Virtual Screening for Type II B Inhibitors of B-RafV600E Kinase

2020 ◽  
Vol 16 (3) ◽  
pp. 222-230
Author(s):  
Kai-Xiong Qiu ◽  
Wen Zhang ◽  
Fang Yu ◽  
Wei Li ◽  
Zhong-Wen Sun ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Cell Lines ◽  
Binding Free Energy ◽  
Type Ii ◽  
Combined Approach ◽  
Pharmacophore Modelling ◽  
A375 Cell ◽  
Important Target ◽  
Zinc Database ◽  
Inhibitory Activities

Background: B-RafV600E kinase was identified as an important target in current cancer treatment, and the type II B inhibitors show good qualities in preclinical studies. Therefore, it is very important to discover novel II B inhibitors of B-RafV600E kinase. Methods: In order to discover novel II B inhibitors of B-RafV600E kinase, virtual screening against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3DQSAR model and binding free energy (ΔGbind) calculation studies. The inhibitory activities against A375 cell lines of the hit compounds were tested by using MTT assay. Results: Five promising hit compounds were obtained after screening, and all the five hit compounds showed good inhibitory rates against A375 cell lines. Conclusion: The combined approach of the virtual screening in our work is effective, which can be used to discover novel inhibitors with a new skeleton. In addition, the five compounds obtained from the screening showed good inhibitory rates against A375 cell lines, which can be considered to develop new II B inhibitors of B-RafV600E kinase.

scholarly journals Working Mechanism of Remdesivir and Discovering New Potential Inhibitors to SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp) using High-Throughput Virtual Screening and Molecular Dynamics Simulations .

2021 ◽  
Author(s):  
Dylan Brunt ◽  
Phillip Lakernick ◽  
CHUN WU
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Virtual Screening ◽  
Rna Polymerase ◽  
High Throughput ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Rna Dependent Rna Polymerase ◽  
Zinc Database ◽  
High Throughput Virtual Screening

Abstract RNA-dependent RNA polymerase (RdRp), is an enzyme essential component in the RNA replication within the life cycle of the severely acute respiratory coronavirus-2 (SARS-CoV-2), causing the deadly respiratory induced sickness COVID-19. Remdesivir is a prodrug that has seen some success in inhibiting this enzyme, however there is still the pressing need for effective alternatives. In this study, we present the discovery of four non-nucleoside small molecules that bind favorably to RdRp over adenosine-triphosphate (ATP) and active-form remdesivir-triphosphate (RTP) using high-throughput virtual screening (HTVS) coupled with extensive (total 4800 ns) molecular dynamics (MD) simulations with using the ZINC compounds database against SARS-CoV-2 RdRp (PDB: 7BV2). We found that the simulations with both ATP and RTP remained stable for the duration of their trajectories, and it was revealed that the phosphate tail of RTP was stabilized by a positive amino acid pocket near the entry channel of RTP and magnesium ions containing residues K551, R553, R555 and K621. It was also found that residues D623, D760, and N691 further stabilized the ribose portion of RTP with U10 on the template RNA strand forming hydrogen pairs with the adenosine motif. Using these models of RdRp, we employed them to screen the ZINC database of ~17 million molecules. Using docking and drug properties scoring, we narrowed down our selection to fourteen candidates. These were subjected to 200 ns simulations each underwent free energy calculations. We identified four hit compounds from the ZINC database that have similar binding poses to RTP while possessing lower overall binding free energies, with ZINC097971592 having a binding free energy two times lower than RTP.

scholarly journals In Silico Study to Identify New Antituberculosis Molecules from Natural Sources by Hierarchical Virtual Screening and Molecular Dynamics Simulations

2019 ◽  
Vol 12 (1) ◽  
pp. 36 ◽  
Author(s):  
Vinícius Pinto ◽  
Janay Araújo ◽  
Rai Silva ◽  
Glauber da Costa ◽  
Jorddy Cruz ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Virtual Screening ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Binding Free Energy ◽  
Natural Sources ◽  
Biological Targets ◽  
Zinc Database ◽  
Dual Action ◽  
Dynamics Simulations

