Identification of potential Tpx inhibitors against pathogen-host interactions

Yersinia organisms cause many infectious diseases by invading human cells and delivering their virulence factors via the type three secretion system (T3SS). One alternative strategy in the fight against these pathogenic organisms is to interfere with their T3SS. Previous studies demonstrated that thiol peroxidase, Tpx is functional in the assembly of T3SS and its inhibition by salicylidene acylhydrazides prevents the secretion of pathogenic effectors. In this study, the aim was to identify potential inhibitors of Tpx using an integrated approach starting with high throughput virtual screening and ending with molecular dynamics simulations of selected ligands. Virtual screening of ZINC database of 500,000 compounds via ligand-based and structure-based pharmacophore models retrieved 10,000 hits. The structure-based pharmacophore model was validated using high-throughput virtual screening (HTVS). After multistep docking (SP and XP), common scaffolds were used to find common substructures and the ligand binding poses were optimized using induced fit docking. The stability of the protein–ligand complex was examined with molecular dynamics simulations and the binding free energy of the complex was calculated. As a final outcome eight compounds with different chemotypes were proposed as potential inhibitors for Tpx. The eight ligands identified by a detailed virtual screening protocol can serve as leads in future drug design efforts against the destructive actions of pathogenic bacteria.     

Homology modeling and molecular dynamic simulation of UDP-N-acetylmuramoyl-l-alanine-d-glutamate ligase (MurD) from Mycobacterium tuberculosis H37Rv using in silico approach

The present study aimed to identify the prospective inhibitors of MurD, a cytoplasmic enzyme that catalyzes the addition of d-glutamate to the UDP-N-acetylmuramoyl-l-alanine nucleotide precursor in Mycobacterium tuberculosis (MTB), using virtual screening, docking studies, pharmacokinetic analysis, Molecular Dynamic (MD) simulation, and Molecular Mechanics Generalized Born and Surface Area (MM-GBSA) analyses. The three dimensional (3D) structure was determined based on the homology technique using a template from Streptococcus agalactiae. The modeled structure had three binding sites, namely; substrate binding site (Val18, Thr19, Asp39, Asp40, Gly75, Asn147, Gln171 and His192), the ATP binding site (Gly123, Lys124, Thr125, Thr126, Glu166, Asp283, and Arg314) and the glutamic acid binding site (Arg382, Ser463, and Tyr470). These residues mentioned above play a critical role in the catalytic activity of the enzyme, and their inhibition could serve as a stumbling block to the normal function of the enzyme. A total of 10,344 obtained from virtual screened of Zinc and PubChem databases. These compounds further screened for Lipinski rule of five, docking studies and pharmacokinetic analysis. Four compounds with good binding energies (ZINC11881196 = −10.33 kcal/mol, ZINC12247644 = −8.90 kcal/mol, ZINC14995379 =−8.42 kcal/mol, and PubChem6185 = −8.20 kcal/mol), better than the binding energies of the ATP (−2.31 kcal/mol) and the ligand with known IC₅₀, Aminothiazole (−7.11 kcal/mol) were selected for the MD simulation and MM-GBSA analyses. The result of the analyses showed that all the four ligands formed a stable complex and had the binding free energies better than the binding energy of ATP. Therefore, these ligands considered as suitable prospective inhibitors of the MurD after experimental validation.     

Using free energy of binding calculations to improve the accuracy of virtual screening predictions

Virtual screening of small molecule databases against macromolecular targets was used to identify binding ligands and predict their lowest energy bound conformation (i.e., pose). AutoDock4-generated poses were rescored using mean-field pathway decoupling free energy of binding calculations and evaluated if these calculations improved virtual screening discrimination between bound and nonbound ligands. Two small molecule databases were used to evaluate the effectiveness of the rescoring algorithm in correctly identifying binders of L99A T4 lysozyme. Self-dock calculations of a database containing compounds with known binding free energies and cocrystal structures largely reproduced experimental measurements, although the mean difference between calculated and experimental binding free energies increased as the predicted bound poses diverged from the experimental poses. In addition, free energy rescoring was more accurate than AutoDock4 scores in discriminating between known binders and nonbinders, suggesting free energy rescoring could be a useful approach to reduce false positive predictions in virtual screening experiments.     

