Investigation on the mechanisms by which the herbal remedies induce anti-prostate cancer activity: uncovering the most practical natural compound

Abstract Prostate cancer (PCa) is one of the most reported cancers among men worldwide. Targeting the essential proteins associated with PCa could be a promising method for cancer treatment. Traditional and herbal remedies (HRs) are the most practical approaches for PCa treatment. Here, the proteins and enzymes associated with PCa were determined based on the information obtained from the DisGeNET database. The proteins with a gene-disease association (GDA) score greater than 0.7 and the genes that have a disease specificity index (DSI) = 1 were selected as the target proteins. 28 HRs with anti-PCa activity as a traditional treatment for PCa were chosen as potential bioactive compounds. More than 500 compound-protein complexes were screened to find the top-ranked bioactives. The results were further evaluated using the molecular dynamics (MD) simulation and binding free energy calculations. The outcomes revealed that procyanidin B2 3,3′‐di‐O‐gallate (B2G2), the most active ingredient of grape seed extract (GSE), can act as an agonist for PTEN. PTEN has a key role in suppressing PCa cells by applying phosphatase activity and inhibiting cell proliferation. B2G2 exhibited a considerable binding affinity to PTEN (11.643 kcal/mol). The MD results indicated that B2G2 could stabilize the key residues of the phosphatase domain of PTEN and increase its activity. Based on the obtained results, the active ingredient of GSE, B2G2, could play an agonist role and effectively increase the phosphatase activity of PTEN. The grape seed extract is a useful nutrition that can be used in men’s diets to inhibit PCa in their bodies. Communicated by Ramaswamy H. Sarma


Introduction
Cancer, a combination of disorders denoted by irregular cell growth, is still one of the top reasons for death worldwide.Considerable efforts have been accomplished to combat this disease in recent years.The development of cytostatic drugs possessing the ability to tackle tumor targets with increased selectivity is an attractive approach in the last decades (Spiegler et al., 2021).Prostate cancer (PCa) is still the most common cancer in men worldwide, with prolonged side effects after treatment (Delpachitra et al., 2020).Despite the novel approaches for diagnostic and treatment of PCa, this cancer is accountable for nearly 20% of cancer-related deaths in the male Western people (Nevedomskaya et al., 2018).Depending on the PCa's stage, various strategies such as active surveillance, local radiotherapy, or prostatectomy could be performed (Keyes et al., 2013).Docetaxel chemotherapy is one of the most utilized chemotherapies for patients with PCa (Rosenthal et al., 2019).The combination of other chemotherapy or agents with docetaxel failed to achieve benefits in most cases (Nader et al., 2018).Various chemotherapies cause adverse effects such as nausea, diarrhea, chills, fever, and headache (Komura et al., 2018;Nader et al., 2018).For instance, abiraterone acetate causes fatigue in the patients (de Bono et al., 2011).Thus, there is a need to find adequate therapy for PCa with lower probable side effects.
Natural products can provide the beneficial bioactive compounds with anticancer effects, which could be used for cancer treatment in various cancer types (Adnan, 2021;Kanwal et al., 2020;Nawaz et al., 2020;W. Wei et al., 2019).Plant extracts are beneficial materials with some approved characteristics such as antibacterial and antioxidant activity, anti-pulmonary fibrosis, and anti-inflammatory effects (Mehrabani, Goudarzi, et al., 2020;Mehrabani, Raeiszadeh, et al., 2020;Mehrzadi et al., 2019Mehrzadi et al., , 2021;;Zafar, 2021).These compounds could be considered a trustworthy treatment for various cancers (Sameri et al., 2021;Sargazi et al., 2021).According to various reports, some plant extracts have potential anticancer activities with approved activities against cancer cells (Ebrahimi et al., 2021;Hodaei et al., 2021;Mansouri et al., 2020).For centuries, herbal remedies (HRs) have been used in Asian countries to treat and prevent various diseases (M.-M.Wei et al., 2021).The use of HRs in combination or as an alternative to synthetic drugs has increased in western countries (Xue et al., 2013).Some essential effects of HRs could be synergistic, additive, and antagonistic (C.Wang et al., 2018).They can affect multiple targets and induce multiple pathways since they usually contain multiple components (C.Y. Wang et al., 2014).Therefore, discovering new bioactive compounds by investigating various plant extracts is becoming of interest for drug development.
The traditional methods for isolating and purification of bioactive compounds are time-consuming processes.In these methods, the components have to be isolated one by one, and their pharmacological activities have to be evaluated in vitro and in vivo.These approaches usually suffer from neglecting the multiple targets and multiple channels of the components available in the HRs (M.-M.Wei et al., 2021).Lately, network pharmacology-based study has been widely employed in the area of biotechnology and computer-aided drug discovery (Yang et al., 2019).Computational approaches can also help biologists to obtain biological data as supplementary information to experimental analysis (Poustforoosh, Farmarz, Nematollahi, Hashemipour, & Pardakhty, 2022;Poustforoosh, Hashemipour, et al., 2022).The combination of computational methods and bioinformatics tools can provide a fascinating opportunity to evaluate the biological activities and targets of the bioactive compounds in HRs (Poustforoosh, Faramarz, Negahdaripour, et al., 2022).The molecular docking study is one of the practical in silico approaches that can provide essential information about the binding affinity of the ligands to the biomolecules and determine the interactions at an atomic level (Jafari-Arvari et al., 2021).Molecular dynamics (MD) simulation is another computational method that can evaluate the interactions between the ligand and biomolecule in a dynamic condition (Hadizadeh et al., 2022).
There are several studies that evaluated the activities of various HRs against PCa (Asadi-Samani et al., 2018;Fort et al., 2018;Livingstone et al., 2019;Mottaghipisheh et al., 2022).For decades, some traditional herbal remedies have been used for PCa treatment.These remedies are not adequately evaluated, and their mechanisms and potential targets have not been determined so far.Here, we have tried to conduct a comprehensive study using computational methods and bioinformatics tools to evaluate traditional HRs against PCa and find a potential component with desirable characteristics for being used against PCa.

