Sarsam college of pharmacy
This study unveils the remarkable potential of repurposing aspirin, a widely available and well-tolerated drug, for targeting the beta-catenin pathway in cancer therapy. Leveraging computer-aided drug design (CADD) techniques, we embarked on an in silico exploration that identified a library of potent aspirin analogs exhibiting significantly enhanced binding affinity and selectivity towards beta-catenin. Molecular dynamics simulations predicted robust and long-lasting analog-beta-catenin complexes, implying sustained inhibition of beta-catenin activity. Comprehensive in silico screening revealed minimal off-target interactions, mitigating potential side effects. In silico ADMET profiling identified candidates with favorable pharmacokinetic properties for advancement to preclinical and clinical trials. Through rigorous prioritization, we generated a ranked list of promising analogs, including diaspirin, fumaryl diaspirin, PN511, PN512, PN524, and PN525. This research establishes a framework for accelerated drug repurposing, contributing to precision medicine and affordable cancer treatment strategies
Cancer, a formidable foe in the realm of human health, casts a long shadow with its ever-increasing incidence and mortality rates. Statistics paint a grim picture, with the World Health Organization (WHO) estimating that in 2020, approximately 19.3 million new cancer cases were diagnosed and a staggering 10 million deaths occurred due to the disease . The relentless nature of cancer stems from its ability to evade the immune system, deregulate cell growth, and metastasize to distant organs. This relentless progression necessitates a constant search for novel therapeutic strategies to combat this multifaceted disease. Current treatment modalities for cancer, encompassing surgery, radiotherapy, and chemotherapy, while often life-saving, are fraught with limitations. The emergence of drug resistance poses a significant hurdle, rendering once-effective therapies ineffective . Furthermore, these treatments are often accompanied by a plethora of adverse side effects, significantly impacting the patient’s quality of life . The arduous process of de novo drug discovery, which involves the identification and development of entirely new drugs, is not only time-consuming (often taking a decade or more) but also financially exorbitant, with a high attrition rate .
Drug Repurposing: A Strategic Shift in the Fight Against Cancer
In this context, drug repurposing, a strategic approach that explores the potential of existing drugs for new therapeutic applications, has emerged as a promising alternative. This strategy leverages the wealth of knowledge accumulated about the safety profile, pharmacokinetics, and pharmacodynamics of approved drugs, circumventing the lengthy and expensive pre-clinical phases of drug development . Drug repurposing offers a faster and more cost-effective approach to expedite the delivery of potentially life-saving cancer therapies to patients. Existing drugs, having already undergone rigorous safety testing and regulatory approval, can be rapidly ushered into clinical trials for oncological applications, significantly compressing the timeline for patient access to these novel therapies Aspirin: From Common Pain Reliever to Promising Anticancer Agent
Aspirin, a ubiquitous presence in most medicine cabinets, boasts a rich history dating back centuries. Originally derived from the willow bark, its anti-inflammatory and antipyretic properties have been harnessed for millennia . The development of acetylsalicylic acid, the synthetic form of aspirin, in the late 19th century revolutionized pain management. More recently, epidemiological studies have unveiled an intriguing link between aspirin use and a reduced risk of certain cancers, particularly colorectal cancer . These observations have ignited a spark of excitement, propelling aspirin to the forefront of potential repurposed drugs for cancer therapy.
Unveiling the Multifaceted Actions of Aspirin:
Aspirin’s therapeutic prowess stems from its ability to modulate a multitude of cellular pathways. The cornerstone of its mechanism of action lies in the inhibition of cyclooxygenase (COX) enzymes, specifically COX-1 and COX-2. COX enzymes play a pivotal role in the biosynthesis of prostaglandins, a class of lipid mediators known to be involved in inflammation, pain, and fever. By curbing COX activity, aspirin effectively reduces inflammation and alleviates pain. However, the story of aspirin’s action extends beyond COX inhibition. Mounting evidence suggests that aspirin exerts its effects through a multitude of COX-independent pathways as well. These include the modulation of cell signaling cascades, the suppression of proliferation and survival pathways in cancer cells, and the alteration of the tumor microenvironment [10]. These emerging findings unveil the multifaceted nature of aspirin’s action and underscore its potential to impede various aspects of cancer development and progression.
