In silico comparison between the mutated and wild-type androgen receptors and their influence on the selection of optimum androgenic receptor blockers for the treatment of prostate cancer

Background: Prostate cancer is a disease that occurs in men aged more than 50 years. In Iraq, 8.89 men per 100,000 population suffer from prostate cancer, with the incidence being 14,016 cases and mortality being 6,367 cases. Despite advances in treatment against prostate cancer, it can become resistant to drugs. Therefore, the aim of current study was to search and identify binding sites for the repositioning of drugs by computational methods (docking). Methods: Based on the protein structure of the wild androgen receptor, the analysis parameters (22x22x22 on the X, Y, and Z axes) were established. Results: The interactions of the natural ligands with androgen receptor were 10.0 (testosterone) and 10.8 (dihydrotestosterone) while mutated androgen receptor (T877A) had a low affinity with testosterone and dihydrotestosterone (-5.3 and -6.7, respectively). In the interactions of both receptors with the reported inhibitors (antagonists), a decrease with Bicalutamide (-8.3 and -4.3, respectively) and an increase in affinity with Flutamide and Nilutamide (-7.7 and 8.6, wild AR; -8.7 and -9.3 AR T877A) were observed. As for Enzalutamide and Apalutamide (second-generation antagonists), the change was minimal between wild androgen receptor and T877A (-7.6 and -7.7; -7.3 and -7.3, respectively). The change in the affinity of the ligands with androgen receptor and androgen receptor T877A shows how a mutation alters the bonds between these molecules. Conclusion: The identification of key sites and potent inhibitors against abnormal androgen receptor functions will enrich prostate cancer treatments.


Introduction
Prostate cancer (PCa) is a malignant growth that occurs in men over the age of 50 years and consists of an increase in prostate size due to an increase in the number of cells.In Iraq, this disease has low incidence and mortality according to previous studies, as 7.6% of all types of cancers are prostate cancer. 1,2In addition, the most likely age for development is between 50 and 74 years.Furthermore, the progression of PCa is related to excess androgen stimulation; however, current treatments include surgery and/or hormones that completely block androgenic receptors. 3,4en the disease reaches a stage of resistance to treatments, it is called Castration-Resistant Prostate Cancer (CRPC). 5lthough new treatment strategies have been developed for CRPC, they are very few and quite inefficient.Many types of CRPC rely on decreasing the activity of the androgen receptor (AR), the signaling pathway for survival.Due to this, the androgen receptor is key to the design of new therapeutic agents. 5To date, more than 600 different mutations have been found in the androgen receptors where the repercussions of these mutations on their (receptors) structure, signaling, and resistance to PCa treatments are analyzed.For this reason, the development of strategies for the identification of effective drugs acting on androgen receptors is of great importance in obtaining new therapeutic agents against PCa. 6This methodology is known as Intensive Structure-Based Virtual Screening (SBVS). 5,67][8][9] In addition, the methodology of drug repositioning, which accelerates the process of discovering new uses of existing therapeutic agents, is both cost-and time-effective.Therefore, the use of computational technologies based on protein structure (SBVS) for the design or repositioning of drugs (new uses of existing drugs) is an alternative method that will favor the investigation of new therapeutic agents against CRPC. 10 Castration-Resistant prostate cancer treatment Despite the cancer being castration-resistant, it may still depend on androgens for growth.Therefore, medications like abiraterone acetate (Zytiga) and enzalutamide (Xtandi) can be effective.These drugs work by either reducing androgen production or preventing androgens from activating their receptors. 11However, enzalutamide failed in some cases and led to resistance. 11There are several research studies attempting to understand the optimal treatment for CRPC and the reasons for this resistance.One such study registered as a clinical trial (NCT02346578) concluded that in patients unresponsive to bicalutamide-combined androgen blockade treatment, enzalutamide demonstrated superior clinical outcomes compared to flutamide.Hence, enzalutamide is recommended over flutamide for these patients.
However, there are no sufficient studies about the reason for this resistance and the binding of this medication to the receptor.
Therefore, the aim of the current study was to find and identify binding sites for both wild-type and mutated androgenic receptors and the best-proposed drug that blocks mutated ones by computational methods (docking); this can give us support or a good explanation of the resistance.

