Recent evidence from in vitro and in vivo studies has shown that anthocyanins and anthocyanidins can reduce and inhibit the amyloid beta (Aβ) species, one of the hallmarks of Alzheimer's disease (AD). However, their inhibition mechanisms on Aβ species at molecular details remain elusive. Therefore, in the present study, molecular modelling methods were employed to investigate their inhibitory mechanisms on Aβ(1-42) peptide. The results highlighted that anthocyanidins effectively inhibited the conformational transitions of helices into beta-sheet (β-sheet) conformation within Aβ(1-42) peptide by two different mechanisms: 1) the obstruction of two terminals from coming into contact due to the binding of anthocyanidins with residues of N- and second hydrophobic core (SHC)-C-terminals, and 2) the prevention of the folding process due to the binding of anthocyanidin with the central polar (Asp23 and Lys28) and native helix (Asp23, Lys28, and Leu34) residues. These new findings on the inhibition of β-sheet formation by targeting both N- and SHC-C-terminals, and the long-established target, D23-K28 salt bridge residues, not with the conventional central hydrophobic core (CHC) as reported in the literature, might aid in designing more potent inhibitors for AD treatment.
Dehalogenase E (DehE) is a non-stereospecific enzyme produced by the soil bacterium, Rhizobium sp. RC1. Till now, the catalytic mechanism of DehE remains unclear although several literature concerning its structure and function are available. Since DehE is non-stereospecific, the enzyme was hypothesized to follow a 'direct attack mechanism' for the catalytic breakdown of a haloacid. For a molecular insight, the DehE modelled structure was docked in silico with the substrate 2-chloropropionic acid (2CP) in the active site. The ideal position of DehE residues that allowed a direct attack mechanism was then assessed via molecular dynamics (MD) simulation. It was revealed that the essential catalytic water was hydrogen bonded to the 'water-bearer', Asn114, at a relatively constant distance of ∼2.0 Å after 50 ns. The same water molecule was also closely sited to the catalytic Asp189 at an average distance of ∼2.0 Å, signifying the imperative role of the latter to initiate proton abstraction for water activation. This reaction was crucial to promote a direct attack on the α-carbon of 2CP to eject the halide ion. The water molecule was oriented favourably towards the α-carbon of 2CP at an angle of ∼75°, mirrored by the formation of stable enzyme-substrate orientations throughout the simulation. The data therefore substantiated that the degradation of a haloacid by DehE followed a 'direct attack mechanism'. Hence, this study offers valuable information into future advancements in the engineering of haloacid dehalogenases with improved activity and selectivity, as well as functionality in solvents other than water.
The pathogenic dengue virus (DV) is a growing global threat, particularly in South East Asia, for which there is no specific treatment available. The virus possesses a two-component (NS2B/NS3) serine protease that cleaves the viral precursor proteins. Here, we performed molecular dynamics simulations of the NS2B/NS3 protease complexes with six peptide substrates (capsid, intNS3, 2A/2B, 4B/5, 3/4A and 2B/3 containing the proteolytic site between P(1) and P(1)' subsites) of DV type 2 to compare the specificity of the protein-substrate binding recognition. Although all substrates were in the active conformation for cleavage reaction by NS2B/NS3 protease, their binding strength was somewhat different. The simulated results of intermolecular hydrogen bonds and decomposition energies suggested that among the ten substrate residues (P(5)-P(5)') the P(1) and P(2) subsites play a major role in the binding with the focused protease. The arginine residue at these two subsites was found to be specific preferential binding at the active site with a stabilization energy of intNS3>2A/2B>4B/5>3/4A>2B/3 in a relative correspondence with previous experimentally derived values.
