MD Trajectories Research Articles

Novel rhodanine-thiazole hybrids as potential antidiabetic agents: a structure-based drug design approach.

New rhodanine-thiazole clubbed compounds (7a-7l) were synthesised and characterised with various spectroscopy methods. The synthesised hybrids underwent in vitro HPA, HLAG inhibition, and peroxisome proliferator-activated receptor-gamma (PPAR-γ) expression assays. Through the biological study, compound 7f showed promising inhibitory activity against HPA with an IC50 value of 27.13 ± 1.02 μM and 7l exhibited better inhibition against HLAG with an IC50 value of 24.21 ± 1.12 μM. In addition, Lineweaver-Burk plot analysis suggested that 7l and 7f behaved as a mixed type of HLAG and HPA inhibitor and further, compound 7f showed significant PPAR-γ expression as compared to controls in a dose dependent manner; the expression can be attributed to its mapped pharmacophoric features with a phase screen score of 1.28 and vector score of 0.62. The proteins modulated by compounds include AMY2A, PPAR, and GAA proteins via MAPK, PPAR signalling pathways identified by cluster analysis and justified by molecular docking studies and MD trajectory analysis to evaluate the binding orientation and stability of the molecules, and the energy profiles of the molecules, both in complex with the protein, were assessed using MM/GBSA and DFT calculations, respectively. Finally, the pharmacokinetic profile was determined using ADMET analysis. Thus, from the above findings, it may demonstrate that rhodanine-thiazole hybrids constitute promising candidates in the pursuit of developing newer oral antidiabetic agents.

Nature's defense against emerging neurodegenerative threats: Dynamic simulation, PCA, DCCM identified potential plant-based antiviral lead targeting borna disease virus nucleoprotein.

The rare zoonotic Borna disease virus (BDV) causes fatal neurological disease in various animals, with a high mortality rate exceeding 90% in central Europe. However, unlike most viruses, it establishes persistent infections within the host cell nucleus, hindering treatment. As successful BDV treatments remain elusive, the researchers turned to a computational approach, utilizing molecular docking, ADME/T, post-docking MMGBSA, MD simulation, DCCM, and PCA to identify promising phytochemical drug candidates targeting the BDV Nucleoprotein (PDB ID: 1N93). From IMPPAT 1940 unique phytochemical compounds of a total of 8617 compounds from 36 Indian medicinal plants were retrieved. Three compounds were chosen as leads with higher binding affinity of -6.244, -6.116, and -6.07 kcal/mol with CID 163114683 (IMPHY000668) Nimbochalcin, CID 20871246 (IMPHY007896) 3,4-Dihydroxy-5-oxocyclohex-3-ene-1-carboxylic acid, and CID 243 (IMPHY002962) Benzoic acid. The three top compounds coordinated with the protein's common amino acid residues at GLN 161, ARG 165, ILE 145, ILE 162, ILE 149, and VAL 229 during molecular docking, which implies that both lead compounds and the control ligand interact within the protein's shared active site. Afterwards, negative binding free energies of Nimbochalcin, 3,4-Dihydroxy-5-oxocyclohex-3-ene-1-carboxylic acid, and Benzoic acid were -51.21, -13.94, and -22.95 kcal/mol, accordingly. Favorable Pk and toxicological characteristics are shared by all of the chosen drugs, indicating their efficacy and safety. Using MD simulation, these three compounds were further assessed, and their stability in binding to the target protein was confirmed and subsequently, DCCM and PCA analyses were carried out from MD trajectory. MD simulations found that the protein binding site is highly stable when complexed with CID 20871246 and has a higher negative binding free energy value, indicating a strong interaction between the compound and the protein. Principal component analysis (PCA) identified three main components (PC1, PC2, and PC3) that accounted for 53.43%, 12.31%, and 5.97% of the variance, respectively. These findings provide intriguing evidence that the CID 20871246-1N93 complex is more stable than the other complexes. The BDV nucleoprotein was the target of this study's investigation where CID 20871246 (3,4-dihydroxy-5-oxocyclohex-3-ene-1-carboxylic acid) exhibited tremendous antiviral activity which is found in the flower of the plant Mangifera indica revealing as a possible therapeutic candidate.

