Hybrid Virtual Screening Research Articles

Identification of Novel Covalent XPO1 Inhibitors Based on a Hybrid Virtual Screening Strategy.

Nuclear export protein 1 (XPO1), a member of the nuclear export protein-p (Karyopherin-P) superfamily, regulates the transport of “cargo” proteins. To facilitate this important process, which is essential for cellular homeostasis, XPO1 must first recognize and bind the cargo proteins. To inhibit this process, small molecule inhibitors have been designed that inhibit XPO1 activity through covalent binding. However, the scaffolds for these inhibitors are very limited. While virtual screening may be used to expand the diversity of the XPO1 inhibitor skeleton, enormous computational resources would be required to accomplish this using traditional screening methods. In the present study, we report the development of a hybrid virtual screening workflow and its application in XPO1 covalent inhibitor screening. After screening, several promising XPO1 covalent molecules were obtained. Of these, compound 8 performed well in both tumor cell proliferation assays and a nuclear export inhibition assay. In addition, molecular dynamics simulations were performed to provide information on the mode of interaction of compound 8 with XPO1. This research has identified a promising new scaffold for XPO1 inhibitors, and it demonstrates an effective and resource-saving workflow for identifying new covalent inhibitors.

Hybrid Pharmacophore- and Structure-Based Virtual Screening Pipeline to Identify Novel EGFR Inhibitors That Suppress Non-Small Cell Lung Cancer Cell Growth.

Dysregulated epidermal growth factor receptor (EGFR) expression is frequently observed in non-small cell lung cancer (NSCLC) growth and metastasis. Despite recent successes in the development of tyrosine kinase inhibitors (TKIs), inevitable resistance to TKIs has led to urgent calls for novel EGFR inhibitors. Herein, we report a rational workflow used to identify novel EGFR-TKIs by combining hybrid ligand- and structure-based pharmacophore models. Three types of models were developed in this workflow, including 3D QSAR-, common feature-, and structure-based EGFR-TK domain-containing pharmacophores. A National Cancer Institute (NCI) compound dataset was adopted for multiple-stage pharmacophore-based virtual screening (PBVS) of various pharmacophore models. The six top-scoring compounds were identified through the PBVS pipeline coupled with molecular docking. Among these compounds, NSC609077 exerted a significant inhibitory effect on EGFR activity in gefitinib-resistant H1975 cells, as determined by an enzyme-linked immunosorbent assay (ELISA). Further investigations showed that NSC609077 inhibited the anchorage-dependent growth and migration of lung cancer cells. Furthermore, NSC609077 exerted a suppressive effect on the EGFR/PI3K/AKT pathway in H1975 cells. In conclusion, these findings suggest that hybrid virtual screening may accelerate the development of targeted drugs for lung cancer treatment.

Discover Novel Covalent Inhibitors Targeting FLT3 through Hybrid Virtual Screening Strategy

FMS-like tyrosine kinase 3 (FLT3) plays a very important role in regulating the proliferation, differentiation and survival of normal hematopoietic stem cells. Internal tandem duplications of the FLT3 gene (FLT3-ITD) mutations are present in 25% of all acute myeloid leukemia (AML) patients and are frequently associated with adverse clinical outcomes. Therefore, FLT3-ITD is a promising target for the treatment of AML. The use of covalent virtual screenings has shown that efficient rational approaches for the rapid discovery of new drugs scaffold. Herein, we report a hybrid virtual screening strategy that led to the discovery of FLT3 inhibitors. Using the combination of non-covalent docking and covalent docking, 8 compounds were found to inhibit FLT3, and G856-8335, S346-0154 are also effective against mutant FLT3. These two compounds also show selectivity to receptor tyrosine kinase (C-KIT), which has the potential for optimization. And this work can be extended to the screening of other covalent inhibitors.