Preparation of bioactive compounds
The active ingredient of several traditional HRs that have been used for PCa treatment in traditional medicine was selected as PCa inhibitors.The chemical activity of 28 bioactives against the selected proteins was evaluated.The structure of the ligands in the SDF format was retrieved from the PubChem database, and the preparation of the compound was conducted using the LigPrep module of Schr€ odinger (Schr€ odinger Release 2020-4: LigPrep, Schr€ odinger, LLC, New York, NY 2020, n.d.).The possible protonation states were produced by conducting the OPLS3e force field, and the Epik module of LigPrep at pH 7.0 ± 0.4 was used for the ligand preparation.The name and structure of the selected compounds are presented in Table 1.

Prostate cancer-associated genes determination
The associated genes in PCa were determined using the DisGeNET database (https://www.disgenet.org).The Malignant neoplasm of prostate (C0376358) was considered as the PCa, and the associated genes were assessed.The genes were categorized into two classifications.The genes with the gene-disease Association (GDA) score greater than 0.7, and the genes that have disease specificity index (DSI) ¼ 1.The obtained results will be more reliable by applying this classification.The selected genes are presented in Table 1.One of the compounds is ellagic acid, which has some famous metabolites in the body produced by the gut.These metabolites are urolithins (urolithin A, isourolithin A, urolithin B, urolithin A glucuronide, isourolithin A glucuronide, and urolithin B glucuronide) that are presented in the table.

