Increased reports of oseltamivir (OTV)-resistant strains of the influenza virus, such as the H274Y mutation on its neuraminidase (NA), have created some cause for concern. Many studies have been conducted in the attempt to uncover the mechanism of OTV resistance in H274Y NA. However, most of the reported studies on H274Y focused only on the drug-bound system, so the direct effects of the mutation on NA itself prior to drug binding still remain unclear. Therefore, molecular dynamics simulations of NA in apo form, followed by principal component analysis and interaction energy calculations, were performed to investigate the structural changes of the NA binding site as a result of the H274Y mutation. It was observed that the disruption of the NA binding site due to the H274Y mutation was initiated by the repulsive effect of Y274 on the 250-loop, which in turn altered the hydrogen-bonding network around residue 274. The rotated W295 side chain caused the upward movement of the 340-loop. Consequently, sliding box docking results suggested that the binding pathway of OTV was compromised because of the disruption of this binding site. This study also highlighted the importance of the functional group at C6 of the sialic acid mimicry. It is hoped that these results will improve the understanding of OTV resistance and shed some light on the design of a novel anti-influenza drug.
Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.
Analysis of 300 ns (ns) molecular dynamics (MD) simulations of an adenosine A2a receptor (A2a AR) model, conducted in triplicate, in 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) and 1-palmitoyl-2-oleoylphosphatidylethanolamine (POPE) bilayers reveals significantly different protein dynamical behavior. Principal component analysis (PCA) shows that the dissimilarities stem from interhelical rather than intrahelical motions. The difference in the hydrophobic thicknesses of these simulated lipid bilayers is potentially a significant reason for the observed difference in results. The distinct lipid headgroups might also lead to different molecular interactions and hence different protein loop motions. Overall, the A2a AR shows higher mobility and flexibility in POPC as compared to POPE.
ProBiS is a new method to identify the binding site of protein through local structural alignment against the nonredundant Protein Data Bank (PDB), which may result in unique findings compared to the energy-based, geometry-based, and sequence-based predictors. In this work, binding sites of Hemagglutinin (HA), which is an important target for drugs and vaccines in influenza treatment, have been revisited by ProBiS. For the first time, the identification of conserved binding sites by local structural alignment across all subtypes and strains of HA available in PDB is presented. ProBiS finds three distinctive conserved sites on HA's structure (named Site 1, Site 2, and Site 3). Compared to other predictors, ProBiS is the only one that accurately defines the receptor binding site (Site 1). Apart from that, Site 2, which is located slightly above the TBHQ binding site, is proposed as a potential novel conserved target for membrane fusion inhibitor. Lastly, Site 3, located around Helix A at the stem domain and recently targeted by cross-reactive antibodies, is predicted to be conserved in the latest H7N9 China 2013 strain as well. The further exploration of these three sites provides valuable insight in optimizing the influenza drug and vaccine development.
The goal of consensus clustering methods is to find a consensus partition that optimally summarizes an ensemble and improves the quality of clustering compared with single clustering algorithms. In this paper, an enhanced voting-based consensus method was introduced and compared with other consensus clustering methods, including co-association-based, graph-based, and voting-based consensus methods. The MDDR and MUV data sets were used for the experiments and were represented by three 2D fingerprints: ALOGP, ECFP_4, and ECFC_4. The results were evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster using four criteria: F-measure, Quality Partition Index (QPI), Rand Index (RI), and Fowlkes-Mallows Index (FMI). The experiments suggest that the consensus methods can deliver significant improvements for the effectiveness of chemical structures clustering.
Molecular dynamics (MD) simulations of membrane-embedded G-protein coupled receptors (GPCRs) have rapidly gained popularity among the molecular simulation community in recent years, a trend which has an obvious link to the tremendous pharmaceutical importance of this group of receptors and the increasing availability of crystal structures. In view of the widespread use of this technique, it is of fundamental importance to ensure the reliability and robustness of the methodologies so they yield valid results and enable sufficiently accurate predictions to be made. In this work, 200 ns simulations of the A2a adenosine receptor (A2a AR) have been produced and evaluated in the light of these requirements. The conformational dynamics of the target protein, as obtained from replicate simulations in both the presence and absence of an inverse agonist ligand (ZM241385), have been investigated and compared using principal component analysis (PCA). Results show that, on this time scale, convergence of the replicates is not readily evident and dependent on the types of the protein motions considered. Thus rates of inter- as opposed to intrahelical relaxation and sampling can be different. When studied individually, we find that helices III and IV have noticeably greater stability than helices I, II, V, VI, and VII in the apo form. The addition of the inverse agonist ligand greatly improves the stability of all helices.
A Bayesian inference network (BIN) provides an interesting alternative to existing tools for similarity-based virtual screening. The BIN is particularly effective when the active molecules being sought have a high degree of structural homogeneity but has been found to perform less well with structurally heterogeneous sets of actives. In this paper, we introduce an alternative network model, called a Bayesian belief network (BBN), that seeks to overcome this limitation of the BIN approach. Simulated virtual screening experiments with the MDDR, WOMBAT and MUV data sets show that the BIN and BBN methods allow effective screening searches to be carried out. However, the results obtained are not obviously superior to those obtained using a much simpler approach that is based on the use of the Tanimoto coefficient and of the square roots of fragment occurrence frequencies.
