Nanosecond Molecular Dynamics Simulations Research Articles

#2263 Computational drug repurposing screen targeting PLA2R antibody binding

Abstract Background and Aims Approximately 60% of patients with membranous nephropathy have antibodies against the phospholipase A2 receptor (PLA2R). The cysteine rich (CysR) epitope of PLA2R is a likely site of protein-antibody interaction. Current treatment regimens for membranous nephropathy involve maximal conservative management or systemic immunosuppression in severe cases. We have developed protocols and programs for an in silico high-throughput repurposing screen using structural modelling, docking, and molecular dynamics (MD). Uniquely, our approach uses a bespoke interface on Google Colab for graphic processing units to run the MD simulations. We describe their application to a repurposing screen aiming to identify larger licensed drug molecules capable of impeding antibody-protein interactions at the site of the CysR epitope. Method A complete model of PLA2R was obtained from I-TASSER using the canonical sequence on the UNIPROT database. This structure was equilibrated using a five nanosecond molecular dynamics (MD) simulation. The simulation was prepared using CHARMM-GUI and run on the GROMACS-ON-COLAB platform. The centroid of the MD system between three and five nanoseconds was used for docking experiments using PLANTS PLP with a study area that included the CysR epitope. A library of compounds listed in the British National Formulary was used for the docking studies. The results would be analysed by PLANTS energy and by key residue overlap score. Results Viable docking results were obtained for 891 of the 1510 compounds tested. 60 of these compounds were in contact with at least 10% of the residues in the CysR region. By restricting these results to compounds in the lowest 20% of the total sample for calculated binding energy, 22 compounds remained. 16 of these compounds have been assessed for their safety for oral or intravenous use. These sixteen compounds were then identified for further investigation by MD to assess the stability of the identified interactions. The sixteen compounds include Lymecycline, Trazodone, Mirabegron, Sulfasalazine, Methotrexate, Rosuvastatin and Montelukast. Conclusion Structural bioinformatics methods provide a relatively fast and economical option for identifying protein-drug interactions that could result in new treatment strategies. The compounds identified for investigation are used for an array of different health conditions. However, they all share the chemical properties of large molecular weight and have the potential to form multiple hydrogen bonds. If validated experimentally, these compounds could provide new treatment options for PLA2R antibody positive membranous nephropathy.

Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration

In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1–5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1–5). Molecular docking was used to assess the binding interactions of these derivatives (1–5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol−1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides.Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1–5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1–5.

In Silico Study on Natural Chemical Compounds from Citric Essential Oils as Potential Inhibitors of an Omicron (BA.1) SARS-CoV-2 Mutants' Spike Glycoprotein.

SARS-CoV-2's remarkable capacity for genetic mutation enables it to swiftly adapt to environmental changes, influencing critical attributes, such as antigenicity and transmissibility. Thus, multi-target inhibitors capable of effectively combating various viral mutants concurrently are of great interest. This study aimed to investigate natural compounds that could unitedly inhibit spike glycoproteins of various Omicron mutants. Implementation of various in silico approaches allows us to scan a library of compounds against a variety of mutants in order to find the ones that would inhibit the viral entry disregard of occurred mutations. An extensive analysis of relevant literature was conducted to compile a library of chemical compounds sourced from citrus essential oils. Ten homology models representing mutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1), and the compound library was screened against them. Subsequently, employing comprehensive molecular docking and molecular dynamics simulations, we successfully identified promising compounds that exhibited sufficient binding efficacy towards the receptor binding domains (RBDs) of the mutant viral strains. The scoring of ligands was based on their average potency against all models generated herein, in addition to a reference Omicron RBD structure. Furthermore, the toxicity profile of the highest-scoring compounds was predicted. Out of ten built homology models, seven were successfully validated and showed to be reliable for In Silico studies. Three models of clades 22C, 22D, and 22E had major deviations in their secondary structure and needed further refinement. Notably, through a 100 nanosecond molecular dynamics simulation, terpinen-4-ol emerged as a potent inhibitor of the Omicron SARS-CoV-2 RBD from the 21K clade (BA.1); however, it did not show high stability in complexes with other mutants. This suggests the need for the utilization of a larger library of chemical compounds as potential inhibitors. The outcomes of this investigation hold significant potential for the utilization of a homology modeling approach for the prediction of RBD's secondary structure based on its sequence when the 3D structure of a mutated protein is not available. This opens the opportunities for further advancing the drug discovery process, offering novel avenues for the development of multifunctional, non-toxic natural medications.

