AlphaFold2 models indicate that protein sequence determines both structure and dynamics

Dynamical structures of intrinsically disordered proteins (IDPs) and multi-domain proteins that include large ID regions between the domains are unable to be determined by such conventional methods as X-ray crystallography and electron microscopy. Small-angle X-ray scattering (SAXS) is suitable to determine low-resolution structures of proteins and protein complexes in solution, but the structural data on protein dynamics are averaged over the structural ensemble in protein solution. To overcome this problem, we have developed a novel method, named MD-SAXS, of the combined use of SAXS and molecular dynamics (MD) simulation to analyze protein dynamics in solution of multi-subunit protein complexes and multi-domain proteins toward the structural characterization of IDPs. Here we show validity of the method through the structural characterization of restriction Endonuclease EcoO109I.

Herbal plants are often used as alternative medicine because they contain active compounds for the treatment of diseases and disorders with minimal side effects, and are easily obtained from the surrounding environment. Some of them have antiviral activity. This study aimed to analyze the potential of phytochemical compounds in the leaf of “pangi” (Pangium edule Reinw) as antiSARS-CoV-2 using molecular docking study. The drug- and lead-likeness properties of the selected compounds were obtained from the Swiss ADME and admetSAR online server tools. Molecular dynamics (MD) simulation of the selected ligand was carried out to validate the stability of the interaction. The results suggested that pangi leaves contain three compounds with remarkable binding affinities with Mpro (main protease) and RBD (receptor binding domain) were (5.beta.) pregnane-3,20.beta.-diol, 14.alpha.,18.alpha.-[4-methyl-3-oxo-(1-oxa-4-azabutane-1,4-diyl)]-, diacetate (PD), ethyl cholate (EC), and bis(3,5,5-trimethylhexyl) phthalate. Because EC will be metabolized in the body into cholic acid (Cho), this compound was then docked and validated using MD simulation. The compound has the best free binding energy (ΔG) with SARS-CoV-2 (–7.1 kcal/ mol with Mpro and –6.0 kcal/mol with RBD). Moreover, the compound is bound strongly to the active cavity of Mpro on Thr24, Thr26, His41, and Cys145 residues. The MM-GBSA calculation showed that the interaction of Cho with Mpro was higher than with RBD. According to the RMSD (root mean square deviation), RMSF (root mean square fluctuation), the radius of gyration (Rg), and intermolecular hydrogen bond (H-bond) analysis obtained from 50 ns MD simulations, Cho formed stable interactions with Mpro and RBD. The finding of this study indicated that Cho showed good anti-SARS-CoV-2 activity. The potential of the compound to inhibit the virus can serve as a starting point in the process of developing COVID-19 therapeutic natural medicine.

Molecular dynamics simulations of intrinsically disordered protein regions enable biophysical interpretation of variant effect predictors.

The molecular dynamics (MD) simulation of two structures of human insulin hexamers (Zn-hexamer and Znfree-hexamer) in explicit solvent was performed and the role of the Zn2+ ions in the hexamer’s cavity as it may affect the propensities of the dissociation of insulin hexamer into dimers and monomers investigated. The starting structure of the Zn-hexamer contains two cavity water molecules and two Zn2+ ions in addition to the amino acids residues of the insulin hexamer while the starting structure Znfree-hexamer is made up of only the amino acids residues of the insulin hexamer. The MD simulation was performed for 1 µs under the isothermal-isobaric conditions (NPT) conditions using the GROMACS software, amber ff99-SB force field, TIP 3P water model with periodic boundary conditions imposed on x-, y- and z- directions. Structural analyses of the two experimental structures were carried out and root mean square deviations (RMSD) and root mean square fluctuations (RMSF) computed from the referenced initial structures. The average RMSD value of the backbone atoms for the Zn-hexamer is 0.293 nm and Znfree-hexamer is 0.785 nm. The structural analysis revealed that, there were dimer’s dissociation and pronounced fluctuations of the amino acids residues in the Znfree-hexamer compared to the Zn-hexamer during the MD simulation. This is evident in the higher inter-dimer distances of the six glutamate-13(β) residues in the Znfree-hexamer which confirmed the influence of the removal of the Zn2+ ions and cavity water molecules on dissociation of the insulin hexamer.

