A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat

Detection of Guanine Quadruplexes by Raman Optical Activity and Quantum-Chemical Interpretation of the Spectra

Quadruplexes formed by guanine derivatives or guanine-rich nucleic acids are involved in metabolism and genetic storage of many living organisms, they are used in DNA nanotechnologies or as biosensors. Since many quadruplex geometries are possible the determination of their structures in aqueous solutions is difficult. Raman optical activity (ROA) can make it easier: For guanosine monophosphate (GMP), we observed a distinct change of the spectra upon its condensation and quadruplex formation. The vibrational bands become more numerous, stronger, and narrower. In particular, a huge ROA signal appears below 200 cm-1. The aggregation can be induced by high concentration, low temperature, or by a metal ion. We focused on well-defined quadruplexes stabilized by potassium, where using molecular dynamics and density functional theory the spectra and particular features related to GMP geometric parameters could be understood. The simulations explain the main experimental trends and confirm that the ROA spectroscopy is sensitive to fine structural details, including guanine base twist in the quadruplex helix.

Structural Basis for Antagonist Binding to Vasopressin V1b Receptor Revealed by the Molecular Dynamics Simulations

The human V1b receptor (V1bR) is primarily expressed in the corticotropic cells of the anterior pituitary where it is involved in the regulation of the hypothalamic-pituitary-adrenal (HPA) axis. The activation of V1bR induces the secretion of adrenocorticotropin hormone (ACTH) from the anterior pituitary cells which, in turn, stimulates the production of cortisol via the adrenal cortex. Clinical studies have demonstrated the chronic dysfunction of the HPA axis in patients with several psychiatric disorders. Thus, the inhibition of the V1b receptor and normalizing the HPA axis hyperactivity is a promising approach to the treatment of many stress-related disorders such as anxiety and depression. Nelivaptan is a selective V1bR antagonist that can be used for this purpose and an excellent molecule to study how antagonists interact with V1bR, especially since in recent years the experimental structures of vasopressin V2 and oxytocin receptors were solved, providing high-similarity templates for homology modeling of V1bR. Therefore, in this work, six independent molecular dynamics simulations of a V1bR-nelivaptan complex in a fully hydrated lipid bilayer, yielding a total simulation time of 6.0 μs, have been conducted. In the lowest-energy complexes obtained in this work and proposed to be the most probable structure of the V1bR-nelivaptan complex, the location of the ligand inside the receptor pocket is very similar to that of the other ligands observed in the experimental structures of the vasopressin/oxytocin receptor family. The receptor-ligand interaction has been analyzed and described, revealing the details of the molecular mechanism of this antagonist binding to V1bR and a probable contribution of L2005×40 and T2035×43 to binding selectivity.

NMR structures and magnetic force spectroscopy studies of small molecules binding to models of an RNA CAG repeat expansion

RNA repeat expansions fold into stable structures and cause microsatellite diseases such as Huntington's disease (HD), myotonic dystrophy type 1 (DM1), and spinocerebellar ataxias (SCAs). The trinucleotide expansion of r(CAG), or r(CAG)exp, causes both HD and SCA3, and the RNA's toxicity has been traced to its translation into polyglutamine (polyQ; HD) as well as aberrant pre-mRNA alternative splicing (SCA3 and HD). Previously, a small molecule, 1, was discovered that binds to r(CAG)exp and rescues aberrant pre-mRNA splicing in patient-derived fibroblasts by freeing proteins bound to the repeats. Here, we report the structures of single r(CAG) repeat motif (5'CAG/3'GAC where the underlined adenosines form a 1×1 nucleotide internal loop) in complex with 1 and two other small molecules via nuclear magnetic resonance (NMR) spectroscopy combined with simulated annealing. Compound 2 was designed based on the structure of 1 bound to the RNA while 3 was selected as a diverse chemical scaffold. The three complexes, although adopting different 3D binding pockets upon ligand binding, are stabilized by a combination of stacking interactions with the internal loop's closing GC base pairs, hydrogen bonds, and van der Waals interactions. Molecular dynamics (MD) simulations performed with NMR-derived restraints show that the RNA is stretched and bent upon ligand binding with significant changes in propeller-twist and opening. Compound 3 has a distinct mode of binding by insertion into the helix, displacing one of the loop nucleotides into the major groove and affording a rod-like shape binding pocket. In contrast, 1 and 2 are groove binders. A series of single molecule magnetic force spectroscopy studies provide a mechanistic explanation for how bioactive compounds might rescue disease-associated cellular phenotypes.

Multiple Parameter Replica Exchange Gaussian Accelerated Molecular Dynamics for Enhanced Sampling and Free Energy Calculation of Biomolecular Systems

This study introduces a novel method named multiple parameter replica exchange Gaussian accelerated molecular dynamics (MP-Rex-GaMD), building on the Gaussian accelerated molecular dynamics (GaMD) algorithm. GaMD enhances sampling and retrieves free energy information for biomolecular systems by adding a harmonic boost potential to smooth the potential energy surface without the need for predefined reaction coordinates. Our innovative approach advances the acceleration power and energetic reweighting accuracy of GaMD by incorporating a replica exchange algorithm that enables the exchange of multiple parameters, including the GaMD boost parameters of force constant and energy threshold, as well as temperature. Applying MP-Rex-GaMD to the three model systems of dialanine, chignolin, and HIV protease, we demonstrate its superior capability over conventional molecular dynamics and GaMD simulations in exploring protein conformations and effectively navigating various biomolecular states across energy barriers. MP-Rex-GaMD allows users to accurately map free energy landscapes through energetic reweighting, capturing the ensemble of biomolecular states from low-energy conformations to rare high-energy transitions within practical computational time scales.

Modeling solvent effects and convergence of 31P-NMR shielding calculations with COBRAMM

Solvent effects on 31P-NMR parameters for triphenylphosphine oxide and triphenylphosphine in chloroform have been extensively investigated by testing different solvation models. The solvent is described implicitly, mixed implicitly/explicitly, and using full explicit models. Polarizable continuum model (PCM), molecular dynamic (MD) simulations, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations are used to disclose the effects of solute/solvent interactions and, more generally, the role of the embedding in NMR simulations. The results show the beneficial effect of carrying out QM/MM optimizations on top of geometries directly extracted from classical MD simulations, used to ensure representative conformational sampling. The nuclear shielding convergence has been tested against a different number of snapshots and with the inclusion of solvent shells into the QM region. An automated MD//QM/MM//GIAO protocol, implemented in the COBRAMM package, is here proposed and tested on trimethyl phosphite showing that our approach boosts the convergence of nuclear shielding satisfactorily. The present work aims to be a stepping-stone to assess proper QM/MM computational strategies in simulating chemical shifts in non-homogeneous systems like supramolecular and biological systems.

