Evaluation of anti-EGFR-iRGD recombinant protein with GOLD nanoparticles: synergistic effect on antitumor efficiency using optimized deep neural networks

Kaushik, Aman Chandra; Wang, Yanjing; Wang, Xiangeng; Kumar, Ajay; Singh, Satya P.; Pan, Cheng‐Tang; Shiue, Yow‐Ling; Wei, Dong‐Qing

doi:10.1039/c9ra01975h

Cited by 10 publications

(2 citation statements)

References 36 publications

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“…Using molecular docking, the relationship between anti-EGFR-iRGD, a tyrosine kinase connected to several cancers, and gold (Au) nanoparticles was also examined. In this interaction, asn845 was the essential amino acid, with a binding energy estimate of −3.5 kcal/mol [ 156 ]. According to Al-Radadi [ 157 ], gold nanoparticles containing Commiphora myrrh exhibited a stronger negative docking score (−3.976 Kcal/mol) when compared to the VEGFR-2 domain.…”

Section: Analysis Of Biomacromolecule–np Interactions Using Molecular...mentioning

confidence: 99%

Molecular Docking Approach for Biological Interaction of Green Synthesized Nanoparticles

Kar,

Oriola,

Oyedeji

2024

Molecules

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In recent years, significant progress has been made in the subject of nanotechnology, with a range of methods developed to synthesize precise-sized and shaped nanoparticles according to particular requirements. Often, the nanoparticles are created by employing dangerous reducing chemicals to reduce metal ions into uncharged nanoparticles. Green synthesis or biological approaches have been used recently to circumvent this issue because biological techniques are simple, inexpensive, safe, clean, and extremely productive. Nowadays, much research is being conducted on how different kinds of nanoparticles connect to proteins and nucleic acids using molecular docking models. Therefore, this review discusses the most recent advancements in molecular docking capacity to predict the interactions between various nanoparticles (NPs), such as ZnO, CuO, Ag, Au, and Fe3O4, and biological macromolecules.

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Section: Analysis Of Biomacromolecule–np Interactions Using Molecular...mentioning

confidence: 99%

Molecular Docking Approach for Biological Interaction of Green Synthesized Nanoparticles

Kar,

Oriola,

Oyedeji

2024

Molecules

View full text Add to dashboard Cite

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“…Aman Chandra Kaushik et al [43] developed an optimized deep neural network for evaluating the growth receptor bound with gold NPs for cancer therapy. The approach where the mutational details of the receptor units utilized in the method were retrieved furnished insights for the cancer cell targeting and proved the efficiency of the gold NPs in inhibiting the growth factor receptor by the synergistic effect against the growth factor.…”

Section: Literature Reviewmentioning

confidence: 99%

Importance of Nanoparticles in Cancer Therapy and Drug Delivery: A Detailed Theory and Gaps

Patel,

Patel

2024

Drug Development and Safety

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Nanoparticles are a game-changing innovation in cancer therapy and drug delivery. Their ability to enhance drug targeting, overcome biological barriers, and minimize side effects makes them a cornerstone of modern oncology. The challenge lies in effectively distinguishing cancer cells from their regular counterparts in cancer therapy. Nanotechnology has emerged as a transformative solution, addressing this challenge through precise treatment modalities. This chapter delves into the pivotal role of Nanoparticles (NPs) in cancer therapy, primarily focusing on their significance in the drug delivery process. Overcoming the hurdles posed by conventional treatments, the genomic instability of tumors contributes to the variability among cancers, resulting in chemoresistance that challenges therapeutic success. A pioneering deep learning approach coupled with NPs has been proposed to tackle these issues, outshining previous methodologies by delivering drugs with accurate precision to target cancer cells and tissues. Through this innovative deep-learning technique, the proposed model achieves exceptional outcomes. With a remarkable accuracy of 97.591%, sensitivity of 96.644%, and specificity of 96.415%, the deep learning-enabled NPs demonstrate efficiency compared to the modern methods. This proposed model ushers in a new era of hope for patients and clinicians in the fight against cancer.

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EnANNDeep: An Ensemble-based lncRNA–protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models

Peng

Tan

Tian

et al. 2022

Interdiscip Sci Comput Life Sci

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Evaluation of anti-EGFR-iRGD recombinant protein with GOLD nanoparticles: synergistic effect on antitumor efficiency using optimized deep neural networks

Abstract: NP screening through a deep learning approach against Anti-EGFR and validation through docking with AuNP. Biochemical pathway and simulation of AuNP with Anti-EGFR and further implementation in biological circuits.

Cited by 10 publications

References 36 publications

Molecular Docking Approach for Biological Interaction of Green Synthesized Nanoparticles

Molecular Docking Approach for Biological Interaction of Green Synthesized Nanoparticles

Importance of Nanoparticles in Cancer Therapy and Drug Delivery: A Detailed Theory and Gaps

EnANNDeep: An Ensemble-based lncRNA–protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models

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