Rotational Behavior Analysis of Cluster Anions in Solid-State Electrolytes via MD Simulation

Solid-state batteries (SSBs) have the potential to bring about dramatic increases in safety and performance compared to current liquid electrolyte systems, allowing for electrification of crucial sectors such as transportation as well as development of novel device architectures for consumer electronics. Finding a suitable solid-state electrolyte remains a key challenge in the path to realization of SSBs, and finding candidate materials that exhibit sufficient ionic conductivity alongside the many other materials properties required of a solid-state electrolyte is the crux of this challenge. Within the past two decades, historic improvements in the conductivities of solid-state electrolytes have been made by understanding and exploiting the effects of lattice volume, vacancy concentration, and concerted migration mechanisms (amongst others), to the point at which the conductivities of some solid-state electrolytes have surpassed those of commercially used liquid electrolytes.[1] Recently, the influence of the dynamics of the anions, specifically the rotation of “cluster anions” (also known as molecular anions or polyanions such as PS4 3- or BH4 -), on cation migration mechanisms has garnered attention as a potential avenue for designing high conductivity materials.[2] Typical experimental signatures of cluster anion rotation include rotor atom spatial probability density calculated from diffraction techniques showing a different, more spherically symmetric geometry, such as a tetrahedral anion showing an octahedral signal, or a disorder-increasing phase transformation accompanied by a sharp jump in ionic conductivity. Because the cluster anion rotations occur at picosecond and Angstrom time and length scales, understanding the rotational behavior of the cluster anions and determining whether this behavior has an impact on the migration mechanism anion is difficult to do experimentally. Molecular dynamics simulations have been used to probe the rotational behavior of cluster anions, with typical characterizations including vibration/libration spectra, rotational autocorrelation functions, spatial probability densities of rotor atoms, and 2D histograms of θ-ϕ spherical coordinates of rotor bond vectors. However, most of these techniques average the signals from the rotor atoms across clusters and across simulation times in a way that obfuscates important time dependent behavior (see Figure 1A). For example, they are unable to determine the specific set of orientations accessed by a cluster anion species that creates the time and space averaged signal seen by diffraction techniques.In this work, we present a novel framework for MD trajectory analysis which uses a 3D parameterization of the orientation of each cluster in each frame to (1) determine the stable orientations (an orientation-based analog of the position-based concept of a lattice site) of a rotationally active cluster anion, (2) characterize the rotations between stable orientations, and (3) probe the interaction between cluster anion rotations and cation migrations. We apply this framework to the dual cluster anion containing electrolyte sodium amide borohydride (Na2NH2BH4), for which both the tetrahedral borohydride (BH4 -) anion and the bent amide (NH2 -) anion show octahedral signals by X-ray and neutron diffraction. We determine that the borohydride anions achieve this averaged spatial density by pointing one hydrogen atom along the +/- a, b, or c axis and rotating about that axis, while the amide anions achieve this by pointing both hydrogen atoms roughly along two adjacent +/- a, b, or c axes (see Figure 1B). We also corroborate previous results showing that the migration of the sodium cations happens in close concert with the rotation of the amide anions, while the borohydride anions spin more freely.This work was supported as part of the Joint Center for Energy Storage Research (JCESR), an Energy Innovation Hub funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences.

A computational and machine learning approach to identify GPR40-targeting agonists for neurodegenerative disease treatment.

