Introduction

Apoptosis, also known as programmed cell death, is an essential component of cellular homeostasis that is utilized to destroy undesirable cells or debris that has accumulated beyond repair during biochemical activities (Chaudhry et al. 2022). Apoptosis cell death is characterized by cell shrinkage, membrane blebbing, condensation of chromatin fibers, as well as DNA fragmentation (Green and Llambi 2015). Because of the killing of undesirable cells, apoptosis is most crucial for maintaining general cellular structures and functions in multicellular organisms. Stopping apoptosis can result in uncontrolled cell division, which leads to the development of several diseases such as inflammation, atherosclerosis, autoimmune, neurodegenerative and cancer (Loftus et al. 2022). Two pathways, including the intrinsic pathway that leads to mitochondrial-initiated events and the extrinsic pathway that is initiated by death receptors (Xu and Shi 2007) can trigger apoptosis. In the intrinsic pathway, loss in the transmembrane potential of mitochondria releases pro-apoptotic proteins from the inner membrane into the space of the cytosol. As a result, it triggers the activation of caspase proteins, which leads to a misbalance of the apoptosis process (Ouyang et al. 2012). Caspases, regulators of apoptosis, are cysteine proteases that cleave their substrate at aspartate residues. These proteases involve initiator caspases (caspase-2, -8, -9, -10, -11, and -12) and downstream effector caspases (caspase-3, -6, and -7), which are closely coupled to pro-apoptotic signals (Parrish and Freel 2013). Several pro-apoptotic proteins, such as cytochrome c, endonuclease G (EndoG), the second mitochondria-derived activator of caspase/direct inhibitor of apoptosis-binding protein with low pI (Smac/DIABLO), and others, are found in the inner space of the mitochondrial membrane and cause apoptosis when disrupted. The process is known as mitochondrial outer membrane permeabilization (MOMP), which occurs when mitochondrial inner transmembrane potential is lost, resulting in the synthesis of ATP and reactive oxygen species (ROS) and thus triggering cell death (O’Brien and Kirby 2008). Additionally, the protein Apaf-1 and cytochrome c link together to activate caspase-9, which in turn activates caspase-3/-7. During apoptosis, this complete cascade causes membrane blebbing, DNA fragmentation, and cell shrinkage (Shi 2002; Lakhani et al. 2006). According to Matthew Brentnall et al., caspase-3 prevented ROS formation, but caspase-7 has been linked to apoptotic cell detachment, resulting in effective cell death and protein cleavage (Brentnall et al. 2013). The catalytic cysteine residue in the active sites of caspase-3/-7 is identical, and they both cleave the same substrates with comparable efficiency (Kuribayashi et al. 2006). Conversely, both caspases show a high degree of specificity due to selective cleavage at the aspartic acid residue. This specificity relies on a concept of conformational selection, which binds the molecule preferentially in the stabilized site of the protein in a particular conformation while maintaining the equilibrium of numerous conformations (Laskowski et al. 2009). Furthermore, conformational selection can occur when a molecule binds to an orthosteric or allosteric site. When an endogenous ligand binds to an orthosteric site, a modulator molecule can bind to a topographically distinct allosteric site, causing a shift in the equilibrium between protein states and, as a result, an increase or decrease in agonistic action. On the other hand, targeting the ligand at the allosteric sites keeps the protein dynamic in balance, which is why they respond specifically to drug molecules (Conn et al. 2009). Considering the importance of the allostery concept, drug design may benefit from modifying allosteric responses. Allosteric medicines have the potential to display enhanced target selectivity, reduced side effects, and decreased drug resistance by specifically targeting several locations on a single protein (Häcker et al. 2011). As shown in the literature, allosteric inhibition of caspase-3/-7 could serve as a possible therapeutic target to halt apoptosis-based disorders such as cancer, Alzheimer’s, Parkinson’s, cardiac arrest, ischemic strokes, and so on (Kesavardhana et al. 2020). During some decades, several caspase inhibitors targeting binding sites or catalytic pockets have been explored, but they have limited efficacies due to extensive competition between caspases and their indigenous substrates (Becker et al. 2004). Jeanne A. Hardy et al. uncovered new allosteric sites at the dimer interface of caspase-3/-7 enzymes. They screened numerous compounds having thiol linkage against allosteric sites of caspase-3/-7 and found that two molecules, namely 2-(2,4-Dichlorophenoxy)-N-(2-mercapto-ethyl)-acetamide (DICA) and 5-Fluoro-1H-indole-2-carboxylic acid (2-mercapto-ethyl)-amide (FICA), inhibit the peptide binding via the formation of disulfide bridges with cysteine residues, Cys264 in caspase-3 and Cys290 in caspase-7, in the central cavity presented at the dimer interface. The binding of both molecules at allosteric sites disturbs the orthodox binding, which results in the inactivation of caspase-3/-7. That’s why these molecules act as allosteric inhibitors (Hardy et al. 2004). Previous investigations (in vitro and in vivo) have shown that several drugs, including some FDA-approved medications, had caspase inhibitory action (MacKenzie et al. 2010). Deepak et al. found that four compounds, diflunisal, flubendazole, fenoprofen, and pranoprofen, reduce caspase-3 activity in a recombinant caspase-3 enzyme assay. In this approach, every compound had significant IC50 values ranging from 10.37 ± 0.5 to 54.32 ± 0.6 mM (Krishna Deepak et al. 2018). Furthermore, Lee et al. revealed isatin sulphonamide and 5-dialkylaminosulfonylisatins as non-peptide caspase-3/-7 protein inhibitors that reduce apoptosis in mouse bone marrow neutrophils, Jurkat T cells, and human chondrocytes. Interestingly, 5-dialkylaminosulfonylisatinsas binds to the S2 subsite of caspases 3/-7, which contains Tyr204, Trp206, and Phe256 amino acid residues, whereas isatin sulphonamide binds to the S2 subsite but not to the aspartic acid-binding pocket S1 (Lee et al. 2000, 2001).

