Structure-based Pharmacophore Research Articles

The search for peptide deformylase inhibitor from Indonesian Medicinal Plant Database: an in-silico investigation

The peptide deformylase protein (PDF) has emerged as a promising target for the discovery of novel antibiotics with a novel mechanism of action. The current investigation was aimed at identifying potential inhibitor of PDF by using structure-based pharmacophore modelling. The pharmacophore hypothesis consisted of one hydrophobic, one negative ionizable, and one hydrogen bond donor features which were built using the structure of cognate ligand of PDF (BB2). Further, the pharmacophore model was validated and used to screen hit molecule against Indonesian Medicinal Plant Database and retrieved 32 hit molecules. All hit molecules were docked to PDF and four best molecules were subjected for 50-ns molecular dynamics (MD) simulation. MD simulation confirmed the docked poses of ligand as indicated by the RMSD and RMSF values. Prediction of affinities employing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method revealed that quercetin 3-(6''-malonylneohesperidoside) had a comparable affinity with that of BB2, which indicated its potential as a novel herbal-based PDF inhibitor.

Identification and Biological Evaluation of CK2 Allosteric Fragments through Structure-Based Virtual Screening.

Casein kinase II (CK2) is considered as an attractive cancer therapeutic target, and recent efforts have been made to develop its ATP-competitive inhibitors. However, achieving selectivity with respect to related kinases remains challenging due to the highly conserved ATP-binding pocket of kinases. Allosteric inhibitors, by targeting the much more diversified allosteric site relative to the highly conserved ATP-binding pocket, might be a promising strategy with the enhanced selectivity and reduced toxicity than ATP-competitive inhibitors. The previous studies have highlighted the traditional serendipitousity of discovering allosteric inhibitors owing to the complicate allosteric modulation. In this current study, we identified the novel allosteric inhibitors of CK2α by combing structure-based virtual screening and biological evaluation methods. The structure-based pharmacophore model was built based on the crystal structure of CK2α-compound 15 complex. The ChemBridge fragment library was searched by evaluating the fit values of these molecules with the optimized pharmacophore model, as well as the binding affinity of the CK2α-ligand complexes predicted by Alloscore web server. Six hits forming the holistic interaction mechanism with the αD pocket were retained after pharmacophore- and Alloscore-based screening for biological test. Compound 3 was found to be the most potent non-ATP competitive CK2α inhibitor (IC50 = 13.0 μM) with the anti-proliferative activity on A549 cancer cells (IC50 = 23.1 μM). Our results provide new clues for further development of CK2 allosteric inhibitors as anti-cancer hits.

Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study.

c-Met kinase plays a critical role in a myriad of human cancers, and a massive scientific work was devoted to design more potent inhibitors. In this study, 16 molecular dynamics simulations of different complexes of potent c-Met inhibitors with U-shaped binding mode were carried out regarding the dynamic ensembles to design novel potent inhibitors. A cluster analysis was performed, and the most representative frame of each complex was subjected to the structure-based pharmacophore screening. The GOLD docking program investigated the interaction energy and pattern of output hits from the virtual screening. The most promising hits with the highest scoring values that showed critical interactions with c-Met were presented for ADME/Tox analysis. The screening yielded 45,324 hits that all of them were subjected to the docking studies and 10 of them with the highest-scoring values having diverse structures were presented for ADME/Tox analyses. The results indicated that all the hits shared critical Pi-Pi stacked and hydrogen bond interactions with Tyr1230 and Met1160 respectively.

Identification of CHK1 Kinase Inhibitors Using Structure-Based Pharmacophore Modeling and Molecular Docking

The checkpoint kinase, CHK1 plays an important role in repairing DNA damage induced by genotoxic agents for cancer treatment, which renders the cells resistant to such treatment modalities. Therefore, its inhibition appeared as a highly attractive strategy to re-sensitize cancer cells to the DNA damaging chemo and radiotherapies. In this study, a structure-based drug design approach was employed to identify potential ATP competitive CHK1 inhibitors. To this end, 3 crystal structures of CHK1 in complex with ATP competitive inhibitors were utilized to generate structure-based pharmacophore models that were subsequently used for virtual screening of commercial databases. Retrieved hits were filtered, then they were docked into the binding site of the enzyme and the free binding energies of the top-ranked docked hits were calculated. Based on the in silico results, 10 compounds were selected and their CHK1 inhibitory potential was evaluated in vitro. Noteworthy, in this exploratory study compounds 7 and 9 showed moderate but significant inhibition of the catalytic activity of the CHK1 enzyme. These two compounds were identified as promising hits worthy of further optimization towards designing better leads with drug like properties as potential competitive CHK1 inhibitors.

