In Silico Design and Assessment of Coumarin Derivatives for Anticancer Activity

Structure and chemistry of coumarin

Coumarin, chemically known as 2H-chromen-2-one or 1,2-benzopyrone, is an aromatic oxygen-containing heterocyclic compound belonging to the benzopyrone family (7). Its molecular formula is C₉H₆O₂, and it consists of a benzene ring fused with an α-pyrone ring, forming a rigid planar structure. The core structure of coumarin provides a versatile scaffold that allows various substitutions at different positions, which greatly influence its physical, chemical, and biological properties (8). The coumarin nucleus contains two major reactive centers: the lactone ring and the benzene ring. Substitution at positions 3, 4, and 7 is particularly important for modifying its pharmacological activity. For instance, hydroxyl, methoxy, or amino groups at position 7 can enhance antioxidant and anticancer effects, while bulky or heterocyclic substitutions at position 3 often improve lipophilicity and target binding. This structural flexibility makes coumarin an attractive backbone for designing new bioactive derivatives. Coumarins can be synthesized through several methods, such as the Pechmann condensation, Perkin reaction, and Knoevenagel condensation, using simple phenolic and carboxylic precursors. Naturally, coumarins are widely distributed in plants like Murraya paniculata, Aegle marmelos, and Ferulago campestris, where they occur as secondary metabolites. Chemically, coumarins exhibit aromatic stability, moderate lipophilicity, and the ability to participate in hydrogen bonding and π–π interactions, making them suitable for interaction with biological macromolecules. These chemical characteristics underlie their diverse pharmacological actions, including anticoagulant, antimicrobial, antioxidant, and notably, anticancer properties (7).

Mechanism of action in cancer treatment

The anticancer effects of coumarin and its derivatives are mainly attributed to their ability to disrupt essential cellular processes that control the growth and survival of cancer cells. These compounds act through multiple molecular pathways, such as inhibiting key enzymes, triggering programmed cell death (apoptosis), and regulating signaling pathways involved in cell cycle progression (8).

One of the major mechanisms involves the inhibition of DNA topoisomerase IIα, an essential enzyme responsible for regulating DNA topology during replication and transcription. Topoisomerase IIα introduces transient double-strand breaks to relieve torsional strain in the DNA helix. In cancer cells, this enzyme is often overexpressed, promoting rapid cell division. Coumarin derivatives can bind to the active site of Topoisomerase IIα and stabilize the cleavable complex, thereby preventing the re-ligation of DNA strands. This results in DNA damage, replication arrest, and induction of apoptosis in rapidly dividing tumor cells (9,10).

In addition to topoisomerase inhibition, certain coumarins also exhibit antioxidant and anti-angiogenic properties. By scavenging free radicals and reducing oxidative stress, they protect normal cells while sensitizing cancer cells to apoptosis. Some derivatives suppress angiogenesis by inhibiting vascular endothelial growth factor (VEGF) and other pro-angiogenic pathways, restricting the blood supply to tumors.

Furthermore, coumarin analogs have been reported to modulate signaling cascades such as PI3K/Akt, MAPK, and NF-κB, which are crucial for cancer cell survival and proliferation. Through these multifaceted mechanisms, coumarin derivatives demonstrate significant potential as multi-target anticancer agents with lower toxicity compared to conventional chemotherapeutic drugs (11).

Ligand-based drug design

Ligand-Based Drug Design (LBDD) is a computational strategy used to design new drug candidates by utilizing information from previously known molecules that interact with a particular biological target. In contrast to structure-based drug design, which depends on the availability of the three-dimensional structure of the target protein, LBDD focuses on studying compounds that have already demonstrated activity. This approach becomes especially useful when the structural details of the target protein are unavailable or difficult to obtain experimentally (12,13).

The fundamental concept behind LBDD is that compounds with comparable chemical structures are likely to exhibit similar biological effects. By analyzing a group of biologically active molecules, key structural characteristics— such as hydrogen bond donors and acceptors, hydrophobic regions, aromatic systems, and electronic properties—can be recognized. These identified features are then used to construct pharmacophore models that define the essential requirements for biological activity (4,5).

Furthermore, LBDD makes use of several computational techniques, including quantitative structure–activity relationship (QSAR) modeling, molecular similarity analysis, and virtual screening methods. QSAR, in particular, helps in establishing correlations between the structural properties of compounds and their biological activities, enabling the prediction of the effectiveness of new molecules prior to their synthesis (12,14).

Overall, ligand-based drug design serves as a powerful strategy in modern drug discovery, enabling the optimization of lead compounds and the identification of novel analogs with improved activity, selectivity, and pharmacokinetic properties, thereby reducing the cost and time associated with traditional experimental screening (7,8).

Ligand design

The first step of this study involved obtaining a diverse set of coumarin derivatives from the PubChem database, a publicly available repository of chemical compounds. Around 20–30 derivatives were initially selected to ensure a broad representation of structural variations, including substitutions at positions known to affect biological activity, such as positions 3, 4, and 7 of the coumarin ring. To ensure that only safe and drug-like molecules were used, all downloaded compounds were subjected to toxicity and pharmacokinetic screening. ProTox-II, an online toxicity prediction tool, was employed to estimate potential hepatotoxicity, carcinogenicity, mutagenicity, immunotoxicity, and acute toxicity (LD₅₀). Compounds predicted to have high toxicity or adverse effects were eliminated from further analysis. Simultaneously, SwissADME was used to evaluate drug-likeness by analyzing key physicochemical properties such as molecular weight, lipophilicity (LogP), water solubility, hydrogen bond donors and acceptors, and gastrointestinal absorption. Compounds that complied with Lipinski’s Rule of Five and demonstrated low predicted toxicity were considered suitable for further computational analysis, ensuring that the study focused on safe, bioavailable, and potentially active derivatives.

