The allosteric modulation of the homodimeric H10-03-6 protein to glycan ligands L1 and L2, and the STAB19 protein to glycan ligands L3 and L4, respectively, has been studied by molecular dynamics simulations and free energy calculations. The results revealed that the STAB19 protein has a significantly higher affinity for L3 (-11.38 ± 2.32 kcal/mol) than that for L4 (-5.51 ± 1.92 kcal/mol). However, the combination of the H10-03-6 protein with glycan L2 (1.23 ± 6.19 kcal/mol) is energetically unfavorable compared with that of L1 (-13.96 ± 0.35 kcal/mol). Further, the binding of glycan ligands L3 and L4 to STAB19 would result in the significant closure of the two CH2 domains of the STAB19 conformation with the decrease of the centroid distances between the two CH2 domains compared with the H10-03-6/L1/L2 complex. The CH2 domain closure of STAB19 relates directly to the formation of new hydrogen bonds and hydrophobic interactions between the residues Ser239, Val240, Asp265, Glu293, Asn297, Thr299, Ser337, Asp376, Thr393, Pro395, and Pro396 in STAB19 and glycan ligands L3 and L4, which suggests that these key residues would contribute to the specific regulation of STAB19 to L3 and L4. In addition, the distance analysis revealed that the EF loop in the H10-03-6/L1/L2 model presents a high flexibility and partial disorder compared with the stabilized STAB19/L3/L4 complex. These results will be helpful in understanding the specific regulation through the asymmetric structural characteristics in the CH2 and CH3 domains of the H10-03-6 and STAB19 proteins.
Polo-like kinase 1 (PLK1) and p38γ mitogen-activated protein kinase (p38γ) play important roles in cancer pathogenesis by controlling cell cycle progression and are therefore attractive cancer targets. The design of multitarget inhibitors may offer synergistic inhibition of distinct targets and reduce the risk of drug-drug interactions to improve the balance between therapeutic efficacy and safety. We combined deep-learning-based quantitative structure-activity relationship (QSAR) modeling and hybrid-based consensus scoring to screen for inhibitors with potential activity against the targeted proteins. Using this combination strategy, we identified a potent PLK1 inhibitor (compound 4) that inhibited PLK1 activity and liver cancer cell growth in the nanomolar range. Next, we deployed both our QSAR models for PLK1 and p38γ on the Enamine compound library to identify dual-targeting inhibitors against PLK1 and p38γ. Likewise, the identified hits were subsequently subjected to hybrid-based consensus scoring. Using this method, we identified a promising compound (compound 14) that could inhibit both PLK1 and p38γ activities. At nanomolar concentrations, compound 14 inhibited the growth of human hepatocellular carcinoma and hepatoblastoma cells in vitro. This study demonstrates the combined screening strategy to identify novel potential inhibitors for existing targets.
14-3-3σ plays an important role in controlling tumor metabolic reprogramming and cancer cell growth. However, its function is often compromised in many cancers due to its downregulation. Previous studies found that homodimerization of 14-3-3σ is critical for its activity. However, to date, it is not known if stabilization of 14-3-3σ homodimers can improve its activity or prevent its degradation. In our previous work, we have showed that GCP-Lys-OMe is a potential 14-3-3σ homodimer stabilizer. However, its stabilizing effect was not experimentally validated. Therefore, in this study, we have attempted to predict few potential peptides that can stabilize the dimeric form of 14-3-3σ using similar in silico techniques as described previously for GCP-Lys-OMe. Subsequent [1H]-CPMG NMR experiments confirmed the binding of the peptides (peptides 3, 5, 9, and 16) on 14-3-3σ, with peptide 3 showing the strongest binding. Competitive [1H]-CPMG assays further revealed that while peptide 3 does not compete with a 14-3-3σ binding peptide (ExoS) for the protein's amphipathic groove, it was found to improve ExoS binding on 14-3-3σ. When 14-3-3σ was subjected to dynamic light scattering experiments, the 14-3-3σ homodimer was found to undergo dissociation into monomers prior to aggregation. Intriguingly, the presence of peptide 3 increased 14-3-3σ stability against aggregation. Overall, our findings suggest that (1) docking accompanied by MD simulations can be used to identify potential homodimer stabilizing compounds of 14-3-3σ and (2) peptide 3 can slow down 14-3-3σ aggregation (presumably by preventing its dissociation into monomers), as well as improving the binding of 14-3-3σ to ExoS protein.
