Colorectal cancer (CRC) is the third most common cancer next to lung and breast cancers with an estimated diagnosis of 2 million individuals and a mortality of approximately 900,000 annually (Bray et al., 2020; Holowatyj et al., 2020). It is thought to be a disease in high-income countries; however, studies have shown the incidence of CRC to increase at a projected rate of 70% by 2030 for low and middle-income countries (Ferlay et al., 2015) with a 5% lifetime average-risk incidence globally (Weitz et al., 2005). These gory statistics have significant implications for the public health systems both in the country and globally hence the need for a more dynamic scientific approach to the CRC burden.

The onset of CRC follows a pattern of abnormal growth of the epithelial cells of the colon and/or rectum leading to a tumor mass that fills the intestinal lumen, metastasizing into nearby organs of the abdominal area, lymph nodes, and other parts of the body (Adeoti et al., 2016). It usually begins as a small, adenomatous mass of cells known as polyps that form on the inside of the colon, which may become malignant or remain benign (Ikwu et al., 2020). As with many cancers, the cause of CRC is not known (Simon et al., 2017), however, risk factors such as age, lifestyle habits (alcohol and tobacco use), high-fat diet, predisposing medical conditions such as type 2 diabetes, and a family history of CRC have been associated with the disease course. Although traditional chemotherapy options have yielded remarkable results in CRC treatment with possibilities of relapses, limited molecular understanding of the oncogenetic initiation and interplay of biochemical mechanisms/factors have impaired the development of novel pharmacologically therapeutic anti-cancer drug agents.

Cyclin-dependent kinase 1 (CDK1) enzyme has been implicated in the oncogenesis of CRC (Sofi et al., 2022a). It is a serine/threonine kinase known to be the catalytic subunit of the M-phase promoting factor (MPF) complex (Kalous et al., 2020) and belongs to a family of cyclic cell regulatory proteins involved in maintaining cell cycle efficiency (Sofi et al., 2022a; Sofi et al., 2022b). Though involved in many cellular events that ensure cell survival, CDK1 specifically acts by regulating the G₂/M and G₁/S phases oscillating in activity between the M transition stages to bring about replication, activating checkpoints, and more recently has been essential to replication fork maintenance (Adhikari et al., 2012; Liao et al., 2017; Matthews et al., 2022). Prior to initiating cell replication, CDK1 is activated by binding to cyclin B₁ to form CDK1-cyclin B complex (Figure 1) (Brown et al., 2015). However, the over expression of CDK1 has been linked to unrestricted cell proliferation. Its over expression has been linked to unrestricted cell proliferation, tumor development, and dysregulation associated with the initiation of many cancers including colorectal cancer (Li et al., 2020; Sofi et al., 2022a; Sofi et al., 2022b). Gene expression has been associated with biomarkers in complex diseases like prostate cancer (Chikwambi et al., 2023), epilepsy (El Abed et al., 2023), malaria/COVID-19 (Nzungize et al., 2022) and SARS-CoV-2 infection (Nyamari et al., 2023). Several studies suggest that overexpression of CDK1, which is the hallmark event in many malignancies is associated with 5 = fluorouracil resistance through altered activation of Wnt/β-catechin signaling, mTOR, and p53 pathways leading to poor prognosis in CRC (Zhu et al., 2019; Zhu et al., 2020a; Zhu et al., 2020b; Sofi et al., 2022a).

Natural products have drawn a lot of attention recently as potential sources of treatments for a variety of illnesses. In recent years, bioactive compounds from plants have been proven to have opportunities in the pharmaceutical industry for therapeutic purposes (Sasidharan et al., 2011). Resveratrol, a polyphenol has been documented for its ability to reduce or inhibit cell proliferation, reduce apoptosis and suppress angiogenesis and metastasis in cancer cells (Greenlee et al., 2022; Dar et al., 2023). Also, flavopiridol, a flavonoid based substance has undergone clinical trials for its anti-cancer benefits and as a potent Cyclin-Dependent Kinase (CDK) inhibitor (Deep et al., 2018). By specifically targeting CDK1, cell cycle arrest is initiated, slowing down the growth of tumors. Compared to synthetic alternatives, natural products have fewer adverse effects.

Despite recent advances in diagnostics and treatments for CRC as well as the failure of conventional cancer treatments including chemotherapy and radiotherapy to sustain lower relapse rates, there remains a gap in treatment and increasing incidence of CRC cases. With the vast plethora of computer-aided drug design and combinatorial chemistry technologies available, a potentially wide array of therapeutic options from small molecule compounds that can target significant aspects of CDK1 activity exists. Our study investigated potential inhibitors of CDK1 in silico and explored their pharmacokinetic properties using a number of computational techniques.

