Car-Parrinello molecular dynamics

Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment

This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.

Unraveling a Cavity-Induced Molecular Polarization Mechanism from Collective Vibrational Strong Coupling

We demonstrate that collective vibrational strong coupling of molecules in thermal equilibrium can give rise to significant local electronic polarizations in the thermodynamic limit. We do so by first showing that the full nonrelativistic Pauli-Fierz problem of an ensemble of strongly coupled molecules in the dilute-gas limit reduces in the cavity Born-Oppenheimer approximation to a cavity-Hartree equation for the electronic structure. Consequently, each individual molecule experiences a self-consistent coupling to the dipoles of all other molecules, which amount to non-negligible values in the thermodynamic limit (large ensembles). Thus, collective vibrational strong coupling can alter individual molecules strongly for localized "hotspots" within the ensemble. Moreover, the discovered cavity-induced polarization pattern possesses a zero net polarization, which resembles a continuous form of a spin glass (or better polarization glass). Our findings suggest that the thorough understanding of polaritonic chemistry, requires a self-consistent treatment of dressed electronic structure, which can give rise to numerous, so far overlooked, physical mechanisms.

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors

Melatonin receptors MT1 and MT2 are G protein-coupled receptors that mediate the effects of melatonin, a hormone involved in circadian rhythms and other physiological functions. Understanding the molecular interactions between these receptors and their ligands is crucial for developing novel therapeutic agents. In this study, we used molecular docking, molecular dynamics simulations, and quantum mechanics calculation to investigate the binding modes and affinities of three ligands: melatonin (MLT), ramelteon (RMT), and 2-phenylmelatonin (2-PMT) with both receptors. Based on the results, we identified key amino acids that contributed to the receptor-ligand interactions, such as Gln181/194, Phe179/192, and Asn162/175, which are conserved in both receptors. Additionally, we described new meaningful interactions with Gly108/Gly121, Val111/Val124, and Val191/Val204. Our results provide insights into receptor-ligand recognition's structural and energetic determinants and suggest potential strategies for designing more optimized molecules. This study enhances our understanding of receptor-ligand interactions and offers implications for future drug development.

The search for an antiviral lead molecule to combat the neglected emerging Oropouche virus

Oropouche virus (OROV) is a member of the Peribunyaviridae family and the causative agent of a dengue-like febrile illness transmitted by mosquitoes. Although mild symptoms generally occur, complications such as encephalitis and meningitis may develop. A lack of proper diagnosis, makes it a potential candidate for new epidemics and outbreaks like other known arboviruses such as Dengue, Yellow Fever and Zika virus. The study of natural molecules as potential antiviral compounds is a promising alternative for antiviral therapies. Wedelolactone (WDL) has been demonstrated to inhibit some viral proteins and virus replication, making it useful to target a wide range of viruses. In this study, we report the in silico effects of WDL on the OROV N-terminal polymerase and its potential inhibitory effects on several steps of viral infection in mammalian cells in vitro, which revealed that WDL indeed acts as a potential inhibitor molecule against OROV infection.

Characterization of the Coordination and Solvation Dynamics of Solvated Systems─Implications for the Analysis of Molecular Interactions in Solutions and Pure H2O

The characterization of solvation shells of atoms, ions, and molecules in solution is essential to relate solvation properties to chemical phenomena such as complex formation and reactivity. Different definitions of the first-shell coordination sphere from simulation data can lead to potentially conflicting data on the structural properties and associated ligand exchange dynamics. The definition of a solvation shell is typically based on a given threshold distance determined from the respective solute-solvent pair distribution function g(r) (i.e., GC). Alternatively, a nearest neighbor (NN) assignment based on geometric properties of the coordination complex without the need for a predetermined cutoff criterion, such as the relative angular distance (RAD) or the modified Voronoi (MV) tessellation, can be applied. In this study, the effect of different NN algorithms on the coordination number and ligand exchange dynamics evaluated for a series of monatomic ions in aqueous solution, carbon dioxide in aqueous and dichloromethane solutions, and pure liquid water has been investigated. In the case of the monatomic ions, the RAD approach is superior in achieving a well separated definition of the first solvation layer. In contrast, the MV algorithm provides a better separation of the NNs from a molecular point of view, leading to better results in the case of solvated CO2. When analyzing the coordination environment in pure water, the cutoff-based GC framework was found to be the most reliable approach. By comparison of the number of ligand exchange reactions and the associated mean ligand residence times (MRTs) with the properties of the coordination number autocorrelation functions, it is shown that although the average coordination numbers are sensitive to the different definitions of the first solvation shell, highly consistent estimates for the associated MRT of the solvated system are obtained in the majority of cases.

Massively scalable workflows for quantum chemistry: BigChem and ChemCloud

Electronic structure theory, i.e., quantum chemistry, is the fundamental building block for many problems in computational chemistry. We present a new distributed computing framework (BigChem), which allows for an efficient solution of many quantum chemistry problems in parallel. BigChem is designed to be easily composable and leverages industry-standard middleware (e.g., Celery, RabbitMQ, and Redis) for distributed approaches to large scale problems. BigChem can harness any collection of worker nodes, including ones on cloud providers (such as AWS or Azure), local clusters, or supercomputer centers (and any mixture of these). BigChem builds upon MolSSI packages, such as QCEngine to standardize the operation of numerous computational chemistry programs, demonstrated here with Psi4, xtb, geomeTRIC, and TeraChem. BigChem delivers full utilization of compute resources at scale, offers a programable canvas for designing sophisticated quantum chemistry workflows, and is fault tolerant to node failures and network disruptions. We demonstrate linear scalability of BigChem running computational chemistry workloads on up to 125 GPUs. Finally, we present ChemCloud, a web API to BigChem and successor to TeraChem Cloud. ChemCloud delivers scalable and secure access to BigChem over the Internet.