Discovery of novel Staphylococcus aureus penicillin binding protein 2a inhibitors by multistep virtual screening and biological evaluation

Penicillin-binding protein 2a (PBP2a) is an essential protein involved in the resistance to β-lactam antibiotics acquired by methicillin-resistant Staphylococcus aureus (MRSA) and is a potential antibacterial target. In the current study, we employed a strategy that combined virtual screening with biological evaluation to discover novel inhibitors of PBP2a. In this investigation, a hybrid virtual screening method, consisting of drug-likeness evaluation (Lipinski’s Rule of Five and ADMET) and rigid (LibDock) and semi-flexible (CDOCKER) docking-based virtual screenings, was used for retrieving novel PBP2a inhibitors from commercially available chemical databases. 11 compounds were selected from the final hits and subsequently shifted to experimental studies. Among them, Hit 2, Hit 3, and Hit 10 exhibited excellent anti-MRSA ATCC 33591 activity and weak toxicity in vitro. The affinity of the three compounds to bind to PBP2a was further confirmed by surface plasmon resonance (SPR) experiments and molecular dynamics (MD) simulation. An inter-complex interaction study showed that all hit compounds adapted well to the allosteric site of the PBP2a protein. In addition, Hit 2 (with best binding affinity to PBP2a, KD = 1.29 × 10−7 M) significantly inhibits proliferation of MRSA clinical isolates. Together, the 3 hit compounds, especially Hit 2, may be potential non-β-lactam antibiotics against MRSA and the work will provide clues for the future development of specific compounds that block the interaction of PBP2a with their targets.

Identification of novel CDK 9 inhibitors based on virtual screening, molecular dynamics simulation, and biological evaluation

AimsCyclin-dependent kinase 9 (CDK9) is a member of the CDK subfamily and plays a major role in the regulation of transcriptional elongation. It has attracted widespread attention as a therapeutic target for cancer. Here, we aimed to explore novel CDK 9 inhibitors by using a hybrid virtual screening strategy. Main methodsA hybrid virtual screening strategy was constructed with computer-aided drug design (CADD). First, compounds were filtered in accordance with Lipinski's rule of five and adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Second, a 3D-QSAR pharmacophore model was built and used as a 3D query to screen the obtained hit compounds. Third, the hit compounds were subjected to molecular docking studies. Fourth, molecular dynamics (MD) simulations were performed on CDK9 in complex with the final hits to examine the structural stability. Finally, CDK9 kinase biochemical assay was performed to identify the biological activity of the hit compounds. Key findingsSeven hit compounds were screened out. These hit compounds showed drug-like properties in accordance with Lipinski's rule of five and ADMET. Complexes involving the six hit compounds bound to CDK9 exhibited good structural stability in the MD simulation. Furthermore, these six hit compounds had strong inhibitory activity against CDK9 kinase. In particular, hit 3 showed the most promising activity with the percentage of 71%. SignificanceThe six hit compounds may be promising novel CDK9 inhibitors, and the hybrid virtual screening strategy designed in this study provides an important reference for the design and synthesis of novel CDK9 inhibitors.

Histamine H3 receptor ligands by hybrid virtual screening, docking, molecular dynamics simulations, and investigation of their biological effects.

Histamine H3 receptors (H3 R), belonging to G-protein coupled receptors (GPCR) class A superfamily, are responsible for modulating the release of histamine as well as of other neurotransmitters by a negative feedback mechanism mainly in the central nervous system (CNS). These receptors have gained increased attention as therapeutic target for several CNS related neurological diseases. In the current study, we aimed to identify novel H3 R ligands using in silico virtual screening methods. To this end, a combination of ligand- and structure-based approaches was utilized for screening of ZINC database on the homology model of human H3 R. Structural similarity- and pharmacophore-based approaches were employed to generate compound libraries. Various molecular modeling methodologies such as molecular docking and dynamics simulation along with different drug likeness filtering criteria were applied to select anti-H3 R ligands as promising candidate molecules based on different known parent lead compounds. In vitro binding assays of the selected molecules demonstrated three of them being active within the micromolar and submicromolar Ki range. The current integrated computational and experimental methods used in this work can provide new general insights for systematic hit identification for novel anti-H3 R agents from large compound libraries.