Despite the presence of synthetic allosteric caspase inhibitors, many bioactive substances derived from medicinal plants, referred to as plant-derived compounds, have the ability to regulate apoptosis through caspase-dependent or independent processes (Rahman et al. 2021). Except medicinal plants, functional foods have gained a lot of attention as nutraceutical products because of their health benefits due to the presence of bioactive compounds in addition to nutrients like carbohydrates, amino acids, peptides, dietary fibers, vitamins, minerals and microelements (AlAli et al. 2021). Although there are thousands of plant-derived compounds with various pharmacological functions, herein, we will not detail them; instead, we will focus on berry fruits. Several studies revealed that berry fruits have health-improving effects and prevent chronic diseases as they are rich in nutrients and bioactive compounds (Golovinskaia and Wang 2021). Some species of berries, such as blackberries, blueberries, blackcurrants, cranberries, raspberries, and strawberries are good sources of polyphenols including flavonols, flavanols, ellagitannins, hydrolysable tannins, non-hydrolysable tannins, proanthocyanidins, anthocyanins and stilbenes (Nile and Park 2014). These bioactive compounds have been found to show their antioxidant, anti-inflammatory, antidiabetic, antimicrobial, neuroprotective and cardio protective effects. Several in-vitro and in-vivo studies revealed that berry fruits have excellent antioxidant and anti-aging properties due to the presence of a high content of polyphenols, contributing to the organoleptic qualities of fruits (Bader Ul Ain et al. 2022; Baby et al. 2017). As per the in-vitro study, six berries (blackberry, blueberry, raspberry, black raspberry, cranberry and strawberry) and their polyphenol compounds showed the anticancer effect by stimulating apoptosis of the COX-2 enzyme as well as inhibiting cell proliferations in HT-29/HCT116 colon cancer cells (Seeram et al. 2006). Cyanidin-3-glycoside, an anthocyanin of black raspberry, inhibited the oxidative DNA damage in human colon epithelial cells whereas inhibited the apoptosis and G1 phase of the cell population in cultured Caco-2, respectively (Duthie et al. 2004; Elisia and Kitts 2008). In some studies, phenolics and flavonoids rich fractions of cranberry as well as extracts of chokeberry and bilberry inhibited cell proliferation with progressive cell-cycle arresting that leads to apoptosis in HT-29 line colon cells (Ferguson et al. 2004; Zhao et al. 2004). Some lyophilized extracts of strawberries had been found to reduce tumor incidence via inhibiting pro-inflammatory mediators (TNF-α, IL-1β, IL-6, COX-2, and iNOS), suppressing nitrosamine stress, and lowering down the overexpression of PI3-K, Akt, ERK, and NF-κB cell signaling in the AOM/DSS mouse model (Shi et al. 2015). Regulating of cell cycle and apoptosis signaling are shown by ellagitannins (ellagic acid, urolithin A, urolithin B, and ellagic acid), cyanidin chloride, cyanidin-3-O-glucopyranoside and enterolactone in different cancer cell lines (in-vitro) as well as in rat models (in-vivo) as displayed by studies (Cho et al. 2015; Renis et al. 2008; Danbara et al. 2004). Apart from their pharmacological actions, numerous studies have demonstrated that the flavonoids, polyphenols, and withanolides (e.g., perulactones) derived from berry fruits reduce caspase activity via activating caspase enzyme activity, which in turn cleaves the pro-caspase into the active form. (Chien et al. 2009; Shen et al. 2003; Wang et al. 1999; Henrich et al. 2015). Myricetin suppressed caspase-3 activity (IC50 10.2 mM) in rat neural cell cultures, according to research by Shimmyo et al. By using the docking method, they investigated the chemical interaction in which the hydroxyl group on the myricetin B-ring interacted with Glu 123 and the ether oxygen bonded to the Arg 207 amino acid residues of the caspase-3 active site (Shimmyo et al. 2008). Ahmad Abdullah et al. demonstrated an in vitro assay in which kaempferol interacts with the caspase-3 enzyme at allosteric regions and inhibits it via a competitive mechanism. By molecular docking, kaempferol showed hydrophobic interactions and H-bonding interactions with the Cys 290 residue and the Val 292 and Met294 residues of caspase-7, while the Arg 164, Tyr 197, Glu 124, Arg 164, Thr 140, Tyr 195, Val 266, Lys 137, Leu 136, Pro 201, and Gly 125 residues of caspase-3 showed hydrophobic interactions and H-bonding interactions (Abdullah and Ravanan 2018). Nevertheless, kaempferol may block caspase 7 in conjunction with other inhibitors to partially reverse apoptosis, suggesting that kaempferol can induce apoptosis through either an independent or caspase-dependent mechanism (Dang et al. 2015). Furthermore, it was shown that withanolides, like withaferin A, might control apoptosis in different colorectal cancer cell lines by cleaving caspase-3 and reducing anti-apoptotic proteins (Jung et al. 2022). Withaferin A demonstrated molecular interactions via the BIR domain with the apoptotic protein inhibitor in a docking study, which subsequently inhibited caspase-3/-7 (Wadegaonkar and Wadegaonkar 2012). Withanone also bound to the BIR domain of the apoptotic protein Survivin, and through this interaction, the two worked together. As a result, caspases-3/-7 are inhibited, which causes them to undergo apoptosis (Wadegaonkar and Wadegaonkar 2013).