Real-Time Time-Dependent Density Functional Theory for Simulating Nonequilibrium Electron Dynamics

The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. In this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.

Bi-based bracelet-like monolayer with negative in-plane Poisson's ratio and enhanced photocatalytic performance: a first-principles study

Auxetic materials are in high demand for advanced applications due to their relatively rare negative Poisson's ratio in two-dimensional materials. This study investigates the structural, mechanical, electronic, optical and photocatalytic properties of the AsBiTe3monolayer(ML) using first-principles calculations. Through analysis of phonon dispersion curves,ab-initiomolecular dynamics simulations, and Born conditions, we have confirmed the thermal, dynamic, and mechanical stability of the AsBiTe3monolayer. The study of the mechanical properties of this material revealed significant anisotropy and a bidirectional in-plane negative Poisson's ratio (NPR). In addition, electronic band structures calculated, with and without spin-orbit coupling (SOC) using the HSE functional, indicate that this monolayer exhibits the characteristics of an indirect-gap semiconductor around 1.17 and 1.32 eV, respectively. Notably, by assessing the optical properties of AsBiTe3monolayer, it has been found that this monolayer has a strong light-harvesting capability with an absorption coefficient higher than 105 cm-1in the visible region. Fascinatingly, under a biaxial 1%and 4%tensile and -2% compressive strain, the band edge of the AsBiTe3monolayer extends across the redox potential of water at pH = 0, 7 and 14, respectively. This suggests that this monolayer holds promise as a potential material for catalytic water splitting. These results should inspire further experimental and theoretical research, aimed at fully exploring the potential applications of this new class of 2D materials.

Pockets, jumps and filaments: classifying ionic motion and determining the role of structure in electrochemical properties of 2Li2S-GeS2superionic glasses

The structural properties of a typical solid electrolyte system (2Li2S-GeS2) is investigated from First principles molecular dynamics simulations. Results reveal that depolymerization of the base GeS2network by alkali additives takes place but appears reduced with respect to the corresponding sodium analog glass. Experimental structure functions are reproduced and reveal that the network is dominated by GeS4/2tetrahedra that are connected by edges (four-membered rings) and corners and disrupted by the addition of lithium, albeit a non-negligible fraction of connecting tetrahedra (Q2units) are still present in the glass structure. Dynamic and electric properties are also studied and emphasize that the size of the migrating cation (Li) is essential for ensuring a good level of ionic conductivity as it displays increased values with respect to the parent Na-bearing system. On the atomic (picosecond) timescale, different typical Li trajectories are identified and their distribution calculated: reduced cage-like motion in pockets constrained by the surrounding (Ge,S) network, back and forth jump motions with short transition states and long-range filamentary motion.

Quantum biochemical analysis of the binding interactions between a potential inhibitory drug and the Ebola viral glycoprotein

Ebola virus disease (EVD) causes outbreaks and epidemics in West Africa that persist until today. The envelope glycoprotein of Ebola virus (GP) consists of two subunits, GP1 and GP2, and plays a key role in anchoring or fusing the virus to the host cell in its active form on the virion surface. Toremifene (TOR) is a ligand that mainly acts as an estrogen receptor antagonist; however, a recent study showed a strong and efficient interaction with GP. In this context, we aimed to evaluate the energetic affinity features involved in the interaction between GP and toremifene by computer simulation techniques using the Molecular Fractionation Method with Conjugate Caps (MFCC) scheme and quantum-mechanical (QM) calculations, as well as missense mutations to assess protein stability. We identified ASP522, GLU100, TYR517, THR519, LEU186, LEU515 as the most attractive residues in the EBOV glycoprotein structure that form the binding pocket. We divided toremifene into three regions and evaluated that region i was more important than region iii and region ii for the formation of the TOR-GP1/GP2 complex, which might control the molecular remodeling process of TOR. The mutations that caused more destabilization were ARG134, LEU515, TYR517 and ARG559, while those that caused stabilization were GLU523 and ASP522. TYR517 is a critical residue for the binding of TOR, and is highly conserved among EBOV species. Our results may help to elucidate the mechanism of drug action on the GP protein of the Ebola virus and subsequently develop new pharmacological approaches against EVD.Communicated by Ramaswamy H. Sarma.

Acridones as promising drug candidates against Oropouche virus

Oropouche virus (OROV) is an emerging vector-borne arbovirus found in South America that causes Oropouche fever, a febrile infection similar to dengue fever. It has a high epidemic potential, causing illness in over 500,000 cases diagnosed since the virus was first discovered in 1955. Currently, the prevention of human viral infection depends on vaccination, but availability for many viruses is limited, and they are classified as neglected viruses. At present, there are no vaccines or antiviral treatments available. An alternative approach to limiting the spread of the virus is to selectively disrupt viral replication mechanisms. Here, we demonstrate the inhibitory effect of acridones, which efficiently inhibited viral replication by 99.9 % in vitro. To evaluate possible mechanisms of action, we conducted tests with dsRNA, an intermediate in virus replication, as well as MD simulations, docking, and binding free energy analysis. The results showed a strong interaction between FAC21 and the OROV endonuclease, which possibly limits the interaction of viral RNA with other proteins. Therefore, our results suggest a dual mechanism of antiviral action, possibly caused by ds-RNA intercalation. In summary, our findings demonstrate that a new generation of antiviral drugs could be developed based on the selective optimization of molecules.

