COMPUTATIONAL IDENTIFICATION OF NOVEL INHIBITORS FOR RETINOBLASTOMA TREATMENT USING INSILICO MODELLING AND SIMULATION TECHNIQUES

Abstract

This utility patent presents a novel Insilico methodology for identifying potential inhibitors targeting key molecular drivers in retinoblastoma, a highly malignant pediatric eye cancer. Retinoblastoma cells exhibit aberrant activity of Polo-like kinase 1 (PLK1) and Cyclin-dependent kinase 4 (CDK4), which are crucial for tumour progression and cell cycle regulation. This approach utilizes advanced computational techniques to screen and evaluate the efficacy of compounds 2760 and 1950 for PLK1 inhibition and compounds 3396 and 960 for CDK4 inhibition. The patented method applies molecular docking and dynamic simulations to predict the binding affinities of these selected compounds to the active sites of PLK1 and CDK4. The compounds were screened from extensive chemical libraries, followed by rigorous Insilico optimization to assess stability, binding specificity, and favourable pharmacokinetic profiles. Machine learning models trained on large datasets of kinase inhibitors were implemented to further validate compound efficacy, reduce off-target interactions, and minimize toxicity profiles. Key findings reveal that compounds 2760 and 1950 exhibit high binding affinity and specificity for PLK1, while compounds 3396 and 960 demonstrate effective inhibitory action on CDK4, highlighting their potential as novel therapeutic agents for retinoblastoma treatment. The Insilico approach described here significantly accelerates drug discovery timelines, offering a cost-effective, rapid alternative to traditional in vitro and in vivo screening. This patent establishes a strategic framework for using computational methods to identify precise therapeutic inhibitors, providing a promising pathway for advancing retinoblastoma treatment with minimal side effects and enhanced patient outcomes.

