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.     

In silico rationalization of the structural and physicochemical requirements for photobiological activity in angelicine derivatives and their heteroanalogues

In PUVA (Psoralen plus UVA) chemotherapy 8-methoxypsoralen is the most widely used compound, although its efficacy is endowed with undesired side effects. In order to have an evident anti-proliferative activity with a reduced phototoxicity, many linear and angular derivatives have been synthesised. In this paper we describe a QSAR study in which, by means of the neural networks methodology, a useful model for predicting biological activity, expressed as ID₅₀ (the UVA dose that reduces to 50% the DNA synthesis in Ehrlich cells), has been derived. A decision tree that is able to discriminate between active and inactive compounds has been built based on recursive partitioning. The study shows the key structural features responsible for the activity and could be a helpful tool in the rational design of new, less toxic, photochemotherapeuthic agents.     

Molecular modeling and structural analysis of some tetrahydroindazole and cyclopentanepyrazole derivatives as COX-2 inhibitors

In an attempt to rationalize the search for new potential anti-inflammatory compounds on the COX-2 enzyme, we carried out an in silico protocol that successfully combines the prediction of physicochemical and pharmacokinetic properties, molecular docking, molecular dynamic simulation, and free energy calculation. Starting from a small library of compounds synthesized previously, it was found that 70% of the compounds analyzed satisfy with the associated values to physicochemical principles as key evaluation parameters for the drug-likeness; all the compounds presented good gastrointestinal absorption and cerebral permeability and they showed an interaction with the Arg 106 residue of the COX-2 isoenzyme. Finally, it was obtained that compound 3ab has a binding mode, binding energy, and stability in the active site of COX-2 like the reference drug celecoxib, suggesting that this compound could become a powerful candidate in the inhibition of the COX-2 enzyme. In addition, we realized the crystallographic analysis of compounds 3j, 3r, and 3t defining the crystal parameters and the Packing interactions.     

Artificial neural network‐based drug design for diabetes mellitus using flavonoids

Diabetes mellitus is a chronic metabolic disease involving the failure to regulate glucose blood levels in the body and has been linked with numerous detrimental complications. Studies have shown that these complications can be linked to the activities of aldose reductase (AR), an enzyme of the polyol pathway. Flavonoids have been identified as good AR inhibitors (ARIs) and are also strong antioxidants with radical scavenging (RS) activity. As such, flavonoids show potential to become a better class of ARIs because they are able to concurrently address the oxidative stress issue. In this article, we carried out quantitative structure‐activity relationship analysis of flavones and flavonols (members of flavonoid family) using artificial neural networks. Three computer experiments were conducted to study the influence of hydrogen (H), hydroxyl (? OH), and methoxyl (? CH₃) functional groups on eight substitution sites of the lead flavone molecule and to predict potential ARIs. Of 6561 possible flavones and flavonols, in experiment 1, we predicted 69 potent ARIs, and in experiment 2, we predicted 346 compounds with strong RS activity. In experiment 3, we combined these results to find overlapping compounds with both strong AR inhibition and RS activity and we are able to predict 10 potent compounds with strong AR inhibition (IC₅₀ < 0.3 μM) and RS activity (IC₂₅ < 1.0 μM). These 10 compounds show promise of being good therapeutic agents in the prevention of diabetic complications and is suggested to undergo further wet bench experimentation to prove their potency. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

Repurposing approved drugs as potential inhibitors of 3CL-protease of SARS-CoV-2: Virtual screening and structure based drug design

3CL proteases (3CL^pro) are only found in RNA viruses and have a central role in polyprotein processing during replication. Therefore, 3CL^pro has emerged as promising drug target for therapeutic treatment of infections caused by Coronaviruses. In the light of the recent major outbreak of the SARS-CoV-2 virus and the continuously rising numbers of infections and casualties, there is an urgent need for quickly available drugs or vaccines to stop the current COVID-19 pandemic. Repurposing of approved drugs as 3CL^pro inhibitors could dramatically shorten the period up to approval as therapeutic against SARS-CoV-2, since pharmacokinetics and toxicity is already known. Several known drugs, e.g. oxytetracycline, doxorubicin, kanamycin, cefpiramide, teniposide, proanthocyanidin and salvianolic acid B, but also not-approved active compounds from the ZINC15 library were identified as new potential inhibitors of 3CL^pro by using different complementary virtual screening and docking approaches. These compounds have the potential to be further optimized using structure based drug design as demonstrated for oxytetracycline.     

Dihydropyrazole and dihydropyrrole structures based design of Kif15 inhibitors as novel therapeutic agents for cancer

Mitotic Kinesin motors, Eg5 and Kif15, have recently emerged as good targets for cancer as they play an inevitable role during mitosis. But, most of the Eg5 inhibitors were found ineffective when the cancer cells develop resistance to them by escalating the expression of Kif15 as alternative to Eg5. Therefore, the drugs that target Kif15 became necessary to be used either as a single or in combination with Eg5 inhibitors. The present study used 39 dihydropyrazole and 13 dihydropyrrole derivatives that were having in vitro inhibitory potential against kinesin motors to develop a common pharmacophore hypothesis AHRR and atom-based QSAR model. The model was used for virtual screening of ZINC database and the resultant hits were docked against Kif15. The four drug candidates with high docking score were examined for their activity and pharmacokinetic behaviour. Based on the results these drugs could be considered as lead candidates in further drug development for cancer.     