Antiviral Activity and Molecular Dynamics Simulation of Hops Compounds against Oropouche Virus (Peribunyaviridae)

The Oropouche virus (OROV) is a member of the family Peribunyaviridae (order Bunyavirales) and the cause of a dengue-like febrile illness transmitted mainly by biting midges and mosquitoes. In this study, we aimed to explore acylphloroglucinols and xanthohumol from hops (Humulus lupulus L.) as a promising alternative for antiviral therapies. The evaluation of the inhibitory potential of hops compounds on the viral cycle of OROV was performed through two complementary approaches. The first approach applies cell-based assay post-inoculation experiments to explore the inhibitory potential on the latest steps of the viral cycle, such as genome translation, replication, virion assembly, and virion release from the cells. The second part covers in silico methods evaluating the ability of those compounds to inhibit the activity of the endonuclease domain, which is essential for transcription, binding, and cleaving RNA. In conclusion, the beta acids showed strongest inhibitory potential in post-treatment assay (EC50 = 26.7 µg/mL). Xanthohumol had the highest affinity for OROV endonuclease followed by colupulone and cohumulone. This result contrasts with that observed for docking and MM/PBSA analysis, where cohumulone was found to have a higher affinity. Finally, among the three tested ligands, Lys92 and Arg33 exhibited the highest affinity with the protein.

Charge carrier dynamics in conducting polymer PEDOT using ab initio molecular dynamics simulations

As conducting polymers become increasingly important in electronic devices, understanding their charge transport is essential for material and device development. Various semi-empirical approaches have been used to describe temporal charge carrier dynamics in these materials, but there have yet to be any theoretical approaches utilizing ab initio molecular dynamics. In this work, we develop a computational technique based on ab initio Car-Parrinello molecular dynamics to trace charge carrier temporal motion in archetypical conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT). Particularly, we analyze charge dynamics in a single PEDOT chain and in two coupled chains with different degrees of coupling and study the effect of temperature. In our model we first initiate a positively charged polaron (compensated by a negative counterion) at one end of the chain, and subsequently displace the counterion to the other end of the chain and trace polaron dynamics in the system by monitoring bond length alternation in the PEDOT backbone and charge density distribution. We find that at low temperature (T = 1 K) the polaron distortion gradually disappears from its initial location and reappears near the new position of the counterion. At the room temperature (T = 300 K), we find that the distortions induced by polaron, and atomic vibrations are of the same magnitude, which makes tracking the polaron distortion challenging because it is hidden behind the temperature-induced vibrations. The novel approach developed in this work can be used to study polaron mobility along and between the chains, investigate charge transport in highly doped polymers, and explore other flexible polymers, including n-doped ones.

Studies on charge transfer of enalapril maleate: from solid-state to molecular dynamics

INTRODUCTION

Enalapril maleate is an antihypertensive ethyl ester pro-drug with two crystalline forms. A network of hydrogen bonds in both polymorphs plays an important role on solid-state stability, charge transfer process and degradation reactions (when exposed to high humidity, temperature and/or pH changes).

COMPUTATIONAL PROCEDURES

Supramolecular arrangement was proposed by Hirshfeld surface using the CrystalExplorer17 software and quantum theory of atoms in molecules. The electronic structure properties were calculated using the functional hybrid M06-2X with 6-311++G** base function employing diffuse and polarization functions to improve the description of hydrogen atoms on intermolecular interactions. Also, the H+ charge transfer between enalapril and maleate molecules was performed using Car-Parrinello molecular dynamics with the Verlet algorithm. In both simulations, the temperature of the ionic system was maintained around 300 K using the Nosé-Hoover thermostat and the electronic system evolved without the use of the thermostat.

RESULTS

This work evaluates the effect of maleate on the structural stability of enalapril maleate solid state. The electronic structural analysis points out a partially covalent character for N1-H∙∙∙O7 interaction; and the molecular dynamic showed a decentralized hydrogen on maleate driving a decomposition by charge transfer process while a centered hydrogen driving the stabilization. The charge transfer process and the mobility of the proton (H+) between enalapril and maleate molecules was demonstrated using supramolecular modeling analyses and molecular dynamics calculations.

Shadow energy functionals and potentials in Born-Oppenheimer molecular dynamics

In Born-Oppenheimer molecular dynamics (BOMD) simulations based on the density functional theory (DFT), the potential energy and the interatomic forces are calculated from an electronic ground state density that is determined by an iterative self-consistent field optimization procedure, which, in practice, never is fully converged. The calculated energies and forces are, therefore, only approximate, which may lead to an unphysical energy drift and instabilities. Here, we discuss an alternative shadow BOMD approach that is based on backward error analysis. Instead of calculating approximate solutions for an underlying exact regular Born-Oppenheimer potential, we do the opposite. Instead, we calculate the exact electron density, energies, and forces, but for an underlying approximate shadow Born-Oppenheimer potential energy surface. In this way, the calculated forces are conservative with respect to the approximate shadow potential and generate accurate molecular trajectories with long-term energy stabilities. We show how such shadow Born-Oppenheimer potentials can be constructed at different levels of accuracy as a function of the integration time step, δt, from the constrained minimization of a sequence of systematically improvable, but approximate, shadow energy density functionals. For each energy functional, there is a corresponding ground state Born-Oppenheimer potential. These pairs of shadow energy functionals and potentials are higher-level generalizations of the original "zeroth-level" shadow energy functionals and potentials used in extended Lagrangian BOMD [Niklasson, Eur. Phys. J. B 94, 164 (2021)]. The proposed shadow energy functionals and potentials are useful only within this extended dynamical framework, where also the electronic degrees of freedom are propagated as dynamical field variables together with the atomic positions and velocities. The theory is quite general and can be applied to MD simulations using approximate DFT, Hartree-Fock, or semi-empirical methods, as well as to coarse-grained flexible charge models.

