Analysis of a two dimensional molecular Berry phase system

SCELib3.0: The new revision of SCELib, the parallel computational library of molecular properties in the Single Center Approach

A variational method for calculating the critical nuclear charge ${Z}_{C}$ required for the binding of a nucleus to two electrons is reported. The method is very effective and performs well compared to the traditional variational principle for calculating energy. The critical nuclear charge, which corresponds to the minimum charge required for the atomic system to have at least one bound state, has been calculated for heliumlike systems with both infinite and finite nuclear masses. The value of ${Z}_{C}=0.911\phantom{\rule{0.16em}{0ex}}028\phantom{\rule{0.16em}{0ex}}2(3)$ is in very good agreement with recent values in the literature for two-electron atoms with an infinite nuclear mass. When nuclear motion is considered, the value for ${Z}_{C}$ varies from 0.911 030 3(2) for that with a nuclear mass of Ne (the largest heliogenic system considered) to $0.921\phantom{\rule{0.16em}{0ex}}802\phantom{\rule{0.16em}{0ex}}4(4)$ for a system with the nuclear mass of a positron. In all cases the energy varies smoothly as $Z\ensuremath{\rightarrow}0$. It is found that for the finite nuclear mass case, in agreement with previous work for the fixed nucleus mass system, the outer electron remains localized near the nucleus at $Z={Z}_{C}$. Additionally, the electron probability distribution is calculated to determine the behavior of the electrons at low $Z$.

Most human diseases are complex multi-factorial diseases resulting from the combination of various genetic and environmental factors. In the KEGG database resource (http://www.genome.jp/kegg/), diseases are viewed as perturbed states of the molecular system, and drugs as perturbants to the molecular system. Disease information is computerized in two forms: pathway maps and gene/molecule lists. The KEGG PATHWAY database contains pathway maps for the molecular systems in both normal and perturbed states. In the KEGG DISEASE database, each disease is represented by a list of known disease genes, any known environmental factors at the molecular level, diagnostic markers and therapeutic drugs, which may reflect the underlying molecular system. The KEGG DRUG database contains chemical structures and/or chemical components of all drugs in Japan, including crude drugs and TCM (Traditional Chinese Medicine) formulas, and drugs in the USA and Europe. This database also captures knowledge about two types of molecular networks: the interaction network with target molecules, metabolizing enzymes, other drugs, etc. and the chemical structure transformation network in the history of drug development. The new disease/drug information resource named KEGG MEDICUS can be used as a reference knowledge base for computational analysis of molecular networks, especially, by integrating large-scale experimental datasets.

Typical experimental setups for molecular systems must deal with a certain coupling to the external environment, that is, the system is open and exchanges mass, momentum, and energy with its surroundings. Instead, standard molecular simulations are mostly performed using periodic boundary conditions with a constant number of molecules. In this review, we summarize major development of simulation methodologies, which, contrary to standard techniques, open up the boundaries of a molecular system and allow for exchange of energy and matter with the environment, in and out of equilibrium. In particular, we construct the review around the open boundary simulation approaches based on the Adaptive Resolution Scheme (AdResS), which seamlessly couples different levels of resolution in molecular simulations. Ideas and theoretical concepts used in its development lie at the crossroad of different fields and disciplines and open many different directions for future developments in molecular simulation. We examine progress related to theoretical as well as novel modeling approaches bridging length scales from quantum to the continuum description and report on their application in various molecular systems. The outlook of the review is dedicated to the perspective of how to further incorporate rigorous theoretical approaches such as the Bergmann–Lebowitz and Emch–Sewell models into the molecular simulation algorithms and stimulate further development of open boundary simulation methods and their application.

During recent decades it has become feasible to simulate the dynamics of molecular systems on a computer. The method of molecular dynamics (MD) solves Newton's equations of motion for a molecular system, which results in trajectories for all atoms in the system. From these atomic trajectories a variety of properties can be calculated. The aim of computer simulations of molecular systems is to compute macroscopic behavior from microscopic interactions. The main contributions a microscopic consideration can offer are (1) the understanding and (2) interpretation of experimental results, (3) semiquantitative estimates of experimental results, and (4) the capability to interpolate or extrapolate experimental data into regions that are only difficultly accessible in the laboratory. One of the two basic problems in the field of molecular modeling and simulation is how to efficiently search the vast configuration space which is spanned by all possible molecular conformations for the global low (free) energy regions which will be populated by a molecular system in thermal equilibrium. The other basic problem is the derivation of a sufficiently accurate interaction energy function or force field for the molecular system of interest. An important part of the art of computer simulation is to choose the unavoidable assumptions, approximations and simplifications of the molecular model and computational procedure such that their contributions to the overall inaccuracy are of comparable size, without affecting significantly the property of interest. Methodology and some practical applications of computer simulation in the field of (bio)chemistry will be reviewed.