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling,molecular docking, 3D-QSAR model and binding free energy calculation studies

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG_bind) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC₅₀ < 50 μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs.     

The in silico identification of potent anti-cancer agents by targeting the ATP binding site of the N-domain of HSP90

To identify new HSP90 inhibitors, the ATP binding site of the N-domain of HSP90 was targeted by molecular docking of a library of 23,129,083 compounds (from the ZINC database) to the ATP binding site of the N-domain of HSP90. Structure-based virtual screen (SBVS) was performed using idock software on the istar web platform. Based on idock binding energies, 40 molecules were considered as HSP90 inhibitors. In the next step, the 40 molecules and the compound AT13387 (Onalespib) were docked to the XJX binding site using AutoDock Vina software. By comparing the binding energies of the 40 molecules selected with compound AT13387, 26 molecules were selected. By applying the rule of five, eight molecules were selected as hit compounds. The interactions of these eight compounds with the XJX binding site were obtained and investigated, and two-dimensional interaction maps were provided for the others. Finally, computing the toxicity of these compounds with the ProTox-II webserver shows that three compounds, namely ZINC89453765, ZINC23918431 and ZINC12414793, can be considered as good HSP90 inhibitors. These compounds are inactive for nuclear receptor signalling and stress response pathways including heat shock response, so do not have the limitations of common HSP90 inhibitors. They are also inactive for hepatotoxicity, carcinogenicity, immunotoxicity, mutagenicity and cytotoxicity.     

Biocomputational Assessment of Natural Compounds as a Potent Inhibitor to Quorum Sensors in Ralstonia solanacearum

Ralstonia solanacearum is among the most damaging bacterial phytopathogens with a wide number of hosts and a broad geographic distribution worldwide. The pathway of phenotype conversion (Phc) is operated by quorum-sensing signals and modulated through the (R)-methyl 3-hydroxypalmitate (3-OH PAME) in R. solanacearum. However, the molecular structures of the Phc pathway components are not yet established, and the structural consequences of 3-OH PAME on quorum sensing are not well studied. In this study, 3D structures of quorum-sensing proteins of the Phc pathway (PhcA and PhcR) were computationally modeled, followed by the virtual screening of the natural compounds library against the predicted active site residues of PhcA and PhcR proteins that could be employed in limiting signaling through 3-OH PAME. Two of the best scoring common ligands ZINC000014762512 and ZINC000011865192 for PhcA and PhcR were further analyzed utilizing orbital energies such as HOMO and LUMO, followed by molecular dynamics simulations of the complexes for 100 ns to determine the ligands binding stability. The findings indicate that ZINC000014762512 and ZINC000011865192 may be capable of inhibiting both PhcA and PhcR. We believe that, after further validation, these compounds may have the potential to disrupt bacterial quorum sensing and thus control this devastating phytopathogenic bacterial pathogen.     

Virtual Screening of Human O-GlcNAc Transferase Inhibitors

O-GlcNAc transferase (OGT) is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine (UDP-GlcNAc) to hydroxyl groups of serines and threonines (Ser/Thr) in proteins. Dysregulations of cellular O-GlcNAc have been implicated in diabetes, neurodegenerative disease, and cancer, which brings great interest in developing potent and speci c small-molecular OGT inhibitors. In this work, we performed virtual screening on OGT catalytic site to identify potential inhibitors. 7134792 drug-like compounds from ZINC (a free database of commercially available compounds for virtual screening) and 4287550 compounds generated by FOG (fragment optimized growth program) were screened and the top 116 compounds ranked by docking score were analyzed. By comparing the screening results, we found FOG program can generate more compounds with better docking scores than ZINC. The top ZINC compounds ranked by docking score were grouped into two classes, which held the binding positions of UDP and GlcNAc of UDPGlcNAc. Combined with individual fragments in binding pocket, de novo compounds were designed and proved to have better docking score. The screened and designed compounds may become a starting point for developing new drugs.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