The G protein-coupled receptor 40 (GPR40) is known to exert a significant influence on neurogenesis and neurodevelopment within the central nervous system of both humans and rodents. Research findings indicate that the activation of GPR40 by an agonist has been observed to promote the proliferation and viability of hypothalamus cells in the human body. The objective of the present study is to discover new agonist compounds for the GPR40 protein through the utilization of machine learning and pharmacophore-based screening techniques, in conjunction with other computational methodologies such as docking, molecular dynamics simulations, free energy calculations, and investigations of the free energy landscape. In the course of our investigation, we successfully identified five unreported agonist compounds that exhibit robust docking score, displayed stability in ligand RMSD and consistent hydrogen bonding with the receptor in the MD trajectories. Free energy calculations were observed to be higher than control molecule. The measured binding affinities of compounds namely 1, 3, 4, 6 and 10 were -13.9, -13.5, -13.4, -12.9, and -12.1 Kcal/mol, respectively. The identified molecular agonist that has been found can be assessed in terms of its therapeutic efficacy in the treatment of neurological diseases.

A computational study of adsorption on activated carbons containing basic oxygenated surface groups of two priority organochlorine pesticides from water

In previous work, molecular modeling was used to investigate how acidic and nitrogen-containing surface groups (SG) on an activated carbon (AC) model affect the adsorption of chlordecone (CLD) and β-hexachlorocyclohexane (β-HCH), considering the effects of pH and hydration. Interactions involving acidic SGs at neutral pH indicated chemisorption, while interactions with nitrogen basic SGs suggested physisorption. This study presents a theoretical investigation of the interactions between these pesticides and oxygenated SGs on AC. A coronene molecule with functional groups—specifically pyrone, chromene, or ketone at the edges was used as a simplified model of AC. The Multiple Minima Hypersurface methodology was employed to study the interactions between CLD and β-HCH with SGs on AC using the PM7 semi-empirical Hamiltonian. Further re-optimization of the obtained structures for pesticide-AC complexes was performed using Density Functional Theory. The Quantum Theory of Atoms in Molecules was applied to characterize the interaction types using the Nakanishi criteria. No interactions were observed at acidic pH for both pollutants, whereas dispersive interactions were found at neutral and basic pH, indicating a physisorption process. Molecular dynamics simulations were also conducted to illustrate these findings. Ultimately, our previous studies showed that the adsorption process of CLD and β-HCH on AC is more effectively enhanced with acidic SGs rather than basic SGs. Moreover, MD simulations of β-HCH and CLD pesticides at concentrations higher than their solubilities reveal aggregation in both pure aqueous solutions and those containing AC. Analysis of MD trajectories and RDFs shows that hydrophobic interactions lead to aggregation of these molecules. RDFs indicate that β-HCH aggregates more in the solution due to its lower solubility compared to CLD. This aggregation reduces pesticide adsorption on AC surfaces, with β-HCH showing a more significant decrease in adsorption, dropping by more than half. Similar effects were observed with other biochar models for both pesticides.

Molecular Basis of the Substrate Specificity of Phosphotriesterase from Pseudomonas diminuta: A Combined QM/MM MD and Electron Density Study.

The occurrence of organophosphorus compounds, pesticides, and flame-retardants in wastes is an emerging ecological problem. Bacterial phosphotriesterases are capable of hydrolyzing some of them. We utilize modern molecular modeling tools to study the hydrolysis mechanism of organophosphorus compounds with good and poor leaving groups by phosphotriesterase from Pseudomonas diminuta (Pd-PTE). We compute Gibbs energy profiles for enzymes with different cations in the active site: native Zn2+cations and Co2+cations, which increase the steady-state rate constant. Hydrolysis occurs in two elementary steps via an associative mechanism and formation of the pentacoordinated intermediate. The first step, a nucleophilic attack, occurs with a low energy barrier independently of the substrate. The second step has a low energy barrier and considerable stabilization of products for substrates with good leaving groups. For substrates with poor leaving groups, the reaction products are destabilized relative to the ES complex that suppresses the reaction. The reaction proceeds with low energy barriers for substrates with good leaving groups with both Zn2+and Co2+cations in the active site; thus, the product release is likely to be a limiting step. Electron density and geometry analysis of the QM/MM MD trajectories of the intermediate states with all considered compounds allow us to discriminate substrates by their ability to be hydrolyzed by the Pd-PTE. For hydrolyzable substrates, the cleaving bond between a phosphorus atom and a leaving group is elongated, and electron density depletion is observed on the Laplacian of electron density maps.

