Showing papers on "Pharmacophore published in 2018"

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

Abstract: CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Reverse Screening Methods to Search for the Protein Targets of Chemopreventive Compounds.

Abstract: This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrodinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

Identification of novel acetylcholinesterase inhibitors designed by pharmacophore-based virtual screening, molecular docking and bioassay.

Abstract: In this study, pharmacophore based 3D QSAR models for human acetylcholinesterase (AChE) inhibitors were generated, with good significance, statistical values (r2training = 0.73) and predictability (q2training = 0.67). It was further validated by three methods (Fischer’s test, decoy set and Guner-Henry scoring method) to show that the models can be used to predict the biological activities of compounds without costly and time-consuming synthesis. The criteria for virtual screening were also validated by testing the selective AChE inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective AChE inhibitor. Thus, the findings reported herein may provide a new strategy for the discovery of selective AChE inhibitors. The IC50 value of compounds 5c and 6a presented selective inhibition of AChE without inhibiting butyrylcholinesterase (BChE) at uM level. Molecular docking studies were performed to explain the potent AChE inhibition of the target compounds studies to explain high affinity.

Exploring pyrazolo[3,4-d]pyrimidine phosphodiesterase 1 (PDE1) inhibitors: a predictive approach combining comparative validated multiple molecular modelling techniques.

Abstract: Phosphodiesterase 1 (PDE1) is a potential target for a number of neurodegenerative disorders such as Schizophrenia, Parkinson's and Alzheimer's diseases. A number of pyrazolo[3,4-d]pyrimidine PDE1 inhibitors were subjected to different molecular modelling techniques [such as regression-based quantitative structure-activity relationship (QSAR): multiple linear regression, support vector machine and artificial neural network; classification-based QSAR: Bayesian modelling and Recursive partitioning; Monte Carlo based QSAR; Open3DQSAR; pharmacophore mapping and molecular docking analyses] to get a detailed knowledge about the physicochemical and structural requirements for higher inhibitory activity. The planarity of the pyrimidinone ring plays an important role for PDE1 inhibition. The N-methylated function at the 5th position of the pyrazolo[3,4-d]pyrimidine core is required for interacting with the PDE1 enzyme. The cyclopentyl ring fused with the parent scaffold is necessary for PDE1 binding potency. The phenylamino substitution at 3rd position is crucial for PDE1 inhibition. The N2-substitution at the pyrazole moiety is important for PDE1 inhibition compared to the N1-substituted analogues. Moreover, the p-substituted benzyl side chain at N2-position helps to enhance the PDE1 inhibitory profile. Depending on these observations, some new molecules are predicted that may possess better PDE1 inhibition.

A "Motif-Oriented" Total Synthesis of Nannocystin Ax. Preparation and Biological Assessment of Analogues.

Abstract: The highly cytotoxic cyclodepsipeptides of the nannocystin family are known to bind to the eukaryotic translation elongation factor 1α (EF-1α). Analysis of the docking pose, as proposed by a previous in silico study, suggested that the trisubstituted alkene moiety and the neighboring methyl ether form a domain that might be closely correlated with biological activity. This hypothesis sponsored a synthetic campaign which was designed to be “motif-oriented”: specifically, a sequence of ring closing alkyne metathesis (RCAM) followed by hydroxy-directed trans-hydrostannation of the resulting cycloalkyne was conceived, which allowed this potentially anchoring substructure to be systematically addressed at a late stage. This inherently flexible approach opened access to nannocystin Ax (1) itself as well as to 10 non-natural analogues. While the biological data confirmed the remarkable potency of this class of compounds and showed that the domain in question is indeed an innate part of the pharmacophore, the spe...

From Catalysis to Cancer: Toward Structure–Activity Relationships for Benzimidazol-2-ylidene-Derived N-Heterocyclic-Carbene Complexes as Anticancer Agents

Abstract: The promise of the metal(arene) structure as an anticancer pharmacophore has prompted intensive exploration of this chemical space. While N-heterocyclic carbene (NHC) ligands are widely used in catalysis, they have only recently been considered in metal complexes for medicinal applications. Surprisingly, a comparatively small number of studies have been reported in which the NHC ligand was coordinated to the RuII(arene) pharmacophore and even less with an OsII(arene) pharmacophore. Here, we present a systematic study in which we compared symmetrically substituted methyl and benzyl derivatives with the nonsymmetric methyl/benzyl analogues. Through variation of the metal center and the halido ligands, an in-depth study was conducted on ligand exchange properties of these complexes and their biomolecule binding, noting in particular the stability of the M-CNHC bond. In addition, we demonstrated the ability of the complexes to inhibit the selenoenzyme thioredoxin reductase (TrxR), suggested as an important target for anticancer metal-NHC complexes, and their cytotoxicity in human tumor cells. It was found that the most potent TrxR inhibitor diiodido(1,3-dibenzylbenzimidazol-2-ylidene)(η6-p-cymene)ruthenium(II) 1bI was also the most cytotoxic compound of the series, with the antiproliferative effects in general in the low to middle micromolar range. However, since there was no clear correlation between TrxR inhibition and antiproliferative potency across the compounds, TrxR inhibition is unlikely to be the main mode of action for the compound type and other target interactions must be considered in future.