The identification of new ATAD2 bromodomain inhibitors: the application of combined ligand and structure-based virtual screening

Ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches were used to identify new inhibitors for ATAD2 bromodomain. The LBVS approach was used to search 23,129,083 clean compounds to identify compounds similar to an active compound with reported pIC₅₀ equal to 7.2. Based on LBVS results, 19 compounds were selected. To perform SBVS, by applying nine filters on 23,129,083 clean compounds, 1,057,060 compounds were selected. After performing SBVS on these selected compounds with idock software, 16 compounds with the lowest binding energies were selected. More accurate molecular docking analysis was performed on these 35 selected compounds by using iGEMDOCK software and six of them with the lowest binding energies were selected as hit compounds. These compounds were zinc36647229, zinc77969074, zinc13637358, zinc77971540, zinc12991296 and zinc19374204.     

In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease

Alzheimer’s disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC—natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.     

Computational Approaches for the Design of Novel Anticancer Compounds Based on Pyrazolo[3,4-d]pyrimidine Derivatives as TRAP1 Inhibitor

In the present in-silico study, various computational techniques were applied to determine potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of important features required for activity. The 3D QSAR study showed a statistically significant model with R² = 0.96 and Q² = 0.57. Leave one out (LOO) cross-validation (R² CV = 0.58) was used to validate the QSAR model. The molecular docking study showed maximum XP docking scores (−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56, 43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583, SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were validated using the 100 ns MD simulations performed for the selected five docked complexes. The selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules present in the literature. The ZINC database was used for a virtual screening study that screened ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis showed noticeable results. The results of the study may be helpful for the further development of potent TRAP1 inhibitors     

In silico identification of noncompetitive inhibitors targeting an uncharacterized allosteric site of falcipain-2

Falcipain-2 (FP-2) is a Plasmodium falciparum hemoglobinase widely targeted in the search for antimalarials. FP-2 can be allosterically modulated by various noncompetitive inhibitors that have been serendipitously identified. Moreover, the crystal structures of two inhibitors bound to an allosteric site, termed site 6, of the homolog enzyme human cathepsin K (hCatK) suggest that the equivalent region in FP-2 might play a similar role. Here, we conduct the rational identification of FP-2 inhibitors through virtual screenings (VS) of compounds into several pocket-like conformations of site 6, sampled during molecular dynamics (MD) simulations of the free enzyme. Two noncompetitive inhibitors, ZINC03225317 and ZINC72290660, were confirmed using in vitro enzymatic assays and their poses into site 6 led to calculated binding free energies matching the experimental ones. Our results provide strong evidence about the allosteric inhibition of FP-2 through binding of small molecules to site 6, thus opening the way toward the discovery of new inhibitors against this enzyme.

     

Plant-Derived Antiviral Compounds as Potential Entry Inhibitors against Spike Protein of SARS-CoV-2 Wild-Type and Delta Variant: An Integrative in SilicoApproach