Crystal structure of 1-(E)- [(5‑bromo-2-hydroxybenzylidene amino) pyrrolidin-2-one]: Design, synthesis and computational evaluation of a novel racetam congener for epilepsy

The present investigation illustrates the conceptualization, synthesis, crystallographic analysis, and computational assessment of a new racetam derivative with a pyrrolidone ring as the pharmacophore. The compound demonstrates drug-like characteristics similar to LEV, an approved anti-epileptic drug, indicating its potential for developing novel epilepsy drugs. Molecular docking and molecular dynamic simulations were used to evaluate the binding affinity between the compound and SV2A, a protein-ligand complex. The protein-ligand complex attained structural equilibrium in the final 50 nanoseconds of the 200 nanosecond molecular dynamics simulation. The analysis reveals that regions with higher flexibility are primarily located in the extramembrane regions of the protein. Intermolecular contact analysis reveals hydrogen bonding and hydrophobic interactions as the primary types of interactions. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) calculation highlights the energetic aspects of ligand binding and the participation of important residues in the binding pocket. Unique interactions like those involving bifurcated hydrogen bonding, and novel pi-anion interaction makes the study significant. Quantum chemical calculations for the compound (LIG) done using DFT corroborates the protein-ligand interactions on the basis of Molecular Electrostatic Potential (MEP) maps. The study establishes the structure-activity relationship (SAR) of the newly developed pyrrolidone-based compound, identifying it as a promising lead molecule for epilepsy treatment.

Assessing the inhibitory potential of anti-dengue compounds against Japanese encephalitis virus RNA dependent RNA polymerase: an in silico study

Japanese encephalitis (JE), a neurological infection of severe nature, is caused by the Japanese encephalitis virus (JEV) and is transmitted by the mosquito vector. The polymerase domain of Non-structural 5 (NS5), which is also referred to as RdRp (RNA-dependent RNA polymerase), is considered a potential therapeutic target for JEV. The present study employed molecular dynamics modelling and high-throughput virtual screening to evaluate the possible antiviral activity of anti-dengue drugs against JEV RdRp. Furthermore, a ranking was performed utilising the MM/GBSA analysis to identify the three most promising compounds. Compound ID 57409246 exhibited the highest binding affinity with the protein, as evidenced by its minimum binding free energy of −72.96 kcal/mole. In contrast, the other two compounds had minimum binding free energies of −67.57 and −59.19 kcal/mole, respectively. Upon conducting a 100 nanosecond molecular dynamics simulation to confirm the binding of the chemical complexes, it was observed that the three hits, namely 57409246, 70683874, and 44577154, exhibited a consistent and stable RMSD. Subsequently, the binding strength of the trajectory was confirmed through MM/GBSA analysis. The compounds 70683874 and 57409246 exhibited the lowest binding free energies, which were −97.58 kcal/mol and −96.38 kcal/mol, respectively. The binding free energy (ΔG Bind) values for the native ligand ATP and molecule 44577154 were −65.64 kcal/mol and −69.44 kcal/mol, respectively. Overall, compared to the native ligand ATP, all three compounds exhibited higher binding affinity. The study proposes three anti-dengue molecules as a potential remedy for JE, which can be confirmed through in vitro and in vivo investigations. Communicated by Ramaswamy H. Sarma

Designing Bcl-2 protein binding aptamers using screened Coulomb interaction method & regulate apoptosis.