The combined results of the aforementioned studies indicate that a number of flavonoids and withanolides can inhibit apoptotic proteins, such as caspases like caspase-3/-7. However, no information has been provided concerning the molecular mechanism underlying the inhibition of these compounds’ allosteric caspases, which determines how they interact and cleave them. Motivated by this, we propose here that plant-derived compounds, particularly flavonoids and/or polyphenols, as well as withanolides, may offer a promising platform for the development of caspase inhibitors for the treatment of diseases associated with apoptosis. We thus tried to find the best allosteric inhibitor among the one hundred (100) compounds of berry fruits at their allosteric sites of caspase-3/-7 that are executioner proteins in apoptosis pathways. Our findings may help numerous researchers and scientists to build and identify therapeutic leads of plant origin against allosteric regions of caspase-3/-7 proteins.

Methodology

Selection of compounds for ADME screening

ADMET such as absorption, distribution, metabolism, excretion, and toxicity is used to screen the drug leads for their suitability via oral administration. We have prepared a library of 100 compounds from berry fruits premised on their pharmacological activities, especially anticancer activity from the previous literature investigations and then screened them for pharmacokinetics (ADMET) properties using an in silico approach with the help of the QikProp v6.8 module of Schrödinger 2020-4 LCC, New York, USA. All the selected compounds were examined for drug-like characteristics based on Lipinski’s rule of five (Ro5) such as molecular weight (≤ 500), hydrogen bond donor (≤ 5), hydrogen bond acceptor (≤ 10), and lipophilicity (≤ 5). Furthermore, pharmacokinetic parameters such as solubility, blood–brain barrier, human serum albumin, and oral absorption in humans were also determined (Teli et al. 2021). Furthermore, we employed Osiris Property Explorer software and ProTox 3.0 server to screen the toxicity characteristics, such as mutagenic, tumorigenic, irritating, and reproductive effects for all the compounds (https://tox.charite.de/protox3/).

Preparation of ligands and receptors

Amongst the selected compounds, we found only 1–20 compounds by displaying drug-like or drug-ability properties with a full fill of Ro5. Thus, we took 1–20 compounds (Fig. 1) for further in-silico study. The three-dimensional (3D) structures of all compounds, along with the reference drugs, namely 2-(2,4-Dichlorophenoxy)-N-(2-mercapto-ethyl)-acetamide (DICA) and 5-Fluro-1H-indole-2-carboxylic acid (2-mercapto-ethyl)-amide (FICA), were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/). The geometries of chemical structures were cleaned and optimized using the Merck molecular force field (MMFF) visualizer in Biovia Discovery Studio 3.0, then saved in.pdb format. The AutoDock4 software was also used to specify the detecting root, number of torsions, and aromaticity criteria (Khan et al. 2021). The three-dimensional crystallographic structures of caspase-3 (PDB ID:1NME) and caspase-7 (PDB ID:3IBF) receptors, with resolutions of 2.50 Å and 1.60 Å (Erlanson et al. 2003; Agniswamy et al. 2009) were obtained from the RCSB Protein Data Bank (https://www.rcsb.org/). The Biovia Discovery Studio 3.0 visualizer was used to remove the water molecules and heteroatoms from the target protein structures before adding missing hydrogen atoms. To screen the interactions between receptor and ligand, the define site module of the Biovia Discovery Studio 3.0 visualizer was used to estimate the binding site coordinate of the targeted protein receptor. Furthermore, using the AutoDock4 software, polar hydrogen atoms and Kollman charges were used to prepare receptors for molecule docking (Tallei et al. 2020).

Fig. 1
figure 1

The molecular docking poses A molecular interactions of perulactone with caspase 3 (PDB:1NME) protein, and B molecular interactions of perulactone with caspase-7 (PDB:3IBF) protein

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Molecular docking

The molecular docking approaches can be used to predict the ligand-receptor binding affinities. To explore the allosteric sites of 1NME and 3IBF targets against the best 1–20 compounds, the AutoDock Vina 1.1.2 software (developed by Dr. Oleg Trott, Scripps Research Institute) was used to perform receptor-oriented flexible docking. The grid box of 50 × 50 × 50 Å3 dimensions was optimised over the receptor binding site for molecular docking using X = −3.704, Y = 13.032, Z = 4.398 and X = 41.857, Y = 95.643, Z = 24.016 coordinates. The selected compounds were treated as flexible ligands, which mimic the binding with proteins in real system during docking. The final position was visualised using the Biovia Discovery Studio 3.0 visualizer after docking which is based on the lowest binding affinity (Khan et al. 2021; Singh and Purohit 2023; Singh et al. 2024). Herein, we reported the best docking scores in triplicate runs for each of compounds (1–20) against both the targets 1NME and 3IBF.