Conformational search for the most stable geometry connection of 16 sets of polydopamine (PDA) tetramer subunits has been systematically investigated using density functional theory (DFT) calculations. Our results indicated that the more planar subunits are, the more stable they are. This finding is in good agreement with recent experimental observations, which have suggested that PDA are composed of the nearly planar subunits that appear to be stacked together via the π-π interactions to form graphite-like layered aggregates associated with the balance of the intramolecular hydrogen bonds and steric effects from the indole and catechol moieties. Molecular dynamics (MD) simulations of 16 spherical clusters of the tetramer subunits of PDA in the gas and aqueous phase were performed at 298 K and confirmed the stability of supramolecular tetramer aggregates. The complex formation and binding energy of all 16 clusters are very strong although the shapes of the clusters in aqueous solution are not spherical and are very much different from those in the gas phase. The aggregations of all 16 clusters in aqueous solution were also confirmed from the profiles of the Kratky plot and the radius of gyration of all clusters. Our MD results in both gas phase and aqueous solution pointed out that there are high possibilities of aggregations of the 16 kinds of tetramer subunits although the conformations of each tetramer subunit are not flat. In summary, this work brings an insight into the controversial structure of PDA tetramer units and explains some of the important structural features found in the aqueous phase in comparison to the gas phase.
The utilization of cold active lipases in organic solvents proves an excellent approach for chiral synthesis and modification of fats and oil due to the inherent flexibility of lipases under low water conditions. In order to verify whether this lipase can function as a valuable synthetic catalyst, the mechanism concerning activation of the lid and interacting solvent residues in the presence of organic solvent must be well understood. A new alkaline cold-adapted lipase, AMS8, from Pseudomonas fluorescens was studied for its structural adaptation and flexibility prior to its exposure to non-polar, polar aprotic and protic solvents. Solvents such as ethanol, toluene, DMSO and 2-propanol showed to have good interactions with active sites. Asparagine (Asn) and tyrosine (Tyr) were key residues attracted to solvents because they could form hydrogen bonds. Unlike in other solvents, Phe-18, Tyr-236 and Tyr-318 were predicted to have aromatic-aromatic side-chain interactions with toluene. Non-polar solvent also was found to possess highest energy binding compared to polar solvents. Due to this circumstance, the interaction of toluene and AMS8 lipase was primarily based on hydrophobicity and molecular recognition. The molecular dynamic simulation showed that lid 2 (residues 148-167) was very flexible in toluene and Ca(2+). As a result, lid 2 moves away from the catalytic areas, leaving an opening for better substrate accessibility which promotes protein activation. Only a single lid (lid 2) showed the movement following interactions with toluene, although AMS8 lipase displayed double lids. The secondary conformation of AMS8 lipase that was affected by toluene observed a reduction of helical strands and increased coil structure. Overall, this work shows that cold active lipase, AMS8 exhibits distinguish interfacial activation and stability in the presence of polar and non-polar solvents.
Fused tricyclic organic compounds are an important class of organic electronic materials. In designing molecules for organic electronics, knowing what chemical structure that be used to tune the molecular property is one of the keys that can help to improve the material performance. In this research, we applied machine learning and data analytic approaches in addressing this problem. The energy states (Lowest Unoccupied Molecular Orbital (HOMO), Highest Occupied Molecular Orbitals (LUMO), singlet (Es) and triplet (ET) energy) of more than 10 thousand fused tricyclics are calculated. Corresponding descriptors are also generated. We find that the Coulomb matrix is a poorer descriptor than high-level descriptors in a multilayer perceptron neural network. Correlations as high as 0.95 is obtained using a multilayer perceptron neural network with Mean Absolute Error as low as 0.08 eV. The descriptors that are important in tuning the energy levels are revealed using the Random Forest algorithm. Correlations of such descriptors are also plotted. We found that the higher the number of tertiary amines, the deeper are the HOMO and LUMO levels. The presence of NN in the aromatic rings can be used to tune the ES. However, there is no single dominant descriptor that can be correlated with the ET. A collection of descriptors is found to give a far better correlation with ET. This research demonstrated that machine learning and data analytics in guiding how certain chemical substructures correlate with the molecule energy states.
Full Heuslers alloys are a fascinating class of materials leading to many technological applications. These have been studied widely under ambient conditions. However, less attention been paid to study them under the effect of compression and strain. Here in this work Co2YZ (Y= Cr, Nb, Ta, V and Z = Al, Ga) Heusler alloys have been studied comprehensively under pressure variations. Calculated lattice constants are in reasonable agreement with the available data. It is determined that lattice constant deceases with the increase in tensile stress and increases by increasing pressure in reverse direction. Band profiles reveals the half metallic nature of the studied compounds. The bond length decreases while band gap increases in compressive strain. The compounds are found to be reflective in visible region, as characteristics of the metals. The magnetic moments reveal the half-mettalic ferromagnetic nature of the compounds.