Cancer cells develop different physiological abnormalities. One of them is overexpression of Bcl-2 protein, an anti-apoptotic biomolecule helping cancer cells to sustain. We planned to regulate the apoptosis by inhibiting the Bcl-2 protein's functions in cancer cells. We used computer aided drug design techniques to make a nucleic acid-based aptamer drug that targets Bcl-2 proteins. We applied a theoretical biophysics technique ‘screened Coulomb interactions approach (SCIA)’ for designing aptamers. This technique was patented (US10916330B1) and found suitable for designing novel aptamers to target biomoleculesin physiological conditions. Physicochemical analysis of Bcl-2 protein helps detect drug binding site(s) and charge distribution inamino acid structures. We made a judicious choice to select amino acid arginine as our target molecule in Bcl-2 structure. We constructed a universal drug design platform by applying SCIA, developed our algorithms and applied in Mathematica 13 to perform numerical computations (NCs) addressing the drug-target binding energetics. The NC results show that nucleotide guanine has the lowest binding energy over other nucleotides while interacting with arginine. Selection of other subsequent nucleotides as aptamer building blocks at various screening order is being made using their preferred SCI binding energetics with arginine. Thus, the discovery of a few aptamers to target arginine (specifically) and Bcl-2 protein (in general) has been made. Based on target binding energetic preferences we rank the aptamers. We are now working on the following two things: (i) perform 100 nanosecond molecular dynamics (MD) simulations to address drug-target binding kinetics and (ii) perform in vitro protein binding assays using top selected aptamers. Thus, we shall be able to finalize a few candidate drugs as optimal therapeutic agents capable of binding with Bcl-2 proteins and thus inhibit the protein functions. This research will lead us to discovering a few aptamer candidates for future chemotherapy applications.

Novel Small Molecule and Peptide Inhibitors of CREB in Leukemia Cells

Background: Acute Lymphoblastic Leukemia (ALL) and Acute Myelogenous Leukemia (AML) account for nearly 45% of all childhood cancer. Current therapy for acute leukemia results in significant morbidity and late complications in children. Therefore, more effective and less toxic therapies to treat leukemia are needed. Previous work in our laboratory has identified CREB (cAMP Response Element Binding Protein), a transcription factor that promotes cell proliferation and survival in acute leukemia, is overexpressed in primary ALL and AML cells and is a potential target for therapy. We have investigated small molecules and peptides to inhibit the critical interaction between the phosphorylated KID (Kinase-Inducible) domain of CREB and the KIX (KID-interacting) domain of the coactivator CBP (CREB Binding Protein). Methods: We assessed a library of previously untested alpha-mimetic compounds from ChemDiv designed to mimic interactions between α-helices and protein surfaces for predicted interaction with a shallow hydrophobic groove on the interaction surface of KIX. We interrogated the 24,737 compounds in the library using rigid-receptor ligand docking, followed by induced-fit ligand docking of the top compounds using two different software, MOE and Schrodinger's Bioluminate. The top 50 binding poses from each software's rankings were combined to yield 87 candidate alpha-mimetic molecule inhibitors. In addition to our screen of small molecules, we have designed peptide inhibitors that closely mimic the αB helix of pKID. We investigated two methods to enhance the stability and cell-penetrating ability of our peptides: hydrocarbon stapling and the utilization of a rigid scaffold from the scorpion toxin peptide BmBKTtx1. Based on the calculated binding scores and locations, the most promising chimeric peptide designs were further investigated for binding stability using 500 nanosecond molecular dynamics (MD) simulations modeling their interaction with KIX. Results: The binding poses of the final set of small molecules were visually inspected for occupation of key hotspots on the pKID:KIX interaction surface, including the location of the phosphorylation sight of KID. Of the 87 molecules and their binding poses, only 21 of them (24%) obstructed fewer than two of the three hotspots chosen for the analysis. Moreover, 80 of the molecules (92%) extended into the hydrophobic pocket, the most critical hotspot. The multi-residue construction of this pocket likely contributed to the high similarity in interaction fingerprint between these molecules and pKID; occupation of this pocket can serve as a good indicator of strong ligand binding to KIX in future assays. The most-promising peptide designs using the scorpion toxin scaffold were assessed with MD simulations and compared to a control peptide comprised primarily of the αB helix of pKID. The chimeric peptides showed increased binding stability over the control peptide with an average RMSD of 6.8Å vs. 12.5Å, illustrating the benefits of the stability afforded by the scorpion scaffold design. Several of the hydrocarbon stapled peptides were tested in vitro using fluorescence polarization (FP) assay developed by our lab (Chae et al. Bioorganic & Medicinal Chemistry Letters, 2019) and in AML HL-60 and KG-1 cells and were shown to have growth inhibitory effects by Cell-Titer Glo Assays. Discussion: These small molecules and scorpion toxin-derived peptides represent novel candidate inhibitors of the pKID:KIX interaction implicated in leukemia. Based on promising results from our in silico analyses of these inhibitors, we have obtained ten structurally diverse alpha-mimetic small molecules and three chimeric peptides and aim to test their efficacy in vitro using the FP assay. Furthermore, we will obtain high resolution cryo-EM structures of successful compounds and peptides bound to the KIX domain using a double-shell protein scaffold (Zhang et al. ACS Central Science, 2022), and use these structures for further refinement of the inhibitors. The development of new inhibitors for the pKID:KIX interaction promises to reveal insights into the structural relationship between the two domains and the basis for effective, targeted leukemia therapeutics.