Identification of novel dual-specificity phosphatase 26 inhibitors by a hybrid virtual screening approach based on pharmacophore and molecular docking.

Dual-specificity phosphatase 26 (DUSP26) has recently emerged as a target for treatment of human cancers. However, only two small-molecule inhibitors of DUSP26 are known so far, namely NSC-87877 and ethyl-3, 4-dephostatin. DUSP26 contains an N-terminal region (residues 1-60) and a conserved C-terminal catalytic domain (residues 61-211, DUSP26-C). The crystal structure of DUSP26-C, showing a catalytically inactive conformation of the active site, was reported in a previous study. However, the detailed catalytic mechanism of DUSP26 cannot be described based on that structure. In this study, the 3D structure of DUSP26 (residues 42-211) adopting catalytically active conformation, was built by homology modeling, and the established 3D structure was validated using enzyme kinetic assays. Pharmacophore modeling based on the validated 3D structure of human DUSP26 was carried out. The established pharmacophore model was considered as a 3D query for retrieving novel DUSP26 inhibitors from the chemical databases "Diversity Libraries" (129,087 compounds). Next, a docking study was performed to refine the obtained hit compounds. Then a total of 100 compounds were selected based on the ranking order and visual examination, which were then evaluated by an enzyme-based assay. Eight compounds were found to have inhibitory activities against DUSP26, and the most potent compound was assigned No. F1063-0967 with an IC50 value of 11.62μM. The inhibitory activity of F1063-0967 against DUSP26 is higher than that of NCS87877 (IC50 value: 16.67±2.89μM), but lower than that of ethyl-3, 4-dephostatin (IC50 value: 6.8±0.41μM). MTT assay results revealed that F1063-0967 can induce apoptosis in IMR-32 cell line with an IC50 value of 4.13μM. These results suggest that F1063-0967 should be investigated further for other pharmacological properties.

Homology modeling and virtual screening for inhibitors of lipid kinase PI(4)K from Plasmodium.

Malaria parasite strains have emerged to tolerate the therapeutic effects of the prophylactics and drugs presently available. Recent studies have shown that KAI715 and its analogs inhibit malaria parasites growth by binding to lipid kinase PI(4)K (phosphatidylinositol-4-OH kinase) of the parasites. Therefore, targeting PI(4)K may open up new avenues of target-based drug discovery to identify novel anti-malaria drugs. In this investigation, we describe the discovery of novel potent PfPI(4)K (PI(4)K from P. falciparum) inhibitors by employing a proposed hybrid virtual screening (VS) method, including pharmacophore model, drug-likeness prediction and molecular docking approach. 3D structure of PfPI(4)K has been established by homology modeling. Pharmacophore model HypoA of PfPI(4)K inhibitors has been developed based on the ligand complexed with its corresponding receptor. 174 compounds with good ADMET properties were carefully selected by a hybrid virtual screening method. Finally, the 174 hits were further validated by using a new pharmacophore model HypoB built based on the docking pose of BQR685, and 95 compounds passed the last filter. These compounds would be further evaluated by biological activity assays. The molecular interactions of the top two potential inhibitors with the active site residues are discussed in detail. These identified hits can be further used for designing the more potent inhibitors against PfPI(4)K by scaffold hopping, and deserve consideration for further structure-activity relationship (SAR) studies.

Identification and Validation Novel of VIM-2 Metallo-β-lactamase Tripeptide Inhibitors.

The development of novel inhibitors against metallo-β-lactamase is essential to remedy metallo-β-lactamase mediated bacterial resistance. A recently emerged metallo-β-lactamase, VIM-2, has demonstrated resistance to existing β-lactamase inhibitors in the clinic. In this study, a hybrid virtual screening protocol that combines pharmacophore modeling, molecular docking, and calculation of binding free energy was employed to screen an internal tripeptide database for novel inhibitors against VIM-2. This resulted in four tripeptides (WWC, WCW, MCW, YCW) as potential inhibitors, and their effects on VIM-2 metallo-β-lactamase were subsequently tested in vitro. Significantly, two peptides (MCW, YCW) exhibited potent inhibitory activities with IC50 values of 18.15 µM and 52.9 µM, respectively. To our knowledge, this is the first study that employed the hybrid virtual screening of combinational peptide database and discovered potent peptide inhibitors of VIM-2 metallo-β-lactamase.

