Discovery of Entamoeba histolytica hexokinase 1 inhibitors through homology modeling and virtual screening

Abstract

Entamoeba histolytica, the parasite which causes amebiasis is responsible for 110?000 deaths a year. Entamoeba histolytica depends on glycolysis to obtain ATP for cellular work. According to metabolic flux studies, hexokinase exerts the highest flux control of this metabolic pathway; therefore, it is an excellent target in the search of new antiamebic drugs. To this end, a tridimensional model of E. histolytica hexokinase 1 (EhHK1) was constructed and validated by homology modeling. After virtual screening of 14?400 small molecules, the 100 with the best docking scores were selected, purchased and assessed in their inhibitory capacity. The results showed that three molecules (compounds 2921, 11275 and 2755) inhibited EhHK1 with an I₅₀ of 48, 91 and 96?µM, respectively. Thus, we found the first inhibitors of EhHK1 that can be used in the search of new chemotherapeutic agents against amebiasis.     

Identification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening,ADMET prediction and molecular dynamics simulation assay

Histone deacetylases (HDACs) have gained increased attention as targets for anticancer drug design and development. HDAC inhibitors have proven to be effective for reversing the malignant phenotype in HDAC-dependent cancer cases. However, lack of selectivity of the many HDAC inhibitors in clinical use and trials contributes to toxicities to healthy cells. It is believed that, the continued identification of isoform-selective inhibitors will eliminate these undesirable adverse effects – a task that remains a major challenge to HDAC inhibitor designs. Here, in an attempt to identify isoform-selective inhibitors, a large compound library containing 2,703,000 compounds retrieved from Otava database was screened against class I HDACs by exhaustive approach of structure-based virtual screening using rDOCK and Autodock Vina. A total of 41 compounds were found to show high-isoform selectivity and were further redocked into their respective targets using Autodock4. Thirty-six compounds showed remarkable isoform selectivity and passed drug-likeness and absorption, distribution, metabolism, elimination and toxicity prediction tests using ADMET Predictor? and admetSAR. Furthermore, to study the stability of ligand binding modes, 10 ns-molecular dynamics (MD) simulations of the free HDAC isoforms and their complexes with respective best-ranked ligands were performed using nanoscale MD software. The inhibitors remained bound to their respective targets over time of the simulation and the overall potential energy, root-mean-square deviation, root-mean-square fluctuation profiles suggested that the detected compounds may be potential isoform-selective HDAC inhibitors or serve as promising scaffolds for further optimization towards the design of selective inhibitors for cancer therapy.     

Discovery of novel small-molecule Src kinase inhibitors via a kinase-focused druglikeness rule and structure-based virtual screening

Overexpression of the non-receptor tyrosine kinase Src is implicated in the development and progression of various human cancers. Blocking signalling pathways mediated by Src is believed to be a promising anticancer strategy. We report herein the discovery of novel small-molecule Src inhibitors by crystal structure-based virtual screening. A kinase-focused druglikeness rule was proposed and used in the design of compound library. Combination of large-scale docking with DOCK and rescoring with GOLD resulted in 6 hits with moderate to potent inhibitory activity against Src. Among them, compound 1 with an IC₅₀ of 1.2 μM shows the most potent inhibitory activity. By using molecular docking, binding models of the top 3 hits (ranked by potency and ligand efficiency) with Src were constructed to provide a rational strategy that simultaneously exploits hydrogen bonding interaction in the hinge region and hydrophobic stacking in the back pocket. This approach is instructive and meaningful to further structure-based drug design of Src inhibitors.     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

Identification of novel acetylcholinesterase inhibitors through e-pharmacophore-based virtual screening and molecular dynamics simulations