Methods
The in-silico experiments were carried out at the Center for Research in Iraqi Medical and Pharmaceutical Research Center (IMRC).Subsequently, background analysis will be carried out with services provided by protein Data bank-EMBL-EBI (The European Bioinformatics Institute).[14][15][16][17][18] REVISED Amendments from Version 3 1-The abstract was improved.2-We have summarised some of the clinical research on castration resistant prostate cancer.3-We added the benefit of our research which is the aim of the current study was to find and identify binding sites for both wild-type and mutated androgenic receptors and the best-proposed drug that blocks mutated ones by computational methods (docking); this can give us support or provide a good explanation of the resistance.
Collection of 3D structures of the wild and mutated androgen receptor (T877A) This first stage consisted of obtaining 3D structures of the wild androgen receptor (AR) and a mutated one (T877A) which is the mutant associated with drug resistance.The 3D molecules were obtained through the database of the protein data bank with access codes 2AM9 (wild) and 2AX6 (mutation).

Collection of the 3D structures of natural ligands and androgen receptor inhibitors
The structures of the natural ligands of the receptor (Testosterone and Dihydrotestosterone) and its inhibitors (Bicalutamide, Nilutamide, Flutamide, Enzalutamide, and Apalutamide) were obtained from the free database ZINC (http://zinc15.docking.org).These ligands were selected based on the affinity reported in the database ChEMBL.

Adequacy of the wild and mutated androgen receptor
The preparation of AR was carried out through the Chimera USFC program, and this preparation consisted of the addition of hydrogen atoms, removal of water molecules from the protein surface, elimination of ligands present, and the determination of charges that integrate each atom of the receiver.In this case, the selected charges were the AM-BCC [AM1 bond charge corrections BCCs].Subsequently, it was identified and selected based on the basic characteristics of the active androgen receptor site according to PDB [protein data Bank] data.
Adequacy of the natural ligands and androgen receptor inhibitors Ligands, both natural and those reported as inhibitors of AR activity, were subjected to adaptations with the Chimera USFC program for molecular interaction assays with the in-silico androgen receptor, adding hydrogen atoms and assigning Gastieger charges to mimic the changes that occur within a cell according to their nature. 14says of wild AR interactions with natural ligands and AR inhibitors to establish interaction parameters The affinity values (Kcal/mol) were calculated using the AutoDock program, the interactions between wild AR and its natural ligands were analyzed, and the contact between the molecules when the distance was less than or equal to 5Å was considered.Based on the interaction of natural ligands (Testosterone and Dihydrotestosterone), the optimal parameters for evaluating receptor interactions were determined.For validation of these parameters, the interactions of the wild androgen receptor with the five inhibitors were reported against the receptor (Bicalutamide, Nilutamide, Flutamide, Enzalutamide, and Apalutamide). 15The same distance (5Å) is considered for interaction between ligands with AR.In addition, within the validation of the joining site, the size assessment of the coupling site was carried out for the structures of the ligands, which was defined by establishing a cube with the dimensions of 22Â22Â22Å, 15Â15Â15Å, and 10Â10Â10Å.This was to experimentally determine the exact critical parameters for interactions of the receptor with the ligands. 16says of interactions of mutated AR (T877A) with natural ligands and AR inhibitors The interaction analyses between the mutated androgen receptor (T877A) were performed based on the calculations mentioned above, considering the binding site's size is determined for wild AR with natural ligands and inhibitors (22Â22Â22Å).This is to determine if mutation changes affinity of the ligands and/or inhibitors to the receptor.
Identification of the central residues involved in the interaction of wild and mutated AR (T877A) with the ligands The identification of residues of the AR that interact with the natural ligands and inhibitors, that had the best affinity score in the analyses in AutoDock Vina (Kcal/mol), were visualized using the PyMOL program with which each complex between the receptor and the ligand was observed.

Results
The first result obtained from the analysis was carried out with the help of the optimal parameters of the AR binding site which were determined with the use of AutoDock Vina and Chimera.The parameters are described below (Table 1).
With the server of AutoDock Vina de Chimera and AutoDock Vina (direct program), the calculation of the theoretical value for the affinity of the coupling of the natural ligand or inhibitors with androgen receptors, both wild and mutated.The following Tables 2 and 3 showed the analyses of affinities existed in the interactions between wild AR with the natural ligands.
The results showed that Dihydrotestosterone (DHT) ligand has a higher affinity for the AR than testosterone, which is the precursor of DHT.Pang et al. (2021) reported this affinity and mentioned that DHT has a significant effect on the receptor and is active in the functions in which AR is involved, such as transcription of genes for cell survival and growth. 17he validation of the established parameters of the normal androgen receptor binding site, with the use of receptor inhibitors, reflects that the ligand binding site corresponds to the binding site of the natural ligands (testosterone and DHT); however, the drug Enzalutamide and Apalutamide showed high affinity for another receptor site.Also, Chen et al.
(2019) mentioned that Enzalutamide and Apalutamide are second-generation antiandrogens that inhibit AR's activity during cancer development.In contrast, first-generation drugs included Bicalutamide, Flutamide, and Nilutamide. 18The results obtained were presented in Table 4.
The results obtained with Enzalutamide (0.3) and Apalutamide (0.4) showed a low affinity for the common binding site of the androgen receptor, so it was analyzed that in which area of the receptor do these molecules bind and what is their affinity under a cube size of 40Â40Â40Å (Table 5).

