Size effect of human epidermal growth factor-conjugated polystyrene particles on cell proliferation

Identification of new potential candidates to inhibit EGF via machine learning algorithm

One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerate the drug discovery process. Hence, an ensemble computational-experimental approach, consisting of three steps, a machine learning model, simulation of drug-target interaction and experimental characterization, was developed. The machine learning type used here was a different tree classification method, which is one of the best randomize machine learning model to identify potential inhibitors from weak inhibitors. This model was trained more than one-hundred times, and forty top trained models were extracted for the drug repositioning step. The machine learning step aimed to discover the approved drugs with the highest possible success rate in the experimental step. Therefore, among all the identified molecules with more than 0.9 probability in more than 70% of the models, nine compounds, were selected. Besides, out of the nine chosen drugs, seven compounds have been confirmed to inhibit EGF in the published articles since 2019. Hence, two identified compounds, in addition to gefitinib, as a positive control, five weak-inhibitors and one neutral, were considered via molecular docking study. Finally, the eight proposed drugs, including gefitinib, were investigated using MTT assay and In-Cell ELISA to characterize the drugs' effect on A431 cell growth and EGF-signaling. From our experiments, we could conclude that salicylic acid and piperazine could play an EGF-inhibitor role like gefitinib.

Mechanistic investigation into selective cytotoxic activities of gold nanoparticles functionalized with epidermal growth factor variants

Epidermal growth factor (EGF) gains unique selective cytotoxicity against cancer cells upon conjugation with gold nanoparticles (GNPs). We have previously developed several lysine-free EGF mutants for favorable interactions between the nanoparticle conjugates with EGF receptor (EGFR) and found one mutant (SR: K28S/K48R) showing stronger anticancer activities. However, the exact mechanisms for the selective cytotoxicity enhancement in the SR mutant remained unsolved. In this study, we analyzed how the nanoparticle conjugates of EGF variants interacted differently with A431 cancer cells, in terms of receptor binding, activation, and trafficking. Our results indicate that the essential feature of the SR-GNP conjugates in the cytotoxicity enhancement is their preferential activation of the clathrin-independent endocytosis pathway. It is suggested that we should focus on not only ligand-receptor binding affinity but also the selectivity of the receptor endocytic route to optimize the anticancer effects in this modality.

Engineered Platelet-Based Micro/Nanomotors for Cancer Therapy

Engineered platelets (PLT) can bring new possibilities for diseases treatment due to the specific response for a variety of physiological disease environments. However, the deep penetration of engineered PLT in diseased tissues such as tumor is still an important challenge that restricts the therapeutic effect. Herein, the engineered PLT micromotor (PLT@PDA-DOX) is constructed by a universal self-polymerization modification method of dopamine, and the chemotherapeutic drug doxorubicin (DOX) is loaded by both π-π stacking interaction with polydopamine (PDA) and cellular endocytosis of PLT. The experimental results prove that PLT@PDA-DOX can target to tumor site by the specific binding of PLT with cancer cells, and then the secondary PLT-derived microparticles (PMP@PDA-DOX) are released with the activation of PLT@PDA-DOX by tumor microenvironment (TME). Besides, benefiting from the photothermal conversion capability of PDA, PLT@PDA-DOX micromotors and PMP@PDA-DOX nanomotors are driven by near-infrared light to realize deep penetration. And the PLT-based micro/nanomotors with propulsion capability possess good performance for tumor ablating in vitro and in vivo. In consideration of the operability, mildness, universality of this modification method and the good biocompatibility of PDA, this work may provide a general paradigm for the construction of engineered cells in disease treatment.