Microbiome Hijacking Towards an Integrative Pest Management Pipeline.

Pesticides are necessary to fight agricultural pests, yet they are often nonspecific, and their widespread use is a hazard to the environment and human health. The genomic era allows for new approaches to specifically target agricultural pests, based on analysis of their genome and their microbiome. We present such an approach, to combat Bactrocera oleae, a widespread pest whose impact is devastating on olive production. To date, there is no specific pesticide to control it. Herein, we propose a novel strategy to manage this pest via identifying novel pharmacological targets on the genome of its obligate endosymbiotic bacterium Candidatus Erwinia dacicola. Three genes were selected as pharmacological targets. The 3D models of the Helicase, Polymerase, and Protease-C gene products were designed and subsequently optimized by means of molecular dynamics simulations. Successively, a series of structure-based pharmacophore models were elucidated in an effort to pave the way for the efficient high-throughput virtual screening of libraries of low molecular weight compounds and thus the discovery of novel modulating agents. Our methodology provides the means to design, test, and identify highly specific pest control substances that minimize the impact of toxic chemicals on health, economy, and the environment.

Structure-based Pharmacophore Modelling for identifying VEGFR2 Inhibitor

Structure-based Pharmacophore Modelling for identifying VEGFR2 Inhibitor

Structure-Based Virtual Screening and Biological Evaluation of Peptide Inhibitors for Polo-Box Domain.

The polo-box domain of polo-like kinase 1 (PLK1-PBD) is proved to have crucial roles in cell proliferation. Designing PLK1-PBD inhibitors is challenging due to their poor cellular penetration. In this study, we applied a virtual screening workflow based on a combination of structure-based pharmacophore modeling with molecular docking screening techniques, so as to discover potent PLK1-PBD peptide inhibitors. The resulting 9 virtual screening peptides showed affinities for PLK1-PBD in a competitive binding assay. In particular, peptide 5 exhibited an approximately 100-fold increase in inhibitory activity (IC50 = 70 nM), as compared with the control poloboxtide. Moreover, cell cycle experiments indicated that peptide 5 effectively inhibited the expression of p-Cdc25C and cell cycle regulatory proteins by affecting the function of PLK1-PBD, thereby inducing mitotic arrest at the G2/M phase. Overall, peptide 5 can serve as a potent lead for further investigation as PLK1-PBD inhibitors.

Multiple-targets Directed Screening of Flavonoid Compounds from Citrus Species to find out Antimalarial Lead with Predicted Mode of Action: An In Silico and Whole Cell-based In vitro Approach.

Development of resistance by the malaria parasite Plasmodium falciparum has created challenges in the eradication of this deadly infectious disease. Hence newer strategies are adopted to combat this disease and simultaneously, new lead/hit identification is going on worldwide to develop new chemotherapeutic agents against malaria. In this study, 44 flavonoids found mainly in the fruit juice of Citrus species having traditional use in malaria-associated fever were selected for in silico multiple-target directed screening against three vital targets of the parasite namely dihydroorotate dehydrogenase (PfDHODH), dihydrofolate reductase thymidine synthase (PfDHFR-TS) and plasma membrane P-type cation translocating ATPase (PfATP4) to find out new lead molecule(s). The in silico screening was carried out using different protocols of the Biovia Discovery Studio 2018 software and Network analyzer plugin of Cytoscape 3.6.0 followed by in vitro screening of the best lead. After screening, CF8 or luteolin was found to have good binding affinity against PfDHODH and PfATP4 with -CDocker energy 42.2719 and 33.1447 with respect to their cocrystal ligands. These findings were also supported by structure-based pharmacophore, DFT (Density Functional Theory) study and finally by in vitro screening of the lead with IC50 values of 8.23 μm and 12.41 μm against 3D7 (chloroquine-sensitive) and RKL-9 (chloroquine-resistant) strain of P. falciparum, respectively. Our study found a moderately active lead molecule with the predicted mode of action which can be utilized to design some new derivatives with more safety and efficacy by targeting the two enzymes.