The prevalence of colorectal cancer is fast becoming a public health concern (Holowatyj et al., 2020). Development of new pharmacologically therapeutic anti-cancer drug agents has been hampered by the limited molecular understanding of the oncogenetic initiation and the interaction of biochemical mechanisms/factors, although traditional chemotherapy options have produced impressive results in the treatment of CRC with the possibility of relapses.

Natural products are a valuable source of novel therapeutic leads given that they contain a wide variety of chemical components (Cragg and Newman, 2013; Newman and Cragg, 2016). They have been essential in the development of new drugs, particularly for the treatment of cancerous disorders (Atanasov et al., 2015; Harvey et al., 2015). The compounds identified from this study were found to be in the class of flavonoids. There is growing evidence that flavonoids may be useful in the prevention and treatment of cancer and they are also reported to have a variety of anti-cancer effects, including inducing apoptosis in cancer cells, inhibiting cell proliferation, and may enhance chemotherapy (Abotaleb et al., 2018). Flavonoids have also been reported to play a potential role in colorectal cancer therapies (Amado et al., 2014).

Given the importance of cyclin-dependent kinases (CDK) in cancer, targeting CDKs is a viable strategy for combating the cancer menace (Sofi et al., 2022a). Because of the significant role it plays in one of the phases of cell cycle control, which is a crucial one for the growth of tumor cells, specifically targeting CDK1 became a strategic focus for optimized treatment. The drug discovery pipeline greatly benefits from the use of computational screening techniques (Choudhury et al., 2022). In recent years, computer-aided drug development methods have been widely used to find lead compounds with therapeutic value. These technologies include molecular docking, in silico pharmacokinetic profiling, and molecular dynamics simulations (MDS) (Wan, 2013; Salmaso and Moro, 2018). MDS are anticipated to become more significant as new pharmacological therapies are developed (Durrant and McCammon, 2011). Several studies now use these computational methods to quickly identify potential inhibitors of key proteins in disease progression as treatment options (Choudhary et al., 2020; Sofi et al., 2022a; Rathod et al., 2022; Castrosanto et al., 2023) others have identified experimentally validated leads (Kalani et al., 2013; Yilmaz Goler et al., 2022). Here, we used these computational techniques to screen phyto-compounds and identify possible inhibitors of CDK1.

Molecular docking is a computational method used to predict the preferred binding orientation of a ligand to a receptor. The software algorithm used predicts possible binding orientations and provides scores ranked according to the predicted binding affinity between the receptor-ligand complex (Huang and Zou, 2010; Salmaso and Moro, 2018). To better understand the binding dynamics of the four compounds selected in this study to CDK1, they were subjected to molecular dynamics simulations (MDS). Prior to running simulation studies, we carried out induced fit docking (IFD) (Achilonu et al., 2020). Induced fit docking is a more realistic model of how proteins and ligands interact in nature as it considers the flexibility of the protein and ligand, allowing them to move and rotate during the docking process, resulting in more accurate predictions of the binding of ligands. For traditional rigid docking, the proteins and ligands are treated as rigid bodies, and the docking algorithm attempts to find the best orientation of the ligand in the protein’s binding site. However, in reality, proteins are flexible molecules, which can undergo conformational changes upon ligand binding. Both minor backbone relaxations and substantial side-chain conformational changes in the receptor structure are accounted for by the induced-fit docking (IFD) technique (Sherman et al., 2006; Xu and Lill, 2013).

All systems ran through the complete one thousand nanoseconds duration during MDS, except spiraeoside, which ran for only 700 ns? It could be that due to conformational changes in the protein, spiraeoside left the binding site of the protein during the simulation run. For this reason, the post-simulation analysis could not be completed, consequently, results for spiraeoside were excluded.

It is important to pay attention to the protein’s RMSD value to properly infer structural changes occurring in a protein which could affect ligand binding. C𝛂-RMSD demonstrated a stable structural conformation across the course of the simulation, showing that it was balanced. The low RMSD values of LZ9, robinetin and quercetagetin indicate low fluctuations and suggests that the system maintained stability during simulation and the protein did not undergo significant structural changes as a result of binding of the ligands. The higher RMSD value of 6-hydroxyluteolin system might suggest that the binding of this ligand might have perturbed the structure of the CDK1 protein.