Plasticity and strength of an equiatomic and a non-equiatomic HfNbTaTiZr high entropy alloy during uniaxial loading : a molecular dynamics simulation study

Abstract Understanding plasticity and strength of high entropy alloys of HfNbTaTiZr is extremely significant in building nuclear reactors, gas turbines, aerospace devices etc. Here we study an equiatomic (Hf0.20-Nb0.20-Ta0.20-Ti0.2-Zr0.20) and a non-equiatomic (Hf0.35-Nb0.20-Ta0.15-Ti0.15-Zr0.15) mixture of two alloys under uniaxial tensile loading from molecular dynamics simulations. Modified Embedded atom potential is used to model both these bcc alloys and all simulations are performed at 300 K with three different tensile strain rates–0.0002, 0.0005 and 0.001 ps−1. Radial distribution functions, bond-orientational parameters and OVITO are used to analyse the MD trajectories. At 0.001 ps−1 strain, both these alloys deform similarly, but differences are observed at 0.0005 and 0.0002 ps−1 strains. At these rates, both alloys deform elastically till 3%, thereafter they deform plastically till 15%–20% strain. Yield strengths are comparable in the elastic limit but in the plastic limit non-equiatomic alloy have higher strength. In equiatomic alloy, bcc phase transforms to fcc whereas in non-equiatomic alloy bcc phase transforms to both fcc and hcp. Formation of hcp atoms (50%) decrease the plasticity of the non-equiatomic alloy but increases its strength. We also observe that in both these alloys and at all strain rates, bcc atoms transform to fcc/hcp atoms through an intermediate amorphous like state. Local coordination and orientation of all atoms change similarly in equiatomic mixture. But in non-equiatomic mixture local orientation in Hf, Ti and Zr changes differently compared to Nb and Ta.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Machine-Learning Accelerated Description of Polarons in 2D Lead Halide Perovskites

MLFF-based MD trajectories to compute NAC and excited-state dynamics. At each stage, results based on machine learning are compared to traditional ab initio based electronic dissipative dynamics.The limits of this method are explored as we increase the timescale of the calculation beyond those allowed by ab initio molecular dynamics and to determine the effectiveness of MLFF-MD when used for excited-state nonadiabatic dynamics simulations using atomistic models that include charge injection or when an excited-stated potential energy surface is used to account for changes due to an excitation.

Crucial Structural Understanding for Selective HDAC8 Inhibition: Common Pharmacophores, Molecular Docking, Molecular Dynamics, and Zinc Binder Analysis of selective HDAC8 inhibitors.

Overexpression of HDAC8 was observed in various cancers and inhibition of HDAC8 has emerged as a promising therapeutic approach in recent decades. This review aims to facilitate the discovery of novel selective HDAC8 inhibitors by analyzing the structural scaffolds of 66 known selective HDAC8 inhibitors, along with their IC50 values against HDAC8 and other HDACs. The inhibitors were clustered based on structural symmetry, and common pharmacophores for each cluster were identified using Phase. Molecular docking with all HDACs was performed to determine binding affinity and crucial interacting residues for HDAC8 inhibition. Representative inhibitors from each cluster were subjected to molecular dynamics simulation to analyze RMSD, RMSF, active site amino acid residues, and crucial interacting residues responsible for HDAC8 inhibition. The study reviewed the active site amino acid information, active site cavities of all HDACs, and the basic structure of Zn2+ binding groups. Common pharmacophores identified included AADHR_1, AADDR_1, ADDR_1, ADHHR_1, and AADRR_1. Molecular docking analysis revealed crucial interacting residues: HIS- 142, GLY-151, HIS-143, PHE-152, PHE-20 in the main pocket, and ARG-37, TYR-100, TYR-111, TYR-306 in the secondary pocket. The RMSD of protein and RMSF of active site amino acid residues for stable protein-ligand complexes were less than 2.4 Å and 1.0 Å, respectively, as identified from MD trajectories. The range of Molecular Mechanics Generalized Born Surface Area (MMGBSA) ΔG predicted from MD trajectories was between -15.8379 Å and -61.5017 Å kcal/mol. These findings may expedite the rapid discovery of selective HDAC8 inhibitors subject to experimental evaluation.