A new mechanism for realizing negative permeability with a three-level ladder-type atomic (or molecular) system at microwave frequency is suggested. The explicit expressions for the magnetic permeability of both steady and transient cases are presented. Compared with the previous schemes to realize negative permeability within the framework of classical electromagnetic theory, the most remarkable feature in the present mechanism is that it can realize the isotropic material with negative permeability. Such a permeability can be controllably manipulated by external coupling fields and could lead to potential applications in quantum optical devices.

This paper presents an O(N) algorithm and its preliminary computer simulation results for virtual prototyping of molecular systems with a simple chain structure. The algorithm is based on proper integration between an internal coordinate method (ICM) and a multibody molecular model. ICM method makes the use of recursive relations possible between two adjacent subsets within a molecular system. The multibody molecular model takes the benefits of freezing degrees of freedom of some lightly excited high frequency bonds. Because these high frequency bonds would force the use of very small integration step sizes, which severely limits the time scales for virtual prototyping of dynamics of molecular conformation over long periods of time. Thus a new multiscale model and efficient algorithm is produced to increase computational efficiency for virtual prototyping of dynamical behaviors of molecular confirmation. This paper will be initially directed towards introduction of the new model and algorithm. Then attention will be turned to the implementation of the algorithm at macro scale, which can be used to demonstrate the validity of the procedure and algorithm. Final focus will be turned to the implementation of the algorithm to a simple molecular chain at micro scale. The algorithm gives an O(N) computational performance for formation/solution of equations of motion for a molecular chain system.

Continuous advancements in DNA nanotechnology have resulted in innovative information security strategies utilizing biomolecular-based encryption mechanisms to achieve effective protection and reliable storage. However, existing molecular encryption schemes are limited in their practical expansion due to their focus on the precise design and strict management of the key itself while neglecting the impact of complex environments, causing them to suffer from insufficient concealment and poor adaptability to complex access control scenarios. Here, we propose a pH-regulated camouflage strategy that significantly enhances the encryption concealment of molecular systems. Using pH-regulated logical operation transformations, we establish a switchable cascaded logic operation strategy that implements a two-layer DNA molecular firewall access control system. By integrating two distinct camouflage rules, the system constructs four differentiated access modes. This design effectively prevents unauthorized access, conceals true input addresses, and deceives potential attackers, thereby ensuring internal information security. This approach provides a simple method for the design and management of molecular systems and is expected to be applied in fields such as information security and environmental monitoring.

Development of artificial complex molecular systems is of great importance in understanding complexity in natural processes and for achieving new functionalities. One of the strategies is to create them via optimized utilization of noncovalent interactions and dynamic covalent bonds. We report here on a new complex molecular system, which was constructed by integrating the multiple interactions containing a dynamic covalent interaction between 1,2-diol and boronic acid, a coordination interaction between the silver ion and pyridyl, and an easy accessible reaction between secondary amine and formaldehyde. By employing the three dynamic interactions, a pyrene (Py) labeled fluorophore, PPB, was designed and synthesized. The compound reacts with fructose (F), a monosaccharide, in aqueous phase and produces a fluorescent adduct, PPB-F, which can be further used as a sensing platform for formaldehyde (FA) and the silver ion. The respective dynamic interactions are accompanied with color changes due to the reversible switching between Py-monomer emission and excimer emission. The respective experimental detection limits (DLs) for the three analytes are much lower than 0.2 mM, 0.1 mM, and 2.5 μM, respectively. The presence of relevant compounds or ions shows little effect upon the sensing. No doubt, the results as presented show that the integration of supramolecular interactions including dynamic covalent bonds can be employed as a general strategy to develop new functional molecular systems or materials.

In order to maintain tissue homeostasis, cells communicate with the outside environment by receiving molecular signals, transmitting them, and responding accordingly with signaling pathways. Thus, one key challenge in engineering molecular signaling systems involves the design and construction of different modules into a rationally integrated system that mimics the cascade of molecular events. Herein, we rationally design a DNA-based artificial molecular signaling system that uses the confined microenvironment of a giant vesicle, derived from a living cell. This system consists of two main components. First, we build an adenosine triphosphate (ATP)-driven DNA nanogatekeeper. Second, we encapsulate a signaling network in the biomimetic vesicle, consisting of distinct modules, able to sequentially initiate a series of downstream reactions playing the roles of reception, transduction and response. Operationally, in the presence of ATP, nanogatekeeper switches from the closed to open state. The open state then triggers the sequential activation of confined downstream signaling modules.