Biopolymers are versatile molecules that perform myriad cellular functions such as gene regulation and high-energy molecule synthesis. Alterations in biomolecular structure such as those arising from mutations can disrupt important cellular processes and lead to disease. Therefore, accurate biopolymer structure characterization plays an outsized role in improving human health. X-ray crystallography, cryogenic electron microscopy (Cryo-EM), and nuclear magnetic resonance (NMR) spectroscopy are the most powerful techniques for obtaining high-resolution, 3D structures.Valuable structural insight is also obtained using optical rotation, small angle X-ray scattering (SAXS), circular dichroism (CD) spectroscopy, and Forster resonance energy transfer (FRET) spectroscopy. Over the past few years, remarkable advances in computational power and algorithm development have revolutionized the field of biopolymer structure prediction. For example, leveraging machine learning (ML) and artificial intelligence (AI), AlphaFold and Open fold have demonstrated a remarkable ability to predict biopolymer structure from sequence. Although powerful, these techniques are limited in their ability to provide information about challenging systems where the structure is either unknown or highly flexible under physiological conditions. In this work, studies are presented in which structural information is gleaned from challenging biopolymer systems using novel computational and experimental methods. In Chapter 2, a new structure characterization methodology based on hydrogen-deuterium exchange-mass spectrometry (HDX-MS) in combination with molecular dynamics (MD) simulations is introduced. The approach is used to describe the structural motifs of the unstructured peptide, Nt17, a conserved sequence in Huntingtin protein and associated with Huntington’s Disease progression. The model is used to show that, although highly flexible, Nt17 is intrinsically primed for facile conversion to α-helical conformation upon binding with molecular partners. Having shown that HDX reactivity is predictive of the degree of structural flexibility and bias (propensity to form 2° structural elements such as α-helix, β-sheet, and β-turn) for intrinsically disordered regions (IDRs), the work in Chapter 3 explores an extension of structure characterization to protein-ligand systems. In this study human FK506 binding protein (FKBP12) structure is examined in the absence and presence of two, well-recognized ligand molecules (i.e., FK506 and rapamycin). The work provides a better understanding of binding/unbinding events, competitive binding, and folded/unfolded conformer heterogeneity. Native MS and HDX-MS were utilized in conjunction with MD simulations to understand this select intrinsically disordered region (IDR) and IDR-drug conformational landscape. Chapter 4 explores the functional property prediction of Proteorhodopsin, by integrating experimental studies with MD simulations validation. Here, a novel linear regression model accurately predicts the spectral

Insighting the inhibitory potential of novel modafinil drug derivatives against estrogen alpha (ERα) of breast cancer through a triple hybrid computational methodology

Proteins are highly dynamic macromolecules. To analyze their inherent flexibility, computational biologists often use molecular dynamics (MD) simulations. The quantification of protein flexibility is based on various methods such as Root Mean Square Fluctuations (RMSF) that rely on multiple MD snapshots or Normal Mode Analysis (NMA) that rely on a single structure and focus on quantifying large movements. Alternative in silico approaches assess protein motions through the protein residue network or dynamical correlations from MD simulations. An alternative yet powerful approach based on small prototypes or “structural alphabets” (SAs) can be used. SAs approximate conformations of protein backbones and code the local structures of proteins as one-dimensional sequences. Protein Blocks (PBs) are one of these SAs. Applying PB-based approaches to biological systems such as the DARC protein, the human αIIb β3 integrin and the KISSR1 protein highlighted the major interest of PBs in understanding local deformations of large protein structures. Specifically, these analyses have shown that a region considered as highly flexible through RMSF quantifications can be seen using PBs as locally highly rigid. This unexpected behavior is explained by a local rigidity surrounded by deformable regions. To go further, we used PBs to analyze long-range allosteric interactions in the Calf-1 domain of αIIb integrin and will also present new unpublished results. Our tool named PBxplore allows the analyses of MDs in terms of PBs and quantification with entropy index and also different types of visualization. The presentation of this research will be done in 5 successive parts: (i) the presentation and interest of the PBs, (ii) the MD of the integrins, (iii) the analysis of the results using PBs with the PBxplore software, (iv) recent developments based on PBxplore to compare reference and variant proteins, i.e. providing information about potential allosteric events and (v) the extension of the analyses to the disordered protein.