In Silico Studies of a Novel Scaffold of Acetylsalicylic Acid Derivatives Against EGFR by Molecular Docking and Molecular Dynamics Simulations

In this study, a molecular docking study was performed to propose the acetylsalicylic acid derivative 2-[(4-Acetylphenyl)carbamoyl]phenyl acetate (AMPBS) as a potential cancer candidate targeting the Epidermal Growth Factor Receptor (EGFR). The native ligand erlotinib was used as a control compound. The calculated docking score of -7.4 kcal/mol compared to the native ligand erlotinib of -7.0 kcal/mol of AMPBS compound revealed a promising anticancer activity. The stability of the complex was interpreted by careful analysis of the root mean square deviation (RMSD), root mean square fluctuations (RMSF) and mean hydrogen bond number (Hb) plots obtained from the MD trajectories. The ADMET properties of AMPBS were evaluated using relevant online tools. Drug-likeness studies showed that AMPBS is suitable for use in living organisms. It was predicted that AMPBS in the active pocket could be a promising inhibitor due to its high binding energy, interaction mechanism and retention in the active pocket.

Time-Resolved X-ray Emission Spectroscopy and Resonant Inelastic X-ray Scattering Spectroscopy of Laser Irradiated Carbon.

The existence of liquid carbon as an intermediate phase preceding the formation of novel carbon materials has been a point of contention for several decades. Experimental observation of such a liquid state requires nonthermal melting of solid carbon materials at various laser fluences and pulse properties. Reflectivity experiments performed in the mid-1980s reached opposing conclusions regarding the metallic or insulating properties of the purported liquid state. Time-resolved X-ray absorption studies showed shortening of C-C bonds and increasing diffraction densities, thought to evidence a liquid or glassy carbon state, respectively. Nevertheless, none of these experiments provided information on the electronic structure of the proposed liquid state. Herein, we report the results of time-resolved resonant inelastic X-ray scattering (RIXS) and time-resolved X-ray emission spectroscopy (XES) studies on amorphous carbon (a-C) and ultrananocrystalline diamond (UNCD) as a function of delay time between the irradiating pulse and X-ray probe. For both a-C and UNCD, we attribute decreases in RIXS or XES signals to transition blocking, relaxation, and finally, ablation. Increased signal at 20 ps following the irradiation of the UNCD is attributed to the probable formation of nanoscale structures in the ablation plume. Differences in the amount of signal observed between a-C and UNCD are explained by the difference in sample thickness and, specifically, incomplete melting of the UNCD film. Comparisons to spectral simulations based on MD trajectories at extreme conditions indicate that the carbon state in our experiments is crystalline. Normal mode analysis confirmed that symmetrical bending or stretching of the C-C bonds in the diamond lattice results in XES spectra with small intensity differences. Overall, we observed no evidence of melting to a liquid state, as determined by the lack of changes in the spectral properties for up to 100 ps delays following the melting pulses.

Elucidating the Molecular Basis of 14-3-3 Interaction with α-Synuclein: Insights from Molecular Dynamics Simulations and the Design of a Novel Protein-Protein Interaction Inhibitor.