The inelastic neutron scattering (INS) spectrum of the original benzylic amide [2]catenane is recorded and simulated by a semiempirical quantum chemical procedure coupled with the most comprehensive approach available to date, the CLIMAX program. The successful simulation of the spectrum indicates that the modified neglect of differential overlap (MNDO) model can reproduce the intramolecular vibrations of a molecular system as large as a catenane (136 atoms). Because of the computational costs involved and some numerical instabilities, a less expensive approach is attempted which involves the molecular mechanics-based calculation of the INS response in terms of the most basic formulation for the scattering activity. The encouraging results obtained validate the less computationally intensive procedure and allow its extension to the calculation of the INS spectrum for a second, theoretical, co-conformer, which, although structurally and energetically reasonable, is not, in fact, found in the solid state. The second structure was produced by a Monte Carlo simulated annealing method run in the conformational space (a procedure that would have been prohibitively expensive at the semiempirical level) and is characterized by a higher degree of intramolecular hydrogen bonding than the x-ray structure. The two alternative structures yield different simulated spectra, only one of which, the authentic one, is compatible with the experimental data. Comparison of the two simulated and experimental spectra affords the identification of an inelastic neutron scattering spectral signature of the correct hydrogen bonding motif in the region slightly above 700 cm−1. The study illustrates that combinations of simulated INS data and experimental results can be successfully used to discriminate between different proposed structures or possible hydrogen bonding motifs in large functional molecular systems.

With the introduction of the Schrodinger equation in 1926, it was in principle clear how to describe a molecular system and its properties exactly in a nonrelativistic sense. However, for most molecular systems of chemical interest, the analytic solution of the Schrodinger equation is not possible. Therefore, since 1926, a multitude of hierarchical approximations (some of which are displayed in Figure 1) have been devised that allow for a systematic approach to the exact solution of the Schrodinger equation. Although the Schrodinger equation as the fundamental equation in electronic structure theory is already quite old, the field of quantum chemistry is still fairly young and fast moving, and much can be expected in the future for developing and applying quantum chemical methods for the treatment of molecular systems. The importance of the systematic hierarchy for solving the Schrodinger equation cannot be overemphasized, because it allows one, in principle, to systematicallyapproach the exact result for a molecularpropertyof interest. The simplest approach in this hierarchy is the Hartree–Fock (HF) method, which describes electron–electron interactions within a mean-field approach. The electroncorrelation effects neglected in this approach can be described by the so-called

Machine learning interatomic potentials (MLIPs) enables molecular dynamics (MD) simulations with ab initio accuracy and has been applied to various fields of physical science. However, the performance and transferability of MLIPs are limited by insufficient labeled training data, which require expensive ab initio calculations to obtain the labels, especially for complex molecular systems. To address this challenge, we design a novel geometric structure learning paradigm that consists of two stages. We first generate a large quantity of 3D configurations of target molecular system with classical molecular dynamics simulations. Then, we propose geometry-enhanced self-supervised learning consisting of masking, denoising, and contrastive learning to better capture the topology and 3D 1 geometric information from the unlabeled 3D configurations. We evaluate our method on various benchmarks ranging from small molecule datasets to complex periodic molecular systems with more types of elements. The experimental results show that the proposed pre-training method can greatly enhance the accuracy of MLIPs with few extra computational costs and works well with different invariant or equivariant graph neural network architectures. Our method improves the generalization capability of MLIPs and helps to realize accurate MD simulations for complex molecular systems.

This dissertation is devoted to the study of randomness and noise in a number of information systems including computation systems, storage systems, and natural paradigms like molecular systems, where randomness plays important and distinct roles. Motivated by applications in engineering and science we address a number of theoretical research questions. In a computation system, randomness enables to perform tasks faster, simpler, or more space efficient. Hence, randomness is a useful computational resource, and the research question we address is: How to efficiently extract randomness from natural sources? In a molecular system such as a chemical reaction network or a gene regulatory network, randomness is inherent and serves as the key mechanism for producing the desired quantities of molecular species. A chemical reaction can be abstractly described as a probabilistic switch. Hence, given a set of probabilistic switches (with some fixed switching probabilities), the research question we address is: How to synthesize a stochastic network consisting of those switches that computes a pre-specified probability distribution? In an information storage system, like flash memories where information is represented by a relatively small number of electrons, randomness is a threat to data reliability. Hence, the research question we address is: How to represent, write and read information in the presence of randomness (noise)? This dissertation is focusing on the foregoing key questions and describes novel contributions related to randomness generation and extraction, stochastic system synthesis and coding for information storage.

Absorption and emission of a given molecular system are characterized by their specific spectral distributions. Great effort was undertaken to get spectral profiles of liquid dye solutions in analytical forms. One of the infallible methods for a spectral profile description is the momentum method. An observed spectral distribution, independently on a theoretical specification of the system, is represented by the set of moments expressing the maximum positions, half-widths and asymetries of the spectum [1]. It appears that in most cases of stuctureless bands the first three moments suffice for the description of their profiles. Another spectral distribution, accurately reproducing electronic band profiles is the log-normal distribution [2, 3]. This distribution is also a three parameter distribution similar to those, based on the configurational model [4]. Many attempts were undertaken for the adaptations of Gaussian distributions and their superpositions to represent the molecular spectra. Unfortunately molecular electronic spectra never appear as Gaussian. The superposition of Gaussian curves needs more than three parameters, besides it suggests several numbers of transitions, which may not be present. It is a point why does the log-normal distribution fit so well to the description of so many molecular systems?