The wild-type SARS-CoV-2 has continuously evolved into several variants with increased transmissibility and virulence. The Delta variant which was initially identified in India created a devastating impact throughout the country during the second wave. While the efficacy of the existing vaccines against the latest SARS-CoV-2 variants remains unclear, extensive research is being carried out to develop potential antiviral drugs through approaches like in silico screening and drug-repurposing. This study aimed to conduct the docking-based virtual screening of 50 potential phytochemical compounds against a Spike glycoprotein of the wild-type and the Delta SARS-CoV-2 variant. Subsequently, molecular docking was performed for the five best compounds, such as Lupeol, Betulin, Hypericin, Corilagin, and Geraniin, along with synthetic controls. From the results obtained, it was evident that Lupeol exhibited a remarkable binding affinity towards the wild-type Spike protein (−8.54 kcal/mol), while Betulin showed significant binding interactions with the mutated Spike protein (−8.83 kcal/mol), respectively. The binding energy values of the selected plant compounds were slightly higher than that of the controls. Key hydrogen bonding and hydrophobic interactions of the resulting complexes were visualized, which explained their greater binding affinity against the target proteins—the Delta S protein of SARS-CoV-2, in particular. The lower RMSD, the RMSF values of the complexes and the ligands, Rg, H-bonds, and the binding free energies of the complexes together revealed the stability of the complexes and significant binding affinities of the ligands towards the target proteins. Our study suggests that Lupeol and Betulin could be considered as potential ligands for SARS-CoV-2 spike antagonists. Further experimental validations might provide new insights for the possible antiviral therapeutic interventions of the identified lead compounds and their analogs against COVID-19 infection.     

Rational design of inhibitors against LpxA protein of Acinetobacter baumannii using a virtual screening method

BackgroundAcinetobacter baumannii is a highly antimicrobial resistant nosocomial pathogen. Resistance to currently used antibiotics has limited effective drugs against this bacterium. This study aimed to propose a rational inhibitor design against the LpxA protein of A. baumannii using a virtual screening method based on a similar structure of ligands.MethodsIn this study, we targeted LpxA protein, which is involved in the early stage of LPS biosynthesis. In the next step, we used Peptide920 and 1,2- Ethanediol as templates to find similar compounds using Drugbank and Zinc15 webservers, respectively. Subsequently, molecular dynamics (MD) simulations were carried out for LpxA protein and two complexes of ZINC895081 and Macrolactam-1 which represented the highest binding affinity and best conformation. Finally, ADMET properties, water solubility and drug-likeness of the desired compounds were evaluated using SwissADME and DruLiTo softwares.ResultsAccording to considered criteria, Drugbank suggested 5 compunds including Ilomastat, Macrolactam-1, Macrolactam-2, Macimorelin, and Oglufanide. On the other hand, Zinc15 webserver suggested 4 compunds including ZINC895048, ZINC895081, ZINC901061 and ZINC1531008. The result of the HDOCK server and Molegro virtual docker (MVD) showed that Macrolactam-1 and ZINC895081 (Citrate) had the highest docking score. In addition, MD simulations showed that ZINC895081 and Macrolactam-1 ligands have the stable binding to the LpxA protein. According to Lipinski's rule, these two compounds are non-carcinogenic, non-toxic and promising inhibitors against LpxA of A. baumannii.ConclusionIt seems that Macrolactam-1 and ZINC895081 (Citrate) are two valuable promising inhibitors against the LpxA protein of A. baumannii. Further in vitro and in vivo experiments are needed to confirm the capabilities of these proposed compounds against A. baumannii.     

Novel Dual‐Site‐Binding Neuraminidase Inhibitor from Virtual Screening by Pharmacophore and Molecular Dynamics Methods

Neuraminidase is a significant anti‐influenza target that plays crucial role in virus replication cycle. The discovery of 150‐cavity in Group‐1 neuraminidase provides us a novel mentality of designing inhibitor which can bind with both conserved site and 150‐cavity. In order to discover novel dual‐site‐binding inhibitors, a 3D chemical‐feature‐based pharmacophore model was established to cover dual‐site in neuraminidase. The dual‐site‐binding model was consistent in predicting the binding conformation of Group‐1 neuraminidase inhibitor and applied for virtual screening of Specs database. Compound 4 (ZINC05790048) that aligned well to the model was selected after multiple filtrations for molecular dynamics simulations, indicating improved binding energy with neuraminidase. It can sever as the lead compound for a novel series of inhibitors.     