Parkinson's disease is a widespread age-related neurodegenerative disorder characterized by the loss of dopaminergic neurons in the midbrain along with the appearance of protein aggregates, termed as "Lewy bodies" in the surviving neuronal cells. The components of Lewy bodies include proteins such as α-synuclein, 14-3-3, Parkin, and LRRK2, along with other cellular organelles, which, in their native state, perform a plethora of vital biological functions within the human biome. Formation of these aggregates renders these components inactive, thereby interfering with homeostasis. In this regard, the current study attempts to investigate the complexation behavior of all human-based 14-3-3 isoforms with α-synuclein via a combination of classical and enhanced sampling techniques and thereby determine the causality of these protein-protein interactions. The study indicated that upon complexation, the aggregation propensity of both 14-3-3 and α-synuclein increases, and this increment is propelled by the interfacial residues on either protein. Furthermore, mutagenesis studies revealed that Lys214 of 14-3-3 (henceforth termed K214A) is crucial for the formation of this binary complex. Principal component analysis combined with clustering studies unveiled the stability of these complexes in terms of their conformational distribution across the entire MD trajectory. For K214A, these clustered states were sparsely located, thereby making the transitions between them slightly difficult. Dynamic cross-correlation maps (DCCM) revealed the role of residues in the range 80-130 of 14-3-3 having a potential allosteric role in driving this complexation process. Finally, a novel peptide-based supramolecular inhibitor was designed, which exhibited higher proficiency in limiting the 14-3-3/α-synuclein interaction compared to the previous inhibitor model. It was also revealed that the presence of this inhibitor induces structural rigidity in α-synuclein, making changes in its conformations extremely difficult, as observed through Umbrella Sampling studies. Based on available information, the current study provides an insight into the molecular-level understanding of protein-protein interactions underlying Parkinson's disease and adds on to the methods of devising novel therapeutic approaches to treat the same.

Protein Effects on the Excitation Energies and Exciton Dynamics of the CP24 Antenna Complex.

In this study, the site energy fluctuations, energy transfer dynamics, and some spectroscopic properties of the minor light-harvesting complex CP24 in a membrane environment were determined. For this purpose, a 3 μs-long classical molecular dynamics simulation was performed for the CP24 complex. Furthermore, using the density functional tight binding/molecular mechanics molecular dynamics (DFTB/MM MD) approach, we performed excited state calculations for the chlorophyll a and chlorophyll b molecules in the complex starting from five different positions of the MD trajectory. During the extended simulations, we observed variations in the site energies of the different sets as a result of the fluctuating protein environment. In particular, a water coordination to Chl-b 608 occurred only after about 1 μs in the simulations, demonstrating dynamic changes in the environment of this pigment. From the classical and the DFTB/MM MD simulations, spectral densities and the (time-dependent) Hamiltonian of the complex were determined. Based on these results, three independent strongly coupled chlorophyll clusters were revealed within the complex. In addition, absorption and fluorescence spectra were determined together with the exciton relaxation dynamics, which reasonably well agrees with experimental time scales.

Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis.

Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low-energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models, and potent compounds that are capable of inhibiting RET activation were proposed.

Unleashing new MTDL AChE and BuChE inhibitors as potential anti-AD therapeutic agents: In vitro, in vivo and in silico studies