Molecular dynamic simulation

The study of molecular dynamic (MD) simulations is employed to better understand the deep insights of molecular interactions in between ligand–protein complexes. The ligand–protein complexes were created in the TIP3P (Transferable Intermolecular Potential with 3 Points) water system for MD simulation, and four Na+ and five Cl− ions were added to neutralize the entire system of two complexes, such as perulactone-3IBF and perulactone-1NME complexes. The ligand–protein complexes were encased in an orthorhombic box shape with 10 Å × 10 Å × 10 Å dimensions and minimized using the system builder module (Desmond Schrödinger 2020-4 LCC, New York, USA) and the OPLS_2005 (Optimised Potentials for Liquid Simulations) force field. Furthermore, the ligand–protein system as a whole was loaded from the workspace, and the time was set to 100 ns to estimate the complex’s stability in the simulated biological system. Prior to the MD simulation, the NPT thermodynamic parameter with 1.0 bar pressure at 300 K temperature was implemented. Furthermore, the RESPA (Reversible Reference System Propagator Algorithm) was used to calculate the time steps for the near and far-bonded (2–6 fs). The partial mesh was maintained using the Nose–Hoover chain thermostat and Martyna-Tobias-Klein barostat procedures. The electrostatic interaction between atoms was quantified using the Ewald method with a Coulombic radius cutoff of 9.0. After the MD simulations were completed, the energy was measured every 100 ps and the trajectory was analyzed using the SID (Simulation Interaction Diagram) panel (Khan et al. 2022a, b; Sheikh et al. 2023a, b; Kumar et al. 2023).

Prime MMGBSA calculations

Following MD simulation, the free binding energy of the docked complexes perulactone-1NME and perulactone-3IBF was validated using the prime module of the Molecular Mechanics-Generalized Born Surface Area (MMGBSA) module of Schrödinger 2020-4 LCC, New York, USA. The complexes were produced using the implicit VSGB (Variable Dielectric Generalized Born) solvation condition and then reduced using the OPLS_5 force field. The MMGBSA binding free energy of complexes was then computed using the thermal_mmgbsa.py python program (Alghamdi et al. 2023; Khan et al. 2022a, b). The Gibbs-free energy, coulombic energy, generalized solvation energy, and van der Waal energy were calculated using the equation below:

$$ \Delta G_{{\text{binding}}} = \Delta E_{{\text{MM}}} + \Delta G_{{\text{solvent}}} + \Delta G_{{\text{SA}}} $$
(1)

where ΔGbinding = Binding free energy; ΔEMM = difference between ligand–protein complex energy and total energy of ligand and receptor; ΔGsolvent = difference between of solvation energy of ligand–protein complex and total solvation energy of ligand and receptor; ΔGSA = difference between the surface area energy of ligand and receptor.

Result and discussion

Assessment of ADMET properties

The drug-abilities or drug-like properties of 100 compounds of berry fruits were evaluated using ADMET analysis to validate their necessary properties in Lipinski’s rule of five (Ro5) for oral bioavailability. If any compound shows either zero or less than one violation, then it is considered an oral drug lead. Thus, it can be validated that a molecule can be submitted for its molecular docking study. Among the 100 compounds, only twenty compounds (1–20) passed out through the screening test of the Ro5 rule. A literature survey also reveals that these compounds have various pharmacological activities like anticancer, anti-inflammatory, and antioxidant, but no study was reported at allosteric sites that inhibit the apoptosis pathway. In the present study, we obtained the perulactone as the best compound with good agreement with the Ro5 rule, including molecular weight (518.6), hydrogen bond donors (03), hydrogen bond acceptors (09), and lipophilicity (3.76). Moreover, we also predicted the pharmacokinetic properties of perulactone such as −5.78 mol/dm3 aqueous solubility (standard range −6.5 to 0.5 mol/dm3), −1.73 blood–brain barrier (standard range −3.0 to 1.2), 0.68 human serum albumin interaction (standard range −1.5 to 1.5), and high human oral absorptions (standard range 1 = low, 2 = moderate, 3 = high) respectively. Therefore, the perulactone demonstrated outstanding pharmacological activity, a drug-like candidate, and did not have any toxicity including mutagenic, tumorigenic, irritating, or reproductive effects. It also followed the recommended range of parameters of ADMET characteristics (Mohan et al. 2021). For all the compounds (1–20), ADME characteristics are displayed in Table 1 whereas Table 2 shows the toxicity profiles.

Table 1 ADMET properties of the 20 compounds using QikProp tool
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Table 2 The toxicity parameters of the 20 compounds
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Molecular docking analysis