Computer-aided Identification of Novel DprE1 Inhibitors as Potential Anti-TB Lead Compounds: A Hybrid Virtual-screening and Molecular Dynamics Approach

Computer-aided Identification of Novel DprE1 Inhibitors as Potential Anti-TB Lead Compounds: A Hybrid Virtual-screening and Molecular Dynamics Approach

Virtual screening for the identification of novel inhibitors of Mycobacterium tuberculosis cell wall synthesis: Inhibitors targeting RmlB and RmlC

BackgroundTuberculosis remains one of the deadliest infectious diseases in humans. It has caused more than 100 million deaths since its discovery in 1882. Currently, more than 5 million people are infected with TB bacterium each year. The cell wall of Mycobacterium tuberculosis plays an important role in maintaining the ability of mycobacteria to survive in a hostile environment. Therefore, we report a virtual screening (VS) study aiming to identify novel inhibitors that simultaneously target RmlB and RmlC, which are two essential enzymes for the synthesis of the cell wall of M. tuberculosis. MethodsA hybrid VS method that combines drug-likeness prediction, pharmacophore modeling and molecular docking studies was used to indentify inhibitors targeting RmlB and RmlC. ResultsThe pharmacophore models HypoB and HypoC of RmlB inhibitors and RmlC inhibitors, respectively, were developed based on ligands complexing with their corresponding receptors. In total, 20 compounds with good absorption, distribution, metabolism, excretion, and toxicity properties were carefully selected using the hybird VS method. DiscussionWe have established a hybrid VS method to discover novel inhibitors with new scaffolds. The molecular interactions of the selected potential inhibitors with the active-site residues are discussed in detail. These compounds will be further evaluated using biological activity assays and deserve consideration for further structure-activity relationship studies.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity.

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents.

Structure modeling and hybrid virtual screening study of Alzheimer’s associated protease kallikrein 8 for the identification of novel inhibitors

Kallikrein 8 (KLK8) is an extra cellular serine protease which is responsible for nerve growth, and degeneration and nervous plasticity have been associated with Alzheimer’s disease. In silico analysis of KLK8 has not been performed until now. This study is aimed at molecular modeling and lead identification for a potent inhibitor. The hybrid of ligand- and structure-based virtual screening was applied on commercially available compounds. Ligand similarity search was employed, followed by ligand docking protocol. Compound’s potential for their activity was deduced from docking scores and their interactions with the active site. For active permeation of compounds through blood brain barrier, their molecular properties were checked with previously reported compounds. The compound that showed the most potential according to criteria was 1-(3,5-difluorophenyl)-5-hydroxy-7-(4-hydroxy-3,5-dimethoxyphenyl)-6,7-dihydro-1H-pyrrolo[3,2-b] pyridine-3-carboxylic acid (ZINC 61720639).

Combination of pharmacophore hypothesis, genetic function approximation model, and molecular docking to identify novel inhibitors of S6K1

S6K1 has emerged as a potential target for the treatment for obesity, type II diabetes and cancer diseases. Discovery of S6K1 inhibitors has thus attracted much attention in recent years. In this investigation, a hybrid virtual screening method that involves pharmacophore hypothesis, genetic function approximation (GFA) model, and molecular docking technology has been used to discover S6K1 inhibitors especially with novel scaffolds. The common feature pharmacophore hypothesis and GFA regression model of S6K1 inhibitors were first developed and applied in a virtual screen of the Specs database for retrieving S6K1 inhibitors. Then, the molecular docking method was carried out to re-filter these screened compounds. Finally, 60 compounds with promising S6K1 inhibitory activity were carefully selected and have been handed over to the other group to complete the follow-up compound synthesis (or purchase) and activity test.Electronic supplementary materialThe online version of this article (doi:10.1007/s11030-013-9473-7) contains supplementary material, which is available to authorized users.