Alzheimer's disease (AD) is challenging due to its irreversible declining cognitive symptoms and multifactorial nature. This work tackles targeting both acetylcholinesterase (AChE) and BuChE with a multitarget-directed ligand (MTDL) through design, synthesis, and biological and in silico evaluation of a series of twenty eight new 5-substituted-2-anilino-1,3,4-oxadiazole derivatives 4a-g, 5a-g, 9a-g and 13a-g dual inhibitors of the target biomolecules. In vitro cholinesterases inhibition and selectivity assay of the synthesized derivatives showed excellent nanomolar level inhibitory activities. Compound 5a, the most potent inhibitor, elicited IC50s of 46.9 and 3.5 nM against AChE and BuChE, respectively (SI = 0.07), 5 folds better than the known dual inhibitor Rivastagmine. In vivo and ex vivo investigation showed that 5a significantly inhibited MDA levels and increased GSH contents, thus, attenuating the brain tissue oxidative stress. Additionally, 5a significantly decreased AChE and BuChE levels and inhibited self-mediated β-amyloid aggregation in brains of treated rats. Histopathological and immunohistochemical evaluation demonstrated lessened damage and decreased caspase-3 and VEGF expression levels. In silico prediction of 5a's pharmacokinetics and toxicity profiles reflected promising results. Finally, 5a demonstrated tight binding interactions with the two target biomolecules upon docking along with stable complex formation with its bio-targets throughout the 100 ns MD trajectories.

A review on dynamics of permeability-glycoprotein in efflux of chemotherapeutic drugs

Permeability-glycoprotein (P-gp) belongs to the ABS transporter protein family, with a high expression rate in cancerous cells. The substrate/inhibitors of the protein are structurally diverse, with no lucid mechanism of inhibition. There are two schools of thought on the inhibition mechanism: (i) P-gp inhibitors bind to the huge hydrophobic cavity between two Trans-Membrane Domains (TMDs), supported by ample literary proof and (ii) P-gp inhibitors bind to the vicinity of Nucleotide-Binding Sites (NBSs). Structural biologists have presented several experimental and theoretical structures of P-gp with bound nucleotides and inhibitors to explain the same. However, the available experimental P-gp structures are insufficient to address the catalytic transition path of mammalian P-gp in detail, thus the dynamics and mechanism by which drugs are effluxed is still unknown. Targeted Molecular Dynamics (targeted MD) could be used to minutely analyse and explore the catalytic transition inward open (IO) to outward open (OO) and relaxation path (OO to IO). Finally, analysis of targeted MD trajectory may help to explore different conformational states of Pg-p (reaction coordinate of catalytic transition/relaxation), efflux of compounds aided by the dynamics of Nucleotide Binding Domains/NBDs (ATP coupled process) and TMDs (peristalsis-like movement pushes the bound molecule). This review presents an understanding of the catalytic transition and dynamics of protein which provides insights at the efflux of chemotherapeutic drug using in cancer treatment.

Predicting the photodynamics of cyclobutanone triggered by a laser pulse at 200nm and its MeV-UED signals-A trajectory surface hopping and XMS-CASPT2 perspective.

This work is part of a prediction challenge that invited theoretical/computational chemists to predict the photochemistry of cyclobutanone in the gas phase, excited at 200nm by a laser pulse, and the expected signal that will be recorded during a time-resolved megaelectronvolt ultrafast electron diffraction (MeV-UED). We present here our theoretical predictions based on a combination of trajectory surface hopping with XMS-CASPT2 (for the nonadiabatic molecular dynamics) and Born-Oppenheimer molecular dynamics with MP2 (for the athermal ground-state dynamics following internal conversion), coined (NA+BO)MD. The initial conditions were sampled from Born-Oppenheimer molecular dynamics coupled to a quantum thermostat. Our simulations indicate that the main photoproducts after 2ps of dynamics are CO + cyclopropane (50%), CO + propene (10%), and ethene and ketene (34%). The photoexcited cyclobutanone in its second excited electronic state S2 can follow two pathways for its nonradiative decay: (i) a ring-opening in S2 and a subsequent rapid decay to the ground electronic state, where the photoproducts are formed, or (ii) a transfer through a closed-ring conical intersection to S1, where cyclobutanone ring opens and then funnels to the ground state. Lifetimes for the photoproduct and electronic populations were determined. We calculated a stationary MeV-UED signal [difference pair distribution function-ΔPDF(r)] for each (interpolated) pathway as well as a time-resolved signal [ΔPDF(r,t) and ΔI/I(s,t)] for the full swarm of (NA+BO)MD trajectories. Furthermore, our analysis provides time-independent basis functions that can be used to fit the time-dependent experimental UED signals [both ΔPDF(r,t) and ΔI/I(s,t)] and potentially recover the population of photoproducts. We also offer a detailed analysis of the limitations of our model and their potential impact on the predicted experimental signals.