Ligand RMSD provides insight into how stably the bound ligand sits within the protein binding pocket. The Ligand RMSD results show that LZ9, robinetin, and 6-hydroxyluteolin did not move much, therefore forming a stable complex with CDK1, unlike quercetagetin which had a lot of fluctuations. The fluctuations observed with quercetagetin after 400 ns tell us that it is not tightly bound to the protein and has possibly diffused away from the binding pocket, so it forms an unstable protein-ligand complex and is less likely to perform its intended function.

RMSF measures the structural flexibility of a protein and characterizes local perturbations along a protein chain (Cob-Calan et al., 2019). It also provides information on how each amino acid residue is changing relative to its reference position during simulation (Sarkar and Sen, 2022). Here, we analysed the RMSF of the CDK1 protein in the apo and bound states. Peaks represent regions of the protein where the simulation-induced fluctuations were greatest (Tripathi et al., 2022). Illustrative 3D images of the peaks have been presented to clearly elucidate the silent fluctuation dynamics depicted by the represented peaks. The 3D images reveal a comparative conformational variation exhibited by the various system due to the perturbations created by the MD simulation. The 3D images have been color-coded to tally with their respective corresponding RMSF trajectories. The spikes observed from RMSF results may have been caused by increased flexibility within the protein’s loop regions. It may be inferred from the RMSF result that CDK1 has a great deal of flexibility to accommodate the ligand at the binding pocket.

The radius of gyration measures how compact a protein structure is and is equivalent to its principal moment of inertia, describing the common separation of each scattered element from the molecule’s mass center (Lobanov et al., 2008). During simulation, a more rigid structure is represented by lower Rg values (Jiang et al., 2019). Since not much difference was observed between the Apo and bound states, we can say that the binding of the ligands did not interfere with the compact structure of CDK1. In this study, the Rg, RMSD, and RMSF were correlated, and this relationship shed light on how complex compressibility affected the variations in complex RMSD and the residual fluctuations seen in RMSF. No noticeable changes are observed in the bound and unbound states of CDK1, suggesting that the protein structure retained its compact conformation. Our results indicate that the surface area of LZ9 and quercetagetin have higher exposure to water than robinetin and 6-hydroxyluteolin. This result is in tandem with that observed from the ligand-atom interaction diagram.

Hydrogen and hydrophobic bonds play key roles in protein-ligand interactions. Crucial hydrophobic and/or hydrogen bonds, including Ile10, Phe80, Leu83, and Ser84 between CDK1 and the lead compounds that were first seen after molecular docking were maintained during MDS. Phe80 has previously been described as a hydrophobic checkpoint enabling water molecules to gain access to the catalytic portion of the ATP catalytic domain for an additional hydrogen bond (McGrath et al., 2005). Robinetin is seen to form a pi-pi bond with Phe80 during simulation run, which may further account for its strong inhibitory properties. 6-hydroxyluteolin also forms a bond with Thr14 for 88% of the simulation time. Inhibition of Thr14 by small molecule compounds has been proposed as a promising option for the regulation of the G2/M transition of the cell cycle (Schmidt et al., 2017). Inhibition of CDK1 due to the phosphorylation of the kinase on Tyr15 residue by flavonoids (Casagrande and Darbon, 2001) as well as induction of G₂/M phase arrest and apoptosis by the flavonoid tamarixetin on human leukemia cells (Nicolini et al., 2014) have previously been reported.

The hydrophobic and hydrogen bonds formed between the compounds and CDK1 may play a vital role in stabilizing the complexes for the compounds to exert their inhibitory efficacies (Zhang et al., 2011). Ionic bonds observed on only the lead compounds might also play a significant role in their inhibition of CDK1. Interestingly, the lead compounds are all of the flavonoid class; another study by ((Navarro-Retamal and Caballero, 2016)) also gave insight into flavonoids as CDK1 inhibitors. Natural flavonoids such as Luteolin and Daidzein have also been found to inhibit CDK1 (Ravishankar et al., 2013).

Higher free energy values in fact correlate with more preferable binding affinities of a ligand to a protein. Robinetin, which had good binding energy to CDK1, as revealed by the ΔG values, might have been a result of higher electrostatic and van der Waals energy contributions. Interactions between robinetin and Asp86 residue which was observed from molecular docking and induced fit docking results was maintained after the MM/GBSA run. We can say this interaction might be a key factor to stablizing the CDK1-robinetin complex. Energetic analysis reveals that van der Waals interaction and non-polar contributions are favorable in the formation of complexes and amine group of the ligand, which plays a crucial role for binding (Tripathi et al., 2012; He et al., 2023). Potential energy (PE) and RMSD are both vital indicators of protein stability. In previous work done by Yuan et al. (2012) to ascertain if the structures were stabilized, MD simulation was examined using PE and RMSD from the original model structure (Coutsias et al., 2004) The potential energy plot for 6-hydroxyluteolin is a reflection of the trajectory pattern exhibited by the Cα-RMSD plot of 6-hydroxyluteolin system between 230 ns and 420 ns, where a perturbation on the 6-hydroxyluteolin system seems to have created conformational alteration within the system, making it assume a new/different trajectory. The new structural conformational deviation of 6-hydroxyluteolin relative to other systems could presumably have produced the obtained PE.