To filter the small molecule as a drug-like candidate from the chemical structure library, structure-based study is an extremely vital strategy, where molecular docking investigations fit well in the area of ligand-receptor interactions. After screening the ADMET test, we performed a molecular docking study to explore the molecular interactions of compounds (1–20) within the allosteric sites of caspase-3 (1NME) and caspase-7 (3IBF) receptors. In this study, as a consequence of hydrogen bonds, hydrophobic interactions, and involved amino acids, docking scores (binding energy) were noted in kcal/mol. Further, the docking scores (binding energy) of 1–20 compounds were compared with FDA-approved allosteric caspase inhibitors DICA and FICA as reference drugs. In the case of 1NME (caspase-3) target, the majority of the compounds showed good docking scores (>−7.0 kcal/mol) such as perulactone (1) (−9.1 kcal/mol), perulactone B (2) (−8.1 kcal/mol), pinocembrin (3) (−7.8 kcal/mol), myricetin (4) (−7.8 kcal/mol), naringenin (5) (−7.8 kcal/mol), ellagic acid (6) (−7.6 kcal/mol), galangin (7) (−7.9 kcal/mol), pinobanksin (8) (−7.5 kcal/mol), quercetin (9) (−7.8 kcal/mol), catechin (10) (−7.7 kcal/mol), kaempferol (11) (−7.8 kcal/mol), epicatechin (12) (−7.2 kcal/mol), procyanidin C1 (13) (−7.2 kcal/mol), and petunidin (14) (−7.3 kcal/mol) whereas reference molecules DICA and FICA exhibited relatively low docking scores as −5.0 and −5.1 kcal/mol, respectively. Herein, perulactone, having the highest docking score, was selected for a detailed study. Perulactone interacted with 1NME allosteric sites via three H-bonds (Asn208, Ser251, Asp253), one C-H bond (Glu248), four pi-alkyl bonds (Trp206, Trp214, Phe247, Phe256), and three hydrophobic interactions (Ser209, Glu246, Phe252). On the other hand, DICA showed two H-bonds (Trp214), one pi-pi (Phe247), two pi-alkyl (Phe247), one pi-sulphur (Trp206), and eight hydrophobic (Arg207, Asn208, Ser209, Asp211, Gln217, Glu248, Ser249, and Phe250) interactions, whereas FICA exhibited one H-bond (Glu248), a C-H bond (Glu246), pi-pi (Trp206), halogen-bond (Arg207), van der Waal bond (Trp214), and five hydrophobic (Asn208, Ser209, Phe247, Ser247, Ser249, and Phe250) interactions. Comparing the docking scores and molecular interactions, amongst all compounds, perulactone is the most promising agent that binds effectively at allosteric sites of 1NME than that of DICA and FICA drugs. Figure 1A and Table 3 show detailed information on the docking scores of all the screened compounds and molecular interactions (2D and 3D) of the perulactone-1NME complex.

Table 3 Binding affinity list of selected 20 berries compounds and control drugs
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In the case of 3IBF (caspase-7) target, the majority of the compounds showed good docking scores (>−7.1 kcal/mol) such as perulactone (1) (−12.1 kcal/mol), perulactone B (2) (−9.7 kcal/mol), pinocembrin (3) (−8.0 kcal/mol), myricetin (4) (−8.0 kcal/mol), naringenin (5) (−8.0 kcal/mol), ellagic acid (6) (−8.0 kcal/mol), galangin (7) (−7.9 kcal/mol), pinobanksin (8) (−7.9 kcal/mol), quercetin (9) (−7.9 kcal/mol), catechin (10) (−7.9 kcal/mol), kaempferol (11) (−7.8 kcal/mol), epicatechin (12) (−7.8 kcal/mol), procyanidin C1 (13) (−7.7 kcal/mol), and petunidin (14) (−7.5 kcal/mol) whereas reference molecules DICA and FICA exhibited relatively low docking scores as −5.6 and −6.1 kcal/mol, respectively. Similarly, perulactone, having the highest docking score, was selected for a detailed study. It was found that against 3IBF, perulactone showed three alkyl (Ile159, Lys160, Pro227), two pi-alkyl (Phe221, Phe521), and thirteen hydrophobic (Asn148, Thr163, Arg187, Tyr223, Val226, Tyr229, Val292, Asn448, Ile459, Lys460, Thr463, Glu516, Tyr523) molecular interactions. On the other side, DICA showed two H-bonds (Arg487, Tyr523), three alkyl bonds (Val226, Lys460, Met594), one pi-alkyl bond (Pro227), one pi-pi bond (Phe521), and four hydrophobic (Arg187, Val292, Thr463, Val592) interactions, while FICA binds via two H-bonds (Arg487, Tyr523), two pi-alkyl bonds (Pro227, Val592), one pi-pi bond (Phe521), one halogen bond (Glu516), and four hydrophobic (Arg187, Val292, Pro527, Met594) interactions at the allosteric sites (Ansari et al. 2022a, b). Comparing the docking scores and molecular interactions, amongst all compounds, perulactone is the most promising agent that binds effectively at allosteric sites of 3IBF than that of DICA and FICA drugs. Figure 1B and Table 3 show detailed information on the docking scores of all the screened compounds and molecular interactions (2D and 3D) of the perulactone-3IBF complex.

Overall, perulactone had the highest docking score and a higher number of molecular interactions when compared to DICA and FICA, facilitating its functionalities to be tightly bound at allosteric sites of both the 1NME and 3IBF receptors. Furthermore, to explore the binding strengths of Perulactone within the binding pockets of 1NME and 3IBF, a molecular dynamic simulation study was performed for Perulactone-1NME and Perulactone-3IBF complexes.

Molecular dynamic simulation

The MD simulation analyzes the ligand–protein interactions’ stability and conformational changes. In this study, we measured the RMSD (root mean square deviation), RMSF (root mean square fluctuation), SSE (secondary structure elements), Rg (radius of gyration), MolSA (molecular surface area), SASA (solvent accessible surface area), and PSA (polar surface area) of Perulactone-1NME and Perulactone-3IBF complexes for 100 ns MD simulation in triplicate.