Identification of Novel Gyrase B Inhibitors as Potential Anti-TB drugs: Homology Modelling, Hybrid Virtual Screening and Molecular Dynamics Simulations

Using an integrated computational approach involving homology modelling, pharmacophore/structure-based virtual screening, molecular dynamics simulations and per-residue energy contribution, 10 compounds were proposed as potential TB inhibitors. Via validated docking calculations, binding free energy calculations showed that the proposed compounds presented better binding affinity with DNA gyrase B when compared to novobiocin. The compiled in silico approach employed in this study may serve as a useful tool in the process of the design and development of drugs, not only against TB, but also for a wide range of biological systems.

Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents.

Discovery of Novel Focal Adhesion Kinase Inhibitors Using a Hybrid Protocol of Virtual Screening Approach Based on Multicomplex-Based Pharmacophore and Molecular Docking

Focal adhesion kinase (FAK) is a tyrosine kinase that functions as a key orchestrator of signals leading to invasion and metastasis. In the current study, the multicomplex-based pharmacophore (MCBP)-guided method has been suggested to generate a comprehensive pharmacophore of FAK kinase based on seven crystal structures of FAK-inhibitor complexes. In this investigation, a hybrid protocol of virtual screening methods, comprising of pharmacophore model-based virtual screening (PB-VS) and docking-based virtual screening (DB-VS), is used for retrieving new FAK inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen several chemical databases, including the Specs (202,408 compounds) database. Thirty-five compounds were selected from the final hits and should be shifted to experimental studies. These results may provide important information for further research of novel FAK inhibitors.

Retrieving novel C5aR antagonists using a hybrid ligand-based virtual screening protocol based on SVM classification and pharmacophore models

C5aR antagonists have been thought as potential immune mediators in various inflammatory and autoimmune diseases, and discovery of C5aR antagonists has attracted much attention in recent years. The discovery of C5aR antagonists was usually achieved through high-throughput screening, which usually suffered a high cost and a low success rate. Currently, the fast developing computer-aided virtual screening (VS) methods provide economic and rapid approaches to the lead discovery. In this account, we proposed a hybrid ligand-based VS protocol that is based on support vector machine (SVM) classification and pharmacophore models for retrieving novel C5aR antagonists. Performance evaluation of this hybrid VS protocol in virtual screening against a large independent test set, T-CHEM, showed that the hybrid VS approach significantly increased the hit rate and enrichment factor compared with the individual SVM classification model-based VS and pharmacophore model-based VS, as well as molecular docking-based VS in that the receptor structure was created by homology modeling. The hybrid VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally, a total of 20 compounds were selected from the top ranking hits, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future.

Discovery of Novel Bruton’s Tyrosine Kinase Inhibitors Using a Hybrid Protocol of Virtual Screening Approaches Based on SVM Model, Pharmacophore and Molecular Docking

Bruton's tyrosine kinase has emerged as a potential target for the treatment for B-cell malignancies and autoimmune diseases. Discovery of Bruton's tyrosine kinase inhibitors has thus attracted much attention recently. In this investigation, we introduced a hybrid protocol of virtual screening methods including support vector machine model-based virtual screening, pharmacophore model-based virtual screening and docking-based virtual screening for retrieving new Bruton's tyrosine kinase inhibitors from commercially available chemical databases. Performances of the hybrid virtual screening approach were evaluated against a test set, which results showed that the hybrid virtual screening approach significantly shortened the overall screening time, and considerably increased the hit rate and enrichment factor compared with the individual method (SB-VS, PB-VS and DB-VS) or their combinations by twos. This hybrid virtual screening approach was then applied to screen several chemical databases including Specs (202,408 compounds) and Enamine (980,000 compounds) databases. Thirty-nine compounds were selected from the final hits and have been shifted to experimental studies.

Identification of Novel Polo‐like Kinase 1 Inhibitors by a Hybrid Virtual Screening

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC(50) value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.