Molecular Mechanism of Food-Derived Polyphenols on PD-L1 Dimerization: A Molecular Dynamics Simulation Study.

In cancer immunotherapy, an emerging approach is to block the interactions of programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) using small-molecule inhibitors. The food-derived polyphenols curcumin (CC), resveratrol (RSV) and epigallocatechin gallate (EGCG) have anticancer immunologic functions, which, recently, have been proposed to act via the downregulation of PD-L1 expression. However, it remains unclear whether they can directly target PD-L1 dimerization and, thus, interrupt the PD-1/PD-L1 pathway. To elucidate the molecular mechanism of such compounds on PD-L1 dimerization, molecular docking and nanosecond molecular dynamics simulations were performed. Binding free energy calculations show that the affinities of CC, RSV and EGCG to the PD-L1 dimer follow a trend of CC > RSV > EGCG. Hence, CC is the most effective inhibitor of the PD-1/PD-L1 pathway. Analysis on contact numbers, nonbonded interactions and residue energy decomposition indicate that such compounds mainly interact with the C-, F- and G-sheet fragments of the PD-L1 dimer, which are involved in interactions with PD-1. More importantly, nonpolar interactions between these compounds and the key residues Ile54, Tyr56, Met115, Ala121 and Tyr123 play a dominant role in binding. Free energy landscape and secondary structure analyses further demonstrate that such compounds can stably interact with the binding domain of the PD-L1 dimer. The results provide evidence that CC, RSV and EGCG can inhibit PD-1/PD-L1 interactions by directly targeting PD-L1 dimerization. This provides a novel approach to discovering food-derived small-molecule inhibitors of the PD-1/PD-L1 pathway with potential applications in cancer immunotherapy.

Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations.

Estrogen receptor alpha (ERα) is a ligand-dependent transcriptional factor in the nuclear receptor superfamily. Many structures of ERα bound with agonists and antagonists have been determined. However, the dynamic binding patterns of agonists and antagonists in the binding site of ERα remains unclear. Therefore, we performed molecular docking, molecular dynamics (MD) simulations, and quantum mechanical calculations to elucidate agonist and antagonist dynamic binding patterns in ERα. 17β-estradiol (E2) and 4-hydroxytamoxifen (OHT) were docked in the ligand binding pockets of the agonist and antagonist bound ERα. The best complex conformations from molecular docking were subjected to 100 nanosecond MD simulations. Hierarchical clustering was conducted to group the structures in the trajectory from MD simulations. The representative structure from each cluster was selected to calculate the binding interaction energy value for elucidation of the dynamic binding patterns of agonists and antagonists in the binding site of ERα. The binding interaction energy analysis revealed that OHT binds ERα more tightly in the antagonist conformer, while E2 prefers the agonist conformer. The results may help identify ERα antagonists as drug candidates and facilitate risk assessment of chemicals through ER-mediated responses.