Reactions dynamics for X + H2 insertion reactions (X = C(1D), N(2D), O(1D), S(1D)) with Cayley propagator ring-polymer molecular dynamics

In this work, rate coefficients of four prototypical insertion reactions, X + H2 → H + XH (X = C(1D), N(2D), O(1D), S(1D)), and associated isotope reactions are calculated based on ring polymer molecular dynamics (RPMD) with Cayley propagator (Cayley-RPMD). The associated kinetic isotope effects are systematically studied too. The Cayley propagator used in this work increases the stability of numerical integration in RPMD calculations and also supports a larger evolution time interval, allowing us to reach both high accuracy and efficiency. So, our results do not only provide chemical kinetic data for the title reactions in an extended temperature range but also consist of experimental results, standard RPMD, and other theoretical methods. The results in this work also reflect that Cayley-RPMD has strong consistency and high reliability in its investigations of chemical dynamics for insertion reactions.

Exploring Novel Antimalarial Compounds Targeting Plasmodium falciparum Enoyl-ACP Reductase: Computational and Experimental Insights

Malaria, caused by Plasmodium protozoa with Plasmodium falciparum as the most virulent species, continues to pose significant health challenges. Despite the availability of effective antimalarial drugs, the emergence of resistance has heightened the urgency for developing novel therapeutic compounds. In this study, we investigated the enoyl-ACP reductase enzyme of P. falciparum (PfENR) as a promising target for antimalarial drug discovery. Through a comprehensive analysis, we conducted a comparative evaluation of two lead compounds, LD1 (CID: 44405336, lead compounds 1) and LD2 (CID: 72703246, lead compounds 2), obtained from the PubChem/NCBI ligand database, to serve as reference molecules in the identification of potential derivatives using virtual screening assays. Among the newly identified candidates, Ligand 1 (LG1) and Ligand 2 (LG2) exhibited intriguing characteristics and underwent further investigation through docking and molecular dynamics simulations. Ligand 1 (LG1) demonstrated interactions similar to LD1, including hydrogen bonding with Asp218, while Ligand 2 (LG2) displayed superior binding energy comparable to LD1 and LD2, despite lacking hydrogen bonding interactions observed in the control compounds triclosan and its derivative 7-(4-chloro-2-hydroxyphenoxy)-4-methyl-2H-chromen-2-one (CHJ). Following computational validation using the MM/GBSA method to estimate binding free energy, commercially acquired LG1 and LG2 ligands were subjected to in vitro testing. Inhibition assays were performed to evaluate their potential as PfENR inhibitors alongside triclosan as a control compound. LG1 exhibited no inhibitory effects, while LG2 demonstrated inhibitory effects like triclosan. In conclusion, this study contributes valuable insights into developing novel antimalarial drugs by identifying LG2 as a potential ligand and employing a comprehensive approach integrating computational and experimental methodologies.

Structural Insights into Seeding Mechanisms of hIAPP Fibril Formation

The deposition of islet amyloid polypeptide (hIAPP) fibrils is a hallmark of β-cell death in type II diabetes. In this study, we employ state-of-the-art MAS solid-state spectroscopy to investigate the previously elusive N-terminal region of hIAPP fibrils, uncovering both rigidity and heterogeneity. Comparative analysis between wild-type hIAPP and a disulfide-deficient variant (hIAPPC2S,C7S) unveils shared fibril core structures yet strikingly distinct dynamics in the N-terminus. Specifically, the variant fibrils exhibit extended β-strand conformations, facilitating surface nucleation. Moreover, our findings illuminate the pivotal roles of specific residues in modulating secondary nucleation rates. These results deepen our understanding of hIAPP fibril assembly and provide critical insights into the molecular mechanisms underpinning type II diabetes, holding promise for future therapeutic strategies.

An intrinsic network of polar interactions is responsible for binding of UL49.5 C-degron by the CRL2KLHDC3 ubiquitin ligase

Bovine herpesvirus type 1 (BoHV-1) is a pathogen of cattle responsible for infectious bovine rhinotracheitis. The BoHV-1 UL49.5 is a transmembrane protein that binds to the transporter associated with antigen processing (TAP) and downregulates cell surface expression of the antigenic peptide complexes with the major histocompatibility complex class I (MHC-I). KLHDC3 is a kelch domain-containing protein 3 and a substrate receptor of a cullin2-RING (CRL2) E3 ubiquitin ligase. Recently, it has been identified that CRL2KLHDC3 is responsible for UL49.5-triggered TAP degradation via a C-degron pathway and the presence of the degron sequence does not lead to the degradation of UL49.5 itself. The molecular modeling of KLHDC3 in complexes with four UL49.5 C-terminal decapeptides (one native protein and three mutants) revealed their activity to be closely correlated with the conformation which they adopt in KLHDC3 binding cleft. To analyze the interaction between UL49.5 and KLHDC3 in detail, in this work a total of 3.6 μs long molecular dynamics simulations have been performed. The complete UL49.5-KLHDC3 complexes were embedded into the fully hydrated all-atom lipid membrane model with explicit water molecules. The network of polar interactions has been proposed to be responsible for the recognition and binding of the degron in KLHDC3. The interaction network within the binding pocket appeared to be very similar between two CRL2 substrate receptors: KLHDC3 and KLHDC2.

Multiple-time scale integration method based on an interpolated potential energy surface for ab initio path integral molecular dynamics

A new multiple-time scale integration method is presented that propagates ab initio path integral molecular dynamics (PIMD). This method uses a large time step to generate an approximate geometrical configuration whose energy and gradient are evaluated at the level of an ab initio method, and then, a more precise integration scheme, e.g., the Bulirsch-Stoer method or velocity Verlet integration with a smaller time step, is used to integrate from the previous step using the computationally efficient interpolated potential energy surface constructed from two consecutive points. This method makes the integration of PIMD more efficient and accurate compared with the velocity Verlet integration. A Nosé-Hoover chain thermostat combined with this new multiple-time scale method has good energy conservation even with a large time step, which is usually challenging in velocity Verlet integration for PIMD due to the very small chain mass when a large number of beads are used. The new method is used to calculate infrared spectra and free energy profiles to demonstrate its accuracy and capabilities.

Assessing the mechanism of fast-cycling cancer-associated mutations of Rac1 small Rho GTPase

Rho-GTPases proteins function as molecular switches alternating from an active to an inactive state upon Guanosine triphosphate (GTP) binding and hydrolysis to Guanosine diphosphate (GDP). Among them, Rac subfamily regulates cell dynamics, being overexpressed in distinct cancer types. Notably, these proteins are object of frequent cancer-associated mutations at Pro29 (P29S, P29L, and P29Q). To assess the impact of these mutations on Rac1 structure and function, we performed extensive all-atom molecular dynamics simulations on wild-type (wt) and oncogenic isoforms of this protein in GDP- and GTP-bound states. Our results unprecedentedly elucidate that P29Q/S-induced structural and dynamical perturbations of Rac1 core domain weaken the binding of the catalytic site Mg2+ ion, and reduce the GDP residence time within protein, enhancing the GDP/GTP exchange rate and Rac1 activity. This broadens our knowledge of the role of cancer-associated mutations on small GTPases mechanism supplying valuable information for future drug discovery efforts targeting specific Rac1 isoforms.