Although cancer continues to be one of the world’s major causes of death, current cancer drugs have many serious side effects. There remains a need for new anticancer agents to overcome these shortcomings. Alternaria is one of the most widespread fungal genera, many species of which produce several classes of metabolites with potential polypharmacological activities. A few quinones and pyrones from Alternaria spp. have proven to exert cytotoxic effects against certain cancer cell lines, but their molecular mode of action is not known. The current study aimed to investigate the potential mechanisms that underlie the anticancer activity of a few selected quinones and pyrones from Alternaria solani and Alternaria alternata by molecular docking and dynamic simulation approaches. The selected metabolites were screened for their binding affinity to Heat shock protein 90 (HSP90), which is a known anticancer drug target. Molecular docking studies have revealed that Macrosporin, Altersolanol B, Fonsecin, and Neoaltenuene have good binding affinities with the target protein and the stabilities of the formed complexes were evaluated through molecular dynamics simulations. By analyzing the Root Mean Square Distance (RMSD), Root Mean Square Fluctuation (RMSF), and Principal Component Analysis (PCA) plots obtained from molecular dynamics simulations, this study shows that the complexes of all 4 lead molecules with target protein are stable over a 100 ns period. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations were used to compute the binding free energies. The lead molecules were studied using in-silico analysis to determine their drug-likeness based on their Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and physicochemical properties. The results demonstrate that Macrosporin, Fonsecin, and Neoaltenuene could become promising anticancer molecules that target HSP90. Communicated by Ramaswamy H. Sarma

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major respiratory disorder that is characterized by persistent airflow limitation and an abnormal inflammation response to noxious particles, such as cigarette smoke and environmental pollution. COPD is a leading cause of mortality, causing a significant economic and social burden in many countries worldwide. Umbelliferone, which is a coumarin derivative, has been shown to possess anti-inflammatory and antioxidant properties, which may be useful in alleviating COPD. METHODS: An integrative bioinformatics approach was adopted to analyze gene expression datasets from gene expression omnibus (GSE275503 for bulk RNA sequencing and GSE183974 for single-cell RNA sequencing). Differentially expressed genes (DEGs) were identified and overlapped with COPD-associated genes from GeneCards. Common genes were analyzed using the STRING database to construct a protein-protein interactions (PPI) network, and further processed in Cytoscape using the “cytoHubba” plug-in to identify the top 10 hub genes. Molecular docking of these genes, along with three key genes from single-cell analysis, was performed using AutoDock vina in SAMSON software. A molecular dynamic (MD) simulation study was carried out using Desmond and Schrodinger software. The MD simulations were performed to investigate the stability and dynamic behavior of the UMB with 6E3K and 1S9V over time 200 ns. RESULTS: From bulk and single-cell RNA sequencing analyses, 50 and 1053 DEGs were extracted, respectively, with the cut-off value of LogFC > 1 and [Formula: see text]-value < 0.05. A total number of 562 overlapping genes were identified between the DEGs and COPD-associated genes from GeneCards. The top 10 hub genes from the PPI network were ITGAM, CCL2, IFN-[Formula: see text], CCL5, FN1, IL-1B, BCL2, CDH1, IL-1A and CXCL8. Among these, molecular docking revealed the highest binding affinities for IFN-[Formula: see text] (PDB ID: 6E3K, −7.4 kcal/mol), ITGAM (PDB ID: 1NA5, −6.6 kcal/mol), IL-1B (PDB ID: 8C3U, −6.2 kcal/mol), FN1 (PDB ID: 3M7P, −6.1 kcal/mol) and BCL2 (PDB ID: 6YLD, −5.9 kcal/mol). Additionally, single-cell RNA analysis identified HLA-DQA2 (PDB ID: 1H15, −2.7 kcal/mol), HLA-DRB5 (PDB ID: 1S9V, −4.9 kcal/mol) and S100A9 (PDB ID: 6ZDY, −5.3 kcal/mol) as the top three genes. An MD simulation study evaluated protein-ligand stability, binding dynamics and conformational changes. Root mean square deviation (RMSD) and Root mean square fluctuation (RMSF) analyses identified key interacting residues involved in hydrogen bonding, hydrophobic interactions and water bridges. The 6E3K complex exhibited protein backbone RMSD of 5−7 Å, ligand RMSD of 2−5 Å and residue fluctuations <3 Å. The 1S9V complex showed protein RMSD of 2.85 Å, ligand RMSD of 1.95−2.30 Å and residue fluctuations around 1.25−3.25 Å. CONCLUSION: The top 10 Genes from the PPI network and the top 3 genes from the single-cell RNA analysis were associated with COPD-related pathways. Molecular docking with the UMB showed strong binding affinities, indicating its potential to inhibit these pathways and serve as a therapeutic option for COPD. The MD simulation confirmed stable binding, key interactions and structural flexibility.