This paper discusses the weighting of two-dimensional fingerprints for similarity-based virtual screening, specifically the use of weights that assign greatest importance to the substructural fragments that occur least frequently in the database that is being screened. Virtual screening experiments using the MDL Drug Data Report and World of Molecular Bioactivity databases show that the use of such inverse frequency weighting schemes can result, in some circumstances, in marked increases in screening effectiveness when compared with the use of conventional, unweighted fingerprints. Analysis of the characteristics of the various schemes demonstrates that such weights are best used to weight the fingerprint of the reference structure in a similarity search, with the database structures' fingerprints unweighted. However, the increases in performance resulting from such weights are only observed with structurally homogeneous sets of active molecules; when the actives are diverse, the best results are obtained using conventional, unweighted fingerprints for both the reference structure and the database structures.
Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in the Bayesian network are encoded using a set of conditional probability distributions, which can be estimated by the fragment weighting function, a function of the frequencies of the fragments in the molecule or the reference structure as well as throughout the collection. The weighting function combines one or more fragment weighting schemes. In this paper, we have investigated five different weighting functions and present a new fragment weighting scheme. Later on, these functions were modified to combine the new weighting scheme. Simulated virtual screening experiments with the MDL Drug Data Report (23) and maximum unbiased validation data sets show that the use of new weighting scheme can provide significantly more effective screening when compared with the use of current weighting schemes.
T1 lipase is isolated from the palm Geobacillus zalihae strain T1 in Malaysia, functioning as a secreted protein responsible for the catalyzing hydrolysis of long-chain triglycerides into fatty acids and glycerol at high temperatures. In the current study, using 30 ns molecular dynamics simulations at different temperatures, an aqueous activation was detected for T1 lipase. This aqueous activation in T1 lipase was mainly caused by a double-flap movement mechanism. The double flaps were constituted by the hydrophobic helices 6 and 9. Helix 6 employed two major components with the hydrophilic part at the surface and the hydrophobic part inside. In the aqueous solution, the hydrophobic part could provide enough power for helix 6 to move away, driving the protein into an open configuration and exposing the catalytic triad. Our findings could provide structural evidence to support the double-flap movement, revealing the catalytic mechanism for T1 lipase.
Erythromycin A and roxithromycin are clinically important macrolide antibiotics that selectively act on the bacterial 50S large ribosomal subunit to inhibit bacteria's protein elongation process by blocking the exit tunnel for the nascent peptide away from ribosome. The detailed molecular mechanism of macrolide binding is yet to be elucidated as it is currently known to the most general idea only. In this study, molecular dynamics (MD) simulation was employed to study their interaction at the molecular level, and the binding free energies for both systems were calculated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The calculated binding free energies for both systems were slightly overestimated compared to the experimental values, but individual energy terms enabled better understanding in the binding for both systems. Decomposition of results into residue basis was able to show the contribution of each residue at the binding pocket toward the binding affinity of macrolides and hence identified several key interacting residues that were in agreement with previous experimental and computational data. Results also indicated the contributions from van der Waals are more important and significant than electrostatic contribution in the binding of macrolides to the binding pocket. The findings from this study are expected to contribute to the understanding of a detailed mechanism of action in a quantitative matter and thus assisting in the development of a safer macrolide antibiotic.
The continuing rise in tuberculosis incidence and the problem of drug resistance strains have prompted the research on new drug candidates and the mechanism of drug resistance. Molecular docking and molecular dynamics simulation (MD) were performed to study the binding of isoniazid onto the active site of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase (InhA) in an attempt to address the mycobacterial resistance against isoniazid. Results show that isonicotinic acyl-NADH (INADH) has an extremely high binding affinity toward the wild type InhA by forming stronger interactions compared to the parent drug (isoniazid) (INH). Due to the increase of hydrophobicity and reduction in the side chain's volume of A94 of mutant type InhA, both INADH and the mutated protein become more mobile. Due to this reason, the molecular interactions of INADH with mutant type are weaker than that observed with the wild type. However, the reduced interaction caused by the fluctuation of INADH and the mutant protein only inflected minor resistance in the mutant strain as inferred from free energy calculation. MD results also showed there exists a water-mediated hydrogen bond between INADH and InhA. However, the bridged water molecule is only present in the INADH-wild type complex, reflecting the putative role of the water molecule in the binding of INADH to the wild type protein. The results support the assumption that the conversion of prodrug isoniazid into its active form INADH is mediated by KatG as a necessary step prior to target binding on InhA. Our findings also contribute to a better understanding of INH resistance in mutant type.