Caffeic Acid Has Antiviral Activity against Ilhéus Virus In Vitro

Ilhéus virus (ILHV) is a neglected mosquito-borne flavivirus. ILHV infection may lead to Ilhéus fever, an emerging febrile disease like dengue fever with the potential to evolve into a severe neurological disease characterized by meningoencephalitis; no specific treatments are available for this disease. This study assessed the antiviral properties of caffeic acid, an abundant component of plant-based food products that is also compatible with the socioeconomic limitations associated with this neglected infectious disease. The in vitro activity of caffeic acid on ILHV replication was investigated in Vero and A549 cell lines using plaque assays, quantitative RT-PCR, and immunofluorescence assays. We observed that 500 µM caffeic acid was virucidal against ILHV. Molecular docking indicated that caffeic acid might interact with an allosteric binding site on the envelope protein.

Structural Insights into Plasticity and Discovery of Flavonoid Allosteric Inhibitors of Flavivirus NS2B–NS3 Protease

Flaviviruses are among the most critical pathogens in tropical regions; they cause various severe diseases in developing countries but are not restricted to these countries. The development of antiviral therapeutics is crucial for managing flavivirus outbreaks. Ten proteins are encoded in the flavivirus RNA. The N2B–NS3pro protein complex plays a fundamental role in flavivirus replication and is a promising drug target; however, no flavivirus protease inhibitors have progressed to the preclinical stage. This study analyzed the structural models and plasticity of the NS2B–NS3pro protein complex of five medically important non-dengue flaviviruses (West Nile, Rocio, Ilhéus, yellow fever, and Saint Louis encephalitis). The flavonoids amentoflavone, tetrahydrorobustaflavone, and quercetin were selected for their exceptional binding energies as potential inhibitors of the NS2B–NS3pro protein complex. AutoDock Vina results ranged from −7.0 kcal/mol to −11.5 kcal/mol and the compounds preferentially acted non-competitively. Additionally, the first structural model for the NS2B–NS3pro protein complex was proposed for Ilhéus and Rocio viruses. The NS2B–NS3pro protease is an attractive molecular target for drug development. The three identified natural flavonoids showed great inhibitory potential against the viral species. Nevertheless, further in silico and in vitro studies are required to obtain more information regarding NS2B–NS3pro inhibition by these flavonoids and their therapeutic potential.

Biology and medicine in the landscape of quantum advantages

Quantum computing holds substantial potential for applications in biology and medicine, spanning from the simulation of biomolecules to machine learning methods for subtyping cancers on the basis of clinical features. This potential is encapsulated by the concept of a quantum advantage, which is contingent on a reduction in the consumption of a computational resource, such as time, space or data. Here, we distill the concept of a quantum advantage into a simple framework to aid researchers in biology and medicine pursuing the development of quantum applications. We then apply this framework to a wide variety of computational problems relevant to these domains in an effort to (i) assess the potential of practical advantages in specific application areas and (ii) identify gaps that may be addressed with novel quantum approaches. In doing so, we provide an extensive survey of the intersection of biology and medicine with the current landscape of quantum algorithms and their potential advantages. While we endeavour to identify specific computational problems that may admit practical advantages throughout this work, the rapid pace of change in the fields of quantum computing, classical algorithms and biological research implies that this intersection will remain highly dynamic for the foreseeable future.

Carbon Nanodots from an In Silico Perspective

Carbon nanodots (CNDs) are the latest and most shining rising stars among photoluminescent (PL) nanomaterials. These carbon-based surface-passivated nanostructures compete with other related PL materials, including traditional semiconductor quantum dots and organic dyes, with a long list of benefits and emerging applications. Advantages of CNDs include tunable inherent optical properties and high photostability, rich possibilities for surface functionalization and doping, dispersibility, low toxicity, and viable synthesis (top-down and bottom-up) from organic materials. CNDs can be applied to biomedicine including imaging and sensing, drug-delivery, photodynamic therapy, photocatalysis but also to energy harvesting in solar cells and as LEDs. More applications are reported continuously, making this already a research field of its own. Understanding of the properties of CNDs requires one to go to the levels of electrons, atoms, molecules, and nanostructures at different scales using modern molecular modeling and to correlate it tightly with experiments. This review highlights different in silico techniques and studies, from quantum chemistry to the mesoscale, with particular reference to carbon nanodots, carbonaceous nanoparticles whose structural and photophysical properties are not fully elucidated. The role of experimental investigation is also presented. Hereby, we hope to encourage the reader to investigate CNDs and to apply virtual chemistry to obtain further insights needed to customize these amazing systems for novel prospective applications.

Predicting Antigenic Peptides from Rocio Virus NS1 Protein for Immunodiagnostic Testing Using Immunoinformatics and Molecular Dynamics Simulation

The mosquito-borne disease caused by the Rocio virus is a neglected threat, and new immune inputs for serological testing are urgently required for diagnosis in low-resource settings and epidemiological surveillance. We used in silico approaches to identify a specific antigenic peptide (p_ROCV2) in the NS1 protein of the Rocio virus that was theoretically predicted to be stable and exposed on its surface, where it demonstrated key properties allowing it to interact with antibodies. These findings related to the molecular dynamics of this peptide provide important insights for advancing diagnostic platforms and investigating therapeutic alternatives.

