Dehalogenases continue to garner interest of the scientific community due to their potential applications in bioremediation of halogen-contaminated environment and in synthesis of various industrially relevant products. Example of such enzymes is DehL, an L-2-haloacid dehalogenase (EC 3.8.1.2) from Rhizobium sp. RC1 that catalyses the specific cleavage of halide ion from L-2-halocarboxylic acids to produce the corresponding D-2-hydroxycarboxylic acids. Recently, the catalytic residues of DehL have been identified and its catalytic mechanism has been fully elucidated. However, the enantiospecificity determinants of the enzyme remain unclear. This information alongside a well-defined catalytic mechanism are required for rational engineering of DehL for substrate enantiospecificity. Therefore, using quantum mechanics/molecular mechanics and molecular mechanics Poisson-Boltzmann surface area calculations, the current study theoretically investigated the molecular basis of DehL enantiospecificity. The study found that R51L mutation cancelled out the dehalogenation activity of DehL towards it natural substrate, L-2-chloropropionate. The M48R mutation, however introduced a new activity towards D-2-chloropropionate, conveying the possibility of inverting the enantiospecificity of DehL from L-to d-enantiomer with a minimum of two simultaneous mutations. The findings presented here will play important role in the rational design of DehL dehalogenase for improving substrate utility.
Recent developments in the target based cancer therapies have identified HSF1 as a novel non oncogenic drug target. The present study delineates the design and molecular docking evaluation of Rohinitib (RHT) - Cantharidin (CLA) based novel HSF1 inhibitors for target-based cancer therapy. Here, we exploited the pharmacophoric features of both the parent ligands for the design of novel hybrid HSF1 inhibitors. The RHT-CLA ligands were designed and characterized for ADME/Tox features, interaction with HSF1 DNA binding domain and their pharmacophoric features essential for interaction. From the results, amino acid residues Ala17, Phe61, His63, Asn65, Ser68, Arg71 and Gln72 were found crucial for HSF1 interaction with the Heat shock elements (HSE). The hybrid ligands had better affinity towards the HSF1 DNA binding domain, in comparison to RHT or CLA and interacted with most of the active site residues. Additionally, the HSF1-ligand complex had a reduced affinity towards HSE in comparison to native HSF1. Based on the results, ligand RC15 and RC17 were non carcinogenic, non mutagenic, completely biodegradable under aerobic conditions, had better affinity for HSF1 (1.132 and 1.129 folds increase respectively) and diminished the interaction of HSF1 with HSE (1.203 and 1.239 folds decrease respectively). The simulation analysis also suggested that the ligands formed a stable complex with HSF1, restraining the movement of active site residues. In conclusion, RHT-CLA hybrid ligands can be used as a potential inhibitor of HSF1 for non-oncogene target based cancer therapy.
Aptamers are short oligonucleotides that possess high specificity and affinity against their target. Generated via Systematic Evolution of Ligands by Exponential Enrichment, (SELEX) in vitro, they were screened and enriched. This review covering the study utilizing bioinformatics tools to analyze primary sequence, secondary and tertiary structure prediction, as well as docking simulation for various aptamers and their ligand interaction. Literature was pooled from Web of Science (WoS) and Scopus databases until December 18, 2020 using specific search string related to DNA aptamers, in silico, structure prediction, and docking simulation. Out of 330 published articles, 38 articles were assessed in the analysis based on the predefined inclusion and exclusion criteria. It was found that Mfold and RNA Composer web server is the most popular tool in secondary and tertiary structure prediction of DNA aptamers, respectively. Meanwhile, in docking simulation, ZDOCK and AutoDock are preferred to analyze binding interaction in the aptamer-ligand complex. This review reports a brief framework of recent developments of in silico approaches that provide predictive structural information of ssDNA aptamer.
Effective novel peptide inhibitors which targeted the domain III of the dengue envelope (E) protein by blocking dengue virus (DENV) entry into target cells, were identified. The binding affinities of these peptides towards E-protein were evaluated by using a combination of docking and explicit solvent molecular dynamics (MD) simulation methods. The interactions of these complexes were further investigated by using the Molecular Mechanics-Poisson Boltzmann Surface Area (MMPBSA) and Molecular Mechanics Generalized Born Surface Area (MMGBSA) methods. Free energy calculations of the peptides interacting with the E-protein demonstrated that van der Waals (vdW) and electrostatic interactions were the main driving forces stabilizing the complexes. Interestingly, calculated binding free energies showed good agreement with the experimental dissociation constant (Kd) values. Our results also demonstrated that specific residues might play a crucial role in the effective binding interactions. Thus, this study has demonstrated that a combination of docking and molecular dynamics simulations can accelerate the identification process of peptides as potential inhibitors of dengue virus entry into host cells.