Mechanistic insights into ligand dissociation from the SARS-CoV-2 spike glycoprotein

The COVID-19 pandemic, driven by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spurred an urgent need for effective therapeutic interventions. The spike glycoprotein of the SARS-CoV-2 is crucial for infiltrating host cells, rendering it a key candidate for drug development. By interacting with the human angiotensin-converting enzyme 2 (ACE2) receptor, the spike initiates the infection of SARS-CoV-2. Linoleate is known to bind the spike glycoprotein, subsequently reducing its interaction with ACE2. However, the detailed mechanisms underlying the protein-ligand interaction remain unclear. In this study, we characterized the pathways of ligand dissociation and the conformational changes associated with the spike glycoprotein by using ligand Gaussian accelerated molecular dynamics (LiGaMD). Our simulations resulted in eight complete ligand dissociation trajectories, unveiling two distinct ligand unbinding pathways. The preference between these two pathways depends on the gate distance between two α-helices in the receptor binding domain (RBD) and the position of the N-linked glycan at N343. Our study also highlights the essential contributions of K417, N121 glycan, and N165 glycan in ligand unbinding, which are equally crucial in enhancing spike-ACE2 binding. We suggest that the presence of the ligand influences the motions of these residues and glycans, consequently reducing accessibility for spike-ACE2 binding. These findings enhance our understanding of ligand dissociation from the spike glycoprotein and offer significant implications for drug design strategies in the battle against COVID-19.

In silico and in vitro studies: investigating the chemical composition, DFT, molecular docking, and dynamic simulation of Satureja candidissima (Munby) Briq essential oil as a potential antibacterial agent

This study aimed to investigate the chemical composition and antibacterial properties of the essential oil (EO) derived from the aerial parts of Satureja candidissima (Munby) Briq (SC), as well as the mechanisms of interaction between SCEO chemical components and target proteins related to antibacterial activity mechanisms using a molecular docking approach, and for more accuracy molecular dynamic simulation and DFT calculations were carried out. The GC-MS technique was used to analyze the chemical composition of SCEO. The results showed that SCEO contained various chemical compounds, with pulegone being identified as the major component (53.26%). The results also indicated the presence of (+)-menthone (11.02%), borneol (4.43%), 2-cyclohexen-1-one, 3-methyl-6-(1-methylethylidene) (2.50%), and 3-octanol (2.09%). The study revealed that the SCEO displayed antibacterial activity against all tested gram-positive bacteria. To further understand the mechanism behind its antibacterial activity, in silico molecular docking studies were performed. The results indicated that the antibacterial effect of SCEO compounds could be due to the combination with enoyl-[acyl-carrier-protein] reductase [NADPH] FabI (PDB ID: 4ALL) in a variety of ways. The molecular dynamics simulation analysis yielded favorable outcomes for the docked complex involving 1H-cycloprop[e]azulen-7-ol, decahydro-1,1,7-trimethyl-4-methylene, and 1,4,7-tetramethyldecahydro-1H-cyclopropa[e]azulen-4-ol with enoyl-[acyl-carrier-protein] reductase [NADPH]. Geometry optimization, coupled with Density Functional Theory (DFT), can be employed to assess the importance of quantum chemical descriptors in elucidating potential antibacterial activity. Quantum descriptors were computed based on EHOMO and ELUMO. The results of this study provide important insights into the potential use of Satureja candidissima (Munby) Briq EO as antibacterial agent.Communicated by Ramaswamy H. Sarma.

Antiemetic effects of sclareol, possibly through 5-HT3 and D2 receptor interaction pathways: In-vivo and in-silico studies

BACKGROUND

Emesis is a complex physiological phenomenon that serves as a defense against numerous toxins, stressful situations, adverse medication responses, chemotherapy, and movement. Nevertheless, preventing emesis during chemotherapy or other situations is a significant issue for researchers. Hence, the majority view contends that successfully combining therapy is the best course of action. In-vivo analysis offers a more comprehensive grasp of how compounds behave within a complex biological environment, whereas in-silico evaluation refers to the use of computational models to forecast biological interactions.

OBJECTIVES

The objectives of the present study were to evaluate the effects of Sclareol (SCL) on copper sulphate-induced emetic chicks and to investigate the combined effects of these compounds using a conventional co-treatment approach and in-silico study.

METHODS

SCL (5, 10, and 15 mg/kg) administered orally with or without pre-treatment with anti-emetic drugs (Ondansetron (ODN): 24 mg/kg, Domperidone (DOM): 80 mg/kg, Hyoscine butylbromide (HYS): 100 mg/kg, and Promethazine hydrochloride (PRO): 100 mg/kg) to illustrate the effects and the potential involvement with 5HT3, D2, M3/AChM, H1, or NK1 receptors by SCL. Furthermore, an in-silico analysis was conducted to forecast the role of these receptors in the emetic process.

RESULTS

The results suggest that SCL exerted a dose-dependent anti-emetic effect on the chicks. Pretreatment with SCL-10 significantly minimized the number of retches and lengthened the emesis tendency of the experimental animals. SCL-10 significantly increased the anti-emetic effects of ODN and DOM. However, compared to the ODN-treated group, (SCL-10 + ODN) group considerably (p < 0.0001) extended the latency duration (109.40 ± 1.03 s) and significantly (p < 0.01) decreased the number of retches (20.00 ± 0.70), indicating an anti-emetic effect on the test animals. In in-silico analysis, SCL exhibited promising binding affinities with suggesting receptors.

CONCLUSION

SCL-10 exerted an inhibitory-like effect on emetic chicks, probably through the interaction of the 5HT3 and D2 receptors. Further studies are highly appreciated to validate this study and determine the precise mechanism(s) behind the anti-emetic effects of SCL. We expect that SCL-10 may be utilized as an antiemetic treatment in a single dosage form or that it may function as a synergist with other traditional medicines.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

Molecular dynamics study reveals key disruptors of MEIG1-PACRG interaction

Interactions between the meiosis-expressed gene 1 (MEIG1) and Parkin co-regulated gene (PACRG) protein are critical in the formation of mature sperm cells. Targeting either MEIG1 or PACRG protein could be a contraceptive strategy. The W50A and Y68A mutations on MEIG1 are known to interrupt the MEIG1-PACRG interactions resulting in defective sperm cells. However, the details about how the mutants disrupt the protein-protein binding are not clear. In this study, we reveal insights on MEIG1 and PACRG protein dynamics by applying Gaussian-accelerated molecular dynamics (GaMD) simulations and post-GaMD analysis. Our results show that the mutations destabilize the protein-protein interfacial interaction. The effect of the Y68A mutation is more significant than W50A as Y68 forms stronger polar interactions with PACRG. Because both human and mouse models demonstrate similar dynamic properties, the findings from mouse proteins can be applied to the human system. Moreover, we report a potential ligand binding pocket on the MEIG1 and PACRG interaction surface that could be a target for future drug design to inhibit the MEIG1-PACRG interaction. PACRG shows more qualified pockets along the protein-protein interface, implying that it is a better target than MEIG1. Our work provides a fundamental understanding of MEIG1 and PACRG protein dynamics, paving the way for drug discovery in male-based contraception.