Alzheimer’s disease (AD), a progressive neurodegenerative disorder is the most common cause of dementia among elderly people. To date, the successful therapeutic strategy to treat AD is maintaining the levels of acetylcholine via inhibiting acetylcholinesterase (AChE). The present study involves identification of newer AChE inhibitors by dual approach of e-pharmacophore and structure-based virtual screening of Asinex library. Robustness of docking protocol was validated by enrichment calculation with ROC value .71 and BEDROC value .028. Among 11 selected hits, ZINC72338524 with best MM-GBSA dG binding shows optimal range of CNS properties and ligand–AChE complex stability. Further, molecular dynamics study revealed its molecular interactions with Trp86, Phe338, and Tyr341 amino acid residues of catalytic anionic site and Tyr124, Ser125, and Trp286 amino acid residues of peripheral anionic site. Physicochemical properties and ADMET risk prediction indicates their potential in druggability and safety.     

Identification of potent virtual leads to design novel PLK1 inhibitors: pharmacophore modelling,virtual screening and molecular docking studies

The aim of this study was to identify novel scaffolds and utilise them in designing potent PLK1 inhibitors. Three-dimensional pharmacophore models on the basis of chemical features were developed for PLK1 on the basis of the known inhibitors. The best pharmacophore model, Hypo 1, which has the highest correlation (0.96), the highest cost difference (75.7494), the lowest total cost and RMSD (75.7494, 0.5458), contains two hydrophobics, one ring aromatic and one hydrogen donor. Hypo 1 was validated by the test set, decoy set and the Fischer's randomisation method. Then it was used for chemical database virtual screening. The hit compounds were filtered by Lipinski's rule of five and absorption, distribution, metabolism, elimination and toxicity properties. Finally, 24 compounds with good estimated activity values were used for docking studies. These results will be used to develop new inhibitors of PLK1 as leads.     

In silico high-throughput virtual screening and molecular dynamics simulation study to identify inhibitor for AdeABC efflux pump of Acinetobacter baumannii

Emergence of multi-drug resistant strains of Acinetobacter baumannii has caused significant health problems and is responsible for high morbidity and mortality. Overexpression of AdeABC efflux system is one of the major mechanisms. In this study, we have focused on overcoming the drug resistance by identifying inhibitors that can effectively bind and inhibit integral membrane protein, AdeB of this efflux pump. We performed homology modeling to generate structure of AdeB using MODELLER v9.16 followed by model refinement using 3D-Refine tool and validated using PSVS, ProsaWeb, ERRAT, etc. The energy minimization of modeled protein was done using Protein preparation wizard application included in Schrodinger suite. High-throughput virtual screening of 159,868 medicinal compounds against AdeB was performed using three sequential docking modes (i.e. HTVS, SP and XP). Furthermore, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis was done using QIKPROP. The selected 123 compounds were further analyzed for binding free energy by molecular mechanics (using prime MM-GBSA). We have also performed enrichment study (ROC curve analysis) to validate our docking results. The selected molecule and its interaction with AdeB were validated by molecular dynamics simulation (MDS) using GROMACS v5.1.4. In silico high-throughput virtual screening and MDS validation identified ZINC01155930 ((4R)-3-(cycloheptoxycarbonyl)-4-(4-etochromen-3-yl)-2-methyl-4,6,7,8-tetrahydroquinolin-5-olate) as a possible inhibitor for AdeB. Hence, it might be a suitable efflux pump inhibitor worthy of further investigation in order to be used for controlling infections caused by Acinetobacter baumannii.     

Identification of ALK5 inhibitor via structure-based virtual screening and ADMET prediction

Abstract

TGF-β plays a critical role in the initiation and progression of fibrosis in various organ systems such as kidney, heart, lung and liver. TGF-β and its receptors (ALK5 and TβR II) are able to control the cellular growth and promote several biological responses. To date, many pharmaceutical companies have employed virtual screening to identify potent inhibitors against ALK5. Nevertheless, none of these studies had involved the in silico ADMET evaluation and Raccoon filtering. In our experiment, all 57423 molecules were downloaded from TCM database and were filtered and converted to PDBQT formats by Raccoon software. Then 24?189 structures were run through AutoDock Vina in PyRx 0.8, 164 molecules were selected and further evaluated by ADMET Predictor 6.5, and 56 structures were selected and docked by Glide 6.2. Finally, the top 10 hits were identified as promising oral ALK5 inhibitors according to their Glide scores. The Glide scores of the best two compounds, 40686 and 33534, were ?10.75 and ?10.30?kcal/mol, respectively. This research provides a set of combined and detailed virtual screening protocol and is helpful for explaining the mechanism of receptor–ligand interactions.     