RMSD and RMSF analysis

The RMSD values of the Perulactone-3IBF complex were observed between 1.270–3.088 Å and 1.011–2.069 Å for ligand and protein, as depicted in Table 4. The perulactone showed very compact binding within the active site due to less deviation (Fig. 2A), and it achieved equilibrium from the initial to the end of the simulation. The ligand indicated strong interactions, including H-bonds to Arg487 (62%), Glu216 (74%), water-bridges to Arg187 (74%), Glu447 (75%), Pro527 (37%), and Phe221, which showed hydrophobic interaction to the end of the simulation (Fig. 3A). Secondly, we analyzed the perulactone-1NME complex, showing the RMSD values range from 2.426–9.850 Å and 1.129–3.156 Å for ligand and protein respectively (Table 4). During the simulation, the perulactone deviated from the initial position to 9.540 Å because it bound with the amino acids in the loop region for a small time period (0.80 ns). In Figs. 2B and 3B, perulactone showed the stability through binding within the β-strand region via displaying the H-bond to Ser209 (57%), three water-bridges to Trp206 (36%), Arg207 (33%), Phe250 (30%), and hydrophobic interaction to Tyr204, and Phe256 amino acids of the receptor. Thus, the values of RMSD stated that perulactone forms stable bindings within the 3IBF and 1NME protein receptors (Ansari et al. 2023; Alhakamy et al. 2023).

Table 4 MD simulation parameters of perulactone compound with 3IBF, and 1NME proteins
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Fig. 2
figure 2

The RMSD plots A perulactone-3IBF ligand–protein complex, B perulactone-1NME ligand–protein complex, and RMSF plots C perulactone-3IBF ligand–protein complex, D perulactone-1NME ligand–protein complex

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Fig. 3
figure 3

Ligand interactions: A perulactone-3IBF ligand–protein complex, B perulactone-1NME ligand–protein complex and Bar charts of ligand interactions of C perulactone-3IBF ligand–protein complex, D perulactone-1NME ligand–protein complex

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The RMSF explores the resiliency of the amino acids in proteins. The higher fluctuations of amino acids reveal more flexibility, whereas the lesser fluctuations of amino acids indicate the more compactness of ligands in the active sites of proteins. To check the compactness of perulactone within the 3IBF and 1NME proteins, the RMSF values were found as 0.334–3.997 Å, and 0.408–10.378 Å for perulactone-3IBF, and perulactone-1NME complexes respectively. As depicted in Table 4 as well as Fig. 2C and D, Moreover, high fluctuations were noticed in the loop regions of the active site of caspase 7 including Gln603, Gln303, Glu365, and Asp578 amino acids whereas the fluctuation took place between Thr174, Lys186 amino acids of caspase 3 during the whole duration of simulation as displayed (Sheikh et al. 2023a, b; Sepehri et al. 2022).

Analysis of secondary structure elements (SSE)

The secondary structure elements (SSE) were explored for the variations in the α-helices and β-strand amino acids that arise during MD simulation. The α-helices and β-strand amino acids were monitored for both the complexes such as perulactone-3IBF, and perulactone-1NME. To this, it had been observed that the total percentage of SSE involved 39.53% comprising 21.91% α-helices and 17.62% β-strand, among the total percentage of SSE for the perulactone-3IBF complex, while 37.80% percent, which included 20.58% α-helices and 17.23% β-strand of total SSE was found for perulactone-1NME (Table 5). Thus, perulactone-3IBF complex showed lesser changes in amino acids of the active sites of 3IBF due to α-helices and β-strands (Fig. 4A), whereas more fluctuations were observed in the perulactone-1NME complex due to large loop regions of amino acids over the simulation (Fig. 4B) (Abdalla et al. 2022).

Table 5 Percentage of secondary structure regions amino acid distribution of 3IBF and 1NME proteins throughout 100 ns MD simulations
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Fig. 4
figure 4

The plots of secondary structure elements (SSE) such as α-helices (orange colour) and β-strands (colour) involved for the ligand–protein complexes: A perulactone-3IBF ligand–protein complex, B perulactone-1NME ligand–protein complex during the 100 ns MD simulation

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Radius of gyration (Rg) analysis

The radius of gyration (Rg) is a crucial parameter that defines the folding of ligands in the ligand–protein complex in MD simulation evaluation. In the current study, the calculated values of Rg were found to range from 5.110 to 5.726 Å, and 4.875 to 5.720 Å for perulactone-3IBF, and perulactone-1NME complexes, respectively (Table 4). It indicates that perulactone exhibits robust compactness against both the proteins 3IBF and 1NME over the 100 ns simulation (Ansari et al. 2022a, b).

Solvent accessible surface area (SASA), molecular surface area (MolSA), and polar surface area (PSA) analyses

SASA, MolSA, and PSA discuss the accessible water molecules (equivalent to vander Waal area), molecular surface area and solvent-accessible surface area contributed by the polar (oxygen, nitrogen) atoms of the ligand during the simulation trajectory, respectively. As depicted in Fig. 5 and Table 4, the SASA values (66.244–260.166 Å2, and 208.309–492.363 Å2), MolSA values (444.100–465.672 Å2, and 440.270–462.313 Å2) well as the PSA values (177.744–218.159 Å2, and 180.012–206.505 Å2), appeared for perulactone-3IBF and Perulactone-1NME respectively, throughout the simulation (Umar et al. 2022).

