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Updated: Nov 22, 2025

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Oncological Ligand-Target Binding Systems and Developmental Approaches for Cancer Theranostics
Jaison Jeevanandam1, Godfred Sabbih2, Kei X Tan3
1CQM-Centro de Química da Madeira, MMRG, Universidade da Madeira, Campus da Penteada, 9020-105, Funchal, Portugal.
Abstract:
Targeted treatment of cancer hinges on the identification of specific intracellular molecular receptors on cancer cells to stimulate apoptosis for eventually inhibiting growth; the development of novel ligands to target biomarkers expressed by the cancer cells; and the creation of novel multifunctional carrier systems for targeted delivery of anticancer drugs to specific malignant sites. There are numerous receptors, antigens, and biomarkers that have been discovered as oncological targets (oncotargets) for cancer diagnosis and treatment applications. Oncotargets are critically important to navigate active anticancer drug ingredients to specific disease sites with no/minimal effect on surrounding normal cells. In silico techniques relating to genomics, proteomics, and bioinformatics have catalyzed the discovery of oncotargets for various cancer types. Effective oncotargeting requires high-affinity probes engineered for specific binding of receptors associated with the malignancy. Computational methods such as structural modeling and molecular dynamic (MD) simulations offer opportunities to structurally design novel ligands and optimize binding affinity for specific oncotargets. This article proposes a streamlined approach for the development of ligand-oncotarget bioaffinity systems via integrated structural modeling and MD simulations, making use of proteomics, genomic, and X-ray crystallographic resources, to support targeted diagnosis and treatment of cancers and tumors.
Insights
Developing targeted cancer therapies requires identifying specific molecular targets on cancer cells. This study proposes a computational approach using structural modeling and molecular dynamics simulations to create effective ligand-oncotarget systems for improved cancer treatment.
Area of Science:
- Oncology
- Computational Biology
- Biochemistry
Background:
- Targeted cancer therapy relies on identifying specific molecular receptors (oncotargets) on cancer cells.
- Oncotargets are crucial for delivering anticancer drugs to malignant sites while minimizing harm to healthy cells.
- In silico methods like genomics and proteomics accelerate the discovery of potential oncotargets.
Purpose of the Study:
- To streamline the development of ligand-oncotarget bioaffinity systems for targeted cancer therapy.
- To enhance the design of high-affinity probes for specific oncotarget binding.
- To support the diagnosis and treatment of cancers and tumors through precise targeting.
Main Methods:
- Utilizing integrated structural modeling and molecular dynamics (MD) simulations.
- Leveraging proteomics, genomic, and X-ray crystallographic data.
- Engineering novel ligands for optimized binding affinity to specific oncotargets.
Main Results:
- A proposed streamlined approach for developing ligand-oncotarget bioaffinity systems.
- Demonstrated potential for computational methods to design high-affinity probes.
- Facilitated the identification of specific oncotargets for various cancer types.
Conclusions:
- Integrated computational approaches offer a powerful strategy for developing targeted cancer therapies.
- The proposed method can accelerate the discovery and optimization of ligands for oncotargets.
- This work supports advancements in precision oncology for improved cancer diagnosis and treatment.
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