Preparation of 3-arylmethylindoles as selective COX-2 inhibitors

The 3-arylmethylation of indoles using TMSOTf/Et₃SiH with a wide variety of substituted benzaldehydes has been accomplished. Under these mild Lewis acid mediated reductive conditions, it was demonstrated that indoles bearing both 6-MeSO₂ and 2-methyl substituents could be 3-arylmethylated in good to excellent yields to afford the corresponding 3-arylmethyl indoles, effective as selective COX-2 inhibitors. In addition, the viability of this method for the reductive alkylation of indoles by ketones was demonstrated and shown to be C-3 regioselective. For indoles bearing both a 6-MeSO₂ and 2-cyano substituent where this indole reductive alkylation methodology was unsuccessful, an unprecedented Pd(0) mediated arylorganozinc coupling with the requisite substituted 3-methylcarbonatomethylindole proved successful in affording the desired 2-cyano-6-MeSO₂-3-arylmethylindoles effective as selective COX-2 inhibitors.     

Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors

The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q² _LOO=0.937, q² _{L50% O}=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model.     

Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure–activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.     

In silico drug design and molecular docking of novel amidophosphonates and sulfamidophosphonates as inhibitors of urokinase-type plasminogen activator

Cancer is one of the most serious health problems worldwide, affecting individuals from different sexes, ages, and races. However, the most frequent cancer types in the world are lung, prostate, stomach, colorectal, and esophagus in men; and breast, lung, stomach, colorectal and cervical in women. Currently, the search for new active substances used in oral targeted therapies are legitimate and opens up the possibility of an "ambulatory shift" in cancer treatment. In order to design anti-tumor drug candidates endowed with oral bioavailability, we studied trough an in silico approach the oral bioavailability of newly synthesized biomolecules; α-sulfamidophosphonates and α-amidophosphonates as well as their mechanism of action on the new target urokinase-type plasminogen activator (uPA). The studied compounds have been found to meet the five criteria of. Lipinski's rule. The Osiris, Molinspiration and SWISS/ADME calculations related to the compounds (1d, 2a) have shown that these compounds could be good candidates for interacting with the different targets, they have convincing characteristics in relation to the standard drug used. It can be concluded that these compounds are biologically important and possessing molecular properties desirable for being a drug candidate for oral use.The molecular docking results of the studied compounds revealed a good ligand-target interactions, the compounds (1d, 2a) presented a possibility of interacting as an inhibitor of the anticancer target: urokinase-type plasminogen activator (uPA).     

In-silico profiling,design, molecular docking computation,and drug kinetic model evaluation of novel curcumin derivatives as potential anticancer agents

The alarming trend of leukemia cell lines that are multidrug-resistant has prompted scientists to scramble for effective new anticancer treatments. Therefore, it remains an intriguing scientific task to optimize curcumin by trying to introduce molecular alteration to its vital structure to improve the biological effect against the P388 cell line or get around resistance phenomena. Regardless of the wide range of medications that are now being studied, Prednisone remains the most important and efficient part of chemotherapy that the WHO recommends. This article discusses the QSAR-oriented model and in silico assessment of some potent curcumin derivatives' anticancer activity against the P388 cell line. The solidity and propensity for prediction of the model were ensured by using stringent validation procedures. The activity of these derivatives was shown to be unrelated to lipophilicity, while shorter N-N distances and short substituents result in quite bioactive molecules. This information was used to design potent molecules that demonstrate good quality as per the assessment based on the Lead-Like Soft rule is acceptable for drug-like molecules. Also, molecule d2 does not possess any toxic effects risk alerts, suggesting drug-adherent conduct. While Prednisone the reference drug has a toxicity risk alert in red, suggesting non-adherent conduct for Prednisone. Hence, the novel molecules are promising anticancer agents.     

A new synthesis of 3-arylthioindoles as selective COX-2 inhibitors using PIFA

The direct 3-arylthiolation of 2-substituted indoles using phenyliodine(III)bis trifluoroacetate (PIFA) in (CF₃)₂CHOH with a wide variety of benzenethiols has been accomplished. In particular, indoles bearing a 6-MeSO₂ and either a 2-methyl or 2-carboxymethyl substituent could be 3-arylthiolated in good to excellent yields to afford the corresponding 3-arylthioindoles as selective COX-2 inhibitors. In a study varying the electronic nature of the 5-substituent of 2-CO₂Et indoles, it was discovered that the yield of the reaction improved as the substituent became more electron withdrawing. This result was consistent with a proposed mechanism involving benzenethiol displacement of an intermediate 3-IPh indole complex.     