Discovery of potential novel microsomal triglyceride transfer protein inhibitors via virtual screening of pharmacophore modelling and molecular docking

In order to identify potential natural inhibitors against the microsomal triglyceride transfer protein (MTP), HipHop models were generated using 20 known inhibitors from the Binding Database. Using evaluation indicators, the best hypothesis model, Hypo1, was selected and utilised to screen the Traditional Chinese Medicine Database, which resulted in a hit list of 58 drug-like compounds. A homology model of MTP was built by MODELLER and was minimised by CHARMm force field. It was then validated by Ramachandran plot and Verify-3D so as to obtain a stable structure, which was further used to refine the 58 hits using molecular docking studies. Then, five compounds with higher docking scores which satisfied the docking requirements were discovered. Among them, Ginkgetin and Dauricine were most likely to be candidates that exhibition inhibiting effect on MTP. The screening strategy in this study is relatively new to the discovery of MTP inhibitors in medicinal chemistry. Moreover, it is important to note that, lomitapide, an approved MTP inhibitor, fits well with Hypo1 as well as our homology model of MTP, which confirmed the rationality of our studies. The results indicated the applicability of molecular modeling for the discovery of potential natural MTP inhibitors from traditional Chinese herbs.     

Structural insight into Mycobacterium tuberculosis maltosyl transferase inhibitors: pharmacophore-based virtual screening,docking, and molecular dynamics simulations

Pharmacophore-based virtual screening, subsequent docking, and molecular dynamics (MD) simulations have been done to identify potential inhibitors of maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE). Ligand and structure-based pharmacophore models representing its primary binding site (pbs) and unique secondary binding site 2 (sbs2), respectively, were constructed based on the three dimensional structure of mtb GlgE. These pharmacophore models were further used for screening of ZINC and antituberculosis compounds database (ATD). Virtually screened molecules satisfying Lipinski’s rule of five were then analyzed using docking studies and have identified 23 molecules with better binding affinity than its natural substrate, maltose. Four top scoring ligands from ZINC and ATD that either binds to pbs or sbs2 have been subjected to 10 ns each MD simulations and binding free energy calculations. Results of these studies have confirmed stable protein ligand binding. Results reported in the article are likely to be helpful in antitubercular therapeutic development research.     

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement

With the emergence of drug-resistant strains and the cumulative toxicities associated with current therapies, demand remains for new inhibitors of HIV-1 replication. The inhibition of HIV-1 entry is an attractive, yet underexploited therapeutic approach with implications for salvage and preexposure prophylactic regimens, as well as topical microbicides. Using the combination of a field-derived bioactive conformation template to perform virtual screening and iterative bioisosteric replacements, coupled with in silico predictions of absorption, distribution, metabolism, and excretion, we have identified new leads for HIV-1 entry inhibitors.     

Discovery,molecular dynamic simulation and biological evaluation of structurally diverse cholinesterase inhibitors with new scaffold through shape-based pharmacophore virtual screening

