基于药效团的三维数据库搜索

用表皮生长因子受体酪氨酸激酶抑制剂的药效团作为提问结构在三维数据库中进行了搜索.从得到的命中结构中挑选了12个化合物用柔性受体模型方法对其活性进行了预测, 发现有2个化合物具有一定的预测活性.这2个化合物可能具有酪氨酸激酶抑制剂的活性, 可能作为先导化合物进行结构优化.     

Target-based design,synthesis and biological activity of new pyrazole amide derivatives

Based on the similarities in the conformation of VS008 (N-(4-methylphenyl)-3-(tert-butyl)-1-(phenylmethyl)-1H-pyrazole-5-carboxamide) and BYIO6830 (N'-(3,5-dimethylbenzoyl)-N'-tert-butyl-5-methyl-2,3-dihydro-1,4-benzodioxine-6-carbohydrazide) bound to the active site of the EcR subunit of the ecdysone receptor (EcR)-ultraspiracle protein (USP) heterodimeric receptor, a series of new pyrazole amide derivatives were designed and synthesized. Their structures were confirmed by IR, ¹H NMR, ¹³C NMR and elemental analysis. Results from a preliminary bioassay revealed that two of the pyrazole derivatives exhibited promising insecticidal activity. Specifically, compounds 6e and 6i exhibited good activity against Helicoverpa armigera (cotton bollworm) at low concentration. Symptoms displayed by tebufenozide-treated H. armigera were identical with those displayed by its treated counterpart. 6i showed the same poisoning symptoms as those of tebufenozide. In addition, results from molecular docking result indicated that the binding modes of 6e and 6i at the active site of the EcR subunit of the heterodimeric receptor were similar to that of the bound tebufenozide.     

A new protocol for predicting novel GSK-3β ATP competitive inhibitors

Glycogen synthase kinase 3β (GSK-3β) is a potential therapeutic target for cancer, type-2 diabetes, and Alzheimer's disease. This paper proposes a new lead identification protocol that predicts new GSK-3β ATP competitive inhibitors with topologically diverse scaffolds. First, three-dimensional quantitative structure-activity relationship (3D QSAR) models were built and validated. These models are based upon known GSK-3β inhibitors, benzofuran-3-yl-(indol-3-yl) maleimides, by means of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Second, 28?826 maleimide derivatives were selected from the PubChem database. After filtration via Lipinski's rules, 10?429 maleimide derivatives were left. Third, the FlexX-dock program was employed to virtually screen the 10?429 compounds against GSK-3β. This resulted in 617 virtual hits. Fourth, the 3D QSAR models predicted that from the 617 virtual hits, 93 compounds would have GSK-3β inhibition values of less than 15 nM. Finally, from the 93 predicted active hits, 23 compounds were confirmed as GSK-3β inhibitors from literatures; their GSK-3β inhibition ranged from 1.3 to 480 nM. Therefore, the hits rate of our virtual screening protocol is greater than 25%. The protocol combines ligand- and structure-based approaches and therefore validates both approaches and is capable of identifying new hits with topologically diverse scaffolds.     

Epitopes based drug design for dengue virus envelope protein: A computational approach

Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region “QHGTI” in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset “Chembridge”. A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski’s rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.     

Growth dynamics of self-assembled monolayers in dip-pen nanolithography

Using molecular dynamics simulations, we studied the growth mechanism of self-assembled monolayers in dip-pen nanolithography. A molecule dropping from the tip kicks out a molecule sitting on the substrate, and the displaced molecule in turn kicks out a molecule next to it. This kicking propagates and finally stops when it hits the periphery of the monolayer. This monolayer growth is faster than predicted from the previous diffusion theory. Increasing the molecule-substrate binding strength enhances the molecular deposition rate and makes the monolayer well-ordered.     