Structural parameters, electronic structure and optical properties of the dialkali metal monotelluride M2Te (M = Li, Na, K and Rb) compounds in the cubic antifluorite structure were investigated via ab initio calculations using the all electron linearized augmented plane wave approach based on density functional theory with and without including spin-orbit coupling (SOC). The exchange-correlation interactions were described within the PBEsol version of the generalized gradient approximation and Tran-Blaha modified Becke-Johnson potential (TB-mBJ). Optimized equilibrium lattice parameters are in excellent accordance with existing measured ones. Computed energy band dispersions show that the studied compounds are large band gap materials. Inclusion of SOC reduces the band gap value compared to the corresponding one calculated without including SOC. Determination of the energy band character and interatomic bonding nature are performed using the densities of states diagrams and charge density distribution map. Linear optical function spectra are predicted for a wide energy range and the origin of the dielectric function spectrum peaks are determined.
Xylitol is a high-value low-calorie sweetener used as sugar substitute in food and pharmaceutical industry. Xylitol phosphate dehydrogenase (XPDH) catalyses the conversion of d-xylulose 5-phosphate (XU5P) and d-ribulose 5-phosphate (RU5P) to xylitol and ribitol respectively in the presence of nicotinamide adenine dinucleotide hydride (NADH). Although these enzymes have been shown to produce xylitol and ribitol, there is an incomplete understanding of the mechanism of the catalytic events of these reactions and the detailed mechanism has yet to be elucidated. The main goal of this work is to analyse the conformational changes of XPDH-bound ligands such as zinc, NADH, XU5P, and RU5P to elucidate the key amino acids involved in the substrate binding. In silico modelling, comparative molecular dynamics simulations, interaction analysis and conformational study were carried out on three XPDH enzymes of the Medium-chain dehydrogenase (MDR) family in order to elucidate the atomistic details of conformational transition, especially on the open and closed state of XPDH. The analysis also revealed the possible mechanism of substrate specificity that are responsible in the catalyse hydride transfer are the residues His58 and Ser39 which would act as the proton donor for reduction of XU5P and RU5P respectively. The structural comparison and MD simulations displayed a significant difference in the conformational dynamics of the catalytic and coenzyme loops between Apo and XPDH-complexes and highlight the contribution of newly found triad residues. This study would assist future mutagenesis study and enzyme modification work to increase the catalysis efficiency of xylitol production in the industry.
The allosteric pocket of the Dengue virus (DENV2) NS2B/NS3 protease, which is proximal to its catalytic triad, represents a promising drug target (Othman et al., 2008). We have explored this binding site through large-scale virtual screening and molecular dynamics simulations followed by calculations of binding free energy. We propose two mechanisms for enzyme inhibition. A ligand may either destabilize electronic density or create steric effects relating to the catalytic triad residues NS3-HIS51, NS3-ASP75, and NS3-SER135. A ligand may also disrupt movement of the C-terminal of NS2B required for inter-conversion between the "open" and "closed" conformations. We found that chalcone and adenosine derivatives had the top potential for drug discovery hits, acting through both inhibitory mechanisms. Studying the molecular mechanisms of these compounds might be helpful in further investigations of the allosteric pocket and its potential for drug discovery.