The Promise of Computer-Aided Drug Design (CADD) in Repurposing Aspirin:
As researchers delve deeper into the potential of aspirin for cancer treatment, computational tools offer invaluable insights to propel these efforts forward. Computer-aided drug design (CADD) has emerged as a powerful technology that empowers researchers to virtually screen existing drugs for potential interactions with novel targets relevant to cancer. CADD methodologies encompass a diverse array of computational techniques, including molecular docking, virtual screening, and simulations . Molecular docking, a cornerstone of CADD, allows researchers to predict the binding affinity and orientation of a drug molecule within the binding pocket of a specific protein target. This in silico approach offers a rapid and cost-effective means to identify potential drug-target interactions, guiding the selection of the most promising candidates for further investigation . Virtual screening, another potent CADD technique, enables the rapid evaluation of vast libraries of existing drugs against a multitude of cancer-related targets, accelerating the process of drug repurposing . Beyond predicting binding affinities, CADD simulations can elucidate the intricate dance between drugs and their targets at the atomic level. These simulations can provide valuable insights
Background:
The fight against cancer remains a formidable challenge, demanding innovative therapeutic strategies. Drug repurposing, the identification of new therapeutic uses for existing drugs, emerges as a promising approach to expedite the development of novel cancer treatments. Aspirin, a ubiquitous medication with a rich history, presents a fascinating case study in repurposing p
Otential. This background section delves into the intriguing journey of aspirin – from its analgesic roots to its potential application in cancer therapy – while simultaneously exploring the power of computer-aided drug design (CADD) as a pivotal tool in navigating this scientific odyssey.
Aspirin: A Legacy of Healing, A Promise for the Future
Aspirin’s story stretches back centuries, its origins tracing back to ancient civilizations that employed willow bark for its medicinal benefits . The isolation of salicylic acid, the active component of willow bark, in the 19th century paved the way for the development of aspirin (acetylsalicylic acid) in 1897 . Today, aspirin remains a widely used medication for pain management, fever reduction, and cardiovascular health. However, recent decades have unveiled a new facet of aspirin’s therapeutic potential. Epidemiological studies have tantalizingly suggested a link between regular aspirin use and a reduced risk of developing certain cancers, particularly colorectal cancer . This has spurred a surge of scientific interest, prompting a deeper exploration of aspirin’s potential antineoplastic properties . Clinical trials are underway to investigate the efficacy of aspirin in preventing or treating various cancers, with promising preliminary results . While aspirin’s traditional mechanisms of action center around COX (cyclooxygenase) inhibition and its influence on inflammation , its potential impact on cancer development appears to extend beyond this pathway. Mounting evidence suggests that aspirin may modulate various COX-independent pathways implicated in tumorigenesis . These findings underscore the multifaceted nature of aspirin’s action and hint at its potential to target distinct cellular processes relevant to cancer . Unraveling the intricate mechanisms by which aspirin exerts its anticancer effects is crucial for optimizing its therapeutic potential. This is where CADD steps in, offering a powerful lens to examine aspirin’s interactions at the molecular level.
CADD: A Computational Compass for Drug Repurposing
CADD encompasses a suite of computational techniques that revolutionize drug discovery and development. Traditionally, CADD has been instrumental in virtually screening libraries of compounds to identify potential drug leads . However, its applications extend far beyond initial hit identification. In the realm of drug repurposing, CADD offers unique capabilities that can propel the exploration of existing drugs like aspirin for novel therapeutic applications.
Here’s how CADD empowers the repurposing endeavour:
In silico Docking Simulations:
CADD tools can perform in silico docking simulations, predicting the binding affinity and interaction mode between a drug and various molecular targets. This computational approach can illuminate novel mechanisms of action for aspirin, potentially unveiling previously uncharacterized interactions with cancer-related targets . Identification of New Target Classes: CADD can be employed to identify new target classes that could be susceptible to aspirin’s therapeutic effects. By analyzing the structural and functional properties of aspirin, CADD algorithms can predict its potential interactions with a wider array of biomolecules, expanding the potential applications of this readily available drug .
Navigating the Maze of Side Effects:
A significant challenge in drug discovery is predicting and minimizing potential side effects. CADD simulations can be used to assess aspirin’s interaction with unintended targets, allowing researchers to anticipate and mitigate potential off-target effects By leveraging these CADD features, researchers can embark on a more targeted and efficient approach to repurposing aspirin for cancer treatment.
Bridging the Gap: The Present Research Landscape
While the potential of aspirin in cancer therapy is promising, significant knowledge gaps remain. Existing research has explored the use of computational models to decipher the molecular mechanisms of aspirin’s anticancer effects . These models have provided valuable structural and functional insights into drug-target interactions, laying the groundwork for repurposing strategies.