In silico design,synthesis and activity of potential drug-like chrysin scaffold-derived selective EGFR inhibitors as anticancer agents

Background & objectiveEpidermal growth factor receptor (EGFR) signaling pathway is one of the promising and well-established targets for anticancer therapy. The objective of the present study was to identify new EGFR inhibitors using ligand and structure-based drug designing methods, followed by a synthesis of selected inhibitors and evaluation of their activity.MethodsA series of C-7-hydroxyproton substituted chrysin derivatives were virtually drawn to generate a small compound library that was screened using 3D QSAR model created from forty-two known EGFR tyrosine kinase inhibitors. Next, the obtained hits with fitness score ≥ 1.0 were subjected to molecular docking analysis. Based on the predicted activity and XP glide score, three EGFR inhibitors were synthesized and characterized using ¹H-NMR, ¹³C-NMR and MS. Finally, comparative in vitro investigation of the biological activity of synthesized inhibitors was performed with that of the parent molecule, chrysin.ResultsThe data depicted a 3.2–fold enhanced cytotoxicity of chrysin derivative, CHM-04 against breast cancer cells as compared with chrysin as well as its binding with EGFR protein. Furthermore, the biological activity of CHM-04 was comparable to the standard EGFR inhibitor, AG1478 in increasing apoptosis and decreasing the migratory potential of triple-negative breast cancer cells as well as significantly lowering the mammosphere forming ability of breast cancer stem cells.ConclusionThe present study suggests CHM-04, an EGFR inhibitor possessing drug-like properties as a plausible therapeutic candidate against breast cancer.     

Refined pharmacophore features for virtual screening of human thromboxane A2 receptor antagonists

For a long time, the structural basis of TXA2 receptor is limited due to the lack of crystal structure information, till the release of the crystal structure of TXA2 receptor, which deepens our understanding about ligand recognition and selectivity mechanisms of this physiologically important receptor. In this research, we report the successful implementation in the discovery of an optimal pharmacophore model of human TXA2 receptor antagonists through virtual screening. Structure-based pharmacophore models were generated based on two crystal structures of human TXA2 receptor (PDB entry 6IIU and 6IIV). Docking simulation revealed interaction modes of the virtual screening hits against TXA2 receptor, which was validated through molecular dynamics simulation and binding free energy calculation. ADMET properties were also analyzed to evaluate the toxicity and physio-chemical characteristics of the hits. The research would provide valuable insight into the binding mechanisms of TXA2 receptor antagonists and thus be helpful for designing novel antagonists.     

Stereospecific formation of 7,8β-dihydroanalogs at the reduction of ponasterone acetonide with lithium in liquid ammonia

The reduction of ponasterone A diacetonide with lithium in liquid ammonia stereospecifically led to 7,8β-dihydroanalogs of 5α- and 5β-epimers of ponasterone A and 7,8β-dihydro-6α-hydroxy derivative. 7,8β-Dihydroponasterone A, phytoecdysteroid from the needles of Japanise yew Taxus cuspidata, and its 5α-epimer were synthesized.     

Ozonolysis of Alkenes and Study of Reactions of Polyfunctional Compounds: LXVI.2* Ozonolysis and Hydrogenation of Diacetonides of 24,25- and 25,26-Anhydro-20-hydroxyecdysones. Synthesis of Ponasterone A

Ozonolysis of 2,3:20,22-diacetonides of 24.25-and 25,26-anhydro-20-hydroxyecdysones afforded the corresponding -carbonyl derivatives. The hydrogenation of the mentioned dehydration products of 20-hydroxyecdysone acetonide yielded diacetonide of ponasterone A that provided ponasterone A and its 29,22-acetonide at hydrolysis.     

Interpretation of scoring functions using 3D molecular fields. Mapping the diacyl-hydrazine-binding pocket of an insect ecdysone receptor

A method is presented for the interpretation of receptor docking score values (rough measures of binding affinities) of ligands in terms of 3D molecular field interaction contributions. The FlexX and FlexX-Pharm methods were used to dock the structures of designed sets of ligands into the ligand-binding pocket of a selected receptor. In the next step the relationship was investigated between the FlexX and CScore scores and 3D molecular fields obtained for the docked conformations of the ligands, using the CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) methods. The approach yielded highly significant CoMFA and CoMSIA models demonstrating that a high portion of the variance in the docking score values of the ligands can be explained by steric, electrostatic, hydrophobic, and hydrogen bond donor and acceptor molecular field interaction contributions. The approach was exemplified by using the crystal structure of the ligand-binding domain of the ecdysone receptor (EcR) of the moth Heliotis virescens as well as virtual molecule libraries of analogues of known diacyl-hydrazine (DAH) type ecdysteroid agonists. By docking appropriately designed virtual compound libraries into the DAH binding pocket of EcR followed by CoMFA and CoMSIA of the docked conformations, hitherto unexplored regions of the receptor cavity could be mapped. By mapping the significant molecular field interaction contributions onto the model of the receptor-ligand complex, important receptor-ligand interactions could be highlighted that may help the design of novel highly scored receptor ligands. An advantage of the method is that no experimental biological activity data are required to exhaustively map the receptor-binding site.     

Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro

Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (M^pro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski’s filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as M^pro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.     

Identification of Novel Antagonists Targeting Cannabinoid Receptor 2 Using a Multi-Step Virtual Screening Strategy

The endocannabinoid system plays an essential role in the regulation of analgesia and human immunity, and Cannabinoid Receptor 2 (CB2) has been proved to be an ideal target for the treatment of liver diseases and some cancers. In this study, we identified CB2 antagonists using a three-step “deep learning–pharmacophore–molecular docking” virtual screening approach. From the ChemDiv database (1,178,506 compounds), 15 hits were selected and tested by radioligand binding assays and cAMP functional assays. A total of 7 out of the 15 hits were found to exhibit binding affinities in the radioligand binding assays against CB2 receptor, with a pK_i of 5.15–6.66, among which five compounds showed antagonistic activities with pIC₅₀ of 5.25–6.93 in the cAMP functional assays. Among these hits, Compound 8 with the 4H-pyrido[1,2-a]pyrimidin-4-one scaffold showed the best binding affinity and antagonistic activity with a pK_i of 6.66 and pIC₅₀ of 6.93, respectively. The new scaffold could serve as a lead for further development of CB2 drugs. Additionally, we hope that the model in this study could be further utilized to identify more novel CB2 receptor antagonists, and the developed approach could also be used to design potent ligands for other therapeutic targets.     

Fingerprint directed scaffold hopping for identification of CCR2 antagonists

Chemokine receptors have evolved as attractive targets for disease conditions which arise due to immunomodulation involving host-defense mechanisms. CCR2, a chemokine receptor, is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. This study provides a new strategy of a ligand based technique which exploits fingerprint led fragment features in conjunction with structure-guided design for identifying new scaffolds for CCR2. A fragment based mining (FBM) technique was employed on a chemical database to identify novel scaffold hops. The hits were subjected to 3-point pharmacophore fingerprint procedures with Tanimoto similarity metric to compare pharmacophoric fingerprints. The final 66 hits generated by these exercises were predicted by the validated HQSAR model, and the top predicted were suggested as probable scaffolds for CCR2 antagonism. The identified scaffolds were validated through molecular docking studies. The ligands were docked by providing receptor flexibility in the extra cellular domain (1 and 3), N terminal domain, and in the transmembrane (TM1 & TM7) helix region with IFD approach. Some of the scaffolds showed H-bonding potential which was not explored by the data set molecules. All identified scaffolds highlighted a key hydrogen bonding interaction with Thr292 as supported by mutational studies. The observed pi stacking interaction with Tyr188 in data set molecules was also produced by the new scaffolds. Taking the advantage of receptor flexibility the scaffolds explored the hydrophobic binding cleft between helix 1 and 7 occupied by residues Leu44, Leu45, Leu48 and Ile300, Ile303, Ile304, respectively. Two of the identified molecules have promising outcomes and can be considered as novel scaffolds for CCR2 binding.     

In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands

The kappa opioid receptor (KOR) represents an attractive target for the development of drugs as potential antidepressants, anxiolytics and analgesics. A robust computational approach may guarantee a reduction in costs in the initial stages of drug discovery, novelty and accurate results. In this work, a virtual screening workflow of a library consisting of ~6 million molecules was set up, with the aim to find potential lead compounds that could manifest activity on the KOR. This in silico study provides a significant contribution in the identification of compounds capable of interacting with a specific molecular target. The main computational techniques adopted in this experimental work include: (i) virtual screening; (ii) drug design and leads optimization; (iii) molecular dynamics. The best hits are tripeptides prepared via solution phase peptide synthesis. These were tested in vivo, revealing a good antinociceptive effect after subcutaneous administration. However, further work is due to delineate their full pharmacological profile, in order to verify the features predicted by the in silico outcomes.     