Protein preparation
The 3D structures of the chosen proteins were taken from the EBI AlphaFold database (https://alphafold.ebi.ac.uk) (Jumper et al., 2021;Varadi et al., 2022).Eight proteins with a desirable GDA score and twelve proteins with DSI ¼ 1 were derived from the DisGeNET database.The protein preparation module of the Schr€ odinger suite was employed for the preparation of the proteins, and the system was minimized using the OPLS3e force field (Schr€ odinger Release 2020-4: Protein Preparation Wizard; Epik, Schr€ odinger, LLC, New York, NY 2016; Impact, Schr€ odinger, LLC, New York, NY 2016; Prime, Schr€ odinger, LLC, New York, NY 2020, n.d.).

Determination of the active site and receptor grid generation
After protein structure preparation, their active sites were determined by operating the SiteMap module of Schr€ odinger (Poustforoosh et al., 2021).This module presents the active binding sites in a large-scale validation with the best results for the areas that bind the ligands.After the determination of the active site, a receptor grid was generated around the active site.The size of the box was 20�20�20 (Å 3 ).The van der Waals scaling factor was set to 1 (Å).The partial charge cut-off was kept at 0.25, and the docked ligand length was set as default at 20 (Å).

Virtual screening and molecular docking
The Glide of the Schr€ odinger was used to perform the highthroughput virtual screening (HTVS) and molecular docking of the selected bioactives and essential proteins associated with PCa (Poustforoosh, Faramarz, Nematollahi, Hashemipour, T€ uz€ un, et al., 2022).The prepared file of LigPreps was used for each one of the receptor grids, and the special compounds were specified by developing special properties for each input compound (Poustforoosh, Faramarz, Nematollahi, Hashemipour, Negahdaripour, et al., 2022).The Epik state penalties were utilized for this purpose.The HTVS, standard precision (SP), and extra precision (XP), as the default procedure of the virtual screening workflow, were accomplished to introduce the final three best compounds.The values employed for the scaling factor and partial charge cutoff were set at 0.80 and 0.15, respectively.In addition, the docking study of darolutamide, an approved drug for the treatment of PCa, was accomplished to be compared with the most active compound.

Molecular dynamics (MD) simulation
The interactions between the potential bioactives and their targets were further assessed dynamically.MD simulation is a helpful technique that can estimate the binding features reliably.Desmond of Schr€ odinger (Desmond Molecular Dynamics System, D. E. Shaw Research, New York, NY, 2020.Maestro-Desmond Interoperability Tools, Schr€ odinger, New York, NY, 2020, n.d.) was used to conduct the MD simulation.The complex of the bioactive compound with the highest binding affinity to the related proteins was evaluated by performing the MD simulation.The complex system obtained from the docking calculations was used for the MD simulation.The MD simulation was performed in an orthorhombic box, and the solvent model of transferable intermolecular potential with 3 points (TIP3P) was chosen for the simulation (Poustforoosh, Faramarz, Nematollahi, Hashemipour, T€ uz€ un, et al., 2022).The proper number of Naþ/Cl À ions with a salt concentration of 0.15 M was used to neutralize the system operating the system setup of Schr€ odinger (Sirin et al., 2014).The simulation was then accomplished for the prepared system (100 ns) with the default relaxation protocol of software and the constant number of atoms, pressure, and temperature (NPT) ensemble (Poustforoosh et al., 2023).The Nose-Hoover protocol was used to set the temperature to 310.15 K (37 � C), and the pressure was adjusted to 1 atm employing isotropic scaling (Panwar & Singh, 2021).

Calculation of binding free energy
The free binding energies were estimated by performing the MM/GBSA protocol (Poustforoosh et al., 2022).The prime module of Schr€ odinger was performed for the calculations, and default parameters were used.The solvation model of VSGB was selected for the calculating of binding free energy, and the OPLS-2005 force field was used for the calculations.
The formula used for the determination of binding free energy between the ligand and protein is as follows: where DG bind indicates the binding free energy, G complex is the binding free energy of the complex.The G protein and G ligand present the binding free energy of the protein and ligand, respectively.