Machine learning in accelerating microsphere formulation development

Microspheres have gained much attention from pharmaceutical and medical industry due to the excellent biodegradable and long controlled-release characteristics. However, the drug release behavior of microspheres is influenced by complicated formulation and manufacturing factors. The traditional formulation development of microspheres is intractable and inefficient by the experimentally trial-and-error methods. This research aims to build a prediction model to accelerate microspheres product development for small-molecule drugs by machine learning (ML) techniques. Two hundred eighty-six microsphere formulations with small-molecule drugs were collected from the publications and pharmaceutical company, including the dissolution temperature at both 37 ℃ and 45 ℃. After the comparison of fourteen ML approaches, the consensus model achieved accurate predictions for the validation set at 37 ℃ and 45 ℃ (R² = 0.880 vs. R² = 0.958), indicating the good performance to predict the in vitro drug release profiles at both 37 ℃ and 45 ℃. Meanwhile, the models revealed the feature importance of formulations, which offered meaningful insights to the microspheres development. Experiments of microsphere formulations further validated the accuracy of the consensus model. Furthermore, molecular dynamics (MD) simulation provided a microscopic view of the preparation process of microspheres. In conclusion, the prediction model of microsphere formulations for small-molecule drugs was successfully built with high accuracy, which is able to accelerate microspheres product development and promote the quality control of microspheres for the pharmaceutical industry.

Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: From Force Fields to Machine Learning Potentials

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.

Correlation between protein conformations and water structure and thermodynamics at high pressure: A molecular dynamics study of the Bovine Pancreatic Trypsin Inhibitor (BPTI) protein

Pressure-induced perturbation of a protein structure leading to its folding-unfolding mechanism is an important yet not fully understood phenomenon. The key point here is the role of water and its coupling with protein conformations as a function of pressure. In the current work, using extensive molecular dynamics simulation at 298 K, we systematically examine the coupling between protein conformations and water structures of pressures of 0.001, 5, 10, 15, 20 kbar, starting from (partially) unfolded structures of the protein Bovine Pancreatic Trypsin Inhibitor (BPTI). We also calculate localized thermodynamics at those pressures as a function of protein-water distance. Our findings show that both protein-specific and generic effects of pressure are operating. In particular, we found that (1) the amount of increase in water density near the protein depends on the protein structural heterogeneity; (2) the intra-protein hydrogen bond decreases with pressure, while the water-water hydrogen bond per water in the first solvation shell (FSS) increases; protein-water hydrogen bonds also found to increase with pressure, (3) with pressure hydrogen bonds of waters in the FSS getting twisted; and (4) water's tetrahedrality in the FSS decreases with pressure, but it is dependent on the local environment. Thermodynamically, at higher pressure, the structural perturbation of BPTI is due to the pressure-volume work, while the entropy decreases with the increase of pressure due to the higher translational and rotational rigidity of waters in the FSS. The local and subtle effects of pressure, found in this work, are likely to be typical of pressure-induced protein structure perturbation.

Structural Factors That Determine the Activity of the Xenobiotic Reductase B Enzyme from Pseudomonas putida on Nitroaromatic Compounds

Xenobiotic reductase B (XenB) catalyzes the reduction of the aromatic ring or nitro groups of nitroaromatic compounds with methyl, amino or hydroxyl radicals. This reaction is of biotechnological interest for bioremediation, the reuse of industrial waste or the activation of prodrugs. However, the structural factors that explain the binding of XenB to different substrates are unknown. Molecular dynamics simulations and quantum mechanical calculations were performed to identify the residues involved in the formation and stabilization of the enzyme/substrate complex and to explain the use of different substrates by this enzyme. Our results show that Tyr65 and Tyr335 residues stabilize the ligands through hydrophobic interactions mediated by the aromatic rings of these aminoacids. The higher XenB activity determined with the substrates 1,3,5-trinitrobenzene and 2,4,6-trinitrotoluene is consistent with the lower energy of the highest occupied molecular orbital (LUMO) orbitals and a lower energy of the homo orbital (LUMO), which favors electrophile and nucleophilic activity, respectively. The electrostatic potential maps of these compounds suggest that the bonding requires a large hydrophobic region in the aromatic ring, which is promoted by substituents in ortho and para positions. These results are consistent with experimental data and could be used to propose point mutations that allow this enzyme to process new molecules of biotechnological interest.

Path integral Brownian chain molecular dynamics: A simple approximation of quantum vibrational dynamics

An approximate approach to quantum vibrational dynamics, "Brownian chain molecular dynamics (BCMD)," is proposed to alleviate the chain resonance and curvature problems in the imaginary time-based path integral (PI) simulation. Here the non-centroid velocity is randomized at each step when solving the equation of motion of path integral molecular dynamics. This leads to a combination of the Newton equation and the overdamped Langevin equation for the centroid and non-centroid variables, respectively. BCMD shares the basic properties of other PI approaches such as centroid and ring polymer molecular dynamics: It gives the correct Kubo-transformed correlation function at short times, conserves the time symmetry, has the correct high-temperature/classical limits, gives exactly the position and velocity autocorrelations of harmonic oscillator systems, and does not have the zero-point leakage problem. Numerical tests were done on simple molecular models and liquid water. On-the-fly ab initio BCMD simulations were performed for the protonated water cluster, H 5 O 2 + $$ {\mathrm{H}}_5{\mathrm{O}}_2^{+} $$ , and its isotopologue, D 5 O 2 + $$ {\mathrm{D}}_5{\mathrm{O}}_2^{+} $$ .

New Stable and Fast Ring-Polymer Molecular Dynamics for Calculating Bimolecular Rate Coefficients with an Example of OH + CH4

The accurate and efficient calculation of the rate coefficients of chemical reactions is a key issue in the research of chemical dynamics. In this work, by applying the dimension-free ultrastable Cayley propagator, the thermal rate coefficients of a prototypic high dimensional chemical reaction OH + CH₄ → H₂O + CH₃ in the temperature range of 200 to 1500 K are investigated with ring polymer molecular dynamics (RPMD) on a highly accurate full-dimensional potential energy surface. Kinetic isotope effects (KIEs) for three isotopologues of the title reaction are also studied. The results demonstrate excellent agreement with experimental data, even in the deep tunneling region. Especially, the Cayley propagator shows a high calculation efficiency with little loss of accuracy. The present results confirmed the applicability of the RPMD method, particularly the speed-up using a Cayley propagator, in theoretical calculations of bimolecular reaction rates.

Automatized protocol and interface to simulate QM/MM time-resolved transient absorption at TD-DFT level with COBRAMM

We present a series of new implementations that we recently introduced in COBRAMM, the open-source academic software developed in our group. The goal of these implementations is to offer an automatized workflow and interface to simulate time-resolved transient absorption (TA) spectra of medium-to-big chromophore embedded in a complex environment. Therefore, the excited states absorption and the stimulated emission are simulated along nonadiabatic dynamics performed with trajectory surface hopping. The possibility of treating systems from medium to big size is given by the use of time-dependent density functional theory (TD-DFT) and the presence of the environment is taken into account employing a hybrid quantum mechanics/molecular mechanics (QM/MM) scheme. The full implementation includes a series of auxiliary scripts to properly setup the QM/MM system, the calculation of the wavefunction overlap along the dynamics for the propagation, the evaluation of the transition dipole moment at linear response TD-DFT level, and scripts to setup, run and analyze the TA from an ensemble of trajectories. Altogether, we believe that our implementation will open the door to the easily simulate the time-resolved TA of systems so far computationally inaccessible.