A perspective on ab initio modeling of polaritonic chemistry: The role of non-equilibrium effects and quantum collectivity

This Perspective provides a brief introduction into the theoretical complexity of polaritonic chemistry, which emerges from the hybrid nature of strongly coupled light-matter states. To tackle this complexity, the importance of ab initio methods is highlighted. Based on those, novel ideas and research avenues are developed with respect to quantum collectivity, as well as for resonance phenomena immanent in reaction rates under vibrational strong coupling. Indeed, fundamental theoretical questions arise about the mesoscopic scale of quantum-collectively coupled molecules when considering the depolarization shift in the interpretation of experimental data. Furthermore, to rationalize recent findings based on quantum electrodynamical density-functional theory (QEDFT), a simple, but computationally efficient, Langevin framework is proposed based on well-established methods from molecular dynamics. It suggests the emergence of cavity-induced non-equilibrium nuclear dynamics, where thermal (stochastic) resonance phenomena could emerge in the absence of external periodic driving. Overall, we believe that the latest ab initio results indeed suggest a paradigmatic shift for ground-state chemical reactions under vibrational strong coupling from the collective quantum interpretation toward a more local, (semi)-classically and non-equilibrium dominated perspective. Finally, various extensions toward a refined description of cavity-modified chemistry are introduced in the context of QEDFT, and future directions of the field are sketched.

Simulation of Nuclear Quantum Effects in Condensed Matter Systems via Quantum Baths

This paper reviews methods that aim at simulating nuclear quantum effects (NQEs) using generalized thermal baths. Generalized (or quantum) baths simulate statistical quantum features, and in particular zero-point energy effects, through non-Markovian stochastic dynamics. They make use of generalized Langevin Equations (GLEs), in which the quantum Bose–Einstein energy distribution is enforced by tuning the random and friction forces, while the system degrees of freedom remain classical. Although these baths have been formally justified only for harmonic oscillators, they perform well for several systems, while keeping the cost of the simulations comparable to the classical ones. We review the formal properties and main characteristics of classical and quantum GLEs, in relation with the fluctuation–dissipation theorems. Then, we describe the quantum thermostat and quantum thermal bath, the two generalized baths currently most used, providing several examples of applications for condensed matter systems, including the calculation of vibrational spectra. The most important drawback of these methods, zero-point energy leakage, is discussed in detail with the help of model systems, and a recently proposed scheme to monitor and mitigate or eliminate it—the adaptive quantum thermal bath—is summarised. This approach considerably extends the domain of application of generalized baths, leading, for instance, to the successful simulation of liquid water, where a subtle interplay of NQEs is at play. The paper concludes by overviewing further development opportunities and open challenges of generalized baths.

Virtual screening of small natural compounds against NS1 protein of DENV, YFV and ZIKV

Diseases caused by viruses of the genus Flavivirus are among the main diseases that affect the world and they are a serious public health problem. Three of them stand out: Dengue, Yellow fever and Zika viruses. The non-structural protein 1 (NS1), encoded by this viral genus, in its dimeric form, plays important roles in the pathogenesis and RNA replication of these viruses. Therefore, the identification of chemicals with the potential to inhibit the formation of the NS1 protein dimer of DENV, YFV and ZIKV would enable them to act as a multi-target drug. For this, we selected conformations of the NS1 protein monomer with similar β-roll domain structure among the three virus species from conformations obtained from molecular dynamics simulations performed in GROMACS in 5 replicates of 150 ns for each species. After selecting the protein structures, a virtual screening of compounds from the natural products catalog of the ZINC database was performed using AutoDock Vina. The 100 best compounds were classified according efficiency criteria. Two compounds were observed in common to the species, with energy scores ranging from -9.2 kcal/mol to -10.1 kcal/mol. The results obtained here demonstrate the high similarity of NS1 proteins in the Flavivirus genus and high affinity for the same compounds; thus justifying the potential of these small molecules act in multitarget therapy.Communicated by Ramaswamy H. Sarma.

Electronic and Vibrational Properties of Allene Carotenoids

Carotenoids are conjugated linear molecules built from the repetition of terpene units, which display a large structural diversity in nature. They may, in particular, contain several types of side or end groups, which tune their functional properties, such as absorption position and photochemistry. We report here a detailed experimental study of the absorption and vibrational properties of allene-containing carotenoids, together with an extensive modeling of these experimental data. Our calculations can satisfactorily explain the electronic properties of vaucheriaxanthin, where the allene group introduces the equivalent of one C=C double bond into the conjugated C=C chain. The position of the electronic absorption of fucoxanthin and butanoyloxyfucoxanthin requires long-range corrections to be found correctly on the red side of that of vaucheriaxanthin; however, these corrections tend to overestimate the effect of the conjugated and nonconjugated C=O groups in these molecules. We show that the resonance Raman spectra of these carotenoids are largely perturbed by the presence of the allene group, with the two major Raman contributions split into two components. These perturbations are satisfactorily explained by modeling, through a gain in the Raman intensity of the C=C antisymmetric stretching mode, induced by the presence of the allene group in the carotenoid C=C chain.

Theoretical Modeling of Redox Potentials of Biomolecules

The estimation of the redox potentials of biologically relevant systems by means of theoretical-computational approaches still represents a challenge. In fact, the size of these systems typically does not allow a full quantum-mechanical treatment needed to describe electron loss/gain in such a complex environment, where the redox process takes place. Therefore, a number of different theoretical strategies have been developed so far to make the calculation of the redox free energy feasible with current computational resources. In this review, we provide a survey of such theoretical-computational approaches used in this context, highlighting their physical principles and discussing their advantages and limitations. Several examples of these approaches applied to the estimation of the redox potentials of both proteins and nucleic acids are described and critically discussed. Finally, general considerations on the most promising strategies are reported.

