Pharmacophore mapping of a series of pyrrolopyrimidines, indolopyrimidines and their congeners as multidrug-resistance-associated protein (MRP1) modulators

Computational identification of 2,4-disubstituted amino-pyrimidines as L858R/T790M-EGFR double mutant inhibitors using pharmacophore mapping, molecular docking, binding free energy calculation, DFT study and molecular dynamic simulation

Pharmacophore modelling studies have been performed for a series of 2,4-disubstituted-pyrimidines derivatives as EGFR L858R/T790M tyrosine kinase inhibitors. The high scoring AARR.15 hypothesis was selected as the best pharmacophore model with the highest survival score of 3.436 having two hydrogen bond acceptors and two aromatic ring features. Pharmacophore-based virtual screening followed by structure-based yielded the six molecules (ZINC17013227, ZINC17013215, ZINC9573324, ZINC9573445, ZINC24023331 and ZINC17013503) from the ZINC database with significant in silico predicted activity and strong binding affinity towords the EGFR L858R/T790M tyrosine kinase. In silico toxicity and cytochrome profiling indicates that all the 06 virtually screened compounds were substrate/inhibitors of the CYP-3A4 metabolizing enzyme and were non-carcinogenic and devoid of Ames mutagenesis. Density functional theory (DFT) and molecular dynamic (MD) simulation further validated the obtained hits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00113-x.

An Integrated in silico Approach and in vitro Study for the Discovery of Small-Molecule USP7 Inhibitors as Potential Cancer Therapies

The ubiquitin-specific protease 7 (USP7) is a highly promising well-validated target for a variety of malignancies. USP7 is critical in regulating the tumor suppressor p53 along with numerous epigenetic modifiers and transcription factors. Previous studies showed that USP7 inhibitors led to increased levels of p53 and anti-proliferative effects in hematological and solid tumor cell lines. Thus, this study aimed to identify potent and safe USP7 hit inhibitors as potential anti-cancer therapeutics via an integrated computational approach that combines pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations and post-MD free energy calculations. In this study, the crystal structure of USP7 has been extensively investigated using a combination of three different chemical pharmacophore modeling approaches. We then screened ∼220.000 drug-like small molecule library and the hit ligands predicted to be nontoxic were evaluated further. The identified hits from each pharmacophore modeling study were further examined by 1-ns short MD simulations and MM/GBSA free energy analysis. In total, we ran 1 ns MD simulations for 1137 selected on small compounds. Based on their average MM/GBSA scores, 18 ligands were selected for 50 ns MD simulations along with one highly potent USP7 inhibitor used as a positive control. The in vitro enzymatic inhibition assay testing of our lead 18 molecules confirmed that 7 of these molecules were successful in USP7 inhibition. Screening results showed that within the used screening approaches, the most successful one was structure-based pharmacophore modeling with the success rate of 75 %. The identification of potent and safe USP7 small molecules as potential inhibitors is a step closer to finding appropriate effective therapies for cancer. Our lead ligands can be used as a scaffold for further structural optimization and development, enabling further research in this promising field.

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from non-inhibitors using molecular solvation theory with excellent accuracy and precision. The excess chemical potential and partial molar volume in various solvents are calculated for PgP± (PgP inhibitors and non-inhibitors) compounds with the statistical-mechanical based three-dimensional reference interaction site model with the Kovalenko-Hirata closure approximation (3D-RISM-KH molecular theory of solvation). The statistical importance analysis of descriptors identified the 3D-RISM-KH based descriptors as top molecular descriptors for classification. Among the constructed classification models, the support vector machine predicted the test set of Pgp± compounds with highest accuracy and precision of ~ 97% for test set. The validation of models confirms the robustness of state-of-the-art molecular solvation theory based descriptors in identification of the Pgp± compounds.

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

BACKGROUND & OBJECTIVE

Epidermal 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.

METHODS

A 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.

RESULTS

The 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.