Discussion
The change in Enzalutamide and Apalutamide was due to the interaction of these drugs with another area different from the normal, expected, binding site of AR, giving an increase of 0.3 (Enzalutamide) and 0.4 (Apalutamide) to -7.6 and -7.7, respectively (Figure 1).To visualize the interactions of the complexes, the PyMOL program was used, with which the amino acid residue involved in the interactions between AR with natural ligands were determined, as with inhibitory ligands.For the wild-type AR and the natural ligand, testosterone, complex, it was observed that they are determined by links between the residues threonine 877 with H (2.4Å) and arginine 752 with O (2.3Å) (Figure 1).In the case of the wildtype AR and dihydrotestosterone complex, the affinity is greater than that observed with Testosterone, and the residues involved in the formation of said complex are given by arginine 752 with the terminal nitrogen of DHT (2.4Å), followed by the association between threonine 877 with the opposite oxygen at a distance of 1.9Å, and finally the third interaction occurs between asparagine with the terminal O of DHT, this union is given at a distance of 2.4Å (Figure 2).Moreover, Table 6 showed the interactions between AR and inhibitory ligands, the residues involved are described as the distance between the molecules (Figure 3).The results of the interactions of the receptor (with the T877A mutation) with the ligands analyzed above showed that the affinity of the natural ligands is low compared to that studied in the wild receptor.The affinity of the antiandrogen Bicalutamide, if it has an affinity of -8.3 for the receptor with the T877A mutation, decreased to -4.3.However, the affinity of Flutamide and Nilutamide increased from -7.7 and -8.6 to -8.7 and -9.3, respectively, and second-generation antiandrogens (Enzalutamide and Apalutamide) were stable, as the T877A mutation is not found at the site where these two drugs bind to inhibit the receptor (Tables 7 and 8). 17It was noted that a drug binds to the receptors somewhat well, and this confirms the studies that led to the adoption of a drug for treatment. 18On the other hand, apalutamide and enzalutamide binding affinities did not change for both mutated and wild-type androgenic receptors, which provides an idea to use them even in patient with CRPC and this result encouraged the FDA on (9-2021) approvals of apalutamide for treatment of non-metastatic castrationresistant prostate cancer.The interacting residues in each of the mutated AR-ligand complexes were visualized with the PyMOL program.The residues that are modified in the regular interaction of the natural ligands of AR were Threonine 877 so that the union with the natural ligands was between Arginine 752 that binds to O of the Testosterone ligand (2.8Å), and the Glutamine residue 711 attached to H of the ligand (2.0Å).In the AR-Dihydrotestosterone complex, the amino acids involved are Arginine 752 and Glutamine 711 at distances of 2.9Å with O and 2.4Å with H, respectively (Figure 4). 19,20

Conclusion
Prostate cancer, specifically the castration-resistant form (CRPC), has continued to be a significant challenge in the medical field.Our study, centering on the identification of binding sites for wild-type and mutated androgenic receptors, provides invaluable insights into potential therapeutic interventions for CRPC.Using in-silico methodologies and computational docking techniques, we assessed the binding affinities of known ligands and inhibitors to the androgen receptor (AR), both in its wild and mutated (T877A) forms.
Our findings affirmed that the Dihydrotestosterone (DHT) ligand possesses a higher affinity to the AR compared to testosterone.The different affinities of first and second-generation antiandrogens were elucidated, providing a broader perspective on their effectiveness.Importantly, second-generation antiandrogens, specifically Enzalutamide and Apalutamide, demonstrated alternative binding sites on the AR, which could be an underlying factor contributing to their different therapeutic outcomes in CRPC patients.
Moreover, the observed interactions between the AR and its ligands, facilitated by residues like threonine 877 and arginine 752, offer deeper molecular insights into their binding mechanisms.Such insights are invaluable as they lay the groundwork for designing more targeted therapies in the future.
It is evident from our study that there is a complex interplay of forces governing the interaction between AR and its ligands.This interaction is further complicated by the presence of mutations in the AR, which can potentially alter its binding behavior and drug resistance patterns.Computational methods, such as the ones employed in our study, thus serve as a powerful tool for unraveling these complexities and guiding the future design of therapeutics.
Finally, our study sheds light on the intricate interactions between AR and various ligands, both natural and therapeutic.By understanding these interactions at a molecular level, we open the door to more targeted and effective treatments for CRPC in the future.Further research is essential to translate these findings into tangible clinical outcomes, but the foundation laid by this study is undeniably promising.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
© 2024 Mahmood A. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Ahmed A J Mahmood
Pharmacy college, University of Mosul, Mosul, Nineveh Governorate, Iraq Dear authors I read the version 4 of you research paper, it is really a very good work.The idea and the goal were very interesting, the writing style and the languages were excellent.Although there are some points and notes that you need to review in order to accomplish your work.The following are some notes that may help you to do so: In the abstract there is some mistakes in writing the docking score for testosterone and dihydrotestosterone, the (-) is missing. 1.
Also, in the abstract you need to minimize mentioning the docking score values and replace them by increasing or decreasing, and only the important value must be mentioned here.