Machine Learning Isotropic g Values of Radical Polymers.

Methods for electronic structure computations, such as density functional theory (DFT), are routinely used for the calculation of spectroscopic parameters to establish and validate structure-parameter correlations. DFT calculations, however, are computationally expensive for large systems such as polymers. This work explores the machine learning (ML) of isotropic g values, giso, obtained from electron paramagnetic resonance (EPR) experiments of an organic radical polymer. An ML model based on regression trees is trained on DFT-calculated g values of poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl methacrylate) (PTMA) polymer structures extracted from different time frames of a molecular dynamics trajectory. The DFT-derived g values, gisocalc, for different radical densities of PTMA, are compared against experimentally derived g values obtained from in operando EPR measurements of a PTMA-based organic radical battery. The ML-predicted giso values, gisopred, were compared with gisocalc to evaluate the performance of the model. Mean deviations of gisopred from gisocalc were found to be on the order of 0.0001. Furthermore, a performance evaluation on test structures from a separate MD trajectory indicated that the model is sensitive to the radical density and efficiently learns to predict giso values even for radical densities that were not part of the training data set. Since our trained model can reproduce the changes in giso along the MD trajectory and is sensitive to the extent of equilibration of the polymer structure, it is a promising alternative to computationally more expensive DFT methods, particularly for large systems that cannot be easily represented by a smaller model system.

In silico strategies for identifying therapeutic candidates against Acinetobacter baumannii: spotlight on the UDP-N-acetylmuramoyl-L-alanine-D-glutamate:meso-diaminopimelate ligase (MurE)

The opportunistic bacterium Acinetobacter baumannii, which belongs to ESKAPE group of pathogenic bacteria, is leading cause of infections associated with gram-negative bacteria. Acinetobacter baumannii causes severe diseases, such as VAP (ventilator-associated pneumonia), meningitis, and UTI (urinary tract infections) among the nosocomial infections contracted in hospitals. The high infection rate and growing resistance to the vast array of antibiotics makes it paramount to look for new therapeutic strategies against this pathogen. The most promising therapeutic targets are the proteins involved in the synthesis of peptidoglycan which is chief component of bacterial cell wall, MurE is one of those enzymes and is responsible for the addition of one unit of meso-diaminopimelic acid (meso-A2pm) to the nucleotide precursor, UDPMurNAc-L-Ala-D-Glu, and aids in the formation of crosslinker pentapeptide chain. The three-dimensional structure of MurE was modelled using homology modelling technique and then vHTS was performed using this model against Approved Drug Library on DrugRep server using AutoDock Vina. Out of 500 drug molecules, two were selected based on estimated binding affinity, interaction pattern, interacting residues, etc. The selected drug molecules are DB12887 (Tazemetostat) and DB13879 (Glecaprevir). Then, MD simulations were performed on native MurE and its complexes with ligands to examine their dynamical behaviour, stability, integrity, compactness, and folding properties. The protein-ligand complexes were then subjected to binding free energy calculations using the MM/PBSA-based binding free energy analysis and the values are −109.788 ± 8.03 and −152.753 ± 11.98 kcal for MurE-DB12887 and MurE-DB13879 complex, respectively. All the analysis performed on MD trajectories for the complexes of these ligands with protein provided plenty of dependable evidences to consider these molecules for inhibition of MurE enzyme from A. baumannii. Communicated by Ramaswamy H. Sarma