A group of flavanones and their chalcones, isolated from Boesenbergia rotunda L., were previously reported to show varying degrees of noncompetitive inhibitory activities toward Dengue virus type 2 (Den2) protease. Results obtained from automated docking studies are in agreement with experimental data in which the ligands were shown to bind to sites other than the active site of the protease. The calculated K(i) values are very small, indicating that the ligands bind quite well to the allosteric binding site. Greater inhibition by pinostrobin, compared to the other compounds, can be explained by H-bonding interaction with the backbone carbonyl of Lys74, which is bonded to Asp75 (one of the catalytic triad residues). In addition, structure-activity relationship analysis yields structural information that may be useful for designing more effective therapeutic drugs against dengue virus infections.
Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2(N)). A recursive approximation to the optimal solution scales as O(N(2)), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets.
Melting dynamics of hafnium clusters are investigated using a novel approach based on the idea of the chemical similarity index. Ground state configurations of small hafnium clusters are first derived using Basin-Hopping and Genetic Algorithm in the parallel tempering mode, employing the COMB potential in the energy calculator. These assumed ground state structures are verified by using the Low Lying Structures (LLS) method. The melting process is carried out either by using the direct heating method or prolonged simulated annealing. The melting point is identified by a caloric curve. However, it is found that the global similarity index is much more superior in locating premelting and total melting points of hafnium clusters.
Tuberculosis (TB) still remains a global threat due to the emergence of a drug-resistant strain. Instead of focusing on the drug target of active stage TB, we are highlighting the isocitrate lyase (ICL) at the dormant stage TB. ICL is one of the persistent factors for Mycobacterium tuberculosis (MTB) to survive during the dormant phase. In addition, the absence of ICL in human has made ICL a potential drug target for TB therapy. However, the dynamic details of ICL which could give insights to the ICL-ligand interaction have yet to be solved. Therefore, a series of ICL dimer dynamics studies through molecular dynamics simulation were performed in this work. The ICL active site entrance gate closure is contributed to by hydrogen bonding and electrostatic interactions with the C-terminal. Analysis suggested that the open-closed behavior of the ICL active site entrance depends on the type of ligand present in the active site. We also observed four residues (Ser91, Asp108, Asp153, and Cys191) which could possibly be the nucleophiles for nucleophilic attack on the cleavage of isocitrate at the C2-C3bond. We hope that the elucidation of ICL dynamics can benefit future works such as lead identification or antibody design against ICL for TB therapeutics.
In this Viewpoint, we provide a commentary on the impact of the Journal of Chemical Information and Modeling Special Issue on Women in Computational Chemistry published in May 2019 and the feedback we received.
Isocitrate lyase (ICL) is a persistent factor for the survival of dormant stage Mycobacterium tuberculosis (MTB), thus a potential drug target for tuberculosis treatment. In this work, ensemble docking approach was used to screen for potential inhibitors of ICL. The ensemble conformations of ICL active site were obtained from molecular dynamics simulation on three dimer form systems, namely the apo ICL, ICL in complex with metabolites (glyoxylate and succinate), and ICL in complex with substrate (isocitrate). Together with the ensemble conformations and the X-ray crystal structures, 22 structures were used for the screening against Malaysian Natural Compound Database (NADI). The top 10 compounds for each ensemble conformation were selected. The number of compounds was then further narrowed down to 22 compounds that were within the Lipinski's Rule of Five for drug-likeliness and were also docked into more than one ensemble conformation. Theses 22 compounds were furthered evaluate using whole cell assay. Some compounds were not commercially available; therefore, plant crude extracts were used for the whole cell assay. Compared to itaconate (the known inhibitor of ICL), crude extracts from Manilkara zapota, Morinda citrifolia, Vitex negundo, and Momordica charantia showed some inhibition activity. The MIC/MBC value were 12.5/25, 12.5/25, 0.78/1.6, and 0.39/1.6 mg/mL, respectively. This work could serve as a preliminary study in order to narrow the scope for high throughput screening in the future.
Bioassay-guided isolation protocol was performed on petroleum ether extract of Peperomia blanda (Jacq.) Kunth using column chromatographic techniques. Five compounds were isolated and their structures were elucidated via one-dimensional (1D) and two-dimensional (2D) NMR, gas chromatography mass sectroscopy (GCMS), liquid chromatography mass spectroscopy (LCMS), and ultraviolet (UV) and infrared (IR) analyses. Dindygulerione E (a new compound), and two compounds isolated from P. blanda for the first time-namely, dindygulerione A and flavokawain A-are reported herein. Antimicrobial activity was screened against selected pathogenic microbes, and minimum inhibitory concentrations (MIC) were recorded within the range of 62-250 μg/mL. Assessment of the pharmacotherapeutic potential has also been done for the isolated compounds, using the Prediction of Activity spectra for Substances (PASS) software, and different activities of compounds were predicted. Molecular docking, molecular dynamics simulation and molecular mechanics/Poisson-Boltzmann Surface Area (MM-PBSA) calculations have proposed the binding affinity of these compounds toward methylthioadenosine phosphorylase enzyme, which may explain their inhibitory actions.