ADME/T analysis
The analysis of absorption, distribution, metabolism, and excretion-toxicity (ADME/T) was accomplished to evaluate the drugability of the top-ranked bioactive compound.The ADME/T analysis was performed by using QikProp of Schr€ odinger (Poustforoosh, Hashemipour, T€ uz€ un et al., 2022).
Based on these results, the potential of the designed compound would be assessed for further in vitro and in vivo studies (Gezegen et al., 2021;Taslimi et al., 2021).

Determination of effective bioactives
The essential proteins associated with the malignant neoplasm of prostate (C0376358) with DSI ¼ 1 and GDA greater than 0.7 were determined.There are 20 targets with the mentioned characteristics that are associated with PCa.These proteins and the related information are presented in Table 2.The three top-ranked compounds for each protein are reported in this table.As could be seen in this table, B2G2 is the compound that has emerged as the top-ranked bioactive in many cases.This compound has shown the highest binding affinity to eight essential PCa-associated proteins.These proteins are Brca2, CFAP161, CHEK2, ENPP5, MSMB, PCDHGA2, PTEN, and SP5.The docking scores of B2G2 against these proteins are -8.011, -6.961, -7.478, -9.003, -8.752, -5.860, -11.372, and -11.643 kcal/mol, respectively.
Gallic acid is another bioactive agent that was emerged seven times among the top-ranked compounds.The highest binding affinity of this compound was for RFK with -5.975 kcal/mol.The binding free energy calculations show the stability of the ligand-protein complexes.One of the lowest binding energies belonged to the B2G2-PTEN complex.This considerable binding affinity of B2G2 to PTEN and the remarkable stability of this complex indicated that this compound could interact with PTEN effectively.The docking pose of this compound among the residues of PTEN is presented in Figure 1.The interactions constructed between the compound and protein are displayed in Figure 2. As could be seen, there are four hydrogen bonds between B2G2 and PTEN.These hydrogen bonds are created between some of the hydroxyl groups of the compound and the residues Lys163, Thr167, Glu299, and Asp324.There are also two Pication interactions between two benzene rings of B2G2 and Arg172.A Pi-Pi stacking interaction is also constructed between the compound and Tyr176.The catalytic site of PTEN is constructed of three catalytic loops (J.O. Lee et al., 1999).One of these three loops is the TI-loop, which includes residues 160-171 (Rodr� ıguez-Escudero et al., 2011).B2G2 constructed two hydrogen bonds with residues Gly165 and Thr167 and three hydrophobic contacts with residues Asp153, Lys163, and Lys164.As these residues belong to the catalytic site of PTEN, these hydrogen bonds and hydrophobic contacts can affect the activity of PTEN considerably.The calculations of binding free energies were conducted for the ligand-biomolecule complex in the docking pose of the bioactive compounds among the related targets.The outcomes of MM/GBSA total binding energies are presented in Table 2.As it is obvious, the binding free energy values were  negative for all selected ligand-protein complexes.The negative values indicated that the targets favorably interacted with selected bioactive compounds.
The docking calculations of darolutamide revealed the binding affinity of this approved drug is less than B2G2 with a docking score of -6.369 kcal/mol.The interaction constructed between this drug and PTEN is presented in Figure S1.Like B2G2, this compound has not affected the phosphatase residues of the protein, but the binding affinity of B2G2 is greater than darolutamide.

MD simulation
The ligand-protein complex of B2G2-PTEN was further evaluated using the MD simulation for 100 ns.The RMSD of the protein in this simulation is presented in Figure 3.As could be seen, the fluctuation of protein RMSD for B2G2-PTEN converged at about 5.6 Å.This reduction in the fluctuation indicates the stability of the system after 100 ns.The ligand-protein interactions between B2G2 and PTEN after the simulation time are presented in Figure 4.For a better comparison, the MD simulation of sole PTEN was carried out.The protein RMSD of this simulation is presented in Figure 5, which indicates the structure was stabilized after 100 ns.Figures 6 and 7 show the protein RMSF of PTEN with and without the ligand.The results indicated that the residues of PTEN are more stable when interacting with B2G2 compared to the sole protein.The values of RMSF for the essential residues of the phosphatase domain of PTEN (Das et al., 2003) are presented in Table 3.