Lipoteichoic acid synthase (LtaS) is a key enzyme for the cell wall biosynthesis of Gram-positive bacteria. Gram-positive bacteria that lack lipoteichoic acid (LTA) exhibit impaired cell division and growth defects. Thus, LtaS appears to be an attractive antimicrobial target. The pharmacology around LtaS remains largely unexplored with only two small-molecule LtaS inhibitors reported, namely "compound 1771" and the Congo red dye. Structure-based drug discovery efforts against LtaS remain unattempted due to the lack of an inhibitor-bound structure of LtaS. To address this, we combined the use of a molecular docking technique with molecular dynamics (MD) simulations to model a plausible binding mode of compound 1771 to the extracellular catalytic domain of LtaS (eLtaS). The model was validated using alanine mutagenesis studies combined with isothermal titration calorimetry. Additionally, lead optimization driven by our computational model resulted in an improved version of compound 1771, namely, compound 4 which showed greater affinity for binding to eLtaS than compound 1771 in biophysical assays. Compound 4 reduced LTA production in S. aureus dose-dependently, induced aberrant morphology as seen for LTA-deficient bacteria, and significantly reduced bacteria titers in the lung of mice infected with S. aureus. Analysis of our MD simulation trajectories revealed the possible formation of a transient cryptic pocket in eLtaS. Virtual screening (VS) against the cryptic pocket led to the identification of a new class of inhibitors that could potentiate β-lactams against methicillin-resistant S. aureus. Our overall workflow and data should encourage further drug design campaign against LtaS. Finally, our work reinforces the importance of considering protein conformational flexibility to a successful VS endeavor.
Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both methods bring severe side effects to patients, as these therapies not only attack cancer cells but also damage normal cells. Anticancer peptides (ACPs) are a promising alternative as therapeutic agents that are efficient and selective against tumor cells. Here, we propose a deep learning method based on convolutional neural networks to predict biological activity (EC50, LC50, IC50, and LD50) against six tumor cells, including breast, colon, cervix, lung, skin, and prostate. We show that models derived with multitask learning achieve better performance than conventional single-task models. In repeated 5-fold cross validation using the CancerPPD data set, the best models with the applicability domain defined obtain an average mean squared error of 0.1758, Pearson's correlation coefficient of 0.8086, and Kendall's correlation coefficient of 0.6156. As a step toward model interpretability, we infer the contribution of each residue in the sequence to the predicted activity by means of feature importance weights derived from the convolutional layers of the model. The present method, referred to as xDeep-AcPEP, will help to identify effective ACPs in rational peptide design for therapeutic purposes. The data, script files for reproducing the experiments, and the final prediction models can be downloaded from http://github.com/chen709847237/xDeep-AcPEP. The web server to directly access this prediction method is at https://app.cbbio.online/acpep/home.
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.
Previous studies have reported that compounds bearing an arylamide linked to a heterocyclic planar ring have successfully inhibited the hemopexin-like domain (PEX9) of matrix metalloproteinase 9 (MMP9). PEX9 has been suggested to be more selectively targeted than MMP9's catalytic domain in a degrading extracellular matrix under some pathologic conditions, especially in cancer. In this study, we aim to synthesize and evaluate 10 arylamide compounds as MMP9 inhibitors through an enzymatic assay as well as a cellular assay. The mechanism of inhibition for the most active compounds was investigated via molecular dynamics simulation (MD). Molecular docking was performed using AutoDock4.0 with PEX9 as the protein model to predict the binding of the designed compounds. The synthesis was carried out by reacting aniline derivatives with 3-bromopropanoyl chloride using pyridine as the catalyst at room temperature. The MMP9 assay was conducted using the FRET-based MMP9 kits protocol and gelatin zymography assay. The cytotoxicity assay was done using the MTT method, and the MD simulation was performed using AMBER16. Assay on MMP9 demonstrated activities of three compounds (2, 7, and 9) with more than 50% inhibition. Further inhibition on MMP9 expressed by 4T1 showed that two compounds (7 and 9) inhibited its gelatinolytic activity more than 50%. The cytotoxicity assay against 4T1 cells results in the inhibition of the cell growth with an EC50 of 125 μM and 132 μM for 7 and 9, respectively. The MD simulation explained a stable interaction of 7 and 9 in PEX9 at 100 ns with a free energy of binding of -8.03 kcal/mol and -6.41 kcal/mol, respectively. Arylamides have potential effects as selective MMP9 inhibitors in inhibiting breast cancer cell progression.
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.
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.
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.
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.
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.