Identification of Novel Allosteric Modulators of Glutamate Transporter EAAT2.

Abstract: Dysfunction of excitatory amino acid transporters (EAATs) has been implicated in the pathogenesis of various neurological disorders, such as stroke, brain trauma, epilepsy, and neurodegenerative diseases, among others. EAAT2 is the main subtype responsible for glutamate clearance in the brain, having a key role in regulating transmission and preventing excitotoxicity. Therefore, compounds that increase the expression or activity of EAAT2 have therapeutic potential for neuroprotection. Previous studies identified molecular determinants for EAAT2 transport stimulation in a structural domain that lies at the interface of the rigid trimerization domain and the central substrate binding transport domain. In this work, a hybrid structure based approach was applied, based on this molecular domain, to create a high-resolution pharmacophore. Subsequently, virtual screening of a library of small molecules was performed, identifying 10 hit molecules that interact at the proposed domain. Among these, three compounds ...

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease.

Abstract: Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity

Abstract: Natural products offer unexplored molecular frameworks for the development of chemical leads and innovative drugs. However, the structural complexity of natural products compared with synthetic drug-like molecules often limits the scaffold hopping potential of natural-product-inspired molecular design. Here we introduce a holistic molecular representation incorporating pharmacophore and shape patterns, which facilitates scaffold hopping from natural products to isofunctional synthetic compounds. This computational approach captures simultaneously the partial charge, atom distributions and molecular shape. In a prospective application, we use four natural cannabinoids as queries in a chemical database search for novel synthetic modulators of human cannabinoid receptors. Of the synthetic compounds selected by the new method, 35% are experimentally confirmed as active. These cannabinoid receptor modulators are structurally less complex than their respective natural product templates. The results of this study validate this holistic molecular representation for hit and lead finding in drug discovery. The successful prediction of drug-like structures by scaffold hopping can be limited by the structural complexity of natural products. Here, a molecular descriptor which captures partial charge, atom density distributions, and molecular shape is used to predict novel active compounds which are simpler than the original natural products.

Structure-Activity Relationships and Computational Investigations into the Development of Potent and Balanced Dual-Acting Butyrylcholinesterase Inhibitors and Human Cannabinoid Receptor 2 Ligands with Pro-Cognitive in Vivo Profiles.

Abstract: The enzyme butyrylcholinesterase (BChE) and the human cannabinoid receptor 2 (hCB2R) represent promising targets for pharmacotherapy in the later stages of Alzheimer’s disease We merged pharmacophores for both targets into small benzimidazole-based molecules, investigated SARs, and identified several dual-acting ligands with a balanced affinity/inhibitory activity and an excellent selectivity over both hCB1R and hAChE A homology model for the hCB2R was developed based on the hCB1R crystal structure and used for molecular dynamics studies to investigate binding modes In vitro studies proved hCB2R agonism Unwanted μ-opioid receptor affinity could be designed out One well-balanced dual-acting and selective hBChE inhibitor/hCB2R agonist showed superior in vivo activity over the lead CB2 agonist with regards to cognition improvement The data shows the possibility to combine a small molecule with selective and balanced GPCR-activity/enzyme inhibition and in vivo activity for the therapy of AD and may help

Novel Multitarget-Directed Ligands Aiming at Symptoms and Causes of Alzheimer's Disease.

Abstract: Alzheimer's disease (AD) is a major public health problem, which is due to its increasing prevalence and lack of effective therapy or diagnostics. The complexity of the AD pathomechanism requires complex treatment, e.g. multifunctional ligands targeting both the causes and symptoms of the disease. Here, we present new multitarget-directed ligands combining pharmacophore fragments that provide a blockade of serotonin 5-HT6 receptors, acetyl/butyrylcholinesterase inhibition, and amyloid β antiaggregation activity. Compound 12 has displayed balanced activity as an antagonist of 5-HT6 receptors ( Ki = 18 nM) and noncompetitive inhibitor of cholinesterases (IC50 hAChE = 14 nM, IC50 eqBuChE = 22 nM). In further in vitro studies, compound 12 has shown amyloid β antiaggregation activity (IC50 = 1.27 μM) and ability to permeate through the blood-brain barrier. The presented findings may provide an excellent starting point for further studies and facilitate efforts to develop new effective anti-AD therapy.