CONCLUSION

The present study suggests CHM-04, an EGFR inhibitor possessing drug-like properties as a plausible therapeutic candidate against breast cancer.

Structural and Biological Investigations for a Series of N-5 Substituted Pyrrolo[3,2-d]pyrimidines as Potential Anti-Cancer Therapeutics

Pyrrolo[3,2-d]pyrimidines have been studied for many years as potential lead compounds for the development of antiproliferative agents. Much of the focus has been on modifications to the pyrimidine ring, with enzymatic recognition often modulated by C2 and C4 substituents. In contrast, this work focuses on the N5 of the pyrrole ring by means of a series of novel N5-substituted pyrrolo[3,2-d]pyrimidines. The compounds were screened against the NCI-60 Human Tumor Cell Line panel, and the results were analyzed using the COMPARE algorithm to elucidate potential mechanisms of action. COMPARE analysis returned strong correlation to known DNA alkylators and groove binders, corroborating the hypothesis that these pyrrolo[3,2-d]pyrimidines act as DNA or RNA alkylators. In addition, N5 substitution reduced the EC50 against CCRF-CEM leukemia cells by up to 7-fold, indicating that this position is of interest in the development of antiproliferative lead compounds based on the pyrrolo[3,2-d]pyrimidine scaffold.

Identification of Thienopyrimidine Scaffold as an Inhibitor of the ABC Transport Protein ABCC1 (MRP1) and Related Transporters Using a Combined Virtual Screening Approach

A virtual screening protocol with combination of similarity search and pharmacophore modeling was applied to virtually screen a large compound library to gain new scaffolds regarding ABCC1 inhibition. Biological investigation of promising candidates revealed four compounds as ABCC1 inhibitors, three of them with scaffolds not associated with ABCC1 inhibition until now. The best hit molecule-a thienopyrimidine-was a moderately potent, competitive inhibitor of the ABCC1-mediated transport of calcein AM which also sensitized ABCC1-overexpressing cells toward daunorubicin. Further evaluation showed that it was a moderately potent, competitive inhibitor of the ABCB1-mediated transport of calcein AM, and noncompetitive inhibitor of the ABCG2-mediated pheophorbide A transport. In addition, the thienopyrimidine could also sensitize ABCB1- as well as ABCG2-overexpressing cells toward daunorubicin and SN-38, respectively, in concentration ranges that qualified it as one of the ten best triple ABCC1/ABCB1/ABCG2 inhibitors in the literature. Besides, three more new multitarget inhibitors were identified by this virtual screening approach.

Flavonoid derivatives as selective ABCC1 modulators: Synthesis and functional characterization

A series of chromones, bearing substituted amino groups or N-substituted carboxamide moieties in position 2, was synthesized and characterized in cellular assays for modulation of the ABC transporters ABCC1 (MDCKII-MRP1 cells), ABCB1 (Kb-V1 cells) and ABCG2 (MCF-7/Topo cells). The most potent ABCC1 modulators identified among these flavonoid-type compounds were comparable to the reference compound reversan regarding potency, but superior in terms of selectivity concerning ABCB1 and ABCG2 (2-[4-(Benzo[c][1,2,5]oxadiazol-5-ylmethyl)piperazin-1-yl]-5,7-dimethoxy-4H-chromen-4-one (51): ABCC1, IC50 11.3 μM; inactive at ABCB1 and ABCG2). Compound 51 was as effective as reversan in reverting ABCC1-mediated resistance to cytostatics in MDCKII-MRP1 cells and proved to be stable in mouse plasma and cell culture medium. Modulators, such as compound 51, are of potential value as pharmacological tools for the investigation of the (patho)physiological role of ABCC1.

Ligand-based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore-based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide-quantum-polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques.

Design and synthesis of VEGFR-2 tyrosine kinase inhibitors as potential anticancer agents by virtual based screening

Design and synthesis of VEGFR-2 tyrosine kinase inhibitors as potential anticancer agents has been done by a virtual based screening approach.