Specification

Description:IELD OF THE INVENTION
The current disclosure is related to the broader domain of Computational Identification of Novel Inhibitors for Retinoblastoma Treatment Using Insilico Modelling and Simulation Techniques.
DESCRIPTION
The subsequent comprehensive specification specifically delineates and elucidates the essence of this invention and outlines the method through which it is to be executed:
TECHNICAL FIELD
The currently revealed embodiments pertain, in a broad sense, to the analysis of speech. Specifically, these disclosed embodiments relate to Computational Identification of Novel Inhibitors for Retinoblastoma Treatment Using Insilico Modelling and Simulation Techniques.
BACKGROUND
Retinoblastoma is a rare yet aggressive form of eye cancer predominantly affecting young children. Despite advances in early detection and treatment, retinoblastoma remains life-threatening and may lead to vision loss if not promptly addressed. Current therapeutic approaches, including chemotherapy, radiation, and surgery, have limitations, such as significant side effects, high recurrence rates, and, in some cases, resistance
to standard treatment protocols. Thus, identifying novel, targeted therapies is crucial for improving patient outcomes and providing less invasive options.
Research into the molecular basis of retinoblastoma has highlighted several key proteins involved in tumor growth and cell cycle regulation, including Polo-like kinase 1 (PLK1) and Cyclin-dependent kinase 4 (CDK4). Both PLK1 and CDK4 play essential roles in cell division, making them attractive therapeutic targets. Overexpression or dysregulation of these kinases contributes significantly to the proliferation and survival of retinoblastoma cells. By inhibiting these proteins, it may be possible to halt or reverse tumor growth, presenting a promising approach for developing new retinoblastoma therapies.
PLK1 and CDK4 as Therapeutic Targets
PLK1 is a serine/threonine-protein kinase known for its critical role in regulating the cell cycle and mitotic processes. Overactivation of PLK1 in retinoblastoma cells promotes uncontrolled cell division, which is a hallmark of cancer progression. CDK4, another serine/threonine kinase, works in tandem with Cyclin D to regulate the G1-S phase transition of the cell cycle, driving cells into a proliferative state. Elevated activity of CDK4 has been observed in various cancers, including retinoblastoma, leading to the evasion of normal cell cycle checkpoints.
Inhibiting PLK1 and CDK4 has the potential to disrupt cancer cell division selectively, making these proteins strategic targets in developing novel therapies. While several inhibitors for these targets are in development for other cancers, few have been specifically tailored for retinoblastoma, highlighting an unmet need for disease-specific inhibitors.
INSILICO Approach in Drug Discovery
The rapid evolution of computational and INSILICO methods has opened new possibilities in drug discovery, particularly in identifying potential inhibitors for difficult-to-treat cancers like retinoblastoma. By leveraging molecular docking, dynamics simulations, and machine learning, INSILICO methods can simulate the interactions between a protein target and potential inhibitors in a virtual environment. This approach accelerates the screening process, allowing researchers to analyze the efficacy and specificity of thousands of compounds without the need for traditional in vitro or in vivo testing initially.
Purpose of the Patent
This patent aims to introduce a computational framework for identifying novel inhibitors of PLK1 and CDK4 specifically tailored for retinoblastoma treatment. The compounds-2760 and 1950 for PLK1, and 3396 and 960 for CDK4-were selected through comprehensive INSILICO screening based on binding affinity, selectivity, and predicted pharmacokinetic properties. By targeting PLK1 and CDK4, these compounds have the potential to inhibit cell proliferation in retinoblastoma effectively. This method not only offers a targeted therapeutic approach but also demonstrates the broader applicability of INSILICO techniques in rapid drug discovery, providing a faster, cost-effective pathway for addressing other cancers.
Challenges in Traditional Drug Discovery for Retinoblastoma
Traditional drug discovery methods for retinoblastoma face several key challenges, including the time-intensive process of identifying and validating effective compounds, the high costs associated with extensive laboratory testing, and the risks of side effects and toxicity inherent to general chemotherapy agents. Furthermore, retinoblastoma-specific drug development is limited by the rarity of the disease, making it less commercially attractive for large-scale pharmaceutical investment. These limitations underscore the need for innovative, cost-effective, and efficient approaches, such as INSILICO drug discovery, to advance targeted treatments for this patient population.
Retinoblastoma poses unique challenges at the cellular level as well. The blood-retinal barrier (BRB) restricts drug penetration to the retina, complicating the delivery of therapeutics to the tumor site. Any viable retinoblastoma inhibitor must demonstrate not only efficacy against PLK1 and CDK4 but also the potential to overcome BRB penetration limitations. Traditional drug discovery methods struggle to address this specificity requirement within acceptable timeframes and costs, thus motivating a transition toward INSILICO solutions that can rapidly simulate these conditions.
Advances in INSILICO Techniques for Retinoblastoma Treatment
The INSILICO approach utilizes advanced computational algorithms to simulate drug-target interactions, enabling the rapid screening of thousands of compounds based on their binding affinity, specificity, and predicted toxicity. The application of molecular docking techniques allows researchers to virtually "fit" compounds into the binding pockets of PLK1 and CDK4, modeling how effectively a compound can inhibit kinase activity. Following initial docking, molecular dynamics simulations are employed to evaluate the stability of these interactions under various physiological conditions, providing deeper insights into a compound's potential efficacy and durability as a therapeutic.
