Project description:The COVID-19 pandemic has emerged as a global medico-socio-economic disaster. Given the lack of effective therapeutics against SARS-CoV-2, scientists are racing to disseminate suggestions for rapidly deployable therapeutic options, including drug repurposing and repositioning strategies. Molecular dynamics (MD) simulations have provided the opportunity to make rational scientific breakthroughs in a time of crisis. Advancements in these technologies in recent years have become an indispensable tool for scientists studying protein structure, function, dynamics, interactions, and drug discovery. Integrating the structural data obtained from high-resolution methods with MD simulations has helped in comprehending the process of infection and pathogenesis, as well as the SARS-CoV-2 maturation in host cells, in a short duration of time. It has also guided us to identify and prioritize drug targets and new chemical entities, and to repurpose drugs. Here, we discuss how MD simulation has been explored by the scientific community to accelerate and guide translational research on SARS-CoV-2 in the past year. We have also considered future research directions for researchers, where MD simulations can help fill the existing gaps in COVID-19 research.
Project description:Molecular dynamics simulations are an effective tool to study the structure, dynamics, and thermodynamics of carbohydrates and proteins. However, the simulations of heterogeneous glycoprotein systems have been limited due to the lack of appropriate molecular force field parameters describing the linkage between the carbohydrate and the protein regions as well as the tools to prepare these systems for modeling studies. In this work we outline the recent developments in the CHARMM carbohydrate force field to treat glycoproteins and describe in detail the step-by-step procedures involved in building glycoprotein geometries using CHARMM-GUI Glycan Reader.
Project description:Manuscript describes the daily dynamics of transcriptional responses in whole blood, from acute to convalescent phase, in severe and non-severe COVID-19 patients.
Project description:Today's standard molecular dynamics simulations of moderately sized biomolecular systems at full atomic resolution are typically limited to the nanosecond timescale and therefore suffer from limited conformational sampling. Efficient ensemble-preserving algorithms like replica exchange (REX) may alleviate this problem somewhat but are still computationally prohibitive due to the large number of degrees of freedom involved. Aiming at increased sampling efficiency, we present a novel simulation method combining the ideas of essential dynamics and REX. Unlike standard REX, in each replica only a selection of essential collective modes of a subsystem of interest (essential subspace) is coupled to a higher temperature, with the remainder of the system staying at a reference temperature, T(0). This selective excitation along with the replica framework permits efficient approximate ensemble-preserving conformational sampling and allows much larger temperature differences between replicas, thereby considerably enhancing sampling efficiency. Ensemble properties and sampling performance of the method are discussed using dialanine and guanylin test systems, with multi-microsecond molecular dynamics simulations of these test systems serving as references.
Project description:Multi-omics single-cell profiling of surface proteins, gene expression and lymphocyte immune receptors from hospitalised COVID-19 patient peripheral blood immune cells and healthy controls donors. Identification of the coordinated immune cell compositional and state changes in response to SARS-CoV-2 infection or LPS challenge, compared to healthy control immune cells.
Project description:Ionotropic glutamate receptors (iGluRs) are enticing targets for pharmaceutical research; however, the search for selective ligands is a laborious experimental process. Here we introduce a purely computational procedure as an approach to evaluate ligand-iGluR pharmacology. The ligands are docked into the closed ligand-binding domain and during the molecular dynamics (MD) simulation the bi-lobed interface either opens (partial agonist/antagonist) or stays closed (agonist) according to the properties of the ligand. The procedure is tested with closely related set of analogs of the marine toxin dysiherbaine bound to GluK1 kainate receptor. The modeling is set against the abundant binding data and electrophysiological analyses to test reproducibility and predictive value of the procedure. The MD simulations produce detailed binding modes for analogs, which in turn are used to define structure-activity relationships. The simulations suggest correctly that majority of the analogs induce full domain closure (agonists) but also distinguish exceptions generated by partial agonists and antagonists. Moreover, we report ligand-induced opening of the GluK1 ligand-binding domain in free MD simulations. The strong correlation between in silico analysis and the experimental data imply that MD simulations can be utilized as a predictive tool for iGluR pharmacology and functional classification of ligands.
Project description:In order to study the effects of alkyl chain on the thermal properties of fullerene derivatives, we perform molecular dynamics (MD) simulations to predict the thermal conductivity of fullerene (C60) and its derivative phenyl-C61-butyric acid methyl ester (PCBM). The results of non-equilibrium MD simulations show a length-dependent thermal conductivity for C60 but not for PCBM. The thermal conductivity of C60, obtained from the linear extrapolation of inverse conductivity vs. inverse length curve, is 0.2 W m(-1) K(-1) at room temperature, while the thermal conductivity of PCBM saturates at ~0.075 W m(-1) K(-1) around 20 nm. The different length-dependence behavior of thermal conductivity indicates that the long-wavelength and low-frequency phonons have large contribution to the thermal conduction in C60. The decrease in thermal conductivity of fullerene derivatives can be attributed to the reduction in group velocities, the decrease of the frequency range of acoustic phonons, and the strong scattering of low-frequency phonons with the alkyl chains due to the significant mismatch of vibrational density of states in low frequency regime between buckyball and alkyl chains in PCBM.