Binding free energy
The MM/GBSA method was utilized to calculate binding free energy.These calculations were conducted for the ligandprotein complexes.The detailed outcomes of MM/GBSA binding free energies for B2G2-PTEN are presented in Table 4. DG bind H-bond shows the binding free energy of hydrogen bond, and DG bind Lipo and DG bind vdW show the binding free energies of lipophilic energy and van der Waals energy, respectively.DG bind covalent indicates the covalent binding energy.DG bind Coulomb and DG bind solv.GB shows the binding free energies of coulomb energy and generalized Born electrostatic solvation energy, respectively.The lowest energies for B2G2-PTEN belong to van der Waals energy and coulomb energy with -56.95 and -38.85 (kcal/mol), respectively.This investigation on the contribution of each energy revealed that and Van der Waals interactions played essential roles in the mentioned complexes.

ADME/T analysis
Theoretical ADME/T features of B2G2 with acceptable binding characteristics were predicted by conducting the ADME/T analysis.One of the main reasons for the failures of drug candidates in the initial trials is largely related to the ADME/T properties of the drug candidates.ADME/T describes the pharmacokinetic problems specifying whether a drug compound will reach the target protein in the body, and how prolonged it will remain in the bloodstream (Dong et al., 2018).This analysis can save a considerable amount of time and money (Y.Wang et al., 2015).Moreover, the existing empirical techniques for ADMET investigation are still expensive and time-consuming and they need much amount of animal testing which is usually inadequate when handling hundreds of compounds in the early phase of drug development.To reduce failures, computational approaches are pursued by medicinal chemists to forecast the fate of pharmaceuticals in an organism, and to identify the risk of toxicity (Rosales-Hern� andez & Correa-Basurto, 2015;Wishart, 2007).Various parameters were gained that are displayed in Table 5.As the molecules must have a certain molecular weight, the first parameter in the table is the molecular weight.Another parameter is the total solvent accessible surface area (SASA) in square angstroms using a probe with a 1.4 Å radius.Another parameter is QP polarizability, which is the predicted polarizability.The unit for this parameter is cubic angstroms.Another critical parameter is QPlog HERG, which is the numerical amount of the estimated IC50 for blockage of HERG K þ channels.The next parameter is QPPCaco.This parameter is the predicted Caco-2 cell permeability in nm/sec for passive transport.Another critical parameter is QPlog BB, which indicates the predicted brain/blood partition coefficient of a drug when orally administered.Another parameter is human oral absorption.It shows the predicted qualitative human oral absorption.It could be 1, 2, or 3 for low, medium, or high, respectively.Two other critical parameters are the rule of five and the rule of three.The rule of five is Lipinski's fifth rule of Pfizer The changes in the secondary structure of the protein were also monitored throughout the simulation.The secondary structure of PTEN when interacting with B2G2 is presented in Figure 8.The changes in the secondary structure of this protein without the ligand throughout the simulation are shown in Figure 9.  ( Lipinski, 2004).The rules are: mol_MW < 500, QPlogPo/w < 5, donor HB � 5, accptHB � 10.The rule of three is the three rules of Jorgensen (Jorgensen & Duffy, 2002).These three rules are: QPlogS > -5.7, QP PCaco > 22 nm/s, # Primary Metabolites < 7.These two parameters must be checked for a compound to be a theoretical drug.
As could be seen in Table 5, some of the parameters are not in the standard ranges, which means B2G2 has to be loaded into a drug carrier.The targeted delivery of the compound to the target site is an essential issue.This problem could be smoothly addressed by using targeted vesicular systems such as virosomes and bioconjugated nanocarriers (Asadikaram et al., 2021;Poustforoosh, Nematollahi, et al., 2022).