Designing small molecule inhibitors targeting cholinesterases (ChEs) is considered as an efficient strategy for the treatment of Alzheimer′s disease (AD). In the present study, based on a shaped-based pharmacophore (SBP) model that we reported previously, virtual screening was performed on four commercial compound databases, from which eight small molecules containing new structurally scaffolds were retained and evaluated. In general, six of these potential hits were identified to be selective ChEs inhibitors. Three compounds exhibited IC₅₀ values and K_i values in micromolar range on acetylcholinesterase (AChE), the most active compound 4 showed IC₅₀ value of 6.31 ± 2.68 μM and K_i value of 4.76 μM. Other three compounds displayed IC₅₀ values and K_i values in micromolar range on butyrylcholinesterase (BChE) with high target selectivity, the most active compound 1 showed IC₅₀ value of 3.87 ± 2.48 μM and K_i value of 1.52 μM. Multiple biological evaluations were performed to determine their cytotoxicity, cyto-protective effects, antioxidant effect as well as druglike properties. These compounds provide new cores for the further design and optimization, with the aim to discover new ChEs inhibitors for the treatment of AD.     

Discovery of new nicotinamides as apoptotic VEGFR-2 inhibitors: virtual screening,synthesis, anti-proliferative,immunomodulatory, ADMET,toxicity, and molecular dynamic simulation studies

A library of modified VEGFR-2 inhibitors was designed as VEGFR-2 inhibitors. Virtual screening was conducted for the hypothetical library using in silico docking, ADMET, and toxicity studies. Four compounds exhibited high in silico affinity against VEGFR-2 and an acceptable range of the drug-likeness. These compounds were synthesised and subjected to in vitro cytotoxicity assay against two cancer cell lines besides VEGFR-2 inhibitory determination. Compound D-1 showed cytotoxic activity against HCT-116 cells almost double that of sorafenib. Compounds A-1, C-6, and D-1 showed good IC₅₀ values against VEGFR-2. Compound D-1 markedly increased the levels of caspase-8 and BAX expression and decreased the anti-apoptotic Bcl-2 level. Additionally, compound D-1 caused cell cycle arrest at pre-G1 and G2-M phases in HCT-116 cells and induced apoptosis at both early and late apoptotic stages. Compound D-1 decreased the level of TNF-α and IL6 and inhibited TNF-α and IL6. MD simulations studies were performed over 100 ns.     

Discovery of 9-phenylacridinediones as highly selective butyrylcholinesterase inhibitors through structure-based virtual screening

Butyrylcholinesterase (BuChE) is considered a promising drug target as it plays an important role in the progression of late stage Alzheimer’s disease (AD). Two compound libraries were selected and 64 124 amine containing moieties were screened using a hierarchical virtual screening protocol to discover new selective BuChE inhibitors. From these and subsequent docking experiments, 9-phenylacridinedione (9-PAD) was identified as a promising scaffold for selective inhibition of BuChE. Selected top dock scored 9-PADs were assayed and compounds 3 and 6 exhibited potent and highly selective human BuChE inhibition (IC₅₀: 98 nM and 142 nM, respectively). Both molecules were also predicted to show sufficient brain permeability, not have any substantial toxicities, especially hepatotoxicity, and no significant in vitro cytotoxicity against SH-SY5Y neuroblastoma cells at concentrations up to 100 µM. These findings indicate that 9-PAD is a promising lead structure for the development of agents able to treat late stage AD.     

Homology modeling,docking and structure-based virtual screening for new inhibitor identification of Klebsiella pneumoniae heptosyltransferase-III

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative opportunistic pathogen commonly associated with hospital-acquired infections that are often resistant even to antibiotics. Heptosyltransferase (HEP) belongs to the family of glycosyltransferase-B (GT-B) and plays an important in the synthesis of lipopolysaccharides (LPS) essential for the formation of bacterial cell membrane. HEP-III participates in the transfer of heptose sugar to the outer surface of bacteria to synthesize LPS. LPS truncation increases the bacterial sensitivity to hydrophobic antibiotics and detergents, making the HEP as a novel drug target. In the present study, we report the 3D homology model of K. pneumoniae HEP-III and its structure validation. Active site was identified based on similarities with known structures using Dali server, and structure-based pharmacophore model was developed for the active site substrate ADP. The generated pharmacophore model was used as a 3D search query for virtual screening of the ASINEX database. The hit compounds were further filtered based on fit value, molecular docking, docking scores, molecular dynamics (MD) simulations of HEP-III complexed with hit molecules, followed by binding free energy calculations using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA). The insights obtained in this work provide the rationale for design of novel inhibitors targeting K. pneumoniae HEP-III and the mechanistic aspects of their binding.