Computational models for predicting the interaction with ABC transporters

There is strong evidence that ATP-binding cassette (ABC) transporters play a critical role in the pharmacokinetic and pharmacodynamic properties of many drugs and xenobiotics. Due to their pharmacological role, several computational approaches have been developed to understand and predict the interaction between ABC transporters and their ligands. Here, we provide an overview of the current state of the art of the ligand-based models that, derived from the transport and inhibitory activities of a set of ligands, have been published for ABC transporters.

Pharmacophore modeling and 3D quantitative structure-activity relationship analysis of febrifugine analogues as potent antimalarial agent

Febrifugine and its derivatives are effective against Plasmodium falciparum. Using PHASE algorithm, a five-point pharmacophore model with two hydrogen bond acceptor (A), one positively ionizable (P) and two aromatic rings (R), was developed to derive a predictive ligand-based statistically significant 3D-quantitative structure-activity relationship (QSAR) model (r² = 0.972, SD = 0.3, F = 173.4, Q² = 0.712, RMSE = 0.3, Person-R = 0.94, and r²_pred = 0.8) to explicate the structural attributes crucial for antimalarial activity. The developed pharmacophore model and 3D QSAR model can be a substantial tool for virtual screening and related antimalarial drug discovery research.

Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions

PURPOSE

Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles.

METHODS

Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1.

RESULTS

QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds.

CONCLUSIONS

The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

QSAR studies on imidazopyrazine derivatives as Aurora A kinase inhibitors

Aurora kinases have emerged as attractive targets for the development of novel anti-cancer agents. A combined study of molecular docking, pharmacophore modelling and 3D-QSAR was performed on a series of imidazo [1, 2-a] pyrazines as novel Aurora kinase inhibitors to gain insights into the structural determinants and their structure-activity relationship. An ensemble of conformations based on molecular docking was used for PHASE pharmacophore studies. The developed best-fitted pharmacophore model was validated by diverse chemotypes of Aurora A kinase inhibitors and was consistent with the structural requirements for the docked binding mechanism. Subsequently, the pharmacophore-based alignment was used to develop PHASE and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models. The best CoMSIA model showed good statistics (q (2 )= 0.567, r (2 )= 0.992), and the predictive ability of the model was validated using an external test set of 13 compounds giving a satisfactory prediction ([Formula: see text]). The 3D contour maps provided insight into the binding mechanism and highlighted key structural features that are essential to the inhibitory activity. Based on the PHASE and CoMSIA 3D-QSAR results, a set of novel Aurora A inhibitors were designed that showed excellent potencies.

Virtual screening of ABCC1 transporter nucleotidebinding domains as a therapeutic target in multidrug resistant cancer

ABCC1 is a member of the ATP-binding Cassette super family of transporters, actively effluxes xenobiotics from cells. Clinically, ABCC1 expression is linked to cancer multidrug resistance. Substrate efflux is energised by ATP binding and hydrolysis at the nucleotide-binding domains (NBDs) and inhibition of these events may help combat drug resistance. The aim of this study is to identify potential inhibitors of ABCC1 through virtual screening of National Cancer Institute (NCI) compounds. A threedimensional model of ABCC1 NBD2 was generated using MODELLER whilst the X-ray crystal structure of ABCC1 NBD1 was retrieved from the Protein Data Bank. A pharmacophore hypothesis was generated based on flavonoids known to bind at the NBDs using PHASE, and used to screen the NCI database. GLIDE was employed in molecular docking studies for all hit compounds identified by pharmacophore screening. The best potential inhibitors were identified as compounds possessing predicted binding affinities greater than ATP. Approximately 5% (13/265) of the hit compounds possessed lower docking scores than ATP in ABCC1 NBD1 (NSC93033, NSC662377, NSC319661, NSC333748, NSC683893, NSC226639, NSC94231, NSC55979, NSC169121, NSC166574, NSC73380, NSC127738, NSC115534), whereas approximately 7% (7/104) of docked NCI compounds were predicted to possess lower docking scores than ATP in ABCC1 NBD2 (NSC91789, NSC529483, NSC211168, NSC318214, NSC116519, NSC372332, NSC526974). Analyses of docking orientations revealed P-loop residues of each NBD and the aromatic amino acids Trp653 (NBD1) and Tyr1302 (NBD2) were key in interacting with high-affinity compounds. On the basis of docked orientation and docking score the compounds identified may be potential inhibitors of ABCC1 and require further pharmacological analysis.