Project description:There are multiple drugs for the treatment of type 2 diabetes, including traditional sulfonylureas biguanides, glinides, thiazolidinediones, α-glucosidase inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase IV (DPP-4) inhibitors, and sodium-glucose cotransporter 2 (SGLT2) inhibitors. α-Glucosidase inhibitors have been used to control postprandial glucose levels caused by type 2 diabetes since 1990. α-Glucosidases are rather crucial in the human metabolic system and are principally found in families 13 and 31. Maltase-glucoamylase (MGAM) belongs to glycoside hydrolase family 31. The main function of MGAM is to digest terminal starch products left after the enzymatic action of α-amylase; hence, MGAM becomes an efficient drug target for insulin resistance. In order to explore the conformational changes in the active pocket and unbinding pathway for NtMGAM, molecular dynamics (MD) simulations and adaptive steered molecular dynamics (ASMD) simulations were performed for two NtMGAM-inhibitor [de-O-sulfonated kotalanol (DSK) and acarbose] complexes. MD simulations indicated that DSK bound to NtMGAM may influence two domains (inserted loop 1 and inserted loop 2) by interfering with the spiralization of residue 497-499. The flexibility of inserted loop 1 and inserted loop 2 can influence the volume of the active pocket of NtMGAM, which can affect the binding progress for DSK to NtMGAM. ASMD simulations showed that compared to acarbose, DSK escaped from NtMGAM easily with lower energy. Asp542 is an important residue on the bottleneck of the active pocket of NtMGAM and could generate hydrogen bonds with DSK continuously. Our theoretical results may provide some useful clues for designing new α-glucosidase inhibitors to treat type 2 diabetes.
Project description:Proteins recognize specific DNA sequences not only through direct contact between amino acids and bases, but also indirectly based on the sequence-dependent conformation and deformability of the DNA (indirect readout). We used molecular dynamics simulations to analyze the sequence-dependent DNA conformations of all 136 possible tetrameric sequences sandwiched between CGCG sequences. The deformability of dimeric steps obtained by the simulations is consistent with that by the crystal structures. The simulation results further showed that the conformation and deformability of the tetramers can highly depend on the flanking base pairs. The conformations of xATx tetramers show the most rigidity and are not affected by the flanking base pairs and the xYRx show by contrast the greatest flexibility and change their conformations depending on the base pairs at both ends, suggesting tetramers with the same central dimer can show different deformabilities. These results suggest that analysis of dimeric steps alone may overlook some conformational features of DNA and provide insight into the mechanism of indirect readout during protein-DNA recognition. Moreover, the sequence dependence of DNA conformation and deformability may be used to estimate the contribution of indirect readout to the specificity of protein-DNA recognition as well as nucleosome positioning and large-scale behavior of nucleic acids.
Project description:Our skin constitutes an effective permeability barrier that protects the body from exogenous substances but concomitantly severely limits the number of pharmaceutical drugs that can be delivered transdermally. In topical formulation design, chemical permeation enhancers (PEs) are used to increase drug skin permeability. In vitro skin permeability experiments can measure net effects of PEs on transdermal drug transport, but they cannot explain the molecular mechanisms of interactions between drugs, permeation enhancers, and skin structure, which limits the possibility to rationally design better new drug formulations. Here we investigate the effect of the PEs water, lauric acid, geraniol, stearic acid, thymol, ethanol, oleic acid, and eucalyptol on the transdermal transport of metronidazole, caffeine, and naproxen. We use atomistic molecular dynamics (MD) simulations in combination with developed molecular models to calculate the free energy difference between 11 PE-containing formulations and the skin's barrier structure. We then utilize the results to calculate the final concentration of PEs in skin. We obtain an RMSE of 0.58 log units for calculated partition coefficients from water into the barrier structure. We then use the modified PE-containing barrier structure to calculate the PEs' permeability enhancement ratios (ERs) on transdermal metronidazole, caffeine, and naproxen transport and compare with the results obtained from in vitro experiments. We show that MD simulations are able to reproduce rankings based on ERs. However, strict quantitative correlation with experimental data needs further refinement, which is complicated by significant deviations between different measurements. Finally, we propose a model for how to use calculations of the potential of mean force of drugs across the skin's barrier structure in a topical formulation design.