Structure–activity relationship (SAR) analysis

1. Trifluoromethyl (–CF₃) or multiple fluorine substitution at the coumarin ring — increases binding affinity and metabolic stability by raising lipophilicity and strengthening hydrophobic/π-stacking interactions in the topoisomerase IIα pocket (examples: ligands containing C(F)(F)F such as L3, L11, L13, L14).

   Rationale: CF₃ groups increase van der Waals contacts and often improve membrane permeability and binding energy.

2. Tertiary amine side chains (N,N-dialkylamino) or basic alkylamino linkers — improve affinity via ionic/hydrogen-bonding interactions with acidic residues and increase solubility (examples: L2, L9, L10, L12, L18).

   Rationale: Basic amines can form salt-bridges or H-bonds with amino acids in the binding site, stabilizing the ligand conformation (L12 shows very favorable binding).

3. Carbonyl-containing substituents (acetyl/ester/amide links) appended to the ring — act as H-bond acceptors to form specific interactions and orient the ligand favorably (examples: acetylated/esterified ligands such as L5, L10, L12).

   Rationale: Carbonyls provide directional H-bonding and improve complementarity with the active site.

4. Rigid, fused tertiary-amine bicyclic motifs (conformational constraint) — increase potency by reducing entropic penalty on binding and enhancing shape complementarity (examples: cyclic tertiary amine containing ligands L9/L10/L12 which showed low RMSD and strong binding).

   Rationale: Pre-organized, rigid substituents often dock more reliably and provide additional hydrophobic contacts.

5. Very large/bulky polyaromatic or highly extended substituents — increase steric clash and molecular weight, often reducing binding or causing poor docking poses (examples: multi-phenyl or highly fused systems such as L19 or the highest-MW ligands).

   Rationale: Excessive bulk can prevent the ligand from fitting into the active site and worsen ADME.

6. Free phenolic hydroxyl(s) on the coumarin core (unprotected OH) — can reduce cell permeability and increase phase II metabolism (example: umbelliferone-like L1).

   Rationale: Polar OH groups can lower membrane penetration and be rapidly conjugated (glucuronidation), reducing effective intracellular concentration.

7. Reactive halogenated acyl groups (e.g., bromo-acetyl) or strongly electrophilic substituents — may raise predicted toxicity and off-target reactivity (example: L15 Br–C(=O)–…), which can reduce overall therapeutic potential despite possible binding.

   Rationale: Such groups can form covalent or unwanted adducts with proteins (toxicity risk) and are therefore undesirable for lead optimization.

Protein selection

The three-dimensional crystal structure of Topoisomerase II was obtained from the Protein Data Bank (PDB). Prior to docking, the structure was refined by eliminating water molecules, co-crystallized ligands, and other unnecessary ions. Hydrogen atoms were subsequently introduced to ensure appropriate bonding interactions, and partial charges were assigned to the protein. The processed structure was then saved in PDBQT format, making it suitable for use with AutoDock Vina.

Molecular docking

Molecular docking studies were performed using AutoDock Vina integrated within the PyRx platform, a commonly utilized software for virtual screening of ligands against target proteins. A grid box was precisely positioned around the active site of Topoisomerase II to ensure that the docking process focused on the functionally important region. Each selected coumarin derivative was docked separately, producing multiple conformations and binding orientations. The conformation exhibiting the lowest binding energy (i.e., the most negative value in kcal/mol) was regarded as the most stable and chosen for further evaluation. For detailed interpretation of ligand–protein interactions, the docking outcomes were analyzed using PyMOL and Discovery Studio Visualizer. Important interactions such as hydrogen bonding, hydrophobic contacts, π–π stacking, and electrostatic forces between the ligand and amino acid residues within the active site were identified. Additionally, comparison with reference anticancer ligands enabled evaluation of the relative binding potential of the tested compounds. This analysis helped in identifying derivatives with strong interaction capability and possible inhibitory effects on Topoisomerase II activity.

ADMET prediction

Following molecular docking, all selected derivatives were further evaluated for their ADMET properties to ensure safety and pharmacokinetic suitability. SwissADME was used to predict physicochemical characteristics such as molecular weight, hydrogen bond donors and acceptors, lipophilicity (LogP), solubility, and gastrointestinal absorption, providing insight into the drug-likeness of each compound. For toxicity assessment, ProTox-II and pkCSM were used to predict hepatotoxicity, cardiotoxicity, mutagenicity, immunotoxicity, and estimated lethal dose (LD50). Compounds that showed low toxicity, high gastrointestinal absorption, good solubility, and compliance with Lipinski’s Rule of Five were prioritized as promising candidates. This dual evaluation ensured that only derivatives with favorable binding affinities, safety profiles, and pharmacokinetic properties were identified as potential anticancer agents.