Local Electronic Charge Transfer in the Helical Induction of Cis-Transoid Poly(4-carboxyphenyl)acetylene by Chiral Amines

Understanding the phenomena that lead to the formation of a specific helicity in helical polymers remains a challenge even today. Various polymers have been shown to assume different helical screw-senses depending on different stimuli. Acid-base chiral amines, for example, can induce helical conformations on cis-transoid poly(4-carboxyphenyl)acetylene yielding high-intensity circular dichroism signals. There have been many experimental attempts to elucidate the driving forces involved, but the induction process remains unclear. Here, we investigate the mechanism of helical polymer formation by both Molecular Dynamics (MD) and Density Functional Theory (DFT) approaches. We find that DFT calculations and the dissociation energies between 4 monomer polymers and amines show a clear trend in the affinity of R and S conformers with clockwise and counterclockwise polymer screw-senses, respectively. The charge analysis revealed that the local charge transfer effect plays a crucial role that leads to the helical polymer-amine induction.

Ab initio molecular dynamics with enhanced sampling in heterogeneous catalysis

Enhanced sampling ab initio simulations enable to study chemical phenomena in catalytic systems including thermal effects & anharmonicity, & collective dynamics describing enthalpic & entropic contributions, which can significantly impact on reaction free energy landscapes.

Ab Initio Direct Dynamics

The reactivity and dynamics of molecular systems can be explored computationally by classical trajectory calculations. The traditional approach involves fitting a functional form of a potential energy surface (PES) to the energies from a large number of electronic structure calculations and then integrating numerous trajectories on this fitted PES to model the molecular dynamics. The ever-decreasing cost of computing and continuing advances in computational chemistry software have made it possible to use electronic structure calculations directly in molecular dynamics simulations without first having to construct a fitted PES. In this "on-the-fly" approach, every time the energy and its derivatives are needed for the integration of the equations of motion, they are obtained directly from quantum chemical calculations. This approach started to become practical in the mid-1990s as a result of increased availability of inexpensive computer resources and improved computational chemistry software. The application of direct dynamics calculations has grown rapidly over the last 25 years and would require a lengthy review article. The present Account is limited to some of our contributions to methods development and various applications. To improve the efficiency of direct dynamics calculations, we developed a Hessian-based predictor-corrector algorithm for integrating classical trajectories. Hessian updating made this even more efficient. This approach was also used to improve algorithms for following the steepest descent reaction paths. For larger molecular systems, we developed an extended Lagrangian approach in which the electronic structure is propagated along with the molecular structure. Strong field chemistry is a rapidly growing area, and to improve the accuracy of molecular dynamics in intense laser fields, we included the time-varying electric field in a novel predictor-corrector trajectory integration algorithm. Since intense laser fields can excite and ionize molecules, we extended our studies to include electron dynamics. Specifically, we developed code for time-dependent configuration interaction electron dynamics to simulate strong field ionization by intense laser pulses. Our initial application of ab initio direct dynamics in 1994 was to CH₂O → H₂ + CO; the calculated vibrational distributions in the products were in very good agreement with experiment. In the intervening years, we have used direct dynamics to explore energy partitioning in various dissociation reactions, unimolecular dissociations yielding three fragments, reactions with branching after the transition state, nonstatistical dynamics of chemically activated molecules, dynamics of molecular fragmentation by intense infrared laser pulses, selective activation of specific dissociation channels by aligned intense infrared laser fields, angular dependence of strong field ionization, and simulation of sequential double ionization.

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix-matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born-Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born-Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

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.

Isohemigossypolone: Antiophidic properties of a naphthoquinone isolated from Pachira aquatica Aubl

We investigated the antiophidic properties of isohemigossypolone (ISO), a naphthoquinone isolated from the outer bark of the Pachira aquatic Aubl. The inhibition of phospholipase A₂, coagulant, fibrinogenolytic, hemorrhagic and myotoxic activities induced by Bothrops pauloensis venom (Pb) was investigated. For this, we use samples resulting from the incubation of Pb with ISO in different concentrations (1:1, 1:5 and 1:10 w/w), we also evaluated the condition of treatment using ISO after 15 min of venom inoculation. The activities of phospholipase A₂, coagulant, fibrinogenolytic, hemorrhagic and myotoxic induced by the B. pauloensis venom were significantly inhibited when the ISO was pre-incubated with the crude venom. For in vivo neutralization tests, the results were observed even when the ISO was applied after 15 min of inoculation of the venom or metalloprotease (BthMP). Also, to identify the inhibition mechanism, we performed in silico assays, across simulations of molecular coupling and molecular dynamics, it was possible to identify the modes of interaction between ISO and bothropic toxins BmooMPα-I, Jararacussin-I and BNSP-7. The present study shows that naphthoquinone isohemigossypolone isolated from the P. aquatica plant inhibited part of the local and systemic damage caused by venom proteins, demonstrating the pharmacological potential of this compound in neutralizing the harmful effects caused by snakebites.