The molecular dynamics (MD) method is a promising approach toward elucidating the molecular mechanisms of intrinsically disordered regions (IDRs) of proteins and their fuzzy complexes. This mini-review introduces recent studies that apply MD simulations to investigate the molecular recognition of IDRs. Firstly, methodological issues by which MD simulations treat IDRs, such as developing force fields, treating periodic boundary conditions, and enhanced sampling approaches, are discussed. Then, several examples of the applications of MD to investigate molecular interactions of IDRs in terms of the two kinds of complex formations; coupled-folding and binding and fuzzy complex. MD simulations provide insight into the molecular mechanisms of these binding processes by sampling conformational ensembles of flexible IDRs. In particular, we focused on all-atom explicit-solvent MD simulations except for studies of higher-order assembly of IDRs. Recent advances in MD methods, and computational power make it possible to dissect the molecular details of realistic molecular systems involving the dynamic behavior of IDRs.

An open and a closed conformation of a surface loop in PhaZ7 extracellular poly(3-hydroxybutyrate) depolymerase were identified in two high-resolution crystal structures of a PhaZ7 Y105E mutant. Molecular dynamics (MD) simulations revealed high root mean square fluctuations (RMSF) of the 281-295 loop, in particular at residue Asp289 (RMSF 7.62 Å). Covalent docking between a 3-hydroxybutyric acid trimer and the catalytic residue Ser136 showed that the binding energy of the substrate is significantly more favorable in the open loop conformation compared to that in the closed loop conformation. MD simulations with the substrate covalently bound depicted 1 Å RMSF higher values for the residues 281-295 in comparison to the apo (substrate-free) form. In addition, the presence of the substrate in the active site enhanced the ability of the loop to adopt a closed form. Taken together, the analysis suggests that the flexible loop 281-295 of PhaZ7 depolymerase can act as a lid domain to control substrate access to the active site of the enzyme. Proteins 2017; 85:1351-1361. © 2017 Wiley Periodicals, Inc.

Molecular dynamics (MD) simulations of six upgraded empirical force fields were compared and evaluated with short peptides, intrinsically disordered proteins, and folded proteins using trajectories of 1, 1.5, 5, or 10 μs (five replicates of 200 ns, 300 ns, 1 μs, or 2 μs) for each system. Previous studies have shown that different force fields, water models, simulation methods, and parameters can affect simulation outcomes. Here, the MD simulations were done in an explicit solvent with RS-peptide, HEWL19, HIV-rev, β amyloid (Aβ)-40, Aβ-42, phosphodiesterase-γ, CspTm, and ubiquitin using ff99IDPs, ff14IDPs, ff14IDPSFF, ff03w, CHARMM36m, and CHARMM22* force fields. The IDP ensembles generated by six all-atom empirical force fields were compared against NMR data. Despite using identical starting structures and simulation parameters, ensembles obtained with different force fields exhibit significant differences in NMR RMDs, secondary structure contents, and global properties such as the radius of gyration. The intrinsically disordered protein (IDP)-specific force fields could substantially reproduce the experimental observables in force field comparison: they have the lowest error in chemical shifts and J-couplings for short peptides/proteins, reasonably well for large IDPs and reasonably well with the radius of gyration. A high population of disorderness was observed in the IDP-specific force field for the IDP ensemble with a fraction of β sheets for β-amyloids. CHARMM22* performs better for many observables; however, it still has a preference toward the helicity for short peptides. The results of β-amyloid 42 starting from two different initial structures (Aβ421Z0Q and Aβ42model) were also compared with DSSP and NMR data. The results obtained with IDP-specific force fields within 2 μs simulation time are similar, even though starting from different structures. The current force fields perform equally well for folded proteins. The results of currently developed or modified force fields for IDPs are capable of enlightening the overall performance of the force field for disordered as well as folded proteins, thereby contributing to force field development.

Developing a Protocol for Ensemble and Vibrational Probe-Containing Molecular Dynamics Simulations of the Nipah Ntail-XD Complex

Measuring Disorder and Dynamical Properties of FG-Nucleoporins

Structure and dynamic studies of lunatic, manic and radical fringe