Fig. 5
figure 5

Ligand properties of A perulactone with 3IBF protein ligand–protein complex, and B perulactone with 1NME ligand–protein complex for 100 ns simulation

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MMGBSA analysis

To calculate the free binding energy of the ligand–protein complex, we implemented the MMGBSA approach, which enumerates the free binding energy of the ligand with the targeted receptor. The lowest binding energy interprets the most reliable and stable ligand in the active site of the receptor (Tuccinardi 2021). Now, we estimated the pre- and post-simulation free binding energy of lead compounds against the targeted receptors (Table 6). Consequently, we obtained the values of the lowest Gibbs (ΔG) free energy −62.35 kcal/mol and −66.32 kcal/mol for perulactone-3IBF and perulactone-1NME complexes, respectively. Similarly, the control drugs DICA and FICA revealed Gibbs’s (ΔG) free energy (−45.29, and −39.51 kcal/mol) and (−26.37, and −15.50 kcal/mol). As a result, the perulactone manifested a more stable candidate than the control drugs Dica and Fica against the targeted receptors (Kausar and Nayeem 2018). All of the screened compounds (1–20) fit Lipinski’s rule and other ADMET properties that are required to fulfill the necessary conditions as potent drug leads. We proposed these drugs as effective allosteric caspase-3/-7 inhibitors for controlling the apoptosis process. As a result, our findings could help forward research into berry fruit components as anti-apoptotic medications for treating a variety of diseases. Furthermore, we are the first to report on perulactone and other phenolic compounds that serve as better allosteric inhibitors than FICA and DICA drug molecules.

Table 6 Estimation of MMGBSA energies of the perulactone compound against 3IBF, and 1NME proteins
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Researchers have found that caspase-3 and -7 allosteric inhibition, which offer the majority of cleavage during apoptosis and govern cell proliferation and differentiation during the cell cycle, is crucial in the treatment of a range of diseases (Murakami et al. 2013). Undoubtedly, the mechanism of apoptosis and inflammation can be better understood with the use of caspase inhibitors. However, synthetic FDA-approved caspase inhibitors have failed clinical studies due to considerable adverse effects, lack of efficacy, poor target specificity and/or selectivity, as the majority of them bind to orthosteric sites (Kudelova et al. 2015). To get over these limitations, targeting allosteric regions in the development of therapeutic drugs for apoptosis-related diseases may be a promising option. As discussed in the “Introduction” section, plant-derived compounds, on the other hand, may be a safer and more effective therapeutic agent for dealing with these issues because they are less expensive and have few, if any, adverse effects. Although several studies have indicated the potential function of compounds derived from plants in inhibiting caspase-3 and caspase-7 at orthogonic regions, allosteric site inhibition and the molecular mechanism of those medications are still to be studied (Garner et al. 2019).

Computer-based research is an established strategy for identifying and developing therapeutic agents for a variety of diseases. In the current study, we used virtual screening to find allosteric caspase-3 and caspase-7 inhibitors among 100 compounds derived from berry fruits, including polyphenols, flavonoids, and withanolides. Prior to molecular docking and molecular dynamic simulation investigations, a library of 100 compounds of berry fruits was evaluated using ADMET. In addition to toxicity measures, Lipinski’s rule of five (Ro5) was used to evaluate the drug-like properties. Twenty compounds (1–20) were taken out of this for additional molecular docking and molecular dynamic simulation analyses. Four of these compounds-perulactone (1), myricetin (4), ellagic acid (6), and quercetin (9) were shown to defy Ro5 by a single parameter, as Table 1 illustrates. However, according to Ro5, compounds with no or at least one violation can be successfully implemented as therapeutically relevant medicines. Thus, the current ADMET study revealed that 1–20 compounds had therapeutic characteristics and good oral bioavailability. Following that, to analyse the molecular interactions of compounds (1–20), molecular docking experiments were performed at caspase-3 and caspase-7 allosteric sites to explore binding mechanisms. Our docking investigation revealed that the complexes contained many different kinds of molecular interactions, including H-bonds, hydrophobic contacts, π–π contacts, cation-π contacts, and salt-bridges. As shown in Table 2, compounds 1–20 demonstrated strong binding efficacy (high negative binding energies) within the allosteric pockets of each of the monomers of caspase-3 and caspase-7 receptors as compared to DICA and FICA as reference compounds. The withanolides, namely perulactone and perulactone B, obtained from cape gooseberry fruits exhibited the highest binding energies of −9.1 and −8.1 kcal/mol against caspase-3 (1NME), whereas −12.7 and −9.7 kcal/mol against caspase-7 (3IBF), respectively. The docking results of perulactone were comparable to previous experimental and virtual data, where they were associated with Arg187 residue of caspase-3 and Arg207 residue of caspase-7 via cation-π contact, as in FDA-approved DICA and FICA drugs. Since the chemical structure of perulactone contains four hydroxyl groups, one lactone ring, and one COCH3 functionality, the formation of hydrogen bonds and salt bridges with essential amino acid residues may further facilitate the allosteric binding of perulactone. Our analysis revealed that the hydroxyl moiety of the lactone ring hinged with the Asn208 residue while the COCH3 functional group interacted with the Ser251 and Asp253 residues through hydrogen bonding in the S4 pocket of caspase-3. It resembled a naturally occurring caspase-3 inhibitor ligand. Additionally, the smaller S2 pocket, which has residues of Trp206 and Phe250 that function as active sites in the S4 pocket was produced by the S4 pocket. (Minini et al. 2017). On the other hand, during the molecular interactions of perulactone and caspase-7, we discovered that the molecular interactions of perulactone were similar to the native tetrapeptide inhibitors in the allosteric regions. Because Tyr223 and Arg187 are necessary for cleaving the active site, the perulactone exhibited aliphatic engagement, a hydrophobic interaction that migrated away from the site. (Hardy et al. 2004). The molecular interactions identified in our molecular docking study were compared to compounds found in the literature. In an in vitro investigation, we observed that quinolone-based drugs, such as quinoline-2-one/pyrazole, suppress caspase-3 via interactions of quinoline C = O and pyrazole C = N functionality with the Arg207 and Gly122 residues, whereas N-acetyl cysteine interacted with Arg207, Gly122 and Arg64 residues through hydrogen bonding (Aly et al. 2020). Similarly, in a further investigation, the anti-apoptotic activity of 6-methoxy-4-(4-((2-oxo-1,2-dihydroquinolin-4-yl)oxy)methyl) was uncovered by Essmat M. El-Sheref et al. after they designed and synthesized some 1,2,3-triazole/Bis-2(1H)-quinolinone derivatives such as 1,2,3-triazol-1-yl-quinolin-2(1H)-one against caspase-3 inhibition in the rat testis serum. Using molecular docking analysis, this study demonstrated that the quinoline NH and triazole C = N functionalities of the chemical interacted with the amino acids Thr140, Gly125, and Lys137 in the catalytic site of caspase-3, resulting in higher stability than the reference molecule N-acetylcysteine. When we compared our findings to the literature, we observed that perulactone was better at showing the molecular interaction with Arg187 and Arg207 residues in the allosteric sites of caspase-3 and -7, respectively.