A Laplacian scoring algorithm for gene selection and the Gini coefficient to identify the genes whose expression varied least across a large set of samples were the state-of-the-art methods used here. These methods have not been trialed for their feasibility in cheminformatics. This was a maiden attempt to investigate a complete comparative analysis of an anthraquinone and chalcone derivatives-based virtual combinatorial library. This computational "proof-of-concept" study illustrated the combinatorial approach used to explain how the structure of the selected natural products (NPs) undergoes molecular diversity analysis. A virtual combinatorial library (1.6 M) based on 20 anthraquinones and 24 chalcones was enumerated. The resulting compounds were optimized to the near drug-likeness properties, and the physicochemical descriptors were calculated for all datasets including FDA, Non-FDA, and NPs from ZINC 15. UMAP and PCA were applied to compare and represent the chemical space coverage of each dataset. Subsequently, the Laplacian score and Gini coefficient were applied to delineate feature selection and selectivity among properties, respectively. Finally, we demonstrated the diversity between the datasets by employing Murcko's and the central scaffolds systems, calculating three fingerprint descriptors and analyzing their diversity by PCA and SOM. The optimized enumeration resulted in 1,610,268 compounds with NP-Likeness, and synthetic feasibility mean scores close to FDA, Non-FDA, and NPs datasets. The overlap between the chemical space of the 1.6 M database was more prominent than with the NPs dataset. A Laplacian score prioritized NP-likeness and hydrogen bond acceptor properties (1.0 and 0.923), respectively, while the Gini coefficient showed that all properties have selective effects on datasets (0.81-0.93). Scaffold and fingerprint diversity indicated that the descending order for the tested datasets was FDA, Non-FDA, NPs and 1.6 M. Virtual combinatorial libraries based on NPs can be considered as a source of the combinatorial compound with NP-likeness properties. Furthermore, measuring molecular diversity is supposed to be performed by different methods to allow for comparison and better judgment.
Ebola virus is a lipid-enveloped filamentous virus that affects human and non-human primates and consists of several types of protein: nucleoprotein, VP30, VP35, L protein, VP40, VP24, and transmembrane glycoprotein. Among the Ebola virus proteins, its matrix protein VP40 is abundantly expressed during infection and plays a number of critical roles in oligomerization, budding and egress from the host cell. VP40 exists predominantly as a monomer at the inner leaflet of the plasma membrane, and has been suggested to interact with negatively charged lipids such as phosphatidylinositol 4,5-bisphosphate (PIP2) and phosphatidylserine (PS) via its cationic patch. The hydrophobic loop at the C-terminal domain has also been shown to be important in the interaction between the VP40 and the membrane. However, details of the molecular mechanisms underpinning their interactions are not fully understood. This study aimed at investigating the effects of mutation in the cationic patch and hydrophobic loop on the interaction between the VP40 monomer and the plasma membrane using coarse-grained molecular dynamics simulation (CGMD). Our simulations revealed that the interaction between VP40 and the plasma membrane is mediated by the cationic patch residues. This led to the clustering of PIP2 around the protein in the inner leaflet as a result of interactions between some cationic residues including R52, K127, K221, K224, K225, K256, K270, K274, K275 and K279 and PIP2 lipids via electrostatic interactions. Mutation of the cationic patch or hydrophobic loop amino acids caused the protein to bind at the inner leaflet of the plasma membrane in a different orientation, where no significant clustering of PIP2 was observed around the mutated protein. This study provides basic understanding of the interaction of the VP40 monomer and its mutants with the plasma membrane.
Maltogenic amylase (MAG1) from Bacillus lehensis G1 displayed the highest hydrolysis activity on β-cyclodextrin (β-CD) to produce maltose as a main product and exhibited high transglycosylation activity on malto-oligosaccharides with polymerization degree of three and above. These substrate and product specificities of MAG1 were elucidated from structural point of view in this study. A three-dimensional structure of MAG1 was constructed using homology modeling. Docking of β-CD and malto-oligosaccharides was then performed in the MAG1 active site. An aromatic platform in the active site was identified which is responsible in substrate recognition especially in determining the enzyme's preference toward β-CD. Molecular dynamics (MD) simulation showed MAG1 structure is most stable when docked with β-CD and least stable when docked with maltose. The docking analysis and MD simulation showed that the main subsites for substrate stabilization in the active site are -2, -1, +1 and +2. A bulky residue, Trp359 at the +2 subsite was identified to cause steric interference to the bound linear malto-oligosaccharides thus prevented it to occupy subsite +3, which can only be reached by a highly bent glucose molecule such as β-CD. The resulted modes of binding from docking simulation show a good correlation with the experimentally determined hydrolysis pattern. The subsite structure generated from this study led to a possible mode of action that revealed how maltose was mainly produced during hydrolysis. Furthermore, maltose only occupies subsite +1 and +2, therefore could not be hydrolyzed or transglycosylated by the enzyme. This important knowledge has paved the way for a novel structure-based molecular design for modulation of its catalytic activities.