Weighted-Graph-Theoretic Methods for Many-Body Corrections within ONIOM: Smooth AIMD and the Role of High-Order Many-Body Terms

We present a weighted-graph-theoretic approach to adaptively compute contributions from many-body approximations for smooth and accurate post-Hartree-Fock (pHF) ab initio molecular dynamics (AIMD) of highly fluxional chemical systems. This approach is ONIOM-like, where the full system is treated at a computationally feasible quality of treatment (density functional theory (DFT) for the size of systems considered in this publication), which is then improved through a perturbative correction that captures local many-body interactions up to a certain order within a higher level of theory (post-Hartree-Fock in this publication) described through graph-theoretic techniques. Due to the fluxional and dynamical nature of the systems studied here, these graphical representations evolve during dynamics. As a result, energetic "hops" appear as the graphical representation deforms with the evolution of the chemical and physical properties of the system. In this paper, we introduce dynamically weighted, linear combinations of graphs, where the transition between graphical representations is smoothly achieved by considering a range of neighboring graphical representations at a given instant during dynamics. We compare these trajectories with those obtained from a set of trajectories where the range of local many-body interactions considered is increased, sometimes to the maximum available limit, which yields conservative trajectories as the order of interactions is increased. The weighted-graph approach presents improved dynamics trajectories while only using lower-order many-body interaction terms. The methods are compared by computing dynamical properties through time-correlation functions and structural distribution functions. In all cases, the weighted-graph approach provides accurate results at a lower cost.

Quantum Chemical Microsolvation by Automated Water Placement

We developed a quantitative approach to quantum chemical microsolvation. Key in our methodology is the automatic placement of individual solvent molecules based on the free energy solvation thermodynamics derived from molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). This protocol enabled us to rigorously define the number, position, and orientation of individual solvent molecules and to determine their interaction with the solute based on physical quantities. The generated solute-solvent clusters served as an input for subsequent quantum chemical investigations. We showcased the applicability, scope, and limitations of this computational approach for a number of small molecules, including urea, 2-aminobenzothiazole, (+)-syn-benzotriborneol, benzoic acid, and helicene. Our results show excellent agreement with the available ab initio molecular dynamics data and experimental results.

Extended Lagrangian Born-Oppenheimer molecular dynamics for orbital-free density-functional theory and polarizable charge equilibration models

Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] is formulated for orbital-free Hohenberg-Kohn density-functional theory and for charge equilibration and polarizable force-field models that can be derived from the same orbital-free framework. The purpose is to introduce the most recent features of orbital-based XL-BOMD to molecular dynamics simulations based on charge equilibration and polarizable force-field models. These features include a metric tensor generalization of the extended harmonic potential, preconditioners, and the ability to use only a single Coulomb summation to determine the fully equilibrated charges and the interatomic forces in each time step for the shadow Born-Oppenheimer potential energy surface. The orbital-free formulation has a charge-dependent, short-range energy term that is separate from long-range Coulomb interactions. This enables local parameterizations of the short-range energy term, while the long-range electrostatic interactions can be treated separately. The theory is illustrated for molecular dynamics simulations of an atomistic system described by a charge equilibration model with periodic boundary conditions. The system of linear equations that determines the equilibrated charges and the forces is diagonal, and only a single Ewald summation is needed in each time step. The simulations exhibit the same features in accuracy, convergence, and stability as are expected from orbital-based XL-BOMD.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Identification of potential drugs against SARS-CoV-2 non-structural protein 1 (nsp1)

Non-structural protein 1 (nsp1) is found in all Betacoronavirus genus, an important viral group that causes severe respiratory human diseases. This protein has significant role in pathogenesis and it is considered a probably major virulence factor. As it is absent in humans, it becomes an interesting target of study, especially when it comes to the rational search for drugs, since it increases the specificity of the target and reduces possible adverse effects that may be caused to the patient. Using approaches in silico we seek to study the behavior of nsp1 in solution to obtain its most stable conformation and find possible drugs with affinity to all of them. For this purpose, complete model of nsp1 of SARS-CoV-2 were predicted and its stability analyzed by molecular dynamics simulations in five different replicas. After main pocket validation using two control drugs and the main conformations of nsp1, molecular docking based on virtual screening were performed to identify novel potential inhibitors from DrugBank database. It has been found 16 molecules in common to all five nsp1 replica conformations. Three of them was ranked as the best compounds among them and showed better energy score than control molecules that have in vitro activity against nsp1 from SARS-CoV-2. The results pointed out here suggest new potential drugs for therapy to aid the rational drug search against COVID-19.

Communicated by Ramaswamy H. Sarma

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

Modeling Dynamic Conformations of Organic Molecules: Alkyne Carotenoids in Solution

Calculating the spectroscopic properties of complex conjugated organic molecules in their relaxed state is far from simple. An additional complexity arises for flexible molecules in solution, where the rotational energy barriers are low enough so that nonminimum conformations may become dynamically populated. These metastable conformations quickly relax during the minimization procedures preliminary to density functional theory calculations, and so accounting for their contribution to the experimentally observed properties is problematic. We describe a strategy for stabilizing these nonminimum conformations in silico, allowing their properties to be calculated. Diadinoxanthin and alloxanthin present atypical vibrational properties in solution, indicating the presence of several conformations. Performing energy calculations in vacuo and polarizable continuum model calculations in different solvents, we found three different conformations with values for the δ dihedral angle of the end ring ca. 0, 180, and 90° with respect to the plane of the conjugated chain. The latter conformation, a nonglobal minimum, is not stable during the minimization necessary for modeling its spectroscopic properties. To circumvent this classical problem, we used a Car–Parinello MD supermolecular approach, in which diadinoxanthin was solvated by water molecules so that metastable conformations were stabilized by hydrogen-bonding interactions. We progressively removed the number of solvating waters to find the minimum required for this stabilization. This strategy represents the first modeling of a carotenoid in a distorted conformation and provides an accurate interpretation of the experimental data.