The physicochemical properties of a compound are important parameters in the pipeline of drug development as they directly affect the absorption, distribution, metabolism, excretion, and toxicity profile (ADMET) of a drug candidate (Manallack et al., 2013). The drug-like and ADMET predictions are used in identifying properties of a ligand suitable for formulation into drugs. Even though all the compounds are adequately hydrophilic and lipophilic, robinetin and 6-hydroxyluteolin showed high intestinal absorption. This implies that the compounds are capable of achieving pharmaceutical and therapeutic bioavailability at the intestinal linings and target cells in the colon. This is further corroborated by their bioavailability scores. A study on natural compounds as inhibitors of CDK1 by Saikat (Saikat, 2021) also reported similar ADME properties.

Lipinski’s Rule of five is used to assess and predict the drug-likeness of compounds based on oral absorption, membrane permeability and bioavailability (Lipinski et al., 1997). Although, parenteral administration may be applicable in most cases of cancer treatment, oral administration is a valuable treatment option for cancer patients as it is more convenient and reduces the frequency of their clinic visits or venipuncture. In recent times, oral anti-cancer drugs such as capecitabine, topotecan and vinorelbin are successfully used in the treatment of a variety of tumours like colon, breast, ovarian or lung cancer (Colomer et al., 2010). With the advent of targeted deliveries, most of the drug molecules approved as oral medications for cancer treatment including hormone therapies such as, dasatinib, sorafenib, imatinib, lapatinib and abiraterone have resulted in good clinical outcomes (Gralow et al., 2008; Rehman and Rosenberg, 2012).

Despite the fact that natural products frequently violate these rules due to their complexity, they still serve as reliable sources for novel drug discovery and development (Doak et al., 2014). Some anti-cancer agents such as vincritine, irinotecan, paclitaxel and etoposide, widely used for decades in cancer treatments originate from natural compounds (Huang et al., 2021).

The ProTox–II server is a web-based tool that predicts the potential toxicity of a given small molecule compound on various organs and systems in the body. The toxicity is predicted using a machine learning model that has been trained on a sizable dataset of toxic and non-toxic molecules. The toxicity prediction and probability score are considered important parameters for predicting a compound’s toxicity (Han et al., 2019). The probability score can be used to evaluate the prediction’s level of confidence. A forecast with a high probability score is more certain to occur, whereas one with a low probability value may not. Additionally, if the organ toxicity and/or toxicity end points of a compound are classified as active, it suggests that the compound may have harmful effects if it is ingested, inhaled, or otherwise exposed to the body. Conversely, “inactive” could mean that the compound has not been predicted to have a toxic effect. Early identification of toxicity in the drug development steps is critical in reducing late-stage attrition rates (Roberts et al., 2014; Segall and Barber, 2014). The predicted toxicity class exhibited by the compounds indicates that they can be administered within the accepted safety doses. Although the test ligands are predicted to be non-hepatotoxic, lead optimization may be required to modify the other toxicity endpoints.

In this study, computational techniques including molecular docking, induced fit docking, molecular dynamics simulation and MM/GBSA were used to study the potential inhibitory activities of natural compounds against CDK1. The findings provided insight into molecular interactions of significant residues involved in inhibitory CDK1 activities through molecular docking and molecular dynamics simulation results. The current investigation of small molecule inhibitors in the activity of the CDK1 explored viable options for the roles of Robinetin and 6-hydroxyluteolin in the pathogenesis of CRC. This research, however, provides a basis for further examination of potential phytochemicals for medical intervention of several cancers. This study aimed to identify potential small molecule inhibitors of CDK1 hence the use of molecular modeling approaches was deployed to highlight compounds of strong binding energies, good spatial amino acid residue arrangement, and better pharmacokinetic properties among others. The MD simulations showed that the hit compounds stably interacted with the CDK1 enzyme and maintained firm positions within the binding pocket of the enzyme over the simulation timeframe. The findings of this study should undergo experimental validation to confirm the interaction between the top ligands identified in our research and the target protein. Additionally, the ADME/Tox properties that were predicted using computational models need to be verified through experimental testing.