Furthermore, a molecular dynamic (MD) simulation study of perulactone within the binding pockets of 1NME and 3IBF receptors was performed over a 100 ns period. In MD simulation, we evaluated the RMSD, RMSF, SSE, Rg, MolSA, SASA, and PSA parameters to gain insight into the stability of perulactone-1NME and perulactone-3IBF complexes. For the perulactone-3IBF complex, Table 4 and Fig. 5 displayed the RMSD value between 1.270–3.088 Å and 1.011–2.069 Å, while for the perulactone-1NME complex, the values were between 2.426–9.850 Å and 1.129–3.156 Å. According to these results, both complexes were compact within the binding pockets. It has been found recently that RMSD values between 2.0 and 3.0 Å may maintain the complexes in the appropriate orientation, but RMSD values less than 2.0 Å are well connected with favourable docking scores (Ramírez and Caballero 2018). The RMSF is used to observe the fluctuation of ligands within protein pockets. Our investigation found that perulactone-3IBF and perulactone-1NME complexes had RMSF values of 0.334–3.997 Å and 0.408–10.378 Å, respectively. According to the prior study, no fluctuations should be noticed within 3.0 Å. In the current investigation, the perulactone-3IBF complex was stable because it was compact within a range of 3.0 Å (De Vita et al. 2021). Furthermore, the values of additional parameters such as SSE, Rg, MolSA, SASA, and PSA were found to be significant for both perulactone-3IBF and perulactone-1NME complexes, and they were in good agreement with those reported in the prior literature (Ferdausi et al. 2022). Finally, we used the MMGBSA method to redock the perulactone-3IBF and perulactone-1NME complexes to validate our docking results. Using this approach, we found that the perulactone-3IBF and perulactone-1NME complexes have the lowest Gibbs (G) free energy compared to DICA and FICA. We conclude, based on the analysis of the docking scores and stability parameters, that perulactone, the main compound of cape gooseberry fruit, is a more promising candidate than the other compounds (2–20) that were investigated as an allosteric inhibitor of caspase-3 and caspase-7. However, additional research using in vitro and in vivo studies is required to further exploration of perulactone and related compounds to identify allosteric caspase-3 and caspase-7 inhibitors for the treatment of apoptosis-related diseases in the coming years.

Conclusion

To identify possible plant-derived compounds as allosteric inhibitors of caspase-3/-7, a library of 100 compounds from berry fruits was prepared based on the pharmacological activities regarding caspase inhibitions. The compounds were then assessed by computer investigations using ADMET, molecular docking, MD simulation, and MMGBSA calculations. Twenty compounds (1–20) and other FDA-approved compounds that were listed in the literature performed better in docking scores after ADMET screening than the reference drug molecules, DICA and FICA. Perulactone demonstrated significant docking scores of −9.1 and −12.1 kcal/mol against caspase-3 and -7, respectively, in the molecular docking study. In contrast, DICA and FICA demonstrated weak docking scores of −5.0 and −5.1 kcal/mol against caspase 3 and −5.6 and −6.1 kcal/mol against caspase 7, respectively. Furthermore, perulactone produced strong binding complexes and showed notable stability inside the allosteric domains of the 3IBF and 1NME targets with the help of the MD simulation approach. These findings were confirmed by redocking MMGBSA calculations. Briefly, our research suggests that perulactone might be a more potent allosteric inhibitor of the caspase-3/-7 proteins that are involved in the process of apoptosis. Numerous links between perulactone and the reference drug molecules in the caspase-3/-7 allosteric regions, along with other interactions, supported our study. It is suggested that perulactone and other compounds from berry fruits may be recommended for further in-vitro and in-vivo studies.