Molecular Dynamics Investigation of Phenolic Oxidative Coupling Protein Hyp-1 Derived from Hypericum perforatum

Molecular dynamics (MD) simulations provide a physics-based approach to understanding protein structure and dynamics. Here, we used this intriguing tool to validate the experimental structural model of Hyp-1, a pathogenesis-related class 10 (PR-10) protein from the medicinal herb Hypericum perforatum, with potential application in various pharmaceutical therapies. A nanosecond MD simulation using the all-atom optimized potentials for liquid simulations (OPLS–AA) force field was performed to reveal that experimental atomic displacement parameters (ADPs) underestimate their values calculated from the simulation. The average structure factors obtained from the simulation confirmed to some extent the relatively high compliance of experimental and simulated Hyp-1 models. We found, however, many outliers between the experimental and simulated side-chain conformations within the Hyp-1 model, which prompted us to propose more reasonable energetically preferred rotameric forms. Therefore, we confirmed that MD simulation may be applicable for the verification of refined, experimental models and the explanation of their structural intricacies.

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

We present the GPU version of DeePMD-kit, which, upon training a deep neural network model using ab initio data, can drive extremely large-scale molecular dynamics (MD) simulation with ab initio accuracy. Our tests show that for a water system of 12,582,912 atoms, the GPU version can be 7 times faster than the CPU version under the same power consumption. The code can scale up to the entire Summit supercomputer. For a copper system of 113,246,208 atoms, the code can perform one nanosecond MD simulation per day, reaching a peak performance of 86 PFLOPS (43% of the peak). Such unprecedented ability to perform MD simulation with ab initio accuracy opens up the possibility of studying many important issues in materials and molecules, such as heterogeneous catalysis, electrochemical cells, irradiation damage, crack propagation, and biochemical reactions. Program summaryProgram Title: DeePMD-kitCPC Library link to program files:https://doi.org/10.17632/phyn4kgsfx.1Developer’s repository link:https://doi.org/10.5281/zenodo.3961106Licensing provisions: LGPLProgramming language: C++/Python/CUDAJournal reference of previous version: Comput. Phys. Commun. 228 (2018), 178–184.Does the new version supersede the previous version?: Yes.Reasons for the new version: Parallelize and optimize the DeePMD-kit for modern high performance computers.Summary of revisions: The optimized DeePMD-kit is capable of computing 100 million atoms molecular dynamics with ab initio accuracy, achieving 86 PFLOPS in double precision.Nature of problem: Modeling the many-body atomic interactions by deep neural network models. Running molecular dynamics simulations with the models.Solution method: The Deep Potential for Molecular Dynamics (DeePMD) method is implemented based on the deep learning framework TensorFlow. Standard and customized TensorFlow operators are optimized for GPU. Massively parallel molecular dynamics simulations with DeePMD models on high performance computers are supported in the new version.

Raw nuclear magnetic resonance data of human linker histone H1x, lacking the C-terminal domain (NGH1x), and trajectory data of nanosecond molecular dynamics simulations of GH1x- and NGH1x-chromatosomes.

Linker histone H1 plays a vital role in the packaging of DNA. H1 has a tripartite structure: a conserved central globular domain that adopts a winged-helix fold, flanked by highly variable and intrinsically unstructured N- and C-terminal domains. The datasets presented in this article include raw 2D and 3D BEST-TROSY NMR data [1H-15 N HSQC; 15 N and 13C HNCO, HN(CO)CACB, HNCACB, HN(CA)CO] recorded for NGH1x, a truncated version of H1x containing the N-terminal and globular domains, but lacking the C-terminal domain. Experiments were conducted on double-labelled (15 N and 13C) NGH1x in 'low' and 'high salt,' to investigate the secondary structure content of the N-terminal domain of H1x under these conditions. We provide modelled structures of NGH1x (in low and high salt) based on the assigned chemical shifts in PDB format. The high salt structure of NGH1x (globular domain of H1x [GH1x; PDB: 2LSO] with the H1x NTD) was docked to the nucleosome to generate NGH1x- and GH1x-chromatosomes. The GH1x-chromatosome was generated for comparative purposes to elucidate the role of the N-terminal domain. We present raw data trajectories of molecular dynamics simulations of these chromatosomes in this article. The MD dataset provides nanosecond resolution data on the dynamics of GH1x- vs NGH1x-chromatosomes, which is useful to elucidate the DNA binding properties of the N-terminal domain of H1x in chromatin, as well as the dynamic behaviour of linker DNA in these chromatosomes.

