B. mori were useful in studying intra specific nucleotide variations and can be used as DNA barcode for future B. mori studies. The divergent strains identified in this study could be used in future breeding programmes for quality silk production.

A solid look at molecules

When molecular model systems, such as polycyclic aromatic hydrocarbons, are ionized by ultrashort extreme ultraviolet pulses, their relaxation path proceeds via electron–phonon scattering, linking molecules to typical solid-state matter behaviour.

Resolution of Gauge Ambiguities in Molecular Cavity Quantum Electrodynamics

This work provides the fundamental theoretical framework for molecular cavity quantum electrodynamics by resolving the gauge ambiguities between the Coulomb gauge and the dipole gauge Hamiltonians under the electronic state truncation. We conjecture that such ambiguity arises because not all operators are consistently constrained in the same truncated electronic subspace for both gauges. We resolve this ambiguity by constructing a unitary transformation operator that properly constrains all light-matter interaction terms in the same subspace. We further derive an equivalent and yet convenient expression for the Coulomb gauge Hamiltonian under the truncated subspace. We finally provide the analytical and numerical results of a model molecular system coupled to the cavity to demonstrate the validity of our theory.

Gas‐Phase Models for the Nickel‐ and Palladium‐Catalyzed Deoxygenation of Fatty Acids

AbstractUsing fatty acids as renewable sources of biofuels requires deoxygenation. While a number of promising catalysts have been developed to achieve this, their operating mechanisms are poorly understood. Here, model molecular systems are studied in the gas phase using mass spectrometry experiments and DFT calculations. The coordinated metal complexes [(phen)M(O2CR)]+ (where phen=1,10‐phenanthroline; M=Ni or Pd; R=CnH2n+1, n≥2) are formed via electrospray ionization. Their collision‐induced dissociation (CID) initiates deoxygenation via loss of CO2 and [C,H2,O2]. The CID spectrum of the stearate complexes (R=C17H35) also shows a series of cations [(phen)M(R’)]+ (where R’ < C17) separated by 14 Da (CH2) corresponding to losses of C2H4‐C16H32 (cracking products). Sequential CID of [(phen)M(R’)]+ ultimately leads to [(phen)M(H)]+ and [(phen)M(CH3)]+, both of which react with volatile carboxylic acids, RCO2H, (acetic, propionic, and butyric) to reform the coordinated carboxylate complexes [(phen)M(O2CR)]+. In contrast, cracking products with longer carbon chains, [(phen)M(R)]+ (R>C2), were unreactive towards these carboxylic acids. DFT calculations are consistent with these results and reveal that the approach of the carboxylic acid to the “free” coordination site is blocked by agostic interactions for R > CH3.

Effect of metal ions on isothermal amplification with Bst exo- DNA polymerase

Over the last two decades, the isothermal amplification has become actively used for nucleic acids analysis. To perform isothermal techniques, DNA polymerases with strand-displacement activity are needed, and Bst exo- polymerase is one of the most widely used. However, Bst exo- is prone to non-specific DNA synthesis (e.g., DNA multimerization) occurring in the absence of the DNA target of interest. Here, we report on the activity of Bst exo- in the presence of Mg2+, Mn2+, Ca2+, Cd2+, Co2+, Cu2+, Ni2+ and Zn2+ in the model molecular systems which included amplification of circular and linear DNA templates; conditions providing effective and highly specific isothermal amplification were determined. It was found that amplification can proceed not only with Mg2+ but with Mn2+, Ca2+, Cd2+ and Cu2+ depending on the type of Bst exo- polymerase and the buffer. Manganese ions turned out to be the most suitable alternative cofactor, which prevents multimerization in some buffers. Molecular docking simulations showed the highest stability for the quaternary ‘polymerase-DNA-triphosphate-cations’ complexes containing Mg2+ and Mn2+, and the moderate one for complexes with Ca2+, Cd2+ and Cu2+. The frequency of nucleotide misincorporation increased in the following row: Mg2+ ≈ Mn2+ ≤ Cd2+ < Ca2+ ≪ Cu2+.

A Perspective on Deep Learning for Molecular Modeling and Simulations.

Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems. However, unlike the mature deployment of deep learning in computer vision and natural language processing, its development in molecular modeling and simulations is still at an early stage, largely because the inductive biases of molecules are completely different from those of images or texts. Footed on these differences, we first reviewed the limitations of traditional deep learning models from the perspective of molecular physics and wrapped up some relevant technical advancement at the interface between molecular modeling and deep learning. We do not focus merely on the ever more complex neural network models; instead, we introduce various useful concepts and ideas brought by modern deep learning. We hope that transacting these ideas into molecular modeling will create new opportunities. For this purpose, we summarized several representative applications, ranging from supervised to unsupervised and reinforcement learning, and discussed their connections with the emerging trends in deep learning. Finally, we give an outlook for promising directions which may help address the existing issues in the current framework of deep molecular modeling.