Molecular docking analysis of MCL-1 inhibitors for breast cancer management

Myeloid leukemia 1 (MCL-1), a BCL-2 protein family member, acts as an anti-apoptotic protein by interacting with pro-apoptotic BCL-2 proteins. Its overexpression is frequently observed in numerous cancer types including breast cancer, and is closely linked to the initiation and progression of tumors as well as poor prognosis and resistance to therapeutic interventions. Here, a database of 3402 chemicals with established therapeutic activity against various diseases was chosen and systematically screened against the MCL-1 protein. Visual inspection and binding energy analysis revealed that the compounds OSU-03012, Raltitrexed, Ostarine (MK-2866), Dovitinib (TKI-258), and Varespladib (LY315920) had strong binding affinity for the MCL-1 protein. Notably, their binding affinity was higher than that of the control compounds. These compounds exhibited strong interactions with critical amino acid residues of the MCL-1 protein. Furthermore, these compounds shared several common amino acid residue interactions with the control compounds. These findings suggest that these compounds may be useful as MCL-1 inhibitors in the treatment of breast cancer. However, additional experimental validation is required to confirm these findings.


Background:
Breast cancer (BC) is currently recognized as one of the most commonly diagnosed malignancies in the worldwide, and it is the fifth leading cause of cancer-related deaths.According to data from GLOBOCAN 2020, approximately 2.3 million new cases of breast cancer are expected to be diagnosed worldwide [1].In addition to its high prevalence, breast cancer is the leading cause of cancerrelated mortality among women globally, accounting for 684,996 deaths at an age-adjusted rate of 13.6 per 100,000 people.Notably, while the incidence rates were highest in developed regions, Asian and African countries accounted for 63% of total breast cancer deaths in 2020 [2].Myeloid leukemia 1 (MCL-1), BCL-2 protein family member has antiapoptotic properties.It acts by preventing mitochondrial outer membrane permeabilization and the subsequent cytochrome C release from the mitochondria.MCL-1 has gained prominence in the context of BC, with increased levels of MCL-1 protein in primary BC samples consistently associated with a poor patient prognosis [3-6].There is substantial evidence that MCL-1 targeting is a promising therapeutic avenue in BC.BC cells may rely on MCL-1 for survival in preclinical models, and inhibiting MCL-1 can improve the efficacy of conventional cancer treatments [7,8].Drug repurposing, also known as drug repositioning, is the process of looking into new applications for existing approved drugs that go beyond their original indications.It provides a promising strategy for expanding the arsenal of cancer treatments and has numerous advantages over developing new drugs from the ground up [9].Extensive studies are not required because repurposed drugs already have well-characterized pharmacokinetic and pharmacodynamic profiles.This simplifies the translational process, lowers associated costs, and contributes to higher drug development success rates [10].Due to its reduced risk, expanded therapeutic options, increased revenue potential, and improved patient outcomes, drug repurposing is very important.Examples include antidepressant medications like bupropion and Dapoxetine, which have been successful in treating nonneurological indications like premature ejaculation and quitting smoking, respectively.Drugs like Duloxetine for stress urinary incontinence, Fluoxetine for premenstrual dysphoria, and the nonpsychoactive medications Propecia and Minoxidil for hair loss have all been developed as a result of repurposing [11].Thalidomide is currently used for treating multiple myeloma, demonstrating the success of repurposing in oncology.The ongoing phase II clinical trial for the effective treatment of radiation dermatitis with esomeprazole highlights the possibility of repurposing currently available medications [12].There are various advantages to drug repurposing over de novo drug development, including greatly decreased time and expense for obtaining approval for a new indication.Repurposed drugs with a track record of safety can be approved in 3-10 years, compared to 10-17 years for novel drugs [13].Furthermore, repurposed candidates had a better approval rate, with 25% progressing from Phase II to approval, compared to only 10% of new drugs [14].Using an in-silico approach, this study aimed to find novel MCL-1 inhibitor to fight the BC.

Methods: Retrieval and preparation of target protein:
The 3D structure MCL-1 (PDB ID: 5FDO) was retrieved from the Protein Data Bank [15].The co-crystal ligand, other heteroatoms, and water molecules were removed from the structure.Subsequently, the protein was modeled using the SWISS-MODEL web tool due to its distorted conformation.

Compound library preparation:
We selected a database consisting of 3402 preclinical and clinical chemicals known for their activity in treating various diseases, including oncology, cardiology, anti-inflammatory, immunology, neuropsychiatry, analgesia, and others.These chemicals exhibit diverse structural properties, possess medicinal activity, and demonstrate cell permeability.

Virtual screening:
The drug discovery process is divided into different stages, including target selection, lead optimization, and preclinical/clinical trials.Computational modeling is strongly related with hit discovery and lead optimization, particularly through the application of structure-based virtual screening (VS)

Results and Discussion:
We performed a computational screening of 3,402 compounds with preclinical and clinical activity against the active sites of MCL-1 protein structures, prompted by the numerous success narratives of drug repurposing in cancer treatment.This screening sought to identify prospective candidates for cancer treatment repurposing.Due to distortions present in the retrieved 3D structure from the PDB, we employed the SWISS-MODEL tool to model the structure.Following the completion of the 3D structure modeling, we conducted a comparison by aligning the modeled structure with the PDB structure as the reference (Figure 1).The alignment revealed an RMSD value of 0.234 nm.As a positive control for this study, we The structure-based screening revealed that several compounds exhibited binding patterns similar to, and even superior to, the positive controls.Based on the analysis of binding affinity, the selected structure of MCL-1, specifically 5X2, displayed an affinity of -8.9 kcal/mol for the inbound ligand.Other controls such as Venetoclax exhibited -8.1 kcal/mol affinities, while Gossypol showed -7.7 kcal/mol affinity.By applying a cutoff based on the binding energy (BE) of 5X2, a total of 16 compounds exhibiting better BE are listed in Table 1.In addition, we estimated the physicochemical and druglikeness properties of these selected compounds to gain further insights.
Although toxicity and ADME analysis are not typically required in drug repurposing approaches, we focused on predicting the general physicochemical and druglikeness properties of the compounds (Table 2).

Conclusion:
MCL-1 overexpression is common in various cancer types, including BC.In this study, the 3402 chemicals with established therapeutic activity against various diseases were screened against the MCL-1 protein.OSU-03012, Raltitrexed, Ostarine (MK-2866), Dovitinib (TKI-258), and Varespladib (LY315920) strongly bind to MCL-1 protein and interact with its key amino acid residues.These compounds have several amino acid residue interactions in common with the control compounds.These compounds could be used as MCL-1 inhibitors in the treatment of BC, however, further experimental validation is required.
[16].Docking, the primary computational technique used in VS, has been extensively investigated and widely used in drug discovery during the last decade [17].The PyRx0.8 tool [18] was used in this study to screen the prepared compound library against the MCL-1 protein.The grid center coordinates were set as X = 7.53, Y = 25.37, and Z = -7.84.

Figure 1 :
Figure 1: Refinement of the target protein 3 D structure.Originally retrieved structure from PDB (A), modelled structure (B), and alignment of original and modelled structure (C).

Table 1 :
Best screened compounds with their respective binding affinity values.