Discussion
PCA is one of the most reported cancers in men all around the world, which indicates the significance of studies to discover drugs for this disease (Kappen et al., 2021).There are a number of traditional remedies with anti-PCa activity, which have been used for decades in Iran and the Asian countries (Asadi-Samani et al., 2018;Liu et al., 2000).Therefore, we decided to find potential natural derivative compounds with considerable anti-PCa activity.
Although there are many reports about the anti-PCa activity of natural compounds, there is not a comprehensive study on these compounds using computational and bioinformatics approaches.Investigation of the proteins and enzymes associated with PCa revealed that there are eight targets with GDA greater than 0.7 and 12 targets with DSI ¼ 1.We retrieved 28 HRs that have been used for PCa in traditional remedies to find the appropriate bioactive compound using the virtual screening.Amongst the natural bioactive compounds, B2G2 showed the highest binding affinity to eight essential PCa-associated proteins.These proteins are Brca2, CFAP161, CHEK2, ENPP5, MSMB, PCDHGA2, PTEN, and SP5.By targeting these crucial PCa associated proteins, B2G2 could be considered as a promising natural compound against PCa.
B2G2 or procyanidin B2 3,3 0 -di-O-gallate is one of the bioactive ingredients of the grape seed extract (GSE), which has been reported to cause growth inhibition and induced apoptotic death of human PCa cells (Agarwal et al., 2007;Kumar et al., 2018;Tyagi et al., 2014).However, a detailed understanding of the way this compound can affect and inhibit PCa is not clear (Tyagi et al., 2019).Here, we tried to understand how this bioactive compound could affect PCa.
The binding affinity of B2G2 to the selected proteins was investigated using molecular docking analysis.An essential parameter obtained from the docking study is the docking score, which shows the binding affinity of the compound to the protein.Based on the docking scores, the greatest binding affinity of B2G2 belongs to PTEN with -11.643 kcal/mol.This target is closely followed by SP5, with a docking score of -11.372 kcal/mol.Therefore, PTEN (phosphatase and tensin homolog) and SP5 (Sp5 transcription factor) are the critical targets amongst the selected proteins.
PTEN is reported to be one of the key tumor suppressors in PCa (Bowen et al., 2019).The loss of PTEN is a frequently reported issue in patients with PCa (Lei et al., 2006).Therefore, regulation of this protein could be an effective way to treat PCa or other cancers (Georgescu, 2010).In a study performed by Hashim et al., the status of PTEN was assessed by immunohistochemistry. Their results showed that PTEN is positively associated with PCa family history, and a large number of the studied patient had a history of PTEN loss and dysregulated expression of this protein in their family (Hashim et al., 2020).The proapoptotic role of PTEN relies on the phosphatase activity of this protein toward PIP3 (phosphatidylinositol-3-phosphate) and inhibition of the PI3K/Akt pathway (Leslie & Downes, 2004).PI3K induces the phosphorylation of PIP2 and changes it to PIP3, and Akt binds to PIP3, which leads to cell survival and apoptosis inhibition (Molinari & Frattini, 2013).PTEN dephosphorylates PIP3 to PIP2 and suppresses this pathway.PTEN agonists can stimulate this activity against PCa.Muthumanickam et al. investigated the ability of various natural and chemical compounds as PTEN agonists using in silico approaches.They screened the compounds based on their binding affinities to PTEN.Their results indicated that naringin, a natural bioactive compound, is a potent PTEN agonist that binds to PTEN with a docking score of -8.083 kcal/mol (Muthumanickam et al., 2022).GSE has been reported to significantly increase PTEN negative regulation on the PI3K pathway (Antonacci, 2014;Engelbrecht et al., 2007).Our results showed that B2G2, as the most active constituent of the GSE (Tyagi et al., 2014), can strongly bind to PTEN and regulate its activity.Therefore, by applying the agonist activity to this protein, B2G2 can affect the growth of PCa cells and inhibit their proliferation.Due to the considerable ing affinity of B2G2 to PTEN with a lower docking score (-11.673kcal/mol) compared to naringin, this compound can inhibit tumor growth and invasion by targeting this receptor.The results of RMSF showed that B2G2 can increase the stability of the essential residues of the PTEN phosphatase domain (Table 3).These residues are R11, K13, R14, R15, and R161 (Das et al., 2003).Stabilizing these residues can enhance the phosphatase activity of PTEN and inhibit the cell survivability of PCa cells.The stability of the secondary structure of the protein throughout the simulation indicated the results are validated and trustworthy.As mentioned above, SP5 is another target of B2G2 with a considerable binding affinity.Morgenbesser et al. reported that SP5 is one of the upregulated transcription factors in PCa (Morgenbesser et al., 2007).SP5 is a transcription factor that binds to the GC box in promoters of many genes and regulates their expression (Y.Chen et al., 2006).Thus, SP5 is an appropriate target in cancer cells (Takahashi et al., 2005).Some transcription factors like Nkx3.1 can bind to SP family members such as SP5 and negatively regulate their transcription activity in prostate-derived cells (Simmons & Horowitz, 2006).Due to the considerable binding affinity of B2G2 to SP5, this natural bioactive compound can act like Nkx3.1 and influence its activity.B2G2, which has a remarkable binding affinity to SP5, can suppress PCa and increase chemotherapy efficiency by targeting SP5.
Considering the obtained outcomes from the bioinformatics databases and computational investigations of the potential targets, B2G2, an essential component of GSE, can inhibit PCa development by targeting some crucial proteins and enzymes.One of the most essential proteins is PTEN, which has a crucial role in suppressing cell proliferation in PCa.