Protein-ligand binding free energy values of wild-type and mutant C-terminal domain of Escherichia coli arginine repressor (ArgRc) protein systems bound to L-arginine or L-citrulline molecules were calculated using the linear interaction energy (LIE) method by molecular dynamics (MD) simulation. The binding behaviour predicted by the dissociation constant (K(d)) calculations from the binding free energy values showed preferences for binding of L-arginine to the wild-type ArgRc but not to the mutant ArgRc(D128N). On the other hand, L-citrulline do not favour binding to wild-type ArgRc but prefer binding to mutant ArgRc(D128N). The dissociation constant for the wild-type ArgRc-L-arginine complex obtained in this study is in agreement with reported experimental results. Our results also support the experimental data for the binding of L-citrulline to the mutant ArgRc(D128N). These showed that LIE method for protein-ligand binding free energy calculation could be applied to the wild-type and the mutant E. coli ArgRc-L-arginine and ArgRc-L-citrulline protein-ligand complexes and possibly to other transcriptional repressor-co-repressor systems as well.
Carbon nanotubes (CNTs) have received enormous attention due to their fascinating properties to be used in various applications including electronics, sensing, energy storage and conversion. The first principles calculations within density functional theory (DFT) have been carried out in order to investigate the structural, electronic and optical properties of un-doped and doped CNT nanostructures. O2, CO2, and CH3OH have been chosen as gas molecules to study the adsorption properties based on zigzag (8,0) SWCNTs. The results demonstrate that the adsorption of O2, CO2, and CH3OH gas molecules on pristine, Si-doped and B-doped SWCNTs are either physisorption or chemisorption. Moreover, the electronic properties indicating SWCNT shows significant improvement toward gas adsorption which provides the impact of selecting the best gas sensor materials towards detecting gas molecule. Therefore, these pristine, Si-, and B-doped SWCNTs can be considered to be very good potential candidates for sensing application.
Transthyretin (TTR) mediated amyloidosis is a highly ruinous illness that affects various organs by aggravating the deposition of misfolded or mutated TTR protein aggregates in tissues. Hence, hindering the formation of TTR amyloid aggregates could be a key strategy in finding an effective cure towards the aggravating disorder. In this analysis, we examined the subversive nature of point mutation, V30M, in TTR that promotes amyloidogenicity using discrete molecular dynamics (DMD) simulations. Besides, we probed the association of naturally occurring polyphenols: EGCG (a proven anti TTR aggregation agent as positive control), resveratrol and curcumin in mitigating the pathogenic repercussions of mutant TTR. Results from the computational studies endorsed that the resveratrol constitutes a restorative potential to subjugate TTR mediated amyloidosis, besides EGCG. Hence, this study could be a reminiscent aspect in understanding the inhibitory role of key polyphenols against the mutant TTR aggregates, which could be an aid towards structure-based drug design in the upcoming research era on familial amyloid disorders.
In the present study, we use the state of art density functional theory (DFT) techniques to calculate the structural, optoelectronic and nonlinear optical (NLO) properties for two novel chalcone derivatives. The geometrical structures of chalcone derivatives compound 1 and 2 are optimized using periodic boundary conditions (PBC) in solid-state phase as well as isolated single molecular geometry in the gas phase. The reasonable agreement is found among experimental, solid-state and gas phase single molecular geometries, which provide us, further confidence to explore the potential of above-entitled derivatives as good functional materials for electro-optical applications. For instance, the frequency dependent real parts of dielectric functions are calculated for compound 1 and 2. The maximum value of real part of the dielectric function for compound 1 and 2 at 0eV are computed as 4.35 and 6.68 for the polarization vectors of (001) directions, respectively, which reveals the fact that the compound 1 and 2 might be good charge transport materials. The reflectivities of the compound 1 and 2 are 0.64 and 0.45 revealing that the compound 2 might be more efficient material for organic photovoltaic (OPV) applications. The results of the refractive index improved by doping the strong electron withdrawing groups (EWGs) shows that the compound 2 might be good refractor of the photon as compared to compound 1. The calculated values for static second-order polarizability are 3498 and 10464 a. u. and for frequency dependent second harmonic generations are 2557 and 6429 a. u. for compound 1 and 2, respectively, which indicates their significant potential for possible nonlinear optical applications.
Structure-based virtual screening offers a good opportunity for the discovery of selective M1 muscarinic acetylcholine receptor (mAChR) agonists for the treatment of Alzheimer's disease. However, no 3-D structure of an M1 mAChR is yet available and the homology models that have been previously reported are only able to identify antagonists in virtual screening experiments. In this study, we generated a homology model of the human M1 mAChR, based on the crystal structure of an M3 mAChR as the template. This initial model was modified, using the agonist-bound crystal structure of a β2-adrenergic receptor as a guide, to give two possible activated structures. The T192 side chain was adjusted in both structures and one of the structures also had the whole of transmembrane (TM) 5 rotated and tilted toward the inner channel of the transmembrane region. The binding sites of all three structures were then refined by induced-fit docking (IFD) with acetylcholine. Virtual screening experiments showed that all three refined models could efficiently differentiate agonists from decoy molecules, with the TM5-modified models also giving good agonist/antagonist selectivity. The whole range of agonists and antagonists was observed to bind within the orthosteric site of the structure obtained by IFD refinement alone, implying that it has inactive state character. In contrast, the two TM5-modified structures were unable to accommodate the antagonists, supporting the proposition that they possess activated state character.
The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test.
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.
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.
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.
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.
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.
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.
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.
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.
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.