Additionally, machine learning models trained on vast datasets of kinase inhibitors have been implemented to predict compound behavior, refine binding predictions, and assess off-target interactions, further reducing the likelihood of adverse effects. These techniques not only streamline the drug discovery process but also allow for the prioritization of compounds based on criteria that are difficult to measure through traditional methods, such as BRB permeability and retinoblastoma-specific gene expression signatures.
Significance and Potential Impact
The development of compounds 2760 and 1950 as PLK1 inhibitors and compounds 3396 and 960 as CDK4 inhibitors through INSILICO methodologies represents a significant advancement in targeted retinoblastoma therapies. These compounds have been designed to selectively target the aberrant kinases driving retinoblastoma progression, potentially offering a more effective, less toxic alternative to conventional therapies. The INSILICO approach reduces reliance on animal testing and physical trials in early drug discovery stages, minimizing ethical concerns while expediting timelines and cutting costs.
By addressing the specific molecular drivers in retinoblastoma, this patent provides a foundation for further optimization and eventual clinical translation of these inhibitors. The broader applicability of this method to other cancers with kinase-driven growth also represents a promising pathway in oncology. The INSILICO approach in this patent could pave the way for more personalized and precision-based treatments in pediatric oncology, ultimately contributing to improved survival rates and quality of life for patients with retinoblastoma and potentially other cancers.
SUMMARY
Retinoblastoma, a rare form of eye cancer, primarily affects children. While traditional treatments exist, there's a pressing need for novel therapeutic approaches. This invention presents a significant advancement in the field of cancer research by identifying novel inhibitors against retinoblastoma through an in silico approach.
In Silico Screening for Novel Inhibitors
The invention focuses on targeting key proteins involved in retinoblastoma progression: PLK1, CDK4, and CDK6. These proteins play crucial roles in cell cycle regulation and tumor growth. By employing
computational techniques, the inventors have successfully identified potential inhibitors for these target proteins.
Identification of Promising Compounds
Through rigorous in silico screening, the following compounds have emerged as promising candidates:
• For PLK1:
o Compound 2760
o Compound 1950
• For CDK4:
o Compound 3396
o Compound 960
These compounds exhibit strong binding affinities to their respective target proteins, suggesting their potential to inhibit tumour growth and induce cell death.
Potential Therapeutic Applications
The identified compounds hold significant promise for the development of novel therapies for retinoblastoma. By targeting key proteins involved in tumorigenesis, these compounds may offer a more effective and less toxic treatment option compared to existing therapies.
This invention represents a significant step forward in the fight against retinoblastoma. The in silico approach employed in this study provides a rapid and efficient method for identifying potential drug candidates. The identified compounds offer a promising avenue for the development of novel therapies that could improve the outcomes for patients with retinoblastoma.
Mechanism of Action
The identified compounds are believed to exert their anti-cancer effects through various mechanisms, including:
• Inhibition of cell cycle progression: By targeting key cell cycle regulatory proteins like PLK1 and CDK4, these compounds can arrest cell cycle progression at specific checkpoints, leading to cell cycle arrest and apoptosis.
• Induction of apoptosis: These compounds may trigger programmed cell death in cancer cells by activating apoptotic pathways or disrupting cellular signalling networks.
• Suppression of tumour angiogenesis: By inhibiting angiogenesis, the formation of new blood vessels that supply nutrients to tumours, these compounds may starve tumours and limit their growth.
Advantages of the In Silico Approach
The in silico approach offers several advantages over traditional drug discovery methods:
• Reduced time and cost: Virtual screening allows for rapid identification of potential drug candidates, significantly reducing the time and cost associated with traditional experimental screening methods.
• Increased efficiency: Computational techniques can analyze vast chemical libraries to identify compounds with desired properties, increasing the efficiency of the drug discovery process.
• Improved selectivity: In silico methods can be used to predict the selectivity of compounds for target proteins, reducing off-target effects and minimizing potential side effects. , Claims:Claims:
I/We Claim:
1. A method for identifying novel inhibitors of retinoblastoma, comprising:
a) Identifying target proteins involved in retinoblastoma, including PLK1, CDK4, and CDK6;
b) Performing in silico screening of a chemical library to identify compounds that bind to said target proteins;
c) Selecting compounds from step (b) that exhibit high binding affinity and selectivity for said target proteins;
d) Validating the identified compounds in vitro and/or in vivo assays to confirm their inhibitory activity against retinoblastoma.
2. A compound selected from the group consisting of:
a) Compound 2760;
b) Compound 1950;
c) Compound 3396;
d) Compound 960;
or a pharmaceutically acceptable salt thereof, for use in the treatment of retinoblastoma.
3. A pharmaceutical composition comprising a therapeutically effective amount of a compound as claimed in claim 2 and a pharmaceutically acceptable carrier or excipient.
4. A method for treating retinoblastoma in a subject in need thereof, comprising administering to the subject a therapeutically effective amount of a compound as claimed in claim 2.
5. Use of a compound as claimed in claim 2 for the manufacture of a medicament for the treatment of retinoblastoma.

Documents