ABBREVIATIONS

ABC - ATP-binding cassette, DHS - dehydrosilybin, MDR - multidrug resistance, NBD - nucleotide-binding domain, PDB - protein data bank.

Pharmacophore modelling and atom-based 3D-QSAR studies on N-methyl pyrimidones as HIV-1 integrase inhibitors

Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to N-methyl pyrimidones as HIV-1 integrase inhibitors. Based on the ligand-based pharmacophore model, we got 5-point pharmacophore model AADDR, with two hydrogen bond acceptors (A), two hydrogen bond donors (D) and one aromatic ring (R). The generated pharmacophore-based alignment was used to derive a predictive atom-based 3D-QSAR model for the training set (r(2) = 0.92, SD = 0.16, F = 84.8, N = 40) and for test set (Q(2) = 0.71, RMSE = 0.06, Pearson R = 0.90, N = 10). From these results, AADDR pharmacophore feature was selected as best common pharmacophore hypothesis, and atom-based 3D-QSAR results also support the outcome by means of favourable and unfavourable regions of hydrophobic and electron-withdrawing groups for the most potent compound 30. These results can be useful for further design of new and potent HIV-1 IN inhibitors.

Pharmacophore mapping and electronic feature analysis for a series of nitroaromatic compounds with antitubercular activity

A five point pharmacophore was generated using PHASE for a series of nitroaromatic compounds and their congeners as antitubercular agents. The generated pharmacophore yielded significant 3D-QSAR model with r(2) of 0.890 for a training set of 92 molecules. The model also showed excellent predictive power with correlation coefficient Q(2) of 0.857 for a test set of 31 compounds. The pharmacophore indicated that presence of a nitro group, a piperazine moiety, one aromatic ring feature and two acceptor features are necessary for potent antitubercular activity. The pharmacophore was supported by electronic property analysis using density functional theory (DFT) at B3LYP/3-21*G level. Molecular electrostatic profile of the compounds was consistent with the generated pharmacophore model, particularly appearance of localized negative potential regions near both the oxygen atoms of nitro group extending laterally to the isoxazole ring system/amide bond in the most active compounds. Calculated data further revealed that all active compounds have smaller LUMO energies located over the nitro group, furan ring, and isoxazole ring/amide bond attached to it. Higher negative values of LUMO energies concentrated over the nitro group are indicative of the electron acceptor capacity of the compounds, suggesting that these compounds are prodrugs and must be activated by TB-nitroreductase. The results obtained from this study should aid in efficient design and development of nitroaromatic compounds as antitubercular agents.

QSAR analysis and molecular modeling of ABCG2-specific inhibitors

In addition to its critical role is controlling drug availability and protecting sensitive organs and stem cells through cellular detoxification, breast cancer resistance protein (BCRP/ABCG2) plays an important role in cancer cell resistance to chemotherapy, together with P-glycoprotein/ABCB1. A main approach to abolish multidrug resistance is to find out specific inhibitors of the drug-efflux activity, able to chemosensitize cancer cell proliferation. Many efforts have been primarily focused on ABCB1, discovered thirty years ago, whereas very few studies have concerned ABCG2, identified much more recently. This review describes the main types of inhibitors presently known for ABCG2, and how quantitative structure-activity relationship analysis among series of compounds may lead to build up molecular models and pharmacophores allowing to design lead inhibitors as future candidates for clinical trials. A special attention is drawn on flavonoids which constitute a structurally-diverse class of compounds, well suited to identify potent ABCG2-specific inhibitors.