Discovery of a Potent PLK1-PBD Small-Molecule Inhibitor as an Anticancer Drug Candidate through Structure-Based Design.

Polo-box domain of polo-like kinase 1 (PLK1-PBD) has a pivotal role in cell proliferation and could be implicated as a potential anticancer target. Although some small-molecule inhibitors have been developed, their clinical application has been restricted by the poor selectivity. Therefore, there is an urgent need to develop effective PLK1-PBD inhibitors. Herein, we have developed a virtual screening protocol to find PLK1-PBD inhibitors by using combination of structure-based pharmacophore modeling and molecular docking. This protocol was successfully applied to screen PLK1-PBD inhibitors from specs database. MTT assay indicated that five screened hits suppressed the growth of HeLa cells. Particularly, hit-5, as a selective PLK1 inhibitor targeting PLK1-PBD, significantly inhibited the progression of HeLa cells-derived xenograft, with no obvious side effects. This work demonstrates that hit-5 may be a potential anticancer agent.

Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking and Biological Evaluation for Identification of Potential Poly (ADP-Ribose) Polymerase-1 (PARP-1) Inhibitors.

Poly (ADP-ribose) polymerase-1 (PARP-1) plays critical roles in many biological processes and is considered as a potential target for anticancer therapy. Although some PARP-1 inhibitors have been reported, their clinical application in cancer therapy is limited by some shortcomings such as weak affinity, low selectivity and adverse side effects. To identify highly potent and selective PARP-1 inhibitors, an integrated protocol that combines pharmacophore mapping, virtual screening and molecular docking was constructed. It was then used as a screening query to identify potent leads with unknown scaffolds from an in-house database. Finally, four retrieved compounds were selected for biological evaluation. Biological testing indicated that the four compounds showed strong inhibitory activities on the PARP-1 (IC50 < 0.2 μM). MTT assay confirmed that compounds 1–4 inhibited the growth of human lung cancer A549 cells in a dose-dependent manner. The obtained compounds from this study may be potential leads for PARP-1 inhibition in the treatment of cancer.

Identification of novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling, virtual screening, flexible docking, molecular dynamics simulation, and post-molecular dynamics analysis

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski’s rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.Communicated by Ramaswamy H. Sarma

Discovery of Novel Biased Opioid Receptor Ligands through Structure-Based Pharmacophore Virtual Screening and Experiment.

Gi -protein-biased agonists with minimal β-arrestin recruitment represent opportunities to overcome the serious adverse effects of human mu opioid receptor (μ-OR) agonists and developing alternative and safe treatments for pain. In order to discover novel non-morphinan opioid receptor agonists, we applied hierarchical virtual screening of our in-house database against a pharmacophore based on modeling the active conformations of opioid receptors. We discovered an initial hit compound, a novel μ-OR agonist with a pyrazoloisoquinoline scaffold. We applied computational R-group screening to this compound and synthesized 14 derivatives predicted to be the best. Of these, a new Gi -protein-biased compound, 1-{5-(3-chlorophenyl)-7,8-dimethoxy-3-[4-(methylsulfonyl)benzyl]-3H-pyrazolo[3,4-c]isoquinolin-1-yl}-N,N-dimethylmethanamine, showed an EC50 value of 179 nm against the μ-OR. This resulted in significant pain relief for mice in the phase II period of formalin response tests. This study provides a new strategy to identify diverse sets of promising compounds that might prove useful for the development of drugs that target other G-protein-coupled receptors.

Natural compounds as potential Hsp90 inhibitors for breast cancer-Pharmacophore guided molecular modelling studies