Conclusions
PCa is the most reported carcinoma in men globally, which denotes the need for finding practical therapies for this cancer.One of the most applicable strategies is to assess the naturally derived compounds and HRs with approved anti-PCa activities.B2G2, an essential component of GSE, is a natural compound with outstanding anticancer activities that have been approved to have anti-cancer activity against various cancer cells so far.Our findings from bioinformatics databases and in silico assessment revealed that B2G2 is a potential treatment for PCa by targeting essential proteins and enzymes associated with PCa.PTEN is one of the most essential proteins associated with PCa.B2G2 showed a considerable binding affinity to this protein with a negative binding free energy.This compound could stabilize the essential residues of PTEN and increase the phosphatase activity of this protein.The agonist role of B2G2 on PTEN could affect and control PCa proliferation efficiently.

Figure 1 .
Figure 1.The docking pose of B2G2 among the PTEN residues.G165 and T167 are the residues of the TI-loop with hydrogen bonds, and residues D153, K163, and K164 are the amino acids of this loop with hydrophobic contacts.

Figure 2 .
Figure 2. The interactions constructed between B2G2 and PTEN, obtained from molecular docking calculations.

Figure 3 .
Figure 3.The protein RMSD of PTEN when interacting with B2G2.The fluctuations converged at about 5.6 Å after 100 ns.

Figure 4 .
Figure 4.The residues involved in the protein-ligand interactions of B2G2-PTEN after 100 ns simulation.

Figure 5 .
Figure 5.The protein RMSD of sole PTEN.The fluctuations converged at about 6.4 Å after 100 ns.

Figure 6 .
Figure 6.The protein RMSF of PTEN when interacting with the ligand.

Figure 7 .
Figure 7.The protein RMSF of PTEN without the ligand.

Figure 8 .
Figure 8.The changes of the secondary structure of PTEN throughout the simulation in the presence of B2G2.

Figure 9 .
Figure 9.The changes of the secondary structure of PTEN throughout the simulation without the ligand.

Table 1 .
The name and sources of the bioactive compounds with correspondent reported activity against PCa.

Table 2 .
The essential proteins associated with PCa (C0376358) and top three inhibitors with the highest biding affinity to these proteins.

Table 3 .
The RMSF values of essential residues of PTEN phosphatase domain.

Table 4 .
The calculated binding free energy of B2G2 and PTEN.

Table 5 .
The ADME/T properties of the most active compound (B2G2).