Critical to the applications of proteins in non-aqueous enzymatic processes is their structural dynamics in relation to solvent polarity. A pool of mutants derived from Geobacillus zalihae T1 lipase was screened in organic solvents (methanol, ethanol, propanol, butanol and pentanol) resulting in the selection of six mutants at initial screening (A83D/K251E, R21C, G35D/S195 N, K84R/R103C/M121I/T272 M and R106H/G327S). Site-directed mutagenesis further yielded quadruple mutants A83D/M121I/K251E/G327S and A83D/M121I/S195 N/T272 M, both of which had improved activity after incubation in methanol. The km and kcat values of these mutants vary marginally with the wild-type enzyme in the methanol/substrate mixture. Thermally induced unfolding of mutants was accompanied with some loss of secondary structure content. The root mean square deviations (RMSD) and B-factors revealed that changes in the structural organization are intertwined with an interplay of the protein backbone with organic solvents. Spatially exposed charged residues showed correlations between the solvation dynamics of the methanol solvent and the hydrophobicity of the residues. The short distances of the radial distribution function provided the required distances for hydrogen bond formation and hydrophobic interactions. These dynamic changes demonstrate newly formed structural interactions could be targeted and incorporated experimentally on the basis of solvent mobility and mutant residues.
GPCR crystal structures have become more readily accessible in recent years. However, homology models of GPCRs continue to play an important role as many GPCR structures remain unsolved. The new crystal structures now available provide not only additional templates for homology modelling but also the opportunity to assess the performance of homology models against their respective crystal structures and gain insight into the performance of such models. In this study we have constructed homology models from templates of various transmembrane sequence identities for eight GPCR targets to better understand the relationship between transmembrane sequence identity and model quality. Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening. Crystal structures significantly outperformed homology models in both assessments. Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking. In virtual screening using homology models still conferred significant enrichment compared to random selection, with a clear benefit also observed in using models optimized through induced fit docking. Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications.
De novo approach was applied to design single chain fragment variable (scFv) for BmR1, a recombinant antigen from Bm17DIII gene which is the primary antigen used for the detection of anti-BmR1 IgG4 antibodies in the diagnostic of lymphatic filariasis. Three epitopes of the BmR1 was previously predicted form an ab initio derived three-dimensional structure. A collection of energetically favourable conformations was generated via hot-spot-centric approach. This resulted in a set of three different scFv scaffolds used to compute the high shape complementary conformations via dock-and-design approach with the predicted epitopes of BmR1. A total of 4227 scFv designs were generated where 200 scFv designs produced binding energies of less than -20 R.E.U with shape complementarity higher than 0.5. We further selected the design with at least one hydrogen bond and one salt bridge with the epitope, thus resulted in a total of 10, 1 and 19 sFv designs for epitope 1, 2 and 3, respectively. The results thus showed that de novo design can be an alternative approach to yield high affinity in silico scFv designs as a starting point for antibody or specific binder discovery processes.
Protein arginine methyltransferases (PRMTs) catalyse the methylation of arginine residues of target proteins. PRMTs utilise S-adenosyl methionine (SAM) as the methyl group donor, leading to S-adenosyl homocysteine (SAH) and monomethylarginine (mMA). A combination of homology modelling, molecular docking, Active Site Pressurisation, molecular dynamic simulations and MM-PBSA free energy calculations is used to investigate the binding poses of three PRMT1 inhibitors (ligands 1-3), which target both SAM and substrate arginine binding sites by containing a guanidine group joined by short linkers with the SAM derivative. It was assumed initially that the adenine moieties of the inhibitors would bind in sub-site 1 (PHE44, GLU137, VAL136 and GLU108), the guanidine side chain would occupy sub-site 2 (GLU 161, TYR160, TYR156 and TRP302), with the amino acid side chain occupying sub-site 3 (GLU152, ARG62, GLY86 and ASP84; pose 1). However, the SAH homocysteine moiety does not fully occupy sub-site 3, suggesting another binding pose may exist (pose 2), whereby the adenine moiety binds in sub-site 1, the guanidine side chain occupies sub-site 3, and the amino acid side chain occupies sub-site 2. Our results indicate that ligand 1 (pose 1 or 2), ligand 2 (pose 2) and ligand 3 (pose 1) are the predominant binding poses and we demonstrate for the first time that sub-site 3 contains a large space that could be exploited in the future to develop novel inhibitors with higher binding affinities.