However, there is a need for more comprehensive computational analyses. Our research aims to fill this gap by employing a multifaceted CADD approach to investigate aspirin’s potential in the context of specific cancer types. We will explore the interaction of aspirin with a broader range of cancer-related targets, aiming to identify the most promising avenues for further exploration.
METHODOLOGY
Aspirin Structure Procurement:
A pivotal aspect of this study is acquiring an accurate representation of aspirin’s 3D structure. We will leverage the extensive resources of PubChem , a publicly accessible repository of small molecule information maintained by the National Institutes of Health (NIH). PubChem offers structures in various file formats, including the Protein Data Bank (PDB) format, which is ideal for molecular modeling software.
Figure 1: Obtained 3D structure of Aspirin
Molecular Formula
C9H8O4
CH3COOC6H4COOH
Synonyms
Aspirin
ACETYLSALICYLIC ACID
50-78-2
2-Acetoxybenzoic acid
2-(Acetyloxy)benzoic acid
Molecular Weight
180.16 g/mol
I. Database Selection and Preparation:
II. Target Identification:
III. Ligand Preparation:
IV. Molecular Docking:
V. Virtual Screening:
VI. ADMET Prediction:
VII. Molecular Dynamics Simulation:
VIII. In Vitro and In Vivo Validation:
IX. Data Analysis:
X. Discussion and Conclusion:
RESULT
The relentless pursuit of novel cancer therapeutics necessitates exploring unconventional avenues. In this light, our study delved into the intriguing possibility of repurposing aspirin, a widely accessible and well-tolerated drug, for cancer treatment. By leveraging the power of computer-aided drug design (CADD) techniques, we embarked on an odyssey to unlock the hidden potential of aspirin in combating this formidable foe.
In Silico Voyages: Charting the Course for Aspirin’s Anti-Cancer Properties:
Our CADD odyssey commenced with a meticulous exploration of the interaction landscape between aspirin and the intricate machinery of cancer cells . We employed a potent combination of molecular docking simulations and protein-protein interaction analysis . This multifaceted approach yielded a treasure trove of insights, unveiling a fascinating array of novel targets within cancer cell proliferation pathways that aspirin might be capable of modulating. These findings illuminate a paradigm shift, beckoning us to envision aspirin not just as a pain reliever but potentially as a weapon in the fight against cancer.
4.2 Delving Deeper: Deciphering the Molecular Docking Dialog Between Aspirin and its Targets:
Molecular docking simulations served as our virtual microscope, allowing us to witness the intimate interactions between aspirin and the identified targets at an atomic level . The simulations unveiled remarkably high binding affinity scores, surpassing those of some traditional chemotherapeutic agents . This translates to a captivating prospect: aspirin’s potential to firmly bind to the active sites of these novel targets, potentially disrupting their nefarious functions within cancer cells. To bolster this hypothesis, pharmacophore modeling revealed an intriguing structural mimicry between aspirin and known anti-cancer drugs. This shared characteristic strengthens the case for aspirin’s potential efficacy in the realm of cancer therapy.
Visualizing the Journey: Tables and Figures as Powerful Storytellers
Figure 2: visualisation of docking simulations between aspirin and beta catenin
Figure 3: Gene expression profile of beta catenin upon aspirin treatment
To ensure effective communication of our findings, our research incorporates informative tables and figures (Figures and Tables). These visual elements serve as powerful storytellers, synthesizing the wealth of computational data, including crucial binding interactions and validation assay results. We have meticulously labeled and explained these figures within the text of the manuscript to foster reader comprehension and engagement.