Breast cancer is one of the major impediments affecting women globally. The ATP-dependant heat shock protein 90 (Hsp90) forms the central component of molecular chaperone machinery that predominantly governs the folding of newly synthesized peptides and their conformational maturation. It regulates the stability and function of numerous client proteins that are frequently upregulated and/or mutated in cancer cells, therefore, making Hsp90 inhibition a promising therapeutic strategy for the development of new efficacious drugs to treat breast cancer. In the present in silico investigation, a structure-based pharmacophore model was generated with hydrogen bond donor, hydrogen bond acceptor and hydrophobic features complementary to crucial residues Ala55, Lys58, Asp93, Ile96, Met98 and Thr184 directed at inhibiting the ATP-binding activity of Hsp90. Subsequently, the phytochemical dataset of 3210 natural compounds was screened to retrieve the prospective inhibitors after rigorous validation of the model pharmacophore. The retrieved 135 phytocompounds were further filtered by drug-likeness parameters including Lipinski’s rule of five and ADMET properties, then investigated via molecular docking-based scoring. Molecular interactions were assessed using Genetic Optimisation for Ligand Docking program for 95 drug-like natural compounds against Hsp90 along with two clinical drugs as reference compounds – Geldanamycin and Radicicol. Docking studies revealed three phytochemicals are better than the investigated clinical drugs. The reference and hit compounds with dock scores of 48.27 (Geldanamycin), 40.90 (Radicicol), 73.04 (Hit1), 72.92 (Hit2) and 68.12 (Hit3) were further validated for their binding stability through molecular dynamics simulations. We propose that the non-macrocyclic scaffolds of three identified phytochemicals might aid in the development of novel therapeutic candidates against Hsp90-driven cancers.

Structure-Based Pharmacophore Design and Virtual Screening for Novel Tubulin Inhibitors with Potential Anticancer Activity.

Tubulin inhibitors have been considered as potential drugs for cancer therapy. However, their drug resistance and serious side-effects are the main reasons for clinical treatment failure. Therefore, there is still an urgent need to develop effective therapeutic drugs. Herein, a structure-based pharmacophore model was developed based on the co-crystallized structures of the tubulin with a high resolution. The model including one hydrogen-bond acceptor feature, two aromatic features, and one hydrophobic feature was further validated using the Gunner–Henry score method. Virtual screening was performed by an integrated protocol that combines drug-likeness analysis, pharmacophore mapping, and molecular docking approaches. Finally, five hits were selected for biological evaluation. The results indicated that all these hits at the concentration of 40 μM showed an inhibition of more than 50% against five human tumor cells (MCF-7, U87MG, HCT-116, MDA-MB-231, and HepG2). Particularly, hit 1 effectively inhibited the proliferation of these tumor cells, with inhibition rates of more than 80%. The results of tubulin polymerization and colchicine-site competition assays suggested that hit 1 significantly inhibited tubulin polymerization by binding to the colchicine site. Thus, hit 1 could be used as a potential chemotherapeutic agent for cancer treatment. This work also demonstrated the potential of our screening protocol to identify biologically active compounds.

Computational evaluation of natural compounds as potential inhibitors of human PEPCK-M: an alternative for lung cancer therapy.

BackgroundLung cancer is the leading cause of cancer-related death worldwide. Among its subtypes, non-small cell lung cancer (NSCLC) is the most common. Recently, the mitochondrial isoform of the enzyme phosphoenolpyruvate carboxykinase (HsPEPCK-M) was identified as responsible for the metabolic adaptation in the NSCLC allowing tumor growth even under conditions of glucose deficiency. This adaptation is possible due to the role of HsPEPCK-M in gluconeogenesis, converting the oxaloacetate to phosphoenolpyruvate in the presence of GTP, which plays an important role in the energetic support of these tumors. In this context, it was shown that the inhibition or knockdown of this enzyme was able to induce apoptosis in NSCLC under low glucose conditions.PurposeIn this study, novel putative inhibitors were proposed for the human PEPCK-M (HsPEPCK-M) based on a computer-aided approach.MethodsComparative modeling was used to generate 3D models for HsPEPCK-M. Subsequently, the set of natural compounds of the ZINC database was screened against HsPEPCK-M models using structure-based pharmacophore modeling and molecular docking approaches. The selected compounds were evaluated according to its chemical diversity and clustered based on chemical similarity.ResultsThe pharmacophore hypotheses, generated based on known PEPCK inhibitors, were able to select 7,124 candidate compounds. These compounds were submitted to molecular docking studies using three conformations of HsPEPCK-M generated by comparative modeling. The aim was to select compounds with high predicted binding affinity for at least one of the conformations of HsPEPCK-M. After molecular docking, 612 molecules were selected as potential inhibitors of HsPEPCK-M. These compounds were clustered according to their structural similarity. Chemical profiling and binding mode analyses of these compounds allowed the proposal of four promising compounds: ZINC01656421, ZINC895296, ZINC00895535 and ZINC02571340.ConclusionThese compounds may be considered as potential candidates for HsPEPCK-M inhibitors and may also be used as lead compounds for the development of novel HsPEPCK-M inhibitors.