Screening a Natural Product-Inspired Library for Anti-Phytophthora Activities

Phytophthora is a genus of microorganisms that cause devastating dieback and root-rot diseases in thousands of plant hosts worldwide. The economic impact of Phytophthora diseases on crops and native ecosystems is estimated to be billions of dollars per annum. These invasive pathogens are extremely difficult to control using existing chemical means, and the effectiveness of the few treatments available is being jeopardized by increasing rates of resistance. There is an urgent need to identify new chemical treatments that are effective against Phytophthora diseases. Natural products have long been regarded as “Nature’s medicine chest”, providing invaluable leads for developing front-line drugs and agrochemical agents. Here, we have screened a natural product-inspired library of 328 chemicals against two key Phytophthora species: Phytophthora cinnamomi and Phytophthora agathidicida. The library was initially screened for inhibition of zoospore germination. From these screens, we identified twenty-one hits that inhibited germination of one or both species. These hits were further tested in mycelial growth inhibition studies to determine their half-maximal inhibitory concentrations (IC₅₀s). Four compounds had IC₅₀ values of approximately 10 µM or less, and our best hit had IC₅₀s of approximately 3 µM against both Phytophthora species tested. Overall, these hits may serve as promising leads for the development of new anti-Phytophthora agrochemicals     

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC₅₀ values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere–Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a Q_FIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.     

Design,synthesis and biological activity of novel substituted pyrazole amide derivatives targeting Ec R/USP receptor

In order to discover highly active ecdysone analogs, a series of new substituted pyrazole amide derivatives were obtained using structure-guided optimization method and further screened for their insecticidal activities, in the basis of the core structures of the two active compounds N-(3-methoxyphenyl)-3-(tert-butyl)-1-phenyl-1H-pyrazole-5-carboxamide(6e) and N-(4-(tert-butyl)phenyl)-3-(tert-butyl)-1-phenyl-1H-pyrazole-5-carboxamide(6i), previously presented by us. The chemical structures of the title compounds were identified by spectral analyses. The preliminary bioassay results indicated that one among the synthesized pyrazole derivatives, compound 34, endowed with good activity against Mythimna Separata at 10 mg/L, which was equal to that displayed by the positive control tebufenozide. In addition, examples of molecular docking and molecular dynamics studies demonstrated that 34 may be the potential inhibitor to Ec R and its docking conformation was similar to that of tebufenozide. In addition, increasing the hydrophobic effect and considering the suitable bulk effect on pyrazole ring are beneficial to the inhibiting activity to Ec R and activity in vivo.     

Identification of potential Gly/NMDA receptor antagonists by cheminformatics approach: a combination of pharmacophore modelling,virtual screening and molecular docking studies

The Gly/NMDA receptor has become known as potential target for the management of neurodegenerative diseases. Discovery of Gly/NMDA antagonists has thus attracted much attention in recent years. In the present research, a cheminformatics approach has been used to determine structural requirements for Gly/NMDA antagonism and to identify potential antagonists. Here, 37 quinoxaline derivatives were selected to develop a significant pharmacophore model with good certainty. The selected model was validated by leave-one-out cross-validation, an external test set, decoy set and Y-randomization test. Applicability domain was verified by the standardization approach. The validated 3D-QSAR model was used to screen virtual hits from the ZINC database by pharmacophore mapping. Molecular docking was used for assessment of receptor–ligand binding modes and binding affinities. The GlideScore and molecular interactions with critical amino acids were considered as crucial features to identify final hits. Furthermore, hits were analysed for in silico pharmacokinetic parameters and Lipinski’s rule of five, demonstrating their potential as drug-like candidates. The PubChem and SciFinder search tools were used to authenticate the novelty of leads retrieved. Finally, five different leads have been suggested as putative novel candidates for the exploration of potent Gly/NMDA receptor antagonists.     

Multi‐Objective Molecular De Novo Design by Adaptive Fragment Prioritization

We present the development and application of a computational molecular de novo design method for obtaining bioactive compounds with desired on‐ and off‐target binding. The approach translates the nature‐inspired concept of ant colony optimization to combinatorial building block selection. By relying on publicly available structure–activity data, we developed a predictive quantitative polypharmacology model for 640 human drug targets. By taking reductive amination as an example of a privileged reaction, we obtained novel subtype‐selective and multitarget‐modulating dopamine D₄ antagonists, as well as ligands selective for the sigma‐1 receptor with accurately predicted affinities. The nanomolar potencies of the hits obtained, their high ligand efficiencies, and an overall success rate of 90 % demonstrate that this ligand‐based computer‐aided molecular design method may guide target‐focused combinatorial chemistry.