Molecular design of N,N-disubstituted 2-aminothiazolines as selective carboxylesterase inhibitors

Selective carboxylesterase inhibitors are employed as modulators of hydrolytic metabolism of ester or amide-containing drugs. Using the Molecular Field Topology Analysis (MFTA), the models for the relationships between the structures and inhibitory activities of 5-halomethyl-2-aminothiazolines against acetylcholinesterase, butyrylcholinesterase, and carboxylesterase were built, the molecular design was performed, and a focused library of potentially active and selective carboxylesterase inhibitors was proposed.     

Structural properties and interaction energies affecting drug design. An approach combining molecular simulations,statistics, interaction energies and neural networks

In order to elucidate some basic principles for protein–ligand interactions, a subset of 87 structures of human proteins with their ligands was obtained from the PDB databank. After a short molecular dynamics simulation (to ensure structure stability), a variety of interaction energies and structural parameters were extracted. Linear regression was performed to determine which of these parameters have a potentially significant contribution to the protein–ligand interaction. The parameters exhibiting relatively high correlation coefficients were selected. Important factors seem to be the number of ligand atoms, the ratio of N, O and S atoms to total ligand atoms, the hydrophobic/polar aminoacid ratio and the ratio of cavity size to the sum of ligand plus water atoms in the cavity. An important factor also seems to be the immobile water molecules in the cavity. Nine of these parameters were used as known inputs to train a neural network in the prediction of seven other. Eight structures were left out of the training to test the quality of the predictions. After optimization of the neural network, the predictions were fairly accurate given the relatively small number of structures, especially in the prediction of the number of nitrogen and sulfur atoms of the ligand.     

In silico study of novel niclosamide derivatives,SARS-CoV-2 nonstructural proteins catalytic residue-targeting small molecules drug candidates

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-mediated coronavirus disease 2019 (COVID-19) infection remains a global pandemic and health emergency with overwhelming social and economic impacts throughout the world. Therapeutics for COVID-19 are limited to only remdesivir; therefore, there is a need for combined, multidisciplinary efforts to develop new therapeutic molecules and explore the effectiveness of existing drugs against SARS-CoV-2. In the present study, we reported eight (SCOV-L-02, SCOV-L-09, SCOV-L-10, SCOV-L-11, SCOV-L-15, SCOV-L-18, SCOV-L-22, and SCOV-L-23) novel structurally related small-molecule derivatives of niclosamide (SCOV-L series) for their targeting potential against angiotensin-converting enzyme-2 (ACE2), type II transmembrane serine protease (TMPRSS2), and SARS-COV-2 nonstructural proteins (NSPs) including NSP5 (3CLpro), NSP3 (PLpro), and RdRp. Our correlation analysis suggested that ACE2 and TMPRSS2 modulate host immune response via regulation of immune-infiltrating cells at the site of tissue/organs entries. In addition, we identified some TMPRSS2 and ACE2 microRNAs target regulatory networks in SARS-CoV-2 infection and thus open up a new window for microRNAs-based therapy for the treatment of SARS-CoV-2 infection. Our in vitro study revealed that with the exception of SCOV-L-11 and SCOV-L-23 which were non-active, the SCOV-L series exhibited strict antiproliferative activities and non-cytotoxic effects against ACE2- and TMPRSS2-expressing cells. Our molecular docking for the analysis of receptor-ligand interactions revealed that SCOV-L series demonstrated high ligand binding efficacies (at higher levels than clinical drugs) against the ACE2, TMPRSS2, and SARS-COV-2 NSPs. SCOV-L-18, SCOV-L-15, and SCOV-L-09 were particularly found to exhibit strong binding affinities with three key SARS-CoV-2’s proteins: 3CLpro, PLpro, and RdRp. These compounds bind to the several catalytic residues of the proteins, and satisfied the criteria of drug-like candidates, having good adsorption, distribution, metabolism, excretion, and toxicity (ADMET) pharmacokinetic profile. Altogether, the present study suggests the therapeutic potential of SCOV-L series for preventing and managing SARs-COV-2 infection and are currently under detailed investigation in our lab.     

An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion

Matrix solid-phase dispersion (MSPD) as a sample preparation method for the determination of two potential endocrine disruptors, linuron and diuron and their common metabolites, 1-(3,4-dichlorophenyl)-3-methylurea (DCPMU), 1-(3,4-dichlorophenyl) urea (DCPU) and 3,4-dichloroaniline (3,4-DCA) in food commodities has been developed. The influence of the main factors on the extraction process yield was thoroughly evaluated. For that purpose, a 3^(4–1) fractional factorial design in further combination with artificial neural networks (ANNs) was employed. The optimal networks found were afterwards used to identify the optimum region corresponding to the highest average recovery displaying at the same time the lowest standard deviation for all analytes. Under final optimal conditions, potato samples (0.5 g) were mixed and dispersed on the same amount of Florisil. The blend was transferred on a polypropylene cartridge and analytes were eluted using 10 ml of methanol. The extract was concentrated to 50 μl of acetonitrile/water (50:50) and injected in a high performance liquid chromatography coupled to UV–diode array detector system (HPLC/UV–DAD). Recoveries ranging from 55 to 96% and quantification limits between 5.3 and 15.2 ng/g were achieved. The method was also applied to other selected food commodities such as apple, carrot, cereals/wheat flour and orange juice demonstrating very good overall performance.