Molecular docking and simulation of Zika virus NS3 helicase

The Zika virus (ZIKV) has gained attention for the last few years due to the congenital microcephaly and Guillain–Barre Syndrome that resulted in humans. The non-structural protein-3 (NS3) helicase of ZIKV play an important role in viral RNA replication. In this article, we performed hundred nanosecond molecular dynamics simulation and molecular docking of the NS3 helicase of ZIKV with 1,4-benzothiazine derivatives. The root mean square deviation (RMSD) analyses showed the stability of the NS3 helicase. The simulation showed that the flexible and rigid domains of the protein play a crucial role during the RNA replication process. All such domains with ligand binding pockets can be targeted for drug design. The molecular docking showed that the strong hydrogen bonding and arene-cation interactions are responsible for the binding between NS3 and 1,4-benzothiazine derivatives, which provides a new dimension for potent drug design for ZIKV.

Halogenated derivatives of methotrexate as human dihydrofolate reductase inhibitors in cancer chemotherapy

Methotrexate is a widely used anti-metabolite in cancer chemotherapy. A series of halogenated drugs is designed from Methotrexate to assess their interactions with human dihydrofolate reductase. The aim of this study is to evaluate the performance of the modified drugs compared to the parent Methotrexate. Density Functional Theory is employed to optimize these drugs. Molecular docking calculation of these optimized drugs against dihydrofolate reductase is performed to find out binding affinity. In addition, molecular dynamics simulation is considered for the complexes of best two modified drugs with their receptors. Modifications by the halogens show significant changes in the charge distribution, dipole moment, thermodynamic stability, enthalpy and free energy. The highest binding affinity value (−36.401 KJ/mol) was obtained for M14. Hybrid quantum mechanics/molecular mechanics calculation shows a binding energy of −255.140 KJ/mol. Modified drugs have significant hydrogen and non-covalent bonding interactions with amino acids of the receptor. Molecular dynamics simulation disclosed that the root-mean-square-deviation of the alpha carbon associated with M6-1KMV and M14-1KMV complexes is 2.367 Å and 2.622 Å, respectively. Moreover, the interactions between modified drugs and receptor are mostly persevered in 25 nanosecond molecular dynamics simulation. Ensemble-based docking also confirmed that modified drugs show strong non-bonding interactions with different crystallographic and molecular dynamics based conformers. The best scored drugs show considerable pharmacokinetic properties. Modified derivatives M5, M6, M8, M10, M13 and M14 show the better binding affinity and a good number of hydrogen and other non-bonding interactions with the target protein which are similar to other anticancer drugs.Communicated by Ramaswamy H. Sarma

