QSAR modeling, pharmacophore-based virtual screening, and ensemble docking insights into predicting potential epigallocatechin gallate (EGCG) analogs against epidermal growth factor receptor

Bommu, Uma Devi; Konidala, Kranthi Kumar; Neeraja, P.; Suneetha, Y.

doi:10.1080/10799893.2018.1564151

Cited by 10 publications

(7 citation statements)

References 27 publications

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“…MD simulation revealed the formation of little more stable complex respect to the Erl-T790M/L858R EGFR one ( Figure S5), but the energy contribution is much far in affinity with respect that calculated for the wild type and ELREA EGFR complexes ( Figure 6). Nonetheless, the overcome resistance in EGFR T790M/L858R after treatment with a combination of EGCG and TKIs was recently found [20].…”

Section: Erl and Egcg Binding With Egfr T790m/l858rmentioning

confidence: 99%

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Conformational Insight on WT- and Mutated-EGFR Receptor Activation and Inhibition by Epigallocatechin-3-Gallate: Over a Rational Basis for the Design of Selective Non-Small-Cell Lung Anticancer Agents

Minnelli

Laudadio

Mobbili

et al. 2020

IJMS

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Non-small cell lung cancer (NSCLC) represents a difficult condition to treat, due to epidermal growth factor receptor (EGFR) kinase domain mutations, which lead to ligand-independent phosphorylation. Deletion of five amino acids (ELREA) in exon 19 and mutational change from leucine to arginine at position 858 (L858R) are responsible for tyrosine kinase domain aberrant activation. These two common types of EGFR-mutated forms are clinically associated with high response with Tyrosine Kinase Inhibitors (TKI); however, the secondary T790M mutation within the Tyrosine Kinase Domain (TKD) determines a resistance to these EGFR-TKIs. Using molecular dynamic simulation (MD), the present study investigated the architectural changes of wild-type and mutants EGFR’s kinase domains in order to detect any conformational differences that could be associated with a constitutively activated state and thus to evaluate the differences between the wild-type and its mutated forms. In addition, in order to evaluate to which extent the EGFR mutations affect its inhibition, Epigallocatechin 3-Gallate (EGCG) and Erlotinib (Erl), known EGFR-TKI, were included in our study. Their binding modes with the EGFR-TK domain were elucidated and the binding differences between EGFR wild-type and the mutated forms were evidenced. The aminoacids mutations directly influence the binding affinity of these two inhibitors, resulting in a different efficacy of Erl and EGCG inhibition. In particular, for the T790M/L858R EGFR, the binding modes of studied inhibitors were compromised by aminoacidic substitution confirming the experimental findings. These results may be useful for novel drug design strategies targeting the dimerization domain of the EGFR mutated forms, thus preventing receptor activation.

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Section: Erl and Egcg Binding With Egfr T790m/l858rmentioning

confidence: 99%

“…This antioxidant compound interacts with the double mutated EGFR form a little more effectively than erlotinib, thanks to a high number of hydrophilic groups, which allow it to create polar interactions with amino acid, even if it is not particularly active [20].…”

Section: Introductionmentioning

confidence: 99%

Conformational Insight on WT- and Mutated-EGFR Receptor Activation and Inhibition by Epigallocatechin-3-Gallate: Over a Rational Basis for the Design of Selective Non-Small-Cell Lung Anticancer Agents