2.
I would prefer if you merge the tables of the docking score for the two enzymes in one table to facilitate the comparison of the scores data, although they were very clear in their present form, but as I sed it will be easier to the reader.

3.
For more accuracy and to potentiate your results, I would prefer to compare the results of the wild enzyme with results of two mutated enzyme and not only one muted enzyme as you presented, this will accurate your data and your conclusion.

4.
And if the previous point can not be achieved, I would prefer to do the MD simulation for selected ligands with the both enzymes pocket, this also would potentiate your results and conclusions.

5.
In the conclusion it will be more convenient to propose the best agents that your results made it a promising agent for the treatment of the prostate cancer.The study aimed to repurpose some drugs against mutated androgen receptor ligand binding domain and could have clinical translation prospects.Authors took publicly available data and used Autodock for docking.The results showed that the mutated receptor had lower affinity towards some ligands ligands while having variable affinity towards others.However, the protein and ligand preparation as well as validation was not rigorous.The docking is a prediction and can be influenced by various factors such as the accuracy of the protein structure, the scoring function used, and the conformational flexibility of the ligand and receptor.Since authors come from LMIC, with limited resources, they could try and validate using energy calculation and dynamics simulation on the least (as access to experimental setup would be limited).Simply docking scores are not enough in most cases and MM-PBSA values etc have been reported to have better results.
Authors mention in abstract that they look androgen receptor structure, whereas it is only part of it (ligand binding domain that is present with the mentioned ID in PDB).Authors need to be clear about this.Name of software needs to be mentioned and parameter portion edited.Abstract lack of information on docking parameters: The abstract mentions that analysis parameters were established for docking, but it does not provide any details on the specific algorithms or software used.This makes it difficult to assess the reliability and reproducibility of the docking results.Authors should also provide a detailed rationale for selecting the ligands (preferably add a table with references that depict use of these ligands in treatment).The scope is somewhat limited, the study only investigated the interactions of a few ligands and inhibitors with the androgen receptor and a specific mutation (T877A).It is unclear whether these findings can be generalized to other ligands, inhibitors, or mutations.Authors could shed some light on this.
Language needs to be edited at several places for clarity and conveying proper scientific meaning.The heading 'Adequacy of the wild and mutated androgen receptor ' and the text beneath it needs reassessment and editing.'subjected to adaptation'?
Same goes for 'Assays of wild AR interactions with natural ligands and AR inhibitors to establishing interaction parameters' heading.Too long and not correct.Natural ligands can act as control for this study.What is L.b and U.b?
Authors took a ligand binding section of the protein, how can they write in conclusion that '….. in addition to the normal receptor ligand binding site, there is another site on which the search and identification of drugs can be based.'.They did not do a site scoring and binding comparison

Figure 1 .
Figure 1.The binding site of androgen receptor inhibitor drugs for both first generation (nilutamide) and second generation (Enzalutamide) drugs.(a) showed uncommon androgen receptors and site of enzalutamide binding (b) showed wild-type androgen receptor binding to a common site.

Table 4 .
The affinity of first-generation antiandrogens, used in PCa, for the binding site of AR with AutoDock Vina.

Table 5 .
The affinity of second-generation antiandrogens, used in PCa, for any site in the wild-type receptor LBD region (2am9).

Table 3 .
Results for the AutoDock Vina program of the interaction between AR (2AM9) with Testosterone.

Table 2 .
Results for the Chimera program of the interaction between AR (2AM9) and Testosterone.

Table 6 .
Interactions between wild-type androgen receptors with inhibitors.

Table 7 .
The affinity of first-generation antiandrogens for mutated androgenic receptor (T877A) binding site with AutoDock Vina.

Table 8 .
The affinity of second-generation antiandrogens, used in PCa, at any site in the LBD region of the mutated receptor (T877A).

Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Not applicable Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests:
No competing interests were disclosed.