The superior effect of edge functionalization relative to basal plane functionalization of graphene in enhancing the thermal conductivity of polymer-graphene nanocomposites - a combined molecular dynamics and Green's functions study

To achieve polymer-graphene nanocomposites with high thermal conductivity (k), it is critically important to achieve efficient thermal coupling between graphene and the surrounding polymer matrix through effective functionalization schemes. In this work, we demonstrate that edge-functionalization of graphene nanoplatelets (GnPs) can enable a larger enhancement of effective thermal conductivity in polymer-graphene nanocomposites relative to basal plane functionalization. Effective thermal conductivity for the edge case is predicted, through molecular dynamics simulations, to be up to 48% higher relative to basal plane bonding for 35 wt% graphene loading with 10 layer thick nanoplatelets. The beneficial effect of edge bonding is related to the anisotropy of thermal transport in graphene, involving very high in-plane thermal conductivity (∼2000 W m^-1 K^-1) compared to the low out-of-plane thermal conductivity (∼10 W m^-1 K^-1). Likewise, in multilayer graphene nanoplatelets (GnPs), the thermal conductivity across the layers is even lower due to the weak van der Waals bonding between each pair of layers. Edge functionalization couples the polymer chains to the high in-plane thermal conduction pathway of graphene, thus leading to overall high thermal conductivity of the composite. Basal-plane functionalization, however, lowers the thermal resistance between the polymer and the surface graphene sheets of the nanoplatelet only, causing the heat conduction through inner layers to be less efficient, thus resulting in the basal plane scheme to be outperformed by the edge scheme. The present study enables fundamentally novel pathways for achieving high thermal conductivity polymer nanocomposites.

Generalized fourth-order decompositions of imaginary time path integral: Implications of the harmonic oscillator

The imaginary time path integral formalism offers a powerful numerical tool for simulating thermodynamic properties of realistic systems. We show that, when second-order and fourth-order decompositions are employed, they share a remarkable unified analytic form for the partition function of the harmonic oscillator. We are then able to obtain the expression of the thermodynamic property and the leading error terms as well. In order to obtain reasonably optimal values of the free parameters in the generalized symmetric fourth-order decomposition scheme, we eliminate the leading error terms to achieve the accuracy of desired order for the thermodynamic property of the harmonic system. Such a strategy leads to an efficient fourth-order decomposition that produces third-order accurate thermodynamic properties for general systems.

Computational Investigation of Bending Properties of RNA AUUCU, CCUG, CAG, and CUG Repeat Expansions Associated With Neuromuscular Disorders

Expansions of RNA AUUCU, CCUG, CAG, and CUG repeats cause spinocerebellar ataxia type 10, myotonic dystrophy type 2, Huntington’s disease, and myotonic dystrophy type 1, respectively. By performing extensive molecular dynamic simulations, we investigated the bending propensities and conformational landscapes adopted by 3×3, 2×2, and 1×1 internal loops observed in RNA AUUCU, CCUG, CAG, and CUG repeat expansions using model systems having biologically relevant repeat sizes. We show that the conformational variability experienced by these loops is more complex than previous reports where a variety of unconventional hydrogen bonds are formed. At the global scale, strong bending propensity was observed in r(AUUCU)₁₀, r(CCUG)₁₅, r(CAG)_20, and r(CUG)_20, and, to a lesser extent, in r(AUUCU)₄, r(CCUG)₁₀, r(CAG)₁₀, and r(CUG)₁₀. Furthermore, RNA CAG repeats exhibit a tendency toward bent states with more than 50% of observed conformations having bending angles greater than 50°, while RNA CUG repeats display relatively linear-like conformations with extremely bent conformations accounting for less than 25% of the observed structures. Conformations experienced by RNA AUUCU repeats are a combination of strongly bent and kinked structures. The bent states in RNA CCUG repeats mostly fall into the moderately bent category with a marginal ensemble experiencing extreme bending. The general pattern observed in all the bent structures indicates the collapse of the major groove width as the mechanical trigger for bending, which is caused by alteration of base pair step parameters at multiple locations along the RNA due to local distortions at the loop sites. Overextension is also observed in all the RNA repeats that is attributed to widening of the major groove width as well as undertwisting phenomenon. This information and the rich structural repository could be applied for structure based small molecule design targeting disease-causing RNAs. The bending propensities of these constructs, at the global level, could also have implications on how expanded RNA repeats interact with proteins.

Elucidating novel antibacterial compounds from the NPASS database against the FimH lectin domain for the treatment of urinary tract infections: an in-silico study

The increase in multidrug-resistant pathogens in urinary tract infections (UTIs) among communities and hospitals threatens our ability to treat these common pathogens. Uropathogenic Escherichia coli (UPEC) strains are the most frequent uropathies linked to the development of UTIs. This work aims to introduce bioactive natural products via virtual screening of small molecules from a public database to prevent biofilm formation by inhibiting FimH, a type 1 fimbriae that plays a crucial role in UPEC pathogenicity. A total of 30926 small molecules from the NPASS database were subjected to screening via molecular docking. Followed by performing in silico ADME studies, seven molecules showed promising docking results ranging from -6.8 to -8.7 kcal/mol. As a result of the docking score findings, 100 ns Molecular dynamics (MD) simulations were performed. Based on MM-PBSA analysis, NPC313334 ligand showed high binding affinity -42 and stability with the binding pocket of FimH protein during molecular dynamic simulations. DFT calculations were also performed on the ligands to calculate the HOMO-LUMO energies of the compounds in order to an idea about their structure and reactivity. This research suggests that NPC313334 may be a possible antibacterial drug candidate that targets FimH to reduce the number of UPEC-related urinary tract infections. Communicated by Ramaswamy H. Sarma.

Affordable Ab Initio Path Integral for Thermodynamic Properties via Molecular Dynamics Simulations Using Semiempirical Reference Potential

Path integral molecular dynamics (PIMD) is becoming a routinely applied method for incorporating the nuclear quantum effect in computer simulations. However, direct PIMD simulations at an ab initio level of theory are formidably expensive. Using the protonated 1,8-bis(dimethylamino)naphthalene molecule as an example, we show in this work that the computational expense for the intramolecular proton transfer between the two nitrogen atoms can be remarkably reduced by implementing the idea of reference-potential methods. The simulation time can be easily extended to a scale of nanoseconds while maintaining the accuracy on an ab initio level of theory for thermodynamic properties. In addition, postprocessing can be carried out in parallel on massive computer nodes. A 545-fold reduction in the total CPU time can be achieved in this way as compared to a direct PIMD simulation at the same ab initio level of theory.

Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm

Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development for mRNA vaccines. Firstly, 325 data samples of mRNA vaccine LNP formulations with IgG titer were collected. The machine learning algorithm, lightGBM, was used to build a prediction model with good performance (R² > 0.87). More importantly, the critical substructures of ionizable lipids in LNPs were identified by the algorithm, which well agreed with published results. The animal experimental results showed that LNP using DLin-MC3-DMA (MC3) as ionizable lipid with an N/P ratio at 6:1 induced higher efficiency in mice than LNP with SM-102, which was consistent with the model prediction. Molecular dynamic modeling further investigated the molecular mechanism of LNPs used in the experiment. The result showed that the lipid molecules aggregated to form LNPs, and mRNA molecules twined around the LNPs. In summary, the machine learning predictive model for LNP-based mRNA vaccines was first developed, validated by experiments, and further integrated with molecular modeling. The prediction model can be used for virtual screening of LNP formulations in the future.

In-silico design of peptides for inhibition of HLA-A*03-KLIETYFSK complex as a new drug design for treatment of multiples sclerosis disease

Multiple sclerosis is recognized as a chronic inflammatory disease. Human leukocyte antigen (HLA) plays an important role in initiating adaptive immune responses. HLA class I is present in almost all nucleated cells and presents the cleaved endogenous peptide antigens to cytotoxic T cells. HLA-A*03 is one of the HLA class I alleles, which is reported as substantially related HLA to MS disease. In 2011, the structure of the HLA-A*03 in complex was identified with an immunodominant proteolipid protein (PLP) epitope (KLIETYFSK). This complex has been reported as an important autoantigen-presenting complex in MS pathogenesis. In this study, new peptides were designed to bind to this complex that may prevent specific pathogenic cytotoxic T cell binding to this autoantigen-presenting complex and CNS demyelination. Herein, 14 new helical peptides containing 19 amino acids were designed and their structures were predicted using the PEP-FOLD server. The binding of each designed peptide to the mentioned complex was then performed. A mutation approach was used by the BeAtMuSiC server to improve the binding affinity of the designed peptide. In each position, amino acid substitutions leading to an increase in the binding affinity of the peptide to the mentioned complex were determined. Finally, the resulting complexes were simulated for 40 ns using AMBER18 software. The results revealed that out of 14 designed peptides, "WRYWWKDWAKQFRQFYRWF" peptide exhibited the highest affinity for binding to the mentioned complex. This peptide can be considered as a potential drug to control multiple sclerosis disease in patients carrying the HLA-A*03 allele.

Mechanistic Insights into the Allosteric Inhibition of Androgen Receptors by Binding Function 3 Antagonists from an Integrated Molecular Modeling Study

An androgen receptor (AR) is an intensively studied treatment target for castration-resistant prostate cancer that is irresponsive to conventional antiandrogen therapeutics. Binding function 3 (BF3) inhibitors with alternative modes of action have emerged as a promising approach to overcoming antiandrogen resistance. However, how these BF3 inhibitors modulate AR function remains elusive, hindering the development of BF3-targeting agents. Here, we performed an integrated computational study to interrogate the binding mechanism of several known BF3 inhibitors with ARs. Our results show that the inhibitory effect of the BF3 antagonists arises from their allosteric modulation of the activation function (AF2) site, which alters the dynamic coupling between the BF3 and AF2 sites as well as the AF2-coactivator (SRC2-3) interaction. Moreover, the per-residue binding energy analyses reveal the "anchor" role of the linker connecting the phenyl ring and benzimidazole/indole in these BF3 inhibitors. Furthermore, the allosteric driver-interacting residues are found to include both "positive", e.g., Phe673 and Asn833, and "negative" ones, e.g., Phe826, and the differential interactions with these residues provide an explanation why stronger binding does not necessarily result in higher inhibitory activities. Finally, our allosteric communication pathway analyses delineate how the allosteric signals triggered by BF3 binding are propagated to the AF2 pocket through multiple short- and/or long-ranged transmission pathways. Collectively, our combined computational study provides a comprehensive structural mechanism underlying how the selected set of BF3 inhibitors modulate AR function, which will help guide future development of BF3 antagonists.

Efficient sampling of thermal averages of interacting quantum particle systems with random batches

An efficient sampling method, the pmmLang + RBM, is proposed to compute the quantum thermal average in the interacting quantum particle system. Benefiting from the random batch method (RBM), the pmmLang + RBM has the potential to reduce the complexity due to interaction forces per time step from O(NP²) to O(NP), where N is the number of beads and P is the number of particles. Although the RBM introduces a random perturbation of the interaction forces at each time step, the long time effects of the random perturbations along the sampling process only result in a small bias in the empirical measure of the pmmLang + RBM from the target distribution, which also implies a small error in the thermal average calculation. We numerically study the convergence of the pmmLang + RBM and quantitatively investigate the dependence of the error in computing the thermal average on the parameters such as batch size, time step, and so on. We also propose an extension of the pmmLang + RBM, which is based on the splitting Monte Carlo method and is applicable when the interacting potential contains a singular part.

Machine learning phase space quantum dynamics approaches

Derived from phase space expressions of the quantum Liouville theorem, equilibrium continuity dynamics is a category of trajectory-based phase space dynamics methods, which satisfies the two critical fundamental criteria: conservation of the quantum Boltzmann distribution for the thermal equilibrium system and being exact for any thermal correlation functions (even of nonlinear operators) in the classical and harmonic limits. The effective force and effective mass matrix are important elements in the equations of motion of equilibrium continuity dynamics, where only the zeroth term of an exact series expansion of the phase space propagator is involved. We introduce a machine learning approach for fitting these elements in quantum phase space, leading to a much more efficient integration of the equations of motion. Proof-of-concept applications to realistic molecules demonstrate that machine learning phase space dynamics approaches are possible as well as competent in producing reasonably accurate results with a modest computation effort.

Potentiality of Moringa oleifera against SARS-CoV-2: identified by a rational computer aided drug design method

Coronavirus disease 2019 (COVID-19) has created a global human health crisis and economic setbacks. Lack of specific therapeutics and limited treatment options against COVID-19 has become a new challenge to identify potential hits in order to develop new therapeutics. One of the crucial life cycle enzymes of SARS-CoV-2 is main protease (M^pro), which plays a major role in mediating viral replication, makes it an attractive drug target. Virtual screening and three times repeated 100 ns molecular dynamics simulation of the best hits were performed to identify potential SARS-CoV-2 M^pro inhibitors from the available compounds of an antiviral plant Moringa oleifera. Three flavonoids isorhamnetin (1), kaempferol (2) and apigenin (3) showed good binding affinity, stable protein-ligand complexes throughout the simulation time, high binding energy and similar binding poses in comparison with known SARS-CoV-2 M^pro inhibitor baicalein. Therefore, different parts of M. oleifera may be emerged as a potential preventive and therapeutic against COVID-19.Communicated by Ramaswamy H. Sarma.