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, responsible for 1.5 million documented deaths in 2016. The increase in reported cases of M. tuberculosis resistance to the main drugs show the need for the development of new and efficient drugs for better TB control. Based on these facts, this work aimed to use combined in silico techniques for the discovery of potential inhibitors to β-ketoacyl-ACP synthase (MtKasA). Initially compounds from natural sources present in the ZINC database were selected, then filters were sequentially applied by virtual screening, initially with pharmacophoric modeling, and later the selected compounds (based on QFIT scores) were submitted to the DOCK 6.5 program. After recategorization of the variables (QFIT score and GRID score), compounds ZINC35465970 and ZINC31170017 were selected. These compounds showed great hydrophobic contributions and for each established system 100 ns of molecular dynamics simulations were performed and the binding free energy was calculated. ZINC35465970 demonstrated a greater capacity for the KasA enzyme inhibition, with a ΔGbind = −30.90 kcal/mol and ZINC31170017 presented a ΔGbind = −27.49 kcal/mol. These data can be used in other studies that aim at the inhibition of the same biological targets through drugs with a dual action.

scholarly journals Revealing SARS-CoV-2 Functional Druggability Through Multi-Target Cadd Screening of Repurposable Drugs

2020 ◽  
Author(s):  
Yash Gupta ◽  
Dawid Maciorowski ◽  
Raman Mathur ◽  
Catherine M. Pearce ◽  
David J. Ilc ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Active Sites ◽  
Binding Free Energy ◽  
Development Program ◽  
Dynamics Simulation ◽  
Protein Preparation ◽  
Target Drug ◽  
Zinc Database ◽  
Investigational Drugs ◽  
Energy Perturbation

The emergence of SARS/MERS drug resistant COVID-19 with high transmission and mortality has recently been declared a deadly pandemic causing economic chaos and significant health problems. Like all coronaviruses, SARS-CoV-2 is a large virus that has many druggable components within its proteome. In this study, we focused on repurposing approved and investigational drugs by identifying potential drugs that are predicted to effectively inhibit critical enzymes within SARS-CoV-2. We shortlisted seven target proteins with enzymatic activities known to be essential at different stages of the virus life cycle. For virtual screening, the energy minimization of a crystal structure or modeled protein was carried out using Protein Preparation Wizard (Schrödinger LLC, 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs (n=5903) that are already approved by worldwide regulatory bodies including the FDA, using the ZINC database. Screening was performed against viral targets using three sequential docking modes (i.e. HTVS, SP and XP). Our in-silico virtual screening identified ~290 potential drugs based on the criteria of energy, docking parameters, ligand and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. A top lead from each target group was further subjected to molecular dynamics simulation (MDS) using the Desmond module to validate the efficacy of the screening pipeline. All of the simulated hit-target complexes were predicted to strongly interact and with highly stable binding. Thus, we have identified a number of approved and investigational drugs with high likelihood of inhibiting a variety of key SARS-CoV-2 proteins. Follow-up studies will continue to identify inhibitors suitable for combination therapy based on drug-drug synergy to thwart resistance. In addition, the screening hits that we have identified provide excellent probes for understanding the binding properties of the active sites of all seven targets, further enabling us to derive consensus molecules through computer-aided drug design (CADD). While infections are expanding at a rampant pace, it must be recognized that resistance will grow commensurately through either genetic shift and/or genetic drift to all small molecule drugs identified. Vaccines should provide a more permanent solution through prevention, but resistivity is still a possible scenario. Nevertheless, a persistent multi-target drug development program is essential to curb this ongoing pandemic and to keep reemergence in check.