Hydration Modulates G‐Protein‐Coupled Receptor Signaling

Rhodopsin is the G‐protein‐coupled receptor (GPCR) responsible for scotopic vision in the retina. Up to this point, the role of water in the activation of GPCRs has remained largely unknown. Recently, however, nanosecond molecular dynamics simulations have revealed an influx of bulk water into rhodopsin during activation [1]. Utilizing rhodopsin as a model GPCR, we tested the hypothesis that rhodopsin activation is hydration mediated using osmotic stress techniques. We subjected rhodopsin within its native lipid membranes to varying osmotic pressures induced by different‐sized polyethylene glycol polymers. UV‐Visible spectroscopy of the photoactivated rhodopsin system reveals the fraction of protein in the active metarhodopsin‐II (MII) conformation, the receptor state capable of activating the G‐protein. We discovered high‐molecular weight osmolytes uniformly favored the closed, inactive metarhodopsin‐I conformation by dehydration of the protein interior. By contrast, small osmolytes penetrated into the transducin binding cleft and stabilized the active MII conformation until a quantifiable saturation point. A universal osmotic response occurred in the limit of increasing osmolyte size and maximal polymer exclusion from rhodopsin. By measuring the thermodynamic dependence of the metarhodopsin equilibrium on osmotic pressure, we determined that rhodopsin activation is coupled to a bulk influx of 80–100 water molecules into the protein core with a substantial increase in compressibility. We propose a new model for the functional role of water in GPCR signal transduction, in which a wet‐dry cycling mechanism amplifies the activation of G‐proteins. Our results necessitate a new understanding of GPCR activation, in which the influx of water plays a critical role in establishing the active receptor conformation.Support or Funding InformationThis work was supported by the NIH (EY026041 and EY012049) and the NSF (MCB 1817862).This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Effects of cholesterol on the binding of the precursor neurotransmitter tryptophan to zwitterionic membranes.

The characterization of the microscopical forces between the essential α-amino-acid tryptophan, precursor of the neurotransmitter serotonin and of the hormone melatonin, and the basic components of cell membranes and their environments (phospholipids, cholesterol, ionic species, and water) is of central importance to elucidate their local structure and dynamics as well as the mechanisms responsible for the access of tryptophan to the interior of the cell. We have performed nanosecond molecular dynamics simulations of tryptophan embedded in model zwitterionic bilayer membranes made by di-palmitoyl-phosphatidyl-choline and cholesterol inside aqueous sodium-chloride solution in order to systematically examine tryptophan-lipid, tryptophan-cholesterol, and tryptophan-water interactions under liquid-crystalline phase conditions. Microscopic properties such as the area per lipid, lipid thickness, radial distribution functions, hydrogen-bonding lengths, atomic spectral densities, and self-diffusion coefficients have been evaluated. Our results show that the presence of tryptophan significantly affects the structure and dynamics of the membrane. Tryptophan spends long periods of time at the water-membrane interface, and it plays a central role by bridging a few lipids and cholesterol chains by means of hydrogen-bonds. The computed spectral densities, in excellent agreement with experimental infrared and Raman data, revealed the participation of each atomic site of tryptophan to the complete spectrum of the molecule. Tryptophan self-diffusion coefficients have been found to be in between 10-7 and 10-6 cm2/s and strongly depending of the concentration of cholesterol in the system.

Implications of sequence conservation patterns of serpin B family leading to structural and functional importance

SERine Proteinase INhibitors Clade B: SERPINS, a largely dispersed family of protease inhibitors that exhibit a conformational alteration to inhibit target enzymes. Atypical serpin proteins often form aggregates that can accumulate to toxic levels within cells. SerpinB4 is a chymotrypsin-like serine proteinase inhibitor. Phylogenetic analysis of Serpin Clade B revealed no duplication throughout the mammalian clades. Thus, elucidating retention of a single copy of human serpin members in nature, endorsing its essentiality as an inhibitor. Epidemiological studies specify that a rising number of patients are inclined to develop chronic liver disease due to SerpinB4 overexpression. This upregulation is therefore not in fine fettle for the human physiology. Molecular docking protocol classified compound 57, a novel inhibitory compound, as the ligand, best able to fit the binding pocket with a Gold Score of 94. A two hundred nanosecond molecular dynamics simulation of docked SerpinB4 illustrated a steady binding pattern of ligand in the protein's active site. Pursuing this, trajectory analysis was implemented to assess various characteristics of the docked system in terms of function of time. These findings may act effectively in designing effective remedies against SerpinB4.