Structure-Activity Relationships in Metal-Binding Pharmacophores for Influenza Endonuclease.

Abstract: Metalloenzymes represent an important target space for drug discovery. A limitation to the early development of metalloenzyme inhibitors has been the lack of established structure–activity relationships (SARs) for molecules that bind the metal ion cofactor(s) of a metalloenzyme. Herein, we employed a bioinorganic perspective to develop an SAR for inhibition of the metalloenzyme influenza RNA polymerase PAN endonuclease. The identified trends highlight the importance of the electronics of the metal-binding pharmacophore (MBP), in addition to MBP sterics, for achieving improved inhibition and selectivity. By optimization of the MBPs for PAN endonuclease, a class of highly active and selective fragments was developed that displays IC50 values <50 nM. This SAR led to structurally distinct molecules that also displayed IC50 values of ∼10 nM, illustrating the utility of a metal-centric development campaign in generating highly active and selective metalloenzyme inhibitors.

Inhibitors of DNA Methyltransferases From Natural Sources: A Computational Perspective.

Abstract: Naturally occurring small molecules include a large variety of natural products from different sources that have confirmed activity against epigenetic targets. In this work we review chemoinformatic, molecular modeling, and other computational approaches that have been used to uncover natural products as inhibitors of DNA methyltransferases, a major family of epigenetic targets with therapeutic interest. Examples of computational approaches surveyed in this work are docking, similarity-based virtual screening, and pharmacophore modeling. It is also discussed the chemoinformatic-guided exploration of the chemical space of naturally occurring compounds as epigenetic modulators which may have significant implications in epigenetic drug discovery and nutriepigenetics.

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes.

Abstract: GPR142 (G protein receptor 142) is a novel orphan GPCR (G protein coupled receptor) belonging to "Class A" of GPCR family and expressed in β cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling, and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

Design and Discovery of Novel Chiral Antifungal Amides with 2-(2-Oxazolinyl)aniline as a Promising Pharmacophore

Abstract: Inspired by established succinate dehydrogenase inhibitors (SDHIs), our continuing efforts toward the discovery of chiral antifungal amides turned to the optimization of their polar regions with 2-(2-oxazolinyl)aniline as a known pharmacophore. Scaffold hopping and bioactivity-guided convergent synthesis enabled the identification of promising antifungal categories. Fine tuning of the substituents and chirality furnished seven amides (1s, 1t, 2d, 2h, 2j, 3k, and 2l) as antifungal candidates, with EC50 values lower than 5 mg/L. The first investigation of chiral amides of acyclic acids as SDHIs was conducted, and compound 2d was selected as a promising candidate against Botrytis cinerea, with a preventative efficacy of up to 93.9% at 50 mg/L, which is better than that of boscalid. The different binding models between compounds with different configurations were simulated for compound 2d and its diastereoisomers. The benefits of synthetic accessibility and cost-effectiveness highlight the practical potential for compound 2d as a good alternative to known SDHI fungicides.

Pharmacophore Nanoarrays on DNA Origami Substrates as a Single-Molecule Assay for Fragment-Based Drug Discovery

Abstract: The rational combination of techniques from the fields of nanotechnology, single molecule detection, and lead discovery could provide elegant solutions to enhance the throughput of drug screening We have synthesized nanoarrays of small pharmacophores on DNA origami substrates that are displayed either as individual ligands or as fragment pairs and thereby reduced the feature size by several orders of magnitude, as compared with standard microarray techniques Atomic force microscopy-based single-molecule detection allowed us to distinguish potent protein-ligand interactions from weak binders Several independent binding events, that is, strong, weak, symmetric bidentate, and asymmetric bidentate binding are directly visualized and evaluated We apply this method to the discovery of bidentate trypsin binders based on benzamidine paired with aromatic fragments Pairing of benzamidine with the dye TAMRA results in tenfold enhancement of the trypsin binding yield

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations

Abstract: MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb) This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 35 software The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore) The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors This study led to the identification of 10 potential

Novel glitazones as PPARγ agonists: molecular design, synthesis, glucose uptake activity and 3D QSAR studies