DNA polymerase β is a 39kDa enzyme that is a major component of Base Excision Repair in human cells. The enzyme comprises two major domains, a 31kDa domain responsible for the polymerase activity and an 8kDa domain, which bind ssDNA and has a deoxyribose phosphate (dRP) lyase activity. DNA polymerase β was shown to be phosphorylated in vitro with protein kinase C (PKC) at serines 44 and 55 (S44 and S55), resulting in loss of its polymerase enzymic activity, but not its ability to bind ssDNA. In this study, we investigate the potential phosphorylation-induced structural changes for DNA polymerase β using molecular dynamics. The simulations show drastic conformational changes of the polymerase structure as a result of S44 phosphorylation. Phosphorylation-induced conformational changes transform the closed (active) enzyme structure into an open one. Further analysis of the results points to a key hydrogen bond and newly formed salt bridges as potential drivers of these structural fluctuations. The changes observed with S44/55 and S55 phosphorylation were less dramatic than S44 and the integrity of the H-bond was not compromised. Thus the phosphorylation of S44 is likely the major contributor to structural fluctuations that lead to loss of enzymatic activity.
DNA polymerase β is a 39 kDa enzyme that is a major component of Base Excision Repair in human cells. The enzyme comprises two major domains, a 31 kDa domain responsible for the polymerase activity and an 8 kDa domain, which bind ssDNA and has a deoxyribose phosphate (dRP) lyase activity. DNA polymerase β was shown to be phosphorylated in vitro with protein kinase C (PKC) at serines 44 and 55 (S44 and S55), resulting in loss of its polymerase enzymic activity, but not its ability to bind ssDNA. In this study, we investigate the potential phosphorylation-induced structural changes for DNA polymerase β using molecular dynamics simulations. The simulations show drastic conformational changes of the polymerase structure as a result of S44 phosphorylation. Phosphorylation-induced conformational changes transform the closed (active) enzyme structure into an open one. Further analysis of the results points to a key hydrogen bond and newly formed salt bridges as potential drivers of these structural fluctuations. The changes observed with S55/44 and S55 phosphorylation were less dramatic and the integrity of the H-bond was not compromised. Thus the phosphorylation of S44 is the major contributor to structural fluctuations that lead to loss of enzymatic activity.
Metal nanoclusters have been considered as a new class of chemical sensors due to their unique electronic structures and the particular physicochemical properties. The interaction of N2 molecule with neutral and ionic magnesium nanoclusters Mg17q(q=0,±1), as well as neutral magnesium nanoclusters with the centrality of beryllium and calcium Mg16M (M=Be, Mg, and Ca) have been investigated using CAM-B3LYP/6-311+G(d) level of theory in the gas phase. The electronic properties of magnesium nanoclusters were significantly affected by the adsorption of N2 molecule. The NBO analysis revealed a charge transfer from the adsorbed N2 molecule to the nanocluster. Based on the adsorption energies and enthalpies, a thermodynamically favorable chemisorption process was predicted for the Mg16Ca-N2 complex. The negative value of the Gibbs free energy of Mg16Ca-N2 confirmed the spontaneous adsorption process. The estimated recovery time for Mg16Ca-N2 complex for 8-MR (0.089 s) and 4-MRs (0.075 s) illustrated a possible desorption process for N2 molecule from the surface of Mg16Ca. Our finding also revealed the Mg16Ca has the ability to use as a sensor for detection and absorption of N2 molecule.