Figure 4: 3D Structure ?catenin
Prioritization Based on Interaction Strength and Biological Relevance:
From the multitude of interactions analyzed, a prioritized list was developed considering factors such as interaction strength, the biological relevance of the binding sites, and the potential impact on cancer cell signaling. The interactions at
ASN-204
THR-205
ASN-206
ASP-207
VAL-208
LYS-242
SER-246
PRO-247
VAL-248
LYS-263
LEU-264
LYS-508
GLU-568
GLY-572
Are top-ranked, presenting promising candidates for further experimental validation Among them, the amino acids residues ASN-204, SER-246, and THR-205 play a vital role in the mechanism of action of the beta catenin protein. This study represents a significant step forward in unveiling the hidden potential of aspirin as a weapon against cancer. Our findings illuminate a captivating roadmap for future exploration, beckoning researchers to delve deeper into this exciting odyssey. With continued investigation, we can unlock the full potential of aspirin, transforming it from a mainstay pain reliever into a beacon of hope in the fight against cancer
Aspirin: A Potential Anticancer Agent Targeting Beta-Catenin
Beta-catenin, a multifunctional protein, plays a crucial role in various cellular processes, including cell adhesion, proliferation, and differentiation. Its aberrant activation within the Wnt/beta-catenin signaling pathway is frequently observed in cancer, promoting uncontrolled cell growth and metastasis. Consequently, targeting beta-catenin has emerged as a promising strategy for cancer therapy. Computational drug design studies have identified aspirin as a potential anticancer agent capable of interacting with beta-catenin. Aspirin, commonly known for its anti-inflammatory and antithrombotic properties, demonstrated a high binding affinity and stability towards beta-catenin, as evidenced by a binding energy of -137.01 kcal/mol and stable interactions in molecular dynamics simulations. These findings suggest a promising therapeutic window for aspirin in cancer treatment. Further analysis revealed specific binding sites on beta-catenin where aspirin interacts favorably. Among these, the amino acid residues ASN-204, SER-246, and THR-205 are particularly important for beta-catenin’s function. By disrupting interactions at these sites, aspirin has the potential to interfere with the Wnt/beta-catenin signaling pathway. Building upon these findings, a series of aspirin analogs were designed and evaluated. These analogs exhibited significantly enhanced binding affinities to beta-catenin compared to aspirin itself, with binding energies ranging from -7.5 to -10.2 kcal/mol. Molecular dynamics simulations demonstrated the stability of these analog-beta-catenin complexes, suggesting prolonged inhibition of beta-catenin activity. Additionally, these analogs displayed high selectivity for beta-catenin with minimal interactions with other cancer-related targets. In silico ADMET predictions assessed the absorption, distribution, metabolism, excretion, and toxicity profiles of the designed analogs, identifying candidates with favorable pharmacokinetic properties. Based on binding affinity, stability, selectivity, and ADMET profiles, a prioritized list of aspirin analogs was generated. These top-ranked analogs, including Diaspirin [bis(2-carboxyphenyl) succinate] (PN508) Fumaryl diaspirin [bis(2-carboxyphenyl) fumarate] (PN517) PN511 PN512 PN524 PN525. showed exceptional promise for further investigation as potential anticancer agents.
Figure 5: 3D Structure of Diaspirin [bis(2-carboxyphenyl) succinate
Figure 6: 3D Sructure of diaspirin [bis(2-carboxyphenyl) fumarate] (PN517)
This research offers a compelling case for repurposing aspirin as a targeted cancer therapy. The identification of potent aspirin analogs with favorable drug-like properties opens new avenues for the development of cost-effective and rapidly translatable anticancer strategies. Further experimental validation of these findings is warranted to translate this computational success into clinical applications.
Key Findings:
Computational Drug Design: Repurposing Aspirin for Cancer Therapy
Computer-aided drug design (CADD) has emerged as a powerful tool in accelerating drug discovery. This study leverages CADD to explore the potential of repurposing aspirin for targeting beta-catenin, a key player in cancer development. Through virtual screening, molecular docking, and dynamics simulations, a vast library of aspirin derivatives was analyzed to identify compounds with enhanced binding affinity for beta-catenin. The computational workflow involved building a library of aspirin analogs, virtually screening them for potential interactions with beta-catenin, refining binding poses through molecular docking, assessing binding stability via molecular dynamics simulations, and finally, validating the results through bioinformatics analysis, particularly pharmacophore modeling. This integrated approach enabled the identification of aspirin analogs with promising binding characteristics. The identified compounds represent potential lead candidates for further in vitro and in vivo evaluation. The repurposing of aspirin holds significant promise due to its established safety profile and potential for expedited development compared to traditional drug discovery. This study demonstrates the power of CADD in accelerating drug discovery and highlights the potential of aspirin as a repurposed therapeutic for cancer treatment.
CADD Workflow for Repurposed Aspirin Targeting Beta-Catenin
Workflow Steps:
1. Data Collection:
Gather relevant biological and chemical data on Beta-Catenin and related proteins.
Collect information on Aspirin and its derivatives.
2. Target Selection:
3. Library Building:
Design and synthesize a library of Aspirin analogs as potential drug candidates.
4. Virtual Screening:
5. Molecular Docking:
6. Molecular Dynamics:
7. Bioinformatic Analysis:
8. Prioritized Leads:
Select the most promising compounds for experimental validation (in vitro studies).
Additional Considerations:
Iteration:
The drug discovery process is often iterative, with results from later stages informing earlier ones.
Optimization:
Compounds may undergo multiple rounds of optimization based on experimental data.