Abstract: An alarming requirement for finding newer antidiabetic glitazones as agonists to PPARγ are on its utmost need from past few years as the side effects associated with the available drug therapy is dreadful. In this context, herein, we have made an attempt to develop some novel glitazones as PPARγ agonists, by rational and computer aided drug design approach by implementing the principles of bioisosterism. The designed glitazones are scored for similarity with the developed 3D pharmacophore model and subjected for docking studies against PPARγ proteins. Synthesized by adopting appropriate synthetic methodology and evaluated for in vitro cytotoxicity and glucose uptake assay. Illustrations about the molecular design of glitazones, synthesis, analysis, glucose uptake activity and SAR via 3D QSAR studies are reported. The computationally designed and synthesized ligands such as 2-(4-((substituted phenylimino)methyl)phenoxy)acetic acid derivatives were analysed by IR, 1H-NMR, 13C-NMR and MS-spectral techniques. The synthesized compounds were evaluated for their in vitro cytotoxicity and glucose uptake assay on 3T3-L1 and L6 cells. Further the activity data was used to develop 3D QSAR model to establish structure activity relationships for glucose uptake activity via CoMSIA studies. The results of pharmacophore, molecular docking study and in vitro evaluation of synthesized compounds were found to be in good correlation. Specifically, CPD03, 07, 08, 18, 19, 21 and 24 are the candidate glitazones exhibited significant glucose uptake activity. 3D-QSAR model revealed the scope for possible further modifications as part of optimisation to find potent anti-diabetic agents.

Discovery of Potent Inhibitors for the Large Neutral Amino Acid Transporter 1 (LAT1) by Structure-Based Methods.

Abstract: The large neutral amino acid transporter 1 (LAT1) is a promising anticancer target that is required for the cellular uptake of essential amino acids that serve as building blocks for cancer growth and proliferation. Here, we report a structure-based approach to identify chemically diverse and potent inhibitors of LAT1. First, a homology model of LAT1 that is based on the atomic structures of the prokaryotic homologs was constructed. Molecular docking of nitrogen mustards (NMs) with a wide range of affinity allowed for deriving a common binding mode that could explain the structure−activity relationship pattern in NMs. Subsequently, validated binding hypotheses were subjected to molecular dynamics simulation, which allowed for extracting a set of dynamic pharmacophores. Finally, a library of ~1.1 million molecules was virtually screened against these pharmacophores, followed by docking. Biological testing of the 30 top-ranked hits revealed 13 actives, with the best compound showing an IC50 value in the sub-μM range.

Computational Studies on Imidazo[1,2-a] Pyridine-3-Carboxamide Analogues as Antimycobacterial Agents: Common Pharmacophore Generation, Atom-based 3D-QSAR, Molecular dynamics Simulation, QikProp, Molecular Docking and Prime MMGBSA Approaches

Abstract: IMB-1402, Q203 and ND09759 analogs were found to have strong efficiency against Multi-drug-resistant tuberculosis (MDR-TB)/Extensively drug-resistant tuberculosis (XDR-TB) strains. To know the structural necessities for imidazo[1,2-a]pyridine-3-carboxamide analogues, we intended to develop the ligand-based pharmacophore, Quantitative structure–activity relationship models(3D-QSAR model). We also performed Molecular docking, molecular simulation and Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA) studies. All the studies like Common pharmacophore hypothesis generation, Atom based 3D-QSAR study, Prime MMGBSA, Docking, Qikprop, and Molecular dynamics simulation were processed using various modules incorporated within the maestro software interface from Schrodinger, LLC, New York USA (release 2017). The common pharmacophore hypothesis(CPH) generation resulted in a five-featured hypothesis HHPRR, containing 1 positive, 2 hydrophobic and 2 aromatic rings. An Atom-based 3D-QSAR model was predicted for twenty seven training sets (a correlation coefficient i.e.R2= 0.9181,Standard deviation i.e.SD =0.3305, variance ratio i.e. F = 85.9) and eleven test sets (cross-validation correlation coefficient i.e.Q2 =0.6745, Root Mean Square Error i.e. RMSE = 0.65, Pearson R = 0.8427, P=1.21E-12) compounds employing alignment based on CPH. The dataset of thirty-eight molecules was allowed for docking into the active site of pantothenate synthetase (PDBID-3IVX) that shows H-bonding (Hydrogen bonding) interactions with residues Gly158, Met195, Pro38 and additionally shows further Pi-cation interactions with a residue like Hie47. We also obtained good simulation results for1.2ns study. From the results, the generated 3D-QSAR model may be applicable for additional designing of various novel potent derivatives in the future.