Machine Learning-based Virtual Screening Strategy Reveals Some Natural Compounds As Potential PAK4 Inhibitors In Triple Negative Breast Cancer

2020 ◽  
Vol 18 ◽  
Author(s):  
Opeyemi Iwaloye ◽  
Olusola Olalekan Elekofehinti ◽  
Babatomiwa Kikiowo ◽  
Emmanuel Ayo Oluwarotimi ◽  
Toyin Mary Fadipe
Keyword(s):  
Breast Cancer ◽  
Virtual Screening ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Energy Calculation ◽  
Reference Drug ◽  
Predictive Quality

Background: P-21 activating kinase 4 (PAK4) is implicated in poor prognosis of many cancers, especially in the progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug candidates as PAK4 inhibitors for breast cancer therapy. Objective: This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach. Methods: An e-pharmacophore model was developed from docked PAK4-coligand complex and used to screen over a thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learningbased approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028, RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations were accessed to determine the predictive quality of the model. Finally the binding free energy calculation was computed. Results: The robustness/predictive quality of the models were affirmed. The hits had better binding affinity than the reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential inhibitors that are predicted to bind with PAK4 better than reference drug tamoxifen. The three potent novel inhibitors vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively while showing moderation for ADME properties and inhibition constant. Conclusion: It is expected that the findings reported in this study may provide insight for designing effective and less toxic PAK4 inhibitors for triple negative breast cancer.

Isolation of New Glycosides from Anemarrhena Asphodeloides Rhizome and Screening of their Anticancer Activity

2019 ◽  
Vol 16 (6) ◽  
pp. 474-477 ◽  
Author(s):  
Pham Van Khang ◽  
Nguyen Thi Hien Lan ◽  
Le Quang Truong ◽  
Mai Thi Minh Chau ◽  
Mai Xuan Truong ◽  
...  
Keyword(s):  
Anticancer Activity ◽  
Spectral Data ◽  
Cell Lines ◽  
Cancer Cell ◽  
Spectroscopic Analysis ◽  
2D Nmr ◽  
Ic50 Values ◽  
Nmr Techniques ◽  
Inhibitory Activities ◽  
Anemarrhena Asphodeloides

In this report, two new steroidal glycosides were isolated and determined from n-butanol fraction of A.asphodeloides. The structures were confirmed in comparison with the spectral data of known compounds by using different spectroscopic analysis approaches including 1D & 2D-NMR techniques and HRMS. The anti-proliferation screening against cancer cell lines A549 and HeLa indicated that compound 1 exhibited good inhibitory activities with IC50 values of 0.79 and 0.55 µg/mL, respectively.

Design, Synthesis and Biological Evaluation: 5-amino-1H-pyrazole-1- carbonyl derivatives as FGFR Inhibitors

2020 ◽  
Vol 17 (11) ◽  
pp. 1330-1341
Author(s):  
Yan Zhang ◽  
Niefang Yu
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Biological Evaluation ◽  
Human Gastric Cancer ◽  
Design Synthesis ◽  
Carbonyl Derivatives ◽  
Ic50 Values ◽  
Inhibitory Activities

Background: Fibroblast growth factors (FGFs) and their high affinity receptors (FGFRs) play a major role in cell proliferation, differentiation, migration, and apoptosis. Aberrant FGFR signaling pathway might accelerate development in a broad panel of malignant solid tumors. However, the full application of most existing small molecule FGFR inhibitors has become a challenge due to the potential target mutation. Hence, it has attracted a great deal of attention from both academic and industrial fields for hunting for novel FGFR inhibitors with potent inhibitory activities and high selectivity. Objective: Novel 5-amino-1H-pyrazole-1-carbonyl derivatives were designed, synthesized, and evaluated as FGFR inhibitors. Methods: A series of 5-amino-1H-pyrazole-1-carbonyl derivatives were established by a condensation of the suitable formyl acetonitrile derivatives with either hydrazine or hydrazide derivatives in the presence of anhydrous ethanol or toluene. The inhibitory activities of the target compounds were screened against the FGFRs and two representative cancer cell lines. Tests were carried out to observe the inhibition of 8e against FGFR phosphorylation and downstream signal phosphorylation in human gastric cancer cell lines (SNU-16). The molecular docking of all the compounds were performed using Molecular Operating Environment in order to evaluate their binding abilities with the corresponding protein kinase. Results: A series of 5-amino-1H-pyrazole-1-carbonyl derivatives have been designed and synthesized, screened for their inhibitory activities against FGFRs and cancer cell lines. Most of the target compounds showed moderate to good anti-proliferate activities against the tested enzymes and cell lines. The most promising compounds 8e suppressed FGFR1-3 with IC50 values of 56.4, 35.2, 95.5 nM, and potently inhibited the SNU-16 and MCF-7 cancer cells with IC50 values of 0.71 1.26 μM, respectively. And 8e inhibited the growth of cancer cells containing FGFR activated by multiple mechanisms. In addition, the binding interactions were quite similar in the molecular models between generated compounds and Debio-1347 with the FGFR1. Conclusion: According to the experimental findings, 5-amino-1H-pyrazole-1-carbonyl might serve as a promising template of an FGFR inhibitor.

Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis

2019 ◽  
Vol 15 (6) ◽  
pp. 588-601 ◽  
Author(s):  
Mahmoud A. Al-Sha'er ◽  
Rua'a A. Al-Aqtash ◽  
Mutasem O. Taha
Keyword(s):  
Virtual Screening ◽  
Inflammatory Diseases ◽  
Qsar Model ◽  
Qsar Analysis ◽  
Pharmacophore Modelling ◽  
Physicochemical Descriptors ◽  
Qsar Modelling ◽  
Ic50 Values ◽  
Phosphoinositide 3 Kinase ◽  
Pharmacophore Models

<P>Background: PI3K&#948; is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3K&#948; inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3K&#948; binding. </P><P> Methods: Seventeen PI3K&#948; crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon combination with other physicochemical descriptors). </P><P> Results: The best QSAR model (r2 = 0.71, r2 LOO = 0.70, r2 press against external testing list of 15 compounds = 0.80) included a single crystallographic pharmacophore of optimal explanatory qualities. The resulting pharmacophore and QSAR model were used to screen the National Cancer Institute (NCI) database for new PI3Kδ inhibitors. Two hits showed low micromolar IC50 values. </P><P> Conclusion: Crystallography-based pharmacophores were successfully combined with QSAR analysis for the identification of novel PI3K&#948; inhibitors.</P>

The Research of New Inhibitors of Bacterial Methionine Aminopeptidase by Structure Based Virtual Screening Approach of ZINC DATABASE and In Vitro Validation

2020 ◽  
Vol 16 (4) ◽  
pp. 389-401 ◽  
Author(s):  
Hanane Boucherit ◽  
Abdelouahab Chikhi ◽  
Abderrahmane Bensegueni ◽  
Amina Merzoug ◽  
Jean-Michel Bolla
Keyword(s):  
Virtual Screening ◽  
Bacterial Survival ◽  
Methionine Aminopeptidase ◽  
Bacterial Strains ◽  
Microdilution Method ◽  
Zinc Database ◽  
Promising Target ◽  
New Antibiotics ◽  
Potential Inhibitors

Background: The great emergence of multi-resistant bacterial strains and the low renewal of antibiotics molecules are leading human and veterinary medicine to certain therapeutic impasses. Therefore, there is an urgent need to find new therapeutic alternatives including new molecules in the current treatments of infectious diseases. Methionine aminopeptidase (MetAP) is a promising target for developing new antibiotics because it is essential for bacterial survival. Objective: To screen for potential MetAP inhibitors by in silico virtual screening of the ZINC database and evaluate the best potential lead molecules by in vitro studies. Methods: We have considered 200,000 compounds from the ZINC database for virtual screening with FlexX software to identify potential inhibitors against bacterial MetAP. Nine chemical compounds of the top hits predicted were purchased and evaluated in vitro. The antimicrobial activity of each inhibitor of MetAP was tested by the disc-diffusion assay against one Gram-positive (Staphylococcus aureus) and two Gram-negative (Escherichia coli & Pseudomonas aeruginosa) bacteria. Among the studied compounds, compounds ZINC04785369 and ZINC03307916 showed promising antibacterial activity. To further characterize their efficacy, the minimum inhibitory concentration was determined for each compound by the microdilution method which showed significant results. Results: These results suggest compounds ZINC04785369 and ZINC03307916 as promising molecules for developing MetAP inhibitors. Conclusion: Furthermore, they could therefore serve as lead molecules for further chemical modifications to obtain clinically useful antibacterial agents.

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