In vitro inhibition studies of coumarin derivatives on Bos taurus enolase and elucidating their interaction by molecular docking, molecular dynamics simulations and MMGB(PB)SA binding energy calculation

Tropical theileriosis is among the most common vector-borne diseases and caused by Theileria parasites. Theileria annulata is an obligate intracellular protozoan parasite and transmitted to especially Bos taurus and Bos indicus by Hyalomma tick vectors. C8 ([4-(3,4-dimethoxyphenyl)-6,7-dihydroxy-2H-chromen-2-one); C9 (4-(3,4-dihydroxyphenyl)-7,8 dihydroxy-2H-chromen-2-one); C21 (4-(3,4-dihydroxyphenyl)-6,7-dihydroxy-2H-chromen-2 one) were identified as potent Theileria annulata enolase (TaEno) inhibitors in our previous studies. An ideal drug compound must inhibit the target parasite enzyme without inhibiting its homolog in the host. In this study, the inhibitory effect of the compounds previously evaluated on TaEno were tested on the host Bos taurus enolase (BtEno3) by in vitro studies. The interactions of enzyme-coumarin and enzyme-coumarin-substrate by in silico studies were also performed. All of the coumarin derivatives tested showed very low inhibitory effects on B. taurus enolase; 36,87% inhibition at 100 μM concentration for C8, 8,13% inhibition at 100 μM concentration for C9 and 77,69 μM of IC₅₀ value for C21. In addition, these three coumarin derivatives and substrate 2PG were docked into the BtEno3 using molecular docking methods. Molecular interactions between enolase-coumarin and enolase-coumarin-substrate complexes were analyzed using molecular dynamics simulation methods for 100 ns. Estimated free energy of bindings of the substrate 2PG and coumarin derivatives to the BtEno3 were calculated by MM-GB(PB)SA methods. In comparison to the inhibition studies performed on TaEno, C8 and C9 coumarin derivatives remain the possible inhibitor candidates as they inhibit the host enolase at very high concentrations. These two promising compounds will be further analyzed by in vitro and in vivo studies towards developing an alternative drug against tropical theileriosis.

A generalized class of strongly stable and dimension-free T-RPMD integrators

Recent work shows that strong stability and dimensionality freedom are essential for robust numerical integration of thermostatted ring-polymer molecular dynamics (T-RPMD) and path-integral molecular dynamics, without which standard integrators exhibit non-ergodicity and other pathologies [R. Korol et al., J. Chem. Phys. 151, 124103 (2019) and R. Korol et al., J. Chem. Phys. 152, 104102 (2020)]. In particular, the BCOCB scheme, obtained via Cayley modification of the standard BAOAB scheme, features a simple reparametrization of the free ring-polymer sub-step that confers strong stability and dimensionality freedom and has been shown to yield excellent numerical accuracy in condensed-phase systems with large time steps. Here, we introduce a broader class of T-RPMD numerical integrators that exhibit strong stability and dimensionality freedom, irrespective of the Ornstein-Uhlenbeck friction schedule. In addition to considering equilibrium accuracy and time step stability as in previous work, we evaluate the integrators on the basis of their rates of convergence to equilibrium and their efficiency at evaluating equilibrium expectation values. Within the generalized class, we find BCOCB to be superior with respect to accuracy and efficiency for various configuration-dependent observables, although other integrators within the generalized class perform better for velocity-dependent quantities. Extensive numerical evidence indicates that the stated performance guarantees hold for the strongly anharmonic case of liquid water. Both analytical and numerical results indicate that BCOCB excels over other known integrators in terms of accuracy, efficiency, and stability with respect to time step for practical applications.

Nuclear Quantum Effects from the Analysis of Smoothed Trajectories: Pilot Study for Water

Nuclear quantum effects have significant contributions to thermodynamic quantities and structural properties; furthermore, very expensive methods are necessary for their accurate computation. In most calculations, these effects, for instance, zero-point energies, are simply neglected or only taken into account within the quantum harmonic oscillator approximation. Herein, we present a new method, Generalized Smoothed Trajectory Analysis, to determine nuclear quantum effects from molecular dynamics simulations. The broad applicability is demonstrated with the examples of a harmonic oscillator and different states of water. Ab initio molecular dynamics simulations have been performed for ideal gas up to the temperature of 5000 K. Classical molecular dynamics have been carried out for hexagonal ice, liquid water, and vapor at atmospheric pressure. With respect to the experimental heat capacity, our method outperforms previous calculations in the literature in a wide temperature range at lower computational cost than other alternatives. Dynamic and structural nuclear quantum effects of water are also discussed.

Gating mechanism of elongating β-ketoacyl-ACP synthases

Carbon-carbon bond forming reactions are essential transformations in natural product biosynthesis. During de novo fatty acid and polyketide biosynthesis, β-ketoacyl-acyl carrier protein (ACP) synthases (KS), catalyze this process via a decarboxylative Claisen-like condensation reaction. KSs must recognize multiple chemically distinct ACPs and choreograph a ping-pong mechanism, often in an iterative fashion. Here, we report crystal structures of substrate mimetic bearing ACPs in complex with the elongating KSs from Escherichia coli, FabF and FabB, in order to better understand the stereochemical features governing substrate discrimination by KSs. Complemented by molecular dynamics (MD) simulations and mutagenesis studies, these structures reveal conformational states accessed during KS catalysis. These data taken together support a gating mechanism that regulates acyl-ACP binding and substrate delivery to the KS active site. Two active site loops undergo large conformational excursions during this dynamic gating mechanism and are likely evolutionarily conserved features in elongating KSs.

Dimension-free path-integral molecular dynamics without preconditioning

Convergence with respect to imaginary-time discretization (i.e., the number of ring-polymer beads) is an essential part of any path-integral-based molecular dynamics (MD) calculation. However, an unfortunate property of existing non-preconditioned numerical integration schemes for path-integral molecular dynamics-including essentially all existing ring-polymer molecular dynamics (RPMD) and thermostatted RPMD (T-RPMD) methods-is that for a given MD time step, the overlap between the exact ring-polymer Boltzmann-Gibbs distribution and that sampled using MD becomes zero in the infinite-bead limit. This has clear implications for hybrid Metropolis Monte Carlo/MD sampling schemes, and it also causes the divergence with bead number of the primitive path-integral kinetic-energy expectation value when using standard RPMD or T-RPMD. We show that these and other problems can be avoided through the introduction of "dimension-free" numerical integration schemes for which the sampled ring-polymer position distribution has non-zero overlap with the exact distribution in the infinite-bead limit for the case of a harmonic potential. Most notably, we introduce the BCOCB integration scheme, which achieves dimension freedom via a particular symmetric splitting of the integration time step and a novel implementation of the Cayley modification [R. Korol et al., J. Chem. Phys. 151, 124103 (2019)] for the free ring-polymer half-steps. More generally, we show that dimension freedom can be achieved via mollification of the forces from the external physical potential. The dimension-free path-integral numerical integration schemes introduced here yield finite error bounds for a given MD time step, even as the number of beads is taken to infinity; these conclusions are proven for the case of a harmonic potential and borne out numerically for anharmonic systems that include liquid water. The numerical results for BCOCB are particularly striking, allowing for nearly three-fold increases in the stable time step for liquid water with respect to the Bussi-Parrinello (OBABO) and Leimkuhler (BAOAB) integrators, while introducing negligible errors in the calculated statistical properties and absorption spectrum. Importantly, the dimension-free, non-preconditioned integration schemes introduced here preserve ergodicity and global second-order accuracy, and they remain simple, black-box methods that avoid additional computational costs, tunable parameters, or system-specific implementations.