Structure-based virtual screening of influenza virus RNA polymerase inhibitors from natural compounds: Molecular dynamics simulation and MM-GBSA calculation

The resistances of matrix protein 2 (M2) protein inhibitors and neuraminidase inhibitors for influenza virus have attracted much attention and there is an urgent need for new drug. The antiviral drugs that selectively act on RNA polymerase are less prone to resistance and possess fewer side effects on the patient. Therefore, there is increased interest in screening compounds that can inhibit influenza virus RNA polymerase. Three natural compounds were found by using molecular docking-based virtual screening, which could bind tightly within the polymerase acidic protein-polymerase basic protein 1 (PA-PB1) subunit of influenza virus polymerase. Firstly, their drug likeness properties were evaluated, which showed that the hepatotoxicity values of all the three compounds indicating they had less or no hepatotoxicity, and did not have the plasma protein biding (PPB) ability, the three compounds needed to be modified in some aspects, like bulky molecular size. The stability of the complexes of PA-hits was validated through molecular dynamics (MD) simulation, revealing compound 2 could form more stable complex with PA subunit. The torsional conformations of each rotatable bond of the ligands in PA subunit were also monitored, to investigate variation in the ligand properties during the simulation, compound 3 had fewer rotatable bonds, indicating that the molecule had stronger rigidity. The bar charts of protein–ligand contacts and contacts over the course of trajectory showed that four key residues (Glu623, Lys643, Asn703 and Trp706) of PA subunit that participated in hydrogen-bond, water bridge and hydrophobic interactions with the hit compounds. Finally, the binding free energy and contributed energies were calculated by using MM-GBSA method. Out of the three compounds, compound 1 showed the lowest total binding free energy. Among all the interactions, the contribution of the covalent binding and the van der Waals energy were more than other items, compound 1 formed more stable hydrogen bonds with the residues of PA subunit binding pocket. This study smoothed the path for the development of novel lead compounds with improved binding properties, high drug likeness, and low toxicity to humans for the treatment of influenza, which provided a good basis for further research on novel and effective influenza virus PA-PB1 interaction inhibitors.     

Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR—the quorum-sensing receptor from Chromobacterium violaceum—as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.     

In silico virtual screening of potent inhibitor to hamper the interaction between HIV-1 integrase and LEDGF/p75 interaction using E-pharmacophore modeling,molecular docking,and dynamics simulations

The rapid increase of HIV-1 infection throughout the globe has a high demand for a superior drug with lesser side effects. LEDGF/p75, the human Lens Epithelium-Derived Growth Factor is identified as a promising cellular cofactor with integrase in facilitating the viral replication in an early stage by acting as a tethering factor in the pre-integration to the chromatin. Therefore, the present study was designed to identify a potent inhibitor by applying an E-pharmacophore based virtual screening, molecular docking, and dynamics simulation approaches. Finally, ZINC22077550 and ZINC32124441 were best identified potent molecules with the efficient binding affinity, strong hydrogen bonding, and acceptable pharmacological properties to hamper the interaction between integrase and LEDGF/p75. Further, the DFT and MDS studies were also analyzed, and shown a favorable energetic state and dynamic stability then reference compound. In conclusion, we suggest that these findings could be novel therapeutics in the future and may increase the lifespan of individuals suffering from viral infection.     

3D QSAR Pharmacophore Based Virtual Screening for Identification of Potential Inhibitors for CDC25B

Owing to its fundamental roles in cell cycle phases, the cell division cycle 25B (CDC25B) was broadly considered as potent clinical drug target for cancers. In this study, 3D QSAR pharmacophore models for CDC25B inhibitors were developed by the module of Hypogen. Three methods (cost analysis, test set prediction, and Fisher’s test) were applied to validate that the models could be used to predict the biological activities of compounds. Subsequently, 26 compounds satisfied Lipinski’s rule of five were obtained by the virtual screening of the Hypo-1-CDC25B against ZINC databases. It was then discovered that 9 identified molecules had better binding affinity than a known CDC25B inhibitors-compound 1 using docking studies. The molecular dynamics simulations showed that the compound had favorable conformations for binding to the CDC25B. Thus, our findings here would be helpful to discover potent lead compounds for the treatment of cancers.