Effects of chirality on single‐file water permeability and diffusivity through single wall carbon nanotubes

In this work, molecular dynamics (MD) simulations of single-file water permeation through carbon nanotube (CNT) membranes have been performed and for a better understanding of the relationship between water transport performance of these biomimetic membranes and chirality of CNTs, the key parameters such as osmotic and diffusive permeability constants and diffusion coefficients are investigated. For this purpose, CNTs with approximately same diameters and different chirality from armchair to zigzag are used to perform 40 nanosecond MD simulations of these membranes. The resulting permeability and diffusivity characteristics of single-file CNT membranes showed that water permeability constant and diffusion coefficient increase by changing in the chirality of CNTs from armchair to zigzag, with approximately similar size in diameter. Finally, the presented results provide useful insights into the design of CNT water transporters with best performance.

Identification of potent inhibitors for chromodomain-helicase- DNA-binding protein 1-like through moleculardocking studies

Chromodomain-helicase-DNA-binding protein 1-like is a chromodomain-containing protein in the SNF2-like family of ATPases. It has the capability to sustain proliferation in cell, encourage tumor growth and prevent apoptosis of cell. The goal of the current study is to build an in silico homology model further to identify the structural features that influence the inhibitory activity of chromodomain-helicase-DNA-binding protein 1-like protein grounded on a variety of 103 set of compounds. GOLD program is used to carry out molecular docking studies to ascertain the binding mode of structurally varied inhibitors of chromodomain-helicase-DNA-binding protein 1-like protein. Most active residues docked with chromodomain-helicase-DNA-binding protein 1-like protein are compound 20, 103 and 22 with their GOLD Scores 90.5, 81.01 and 79.2, respectively. These docked residues exhibited substantial interaction with active site residues of the protein. Ligand-protein binding is further elucidated with the extensive hydrogen bonding and other hydrophobic interactions. Chromodomain-helicase-DNA-binding protein 1-like protein belongs to Snf2 family of proteins with conserved evolutionary function. Another interesting aspect of this study is the presence of a conserved Snf2 N-terminal domain observed in chromodomain-helicase-DNA-binding protein 1-like protein. It controls the catalytic and the helicase activity which is crucial in regulating tumor progression. A hundred nanosecond molecular dynamics simulation of docked chromodomain-helicase-DNA-binding protein 1-like illustrated a stable binding pattern of ligand in the protein’s active site. Furthermore, trajectory analysis was performed to assess various characteristics of the docked system in terms of function of time. This study pinpoints potential novel inhibitors against chromodomain-helicase-DNA-binding protein 1-like protein which have not been reported previously but are involved in the overexpression in different cancers. This finding will help to design a prospective drug for varied number of cancers.

A Jump-from-Cavity Pyrophosphate Ion Release Assisted by a Key Lysine Residue in T7 RNA Polymerase Transcription Elongation.

Pyrophosphate ion (PPi) release during transcription elongation is a signature step in each nucleotide addition cycle. The kinetics and energetics of the process as well as how it proceeds with substantial conformational changes of the polymerase complex determine the mechano-chemical coupling mechanism of the transcription elongation. Here we investigated detailed dynamics of the PPi release process in a single-subunit RNA polymerase (RNAP) from bacteriophage T7, implementing all-atom molecular dynamics (MD) simulations. We obtained a jump-from-cavity kinetic model of the PPi release utilizing extensive nanosecond MD simulations. We found that the PPi release in T7 RNAP is initiated by the PPi dissociation from two catalytic aspartic acids, followed by a comparatively slow jump-from-cavity activation process. Combining with a number of microsecond long MD simulations, we also found that the activation process is hindered by charged residue associations as well as by local steric and hydrogen bond interactions. On the other hand, the activation is greatly assisted by a highly flexible lysine residue Lys472 that swings its side chain to pull PPi out. The mechanism can apply in general to single subunit RNA and DNA polymerases with similar molecular structures and conserved key residues. Remarkably, the flexible lysine or arginine residue appears to be a universal module that assists the PPi release even in multi-subunit RNAPs with charge facilitated hopping mechanisms. We also noticed that the PPi release is not tightly coupled to opening motions of an O-helix on the fingers domain of T7 RNAP according to the microsecond MD simulations. Our study thus supports the Brownian ratchet scenario of the mechano-chemical coupling in the transcription elongation of the single-subunit polymerase.