Minnelli

Laudadio

Mobbili

et al. 2020

IJMS

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“…The use of TK inhibitors resulted in significant toxicities such as gastro-intestinal disorder, skin rash, diarrhea, and other complications ( Hirsh 2011 ). Bommu et al (2019) identified potential lead compounds through a computer-aided drug approach against EGFR protein based on the QASR modeling. Several studies were also carried out to identify potential lead EGFR antagonists using computer-aided drug design, and one in-vitro study was conducted with different databases screening without any comparative analysis with the currently available drugs in use for treatment, as well as without evaluating the toxicity profile, protein–ligand stability analysis via dynamic simulation ( Sangande et al, 2020 ; Weng et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Pharmacophore-based virtual screening approaches to identify novel molecular candidates against EGFR through comprehensive computational approaches and in-vitro studies

et al. 2022

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Alterations to the EGFR (epidermal growth factor receptor) gene, which primarily occur in the axon 18–21 position, have been linked to a variety of cancers, including ovarian, breast, colon, and lung cancer. The use of TK inhibitors (gefitinib, erlotinib, lapatinib, and afatinib) and monoclonal antibodies (cetuximab, panitumumab, and matuzumab) in the treatment of advanced-stage cancer is very common. These drugs are becoming less effective in EGFR targeted cancer treatment and developing resistance to cancer cell eradication, which sometimes necessitates stopping treatment due to the side effects. One in silico study has been conducted to identify EGFR antagonists using other compounds, databases without providing the toxicity profile, comparative analyses, or morphological cell death pattern. The goal of our study was to identify potential lead compounds, and we identified seven compounds based on the docking score and four compounds that were chosen for our study, utilizing toxicity analysis. Molecular docking, virtual screening, dynamic simulation, and in-vitro screening indicated that these compounds’ effects were superior to those of already marketed medication (gefitinib). The four compounds obtained, ZINC96937394, ZINC14611940, ZINC103239230, and ZINC96933670, demonstrated improved binding affinity (−9.9 kcal/mol, −9.6 kcal/mol, −9.5 kcal/mol, and −9.2 kcal/mol, respectively), interaction stability, and a lower toxicity profile. In silico toxicity analysis showed that our compounds have a lower toxicity profile and a higher LD50 value. At the same time, a selected compound, i.e., ZINC103239230, was revealed to attach to a particular active site and bind more tightly to the protein, as well as show better in-vitro results when compared to our selected gefitinib medication. MTT assay, gene expression analysis (BAX, BCL-2, and β-catenin), apoptosis analysis, TEM, cell cycle assay, ELISA, and cell migration assays were conducted to perform the cell death analysis of lung cancer and breast cancer, compared to the marketed product. The MTT assay exhibited 80% cell death for 75 µM and 100µM; however, flow cytometry analysis with the IC50 value demonstrated that the selected compound induced higher apoptosis in MCF-7 (30.8%) than in A549.

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“…More specifically, the pharmacophore and 3D QSAR model was used to virtually screen the aforementioned databases and the hit molecules were used to design a VCL that was evaluated using molecular docking. A similar procedure was followed by Bommu et al to predict potential epigallocatechin gallate (EGCG) analogs against epidermal growth factor receptors [83]. In this case, log P and log S predictions along with the toxicity endpoint were modeled using QSAR, which was combined with a pharmacophore model and molecular docking to identify seven high-potential EGCG analogs as promising pharmacological, anticancer, and drug-like templates that could be used towards moderating lung cancer progression.…”

Section: Applications and Current Trendsmentioning

confidence: 99%

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design

Suay-García

Bueso-Bordils

Falcó

et al. 2022

IJMS

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Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry—many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry–virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

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QSAR modeling, pharmacophore-based virtual screening, and ensemble docking insights into predicting potential epigallocatechin gallate (EGCG) analogs against epidermal growth factor receptor

Cited by 10 publications

References 27 publications

Conformational Insight on WT- and Mutated-EGFR Receptor Activation and Inhibition by Epigallocatechin-3-Gallate: Over a Rational Basis for the Design of Selective Non-Small-Cell Lung Anticancer Agents

Conformational Insight on WT- and Mutated-EGFR Receptor Activation and Inhibition by Epigallocatechin-3-Gallate: Over a Rational Basis for the Design of Selective Non-Small-Cell Lung Anticancer Agents

Pharmacophore-based virtual screening approaches to identify novel molecular candidates against EGFR through comprehensive computational approaches and in-vitro studies

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design

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