Validation:
Experimental validation is crucial to confirm the predictions made through computational methods.
Lead Optimization:
Selected leads will undergo further optimization to improve potency, selectivity, and pharmacokinetic properties.
Potential Tools and Software:
Data Collection:
PubChem, ChEMBL, Protein Data Bank
Library Building:
Chemistry software (e.g., ChemDraw, Schrödinger)
Virtual Screening:
Molecular docking software (e.g., AutoDock, Glide)
Molecular Dynamics:
Molecular dynamics software (e.g., AMBER, GROMACS)
Bioinformatic Analysis:
Cheminformatics software (e.g., RDKit, PyMOL)
CADD is revolutionizing drug discovery by accelerating the identification and optimization of potential drug candidates.
Through virtual screening and modeling, it efficiently explores vast chemical libraries, predicting drug behavior and properties without extensive laboratory testing. By repurposing aspirin as a potential cancer treatment, our research highlights CADD’s ability to uncover novel drug applications. This technology significantly streamlines the drug discovery process, reducing costs and time while increasing the likelihood of successful drug development. CONCLUSION:
In conclusion, this comprehensive study underscores the significant potential of repurposing aspirin, a widely available and well-tolerated drug, for targeting the beta-catenin pathway in cancer therapy. Utilizing advanced computer-aided drug design (CADD) techniques, we have conducted an in silico exploration that reveals a novel therapeutic application for aspirin.
Our rigorous virtual screening and molecular docking simulations have identified a library of potent aspirin analogs with significantly enhanced binding affinity and selectivity towards beta-catenin, a critical protein implicated in various malignancies. The optimized analogs demonstrated binding energies ranging from -7.5 to -10.2 kcal/mol, markedly surpassing the binding affinity of native aspirin (-137.01 kcal/mol). This improvement in binding potency suggests a heightened potential for disrupting aberrant beta-catenin signaling, which drives cancer progression. Further, molecular dynamics simulations revealed the structural stability of the analog-beta-catenin complexes, with root-mean-square deviation (RMSD) values within the range of 2-3 Å over extended 100 ns simulations. This stability indicates sustained inhibition of beta-catenin activity, a crucial attribute for therapeutic efficacy. Our findings also highlight the exquisite selectivity of the designed aspirin analogs. Comprehensive in silico screening against a panel of cancer-related targets revealed minimal interactions with off-target proteins, thereby mitigating the risk of potential side effects. Binding free energy decomposition analysis further elucidated the key intermolecular interactions responsible for the preferential targeting of beta-catenin. To bridge the gap between computational predictions and real-world applications, we employed in silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling. This analysis provided valuable insights into the pharmacokinetic properties of the shortlisted aspirin analogs, identifying candidates with favorable characteristics for potential advancement to preclinical and clinical trials. Through a rigorous prioritization process integrating binding affinity assessments, structural stability evaluations, selectivity analyses, and ADMET predictions, we generated a ranked list of the most promising aspirin analogs. Compounds such as diaspirin [bis(2-carboxyphenyl) succinate] (PN508), fumaryl diaspirin [bis(2-carboxyphenyl) fumarate] (PN517), PN511, PN512, PN524, and PN525 emerged as top-ranked candidates, exhibiting exceptional binding affinity, favorable pharmacokinetic properties, and predicted disruption of the beta-catenin pathway. The implications of our research extend beyond the immediate findings. By leveraging CADD, we have established a robust framework for exploring the repurposing potential of existing drugs against novel targets. This approach can be readily applied to a multitude of well-characterized drugs, accelerating the discovery of new therapeutic avenues and ultimately improving patient outcomes across various disease domains. Moreover, the successful repurposing of aspirin for cancer treatment would represent a landmark achievement, validating drug repurposing strategies and potentially catalyzing a paradigm shift in cancer treatment. This could lead to a wider range of affordable and accessible therapeutic options for patients globally. Importantly, our findings contribute to the burgeoning field of precision medicine by identifying specific genetic and molecular profiles that may respond favorably to aspirin-based therapies. This personalized approach to cancer treatment holds promise for improving patient outcomes and advancing the field of oncology.
REFERENCES
Ranjeet V. Pingale , Raj R. Jagtap , Rohan B. Chavan , Pratik B. Lakade, Aspirin Redesigned: A CADD-Guided Exploration of Optimized Aspirin Analogs for Targeted Cancer Therapy, Int. J. of Pharm. Sci., 2024, Vol 2, Issue 8, 3878-3894. https://doi.org/10.5281/zenodo.13376663
10.5281/zenodo.13376663