Cayley modification for strongly stable path-integral and ring-polymer molecular dynamics

Path-integral-based molecular dynamics (MD) simulations are widely used for the calculation of numerically exact quantum Boltzmann properties and approximate dynamical quantities. A nearly universal feature of MD numerical integration schemes for equations of motion based on imaginary-time path integrals is the use of harmonic normal modes for the exact evolution of the free ring-polymer positions and momenta. In this work, we demonstrate that this standard practice creates numerical artifacts. In the context of conservative (i.e., microcanonical) equations of motion, it leads to numerical instability. In the context of thermostated (i.e., canonical) equations of motion, it leads to nonergodicity of the sampling. These pathologies are generally proven to arise at integration time steps that depend only on the system temperature and the number of ring-polymer beads, and they are numerically demonstrated for the cases of conventional ring-polymer MD (RPMD) and thermostated RPMD (TRPMD). Furthermore, it is demonstrated that these numerical artifacts are removed via replacement of the exact free ring-polymer evolution with a second-order approximation based on the Cayley transform. The Cayley modification introduced here can immediately be employed with almost every existing integration scheme for path-integral-based MD-including path-integral MD (PIMD), RPMD, TRPMD, and centroid MD-providing strong symplectic stability and ergodicity to the numerical integration, at no penalty in terms of computational cost, algorithmic complexity, or accuracy of the overall MD time step. Furthermore, it is shown that the improved numerical stability of the Cayley modification allows for the use of larger MD time steps. We suspect that the Cayley modification will therefore find useful application in many future path-integral-based MD simulations.

Sampling the thermal Wigner density via a generalized Langevin dynamics

The Wigner thermal density is a function of considerable interest in the area of approximate (linearized or semiclassical) quantum dynamics where it is employed to generate initial conditions for the propagation of appropriate sets of classical trajectories. In this paper, we propose an original approach to compute the Wigner density based on a generalized Langevin equation. The stochastic dynamics is nontrivial in that it contains a coordinate-dependent friction coefficient and a generalized force that couples momenta and coordinates. These quantities are, in general, not known analytically and have to be estimated via auxiliary calculations. The performance of the new sampling scheme is tested on standard model systems with highly nonclassical features such as relevant zero point energy effects, correlation between momenta and coordinates, and negative parts of the Wigner density. In its current brute force implementation, the algorithm, whose convergence can be systematically checked, is accurate and has only limited overhead compared to schemes with similar characteristics. We briefly discuss potential ways to further improve its numerical efficiency.

Unified Efficient Thermostat Scheme for the Canonical Ensemble with Holonomic or Isokinetic Constraints via Molecular Dynamics

We have recently proposed a new unified theoretical scheme (the "middle" scheme) for thermostat algorithms for efficient and accurate configurational sampling of the canonical ensemble. In this paper, we extend the "middle" scheme to molecular dynamics algorithms for configurational sampling in systems subject to constraints. Holonomic constraints and isokinetic constraints are used for demonstration. Numerical examples indicate that the "middle" scheme presents a promising approach to calculate configuration-dependent thermodynamic properties and their thermal fluctuations.

A semiclassical initial-value representation for quantum propagator and boltzmann operator

Starting from the position-momentum integral representation, we apply the correction operator method to the derivation of a uniform semiclassical approximation for the quantum propagator and then extend it to approximate the Boltzmann operator. In this approach, the involved classical dynamics is determined by the method itself instead of given beforehand. For the approximate Boltzmann operator, the corresponding classical dynamics is governed by a complex Hamiltonian, which can be described as a pair of real Hamiltonian systems. It is demonstrated that the semiclassical Boltzmann operator is exact for linear systems. A quantum propagator in the complex time is thus proposed and preliminary numerical results show that it is a reasonable approximation for calculating thermal correlation functions of general systems. © 2018 Wiley Periodicals, Inc.

Computation of static quantum triplet structure factors of liquid para-hydrogen

The instantaneous and centroid triplet structure factors, S ( 3 ) ( k 1 , k 2 ) , of liquid (one-center) para-hydrogen are computed on the crystallization line for temperatures T/K ≤ 33. The focus is on salient equilateral and isosceles features, and the methods utilized are path integral Monte Carlo (PIMC) simulations and Ornstein-Zernike (OZ) integral equations, which involve Jackson-Feenberg convolution (JF3) and other distinct closures. Long path integral simulation runs are carried out in the canonical ensemble, so as to obtain sufficiently accurate direct PI triplet results. Conclusions are drawn regarding general triplet structure features and the role and usefulness of the OZ closures. The equilateral features are studied in more detail, and one finds that (a) PIMC results point to the existence of regularity in the centroid main peak amplitudes; (b) some of the studied closures give qualitative descriptions for wave numbers below k ≈ 1 Å^-1, but they all fail to describe the main peak amplitude regions (1.75 < k/Å^-1 < 2.5); and (c) JF3 plays the role of a limit closure that is valid for increasing wave numbers (k ≥ 2.6 Å^-1). In addition, representative isosceles PI features turn out to be reasonably bounded (within Δk = 0.1 Å^-1) by those of some closures.

Theoretical Study on Zearalenol Compounds Binding with Wild Type Zearalenone Hydrolase and V153H Mutant

Zearalenone hydrolase (ZHD) is the only reported α/β-hydrolase that can detoxify zearalenone (ZEN). ZHD has demonstrated its potential as a treatment for ZEN contamination that will not result in damage to cereal crops. Recent researches have shown that the V153H mutant ZHD increased the specific activity against α-ZOL, but decreased its specific activity to β-ZOL. To understand whyV153H mutation showed catalytic specificity for α-ZOL, four molecular dynamics simulations combining with protein network analysis for wild type ZHD α-ZOL, ZHD β-ZOL, V153H α-ZOL, and V153H β-ZOL complexes were performed using Gromacs software. Our theoretical results indicated that the V153H mutant could cause a conformational switch at the cap domain (residues Gly161–Thr190) to affect the relative position catalytic residue (H242). Protein network analysis illustrated that the V153H mutation enhanced the communication with the whole protein and residues with high betweenness in the four complexes, which were primarily assembled in the cap domain and residues Met241 to Tyr245 regions. In addition, the existence of α-ZOL binding to V153H mutation enlarged the distance from the O_AE atom in α-ZOL to the NE2 atom in His242, which prompted the side chain of H242 to the position with catalytic activity, thereby increasing the activity of V153H on the α-ZOL. Furthermore, α-ZOL could easily form a right attack angle and attack distance in the ZHD and α-ZOL complex to guarantee catalytic reaction. The alanine scanning results indicated that modifications of the residues in the cap domain produced significant changes in the binding affinity for α-ZOL and β-ZOL. Our results may provide useful theoretical evidence for the mechanism underlying the catalytic specificity of ZHD.