In Silico Molecular Docking for Personalized Cancer Therapy
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Solution Overview
Problem
Current methods for treating neoplasms, such as cancer, face challenges in identifying effective compounds that specifically bind to mutated tissues, leading to severe side effects and resistance issues with antineoplastic agents, and the drug development process is costly and time-consuming, with limited success in clinical trials.
Innovation Solution
A method involving the identification of mutated genes in diseased tissues, determination of their 3D protein structures, and virtual screening of compounds to find those with high binding affinity to these mutated proteins, allowing for personalized treatment strategies using existing FDA-approved drugs repurposed for antineoplastic therapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional chemotherapy protocols are used based on standard treatment guidelines, then treatment can be standardized and applied to large groups of patients, but treatment success cannot be reliably predicted for individual patients due to individual biological differences
Solution Approach 1:
The patent performs preliminary molecular characterization of individual patient tumors through sequencing and mutation analysis before treatment selection. This preliminary action enables personalized treatment planning by identifying specific mutations and predicting drug responses in advance, resolving the contradiction between standardized treatment efficiency and individualized prediction accuracy.
Solution Approach 2:
The patent changes the parameter of treatment selection from population-based statistical probabilities to individual-based molecular characteristics. By analyzing specific mutations, expression levels, and molecular profiles of each patient's tumor, the system transforms treatment prediction from a general statistical approach to a precise individualized approach, resolving the contradiction between standardization and personalization.
2Reliability
If comprehensive preclinical and clinical tests are conducted to develop new antineoplastic agents, then potentially effective drugs can be identified, but the process becomes highly costly and laborious
Solution Approach 1:
The patent uses in silico molecular docking simulations to create virtual copies of drug-compound interactions, allowing comprehensive screening of potential treatments without physical experimentation. This copying approach enables reliable drug effectiveness prediction through computational modeling while avoiding the complexity and cost of extensive preclinical and clinical testing.
Solution Approach 2:
The patent replaces the mechanical system of physical drug testing and clinical trials with an in silico computational system. By using molecular docking algorithms and in silico simulations, the system substitutes wet-lab experimentation with dry-lab computation, reducing development complexity while maintaining reliability through accurate molecular interaction modeling.
3Reliability
If high doses of antineoplastic agents are administered to kill less responsive tumor cells, then treatment efficacy may be improved, but severe and life-threatening side effects occur that prevent application of sufficient doses
Solution Approach 1:
The patent applies local quality by selecting treatments based on the specific molecular characteristics of each patient's tumor rather than using uniform high-dose chemotherapy. By identifying mutations and molecular profiles unique to individual tumors, the system tailors treatment to the specific local characteristics of each case, achieving efficacy without the need for severe high-dose regimens that cause harmful side effects.
Solution Approach 2:
The patent introduces an intermediary layer of molecular characterization and in silico prediction between the patient and treatment selection. This intermediary analysis of mutations, expression levels, and drug-compound interactions enables precise matching of treatments to individual tumors, achieving effective treatment at lower doses and avoiding the harmful side effects associated with high-dose chemotherapy.
4Loss of time
If existing drugs are repurposed for antineoplastic treatment, then development time and cost can be reduced, but the drugs may act in an inadequate manner without sustainable improvement
Solution Approach 1:
The patent uses in silico molecular docking to create virtual models of drug interactions with mutated targets, enabling rapid assessment of repurposed drugs. This computational copying approach allows quick evaluation of existing drugs for new antineoplastic indications without extensive new development, while maintaining reliability through accurate prediction of binding affinities and molecular interactions.
Solution Approach 2:
The patent changes the parameter of drug evaluation from empirical clinical testing to in silico molecular characterization. By analyzing binding affinities, docking scores, and molecular interactions computationally, the system enables rapid repurposing of existing drugs with reliable prediction of their effectiveness against specific mutated targets, reducing development time while maintaining treatment reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the prediction of drug effects based on individual mutations, potentially overcoming resistance and side effects, and reduces the cost and time of drug development by repurposing existing drugs for targeted cancer therapy.
Implementation Method 1
determination of the binding affinity of a number of compounds to the one or more docking spaces of a mutated gene identified in the individual and identifying one or more compounds specifically binding to the mutated protein
Data Source
AI summary
The present invention relates to a method for identifying one or more compounds specifically binding to a target structure of a given diseased tissue in an individual, said method comprises the determination of the binding affinity of a number of compounds to the one or more docking spaces of a mutated gene identified in the individual and identifying one or more compounds specifically binding to the mutated protein. Further, the present invention relates to a computer program comprising instructions which cause the computer to carry out several steps of the method.