Interactome of Glyceraldehyde-3-Phosphate Dehydrogenase Points to the Existence of Metabolons in Paracoccidioides lutzii

Paracoccidioides is a dimorphic fungus, the causative agent of paracoccidioidomycosis. The disease is endemic within Latin America and prevalent in Brazil. The treatment is based on azoles, sulfonamides and amphotericin B. The seeking for new treatment approaches is a real necessity for neglected infections. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an essential glycolytic enzyme, well known for its multitude of functions within cells, therefore categorized as a moonlight protein. To our knowledge, this is the first approach performed on the Paracoccidioides genus regarding the description of PPIs having GAPDH as a target. Here, we show an overview of experimental GAPDH interactome in different phases of Paracoccidioides lutzii and an in silico analysis of 18 proteins partners. GAPDH interacted with 207 proteins in P. lutzii. Several proteins bound to GAPDH in mycelium, transition and yeast phases are common to important pathways such as glycolysis and TCA. We performed a co-immunoprecipitation assay to validate the complex formed by GAPDH with triose phosphate isomerase, enolase, isocitrate lyase and 2-methylcitrate synthase. We found GAPDH participating in complexes with proteins of specific pathways, indicating the existence of a glycolytic and a TCA metabolon in P. lutzii. GAPDH interacted with several proteins that undergoes regulation by nitrosylation. In addition, we modeled the GAPDH 3-D structure, performed molecular dynamics and molecular docking in order to identify the interacting interface between GAPDH and the interacting proteins. Despite the large number of interacting proteins, GAPDH has only four main regions of contact with interacting proteins, reflecting its ancestrality and conservation over evolution.

Parallel replica dynamics simulations of reactions in shock compressed liquid benzene

The study of the long-term evolution of slow chemical reactions is challenging because quantum-based reactive molecular dynamics simulation times are typically limited to hundreds of picoseconds. Here, the extended Lagrangian Born-Oppenheimer molecular dynamics formalism is used in conjunction with parallel replica dynamics to obtain an accurate tool to describe the long-term chemical dynamics of shock-compressed benzene. Langevin dynamics has been employed at different temperatures to calculate the first reaction times in liquid benzene at pressures and temperatures consistent with its unreacted Hugoniot. Our coupled engine runs for times on the order of nanoseconds (one to two orders of magnitude longer than traditional techniques) and is capable of detecting reactions that are characterized by rates significantly slower than we could study before. At lower pressures and temperatures, we mainly observe Diels-Alder metastable reactions, whereas at higher pressures and temperatures we observe stable polymerization reactions.

Predictive Simulations of Ionization Energies of Solvated Halide Ions with Relativistic Embedded Equation of Motion Coupled Cluster Theory

A subsystem approach for obtaining electron binding energies in the valence region is presented and applied to the case of halide ions (X^{-},X=F-At) in water. This approach is based on electronic structure calculations combining the relativistic equation-of-motion coupled cluster method for electron detachment and density functional theory via the frozen density embedding approach, using structures from classical molecular dynamics with polarizable force fields for discrete systems (in our study, droplets containing the anion and 50 water molecules). Our results indicate that one can accurately capture both the large solvent effect observed for the halides and the splitting of their ionization signals due to the increasingly large spin-orbit coupling of the p_{3/2}-p_{1/2} manifold across the series, at an affordable computational cost. Furthermore, owing to the quantum mechanical treatment of both solute and solvent electron binding energies of semiquantitative quality are also obtained for (bulk) water as by-products of the calculations for the halogens (in droplets).

Single-Ion Thermodynamics from First Principles: Calculation of the Absolute Hydration Free Energy and Single-Electrode Potential of Aqueous Li+ Using ab Initio Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulations

A recently proposed thermodynamic integration (TI) approach formulated in the framework of quantum mechanical/molecular mechanical molecular dynamics (QM/MM MD) simulations is applied to study the structure, dynamics, and absolute intrinsic hydration free energy Δ_s G_M⁺,wat^◦ of the Li⁺ ion at a correlated ab initio level of theory. Based on the results, standard values (298.15 K, ideal gas at 1 bar, ideal solute at 1 molal) for the absolute intrinsic hydration free energy [Formula: see text] of the proton, the surface electric potential jump χ_wat^◦ upon entering bulk water, and the absolute single-electrode potential [Formula: see text] of the reference hydrogen electrode are calculated to be -1099.9 ± 4.2 kJ·mol^-1, 0.13 ± 0.08 V, and 4.28 ± 0.04 V, respectively, in excellent agreement with the standard values recommended by Hünenberger and Reif on the basis of an extensive evaluation of the available experimental data (-1100 ± 5 kJ·mol^-1, 0.13 ± 0.10 V, and 4.28 ± 0.13 V). The simulation results for Li⁺ are also compared to those for Na⁺ and K⁺ from a previous study in terms of relative hydration free energies ΔΔ_s G_M⁺,wat^◦ and relative electrode potentials [Formula: see text]. The calculated values are found to agree extremely well with the experimental differences in standard conventional hydration free energies ΔΔ_s G_M⁺,wat^• and redox potentials [Formula: see text]. The level of agreement between simulation and experiment, which is quantitative within error bars, underlines the substantial accuracy improvement achieved by applying a highly demanding QM/MM approach at the resolution-of-identity second-order Møller-Plesset perturbation (RIMP2) level over calculations relying on purely molecular mechanical or density functional theory (DFT) descriptions. A detailed analysis of the structural and dynamical properties of the Li⁺ hydrate indicates that a correct description of the solvation structure and dynamics is achieved as well at this level of theory. Consideration of the QM/MM potential-energy components also shows that the partitioning into QM and MM zones does not induce any significant energetic artifact for the system considered.