Investigation of Binding Characteristics of Phosphoinositide-dependent Kinase-1 (PDK1) Co-crystallized Ligands Through Virtual Pharmacophore Modeling Leading to Novel Anti-PDK1 Hits.

3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits. This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5). Accordingly, 35 crystals for PDK1 were collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis. Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines. Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.

In silico and in vitro identification of candidate SIRT1 activators from Indonesian medicinal plants compounds database

Sirtuin 1 (SIRT1) is a class III family of protein histone deacetylases involved in NAD+-dependent deacetylation reactions. It has been suggested that SIRT1 activators may have a protective role against type 2 diabetes, the aging process, and inflammation. This study aimed to explore and identify medicinal plant compounds from Indonesian Herbal Database (HerbalDB) that might potentially become a candidate for SIRT1 activators through a combination of in silico and in vitro methods. Two pharmacophore models were developed using co-crystalized ligands that allosterically bind with SIRT1 similar to the putative ligands used by SIRT1 activators. Then, these were used for the virtual screening of HerbalDB. The identified compounds were subjected to molecular docking and 50 ns molecular dynamics simulation. Molecular dynamics simulation was analyzed using MM-GB(PB)SA methods. The compounds identified by these methods were tested in an in vitro study using a SIRT-Glo™ luminescence assay. Virtual screening using structure-based pharmacophores predicted that mulberrin as the best candidate SIRT1 activator. Virtual screening using ligand-based pharmacophores predicted that gartanin, quinidine, and quinine to be the best candidates as SIRT1 activators. The molecular docking studies showed the important residues involved were Ile223 and Ile227 at the allosteric region. The MM-GB(PB)SA calculations confirmed that mulberrin, gartanin, quinidine, quinine showed activity at allosteric region and their EC50 in vitro values are 2.10; 1.79; 1.71; 1.14 μM, respectively. Based on in silico and in vitro study results, mulberin, gartanin, quinidine, and quinine had good activity as SIRT1 activators.

Structure-based pharmacophore design and screening for potential inhibitors of E protein of dengue virus as a loom for dengue

Structure-based pharmacophore design and screening for potential inhibitors of E protein of dengue virus as a loom for dengue

Computational Studies in Drug Design Against Cancer.

The application of in silico tools in the development of anti cancer drugs. The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs. Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development. Structure-based pharmacophore modeling aided in the identification of PUMA inhibitors, structure based approach with high throughput screening for the development of Bcl-2 inhibitors, to derive the most relevant protein-protein interactions, anti mitotic agents; I-Kappa-B Kinase β (IKK- β) inhibitor, screening of new class of aromatase inhibitors that can be important targets in cancer therapy. Application of computational methods in the design of anti cancer drugs was found to be effective.

A Definitive Pharmacophore Modelling Study on CDK2 ATP Pocket Binders: Tracing the Path of New Virtual High-Throughput Screenings.

Cyclin Dependent Kinases-2 (CDK2) are members of serine/threonine protein kinases family. They play an important role in the regulation events of the eukaryotic cell division cycle, especially during the G1 to S phase transition. Experimental evidence indicate that excessive expression of CDK2s should cause abnormal cell cycle regulation. Therefore, since a long time, CDK2s have been considered potential therapeutic targets for cancer therapy. In this work, onehundred and forty-nine complexes of inhibitors bound in the CDK2-ATP pocket were submitted to short MD simulations (10ns) and free energy calculation. Comparison with experimental data (Ki, Kd and pIC50) revealed that short simulations are exhaustive to examine the crucial ligand-protein interactions within the complexes. Information collected on MD simulations of protein-ligand complexes has been used to perform a molecular modelling approach that incorporates flexibility into structure-based pharmacophore modelling (Common Hits Approach, CHA). The high number of pharmacophore models resulting from the MD simulation was thus reduced to a few representative groups of pharmacophore models. The performance of the models has been assessed by using the ROC curves analysis. This definitive set of validated pharmacophore models could be used to screen in-house and/or commercial datasets for detection of new CDK-2 inhibitors. We provide the models to all the researchers involved in this field.