Communicated by Ramaswamy H. Sarma     

Structure-based screening,ADMET profiling,and molecular dynamic studies on mGlu2 receptor for identification of newer antiepileptic agents

Structure-based screening approach targeting mGlu2 receptor was carried out to identify good chemical starting points for anti-epileptic therapy. Interactive modes of final 12 compounds identified on the basis of screening of Asinex library, binding energy analysis, ADME profiling with special emphasis for CNS ranges, and toxicity analysis were studied and showed good binding modes in the mGluR2-active site. Enrichment studies for validating screening protocol were carried out which gave ROC values 0.98 (AUC = 0.96) for SP, 0.97 (AUC = 0.95) for XP with BEDROC analysis. Our results indicate that all the 12 hits showed good CNS drug-like properties, have better binding free energy and ADME profile as compared to co-crystallized ligand with the best ligand hit retaining conserved hydrogen bond interactions with Ala-166, Thr-168, Ser-145, and Arg-61 residues in bilobatevenus fly-trap domain of mGluR2 receptor. Molecular dynamics simulations proved that the two potential hits, qualifying all screening parameters, are stable in the receptor active site pocket, confirming the potential of the identified hits as a specific target for mGluR2. Because the newly discovered mGluR2 agonists are structurally different with T_c values ranging from 0.57 to 0.92, all of them can be considered for further de novo design methods.     

Discovery of LRRK2 inhibitors by using an ensemble of virtual screening methods

In this paper, we present the results of a ligand- and structure-based virtual screen targeting LRRK2, a kinase that has been implicated in Parkinson’s disease. For the ligand-based virtual screen, the structures of 12 competitor compounds were used as queries for a variety of 2D and 3D searches. The structure-based virtual screen relied on homology models of LRRK2, as no X-ray structure is currently available in the public domain. From the virtual screening, 662 compounds were purchased, of which 35 showed IC₅₀ values below 10 μM in wild-type and/or mutant LRRK2 (a hit rate of 5.3%). Of these 35 hits, four were deemed to have potential for medicinal chemistry follow-up.     

3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase

Abstract

Tyrosinase plays an important role in melanin biosynthesis and protects skin against ultraviolet radiations. Functional deficiency of tyrosinase results in serious dermatological diseases. Tyrosinase also participates in neuromelanin formation in the human brain, which leads to neurodegeneration resulting in Parkinson’s disease. In fruits and vegetables, tyrosinase plays a critical role in senescence, causing undesired browning that results in faster deterioration and shorter shelf lines. The only commercially available tyrosinase is mushroom tyrosinase and it shows the highest homology to the mammalian tyrosinase. Although kojic acid is currently used as a tyrosinase inhibitor, they have serious side effects such as dermatitis, carcinogenesis and hepatotoxicity. Therefore, in order to develop a more active and safer tyrosinase inhibitor, 3D QSAR pharmacophore models were generated based on experimentally known inhibitors. The pharmacophore model, Hypo1, was developed with a large cost difference, high correlation coefficient and low RMS deviation. Hypo1 showed a good spatial arrangement; consisting of five-point features including two hydrogen bond acceptor, one hydrogen bond donor and two hydrophobic features. Hypo1 was further validated by cost analysis, test set and Fisher’s randomisation method. Hypo1 was used as a 3D query for screening the in-house drug-like databases, and the hits were further selected by applying ADMET, Lipinski’s rule of five and fit value criteria. To identify binding conformations, the obtained hits were subjected to molecular docking. Finally, molecular dynamics simulations revealed the appropriate binding modes of hit compounds. To conclude, we propose the final three hit compounds with new structural scaffolds as a virtual candidate as tyrosinase inhibitors.

Communicated by Ramaswamy H. Sarma     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.