In Silico Studies of Novel BCL-2 and MCL-1 Inhibitors Using Computational Drug Design Tools

S. Apoorva¹*, Dr. B. Veeresh², G. Harshini², Fatima Mirza³

1 Department of Pharmaceutical Chemistry, G. Pulla Reddy College of Pharmacy, Hyderabad, India.

2 Department of Pharmacology, G. Pulla Reddy College of Pharmacy, Hyderabad, India.

* Correspondence: sapoorva27101996@gmail.com; Tel.: +91 9441214463

DOI: https://doi.org/10.71431/IJRPAS.2025.4505

INTRODUCTION

The clonal proliferation of immature and defective hematopoietic cells is a characteristic of acute myeloid leukaemia (AML) [1]. A few hematopoietic stem cells (HSCs) are responsible for maintaining the hematopoietic compartment [2]. Although HSCs are primarily inactive and have the ability to self-renew, they may be stimulated to form subpopulations of progenitor cells that create a sequence of committed blood cell lineages during normal haematopoiesis [3]. Pre-leukemic stem cells (pre-LSC) can arise from mutations in AML's HSCs. These cells have the ability to perform regular haematopoiesis, but they have a fitness advantage over normal HSCs, which leads to their clonal growth [4]. Pre-LSCs that acquire extra mutations may cause myelodysplastic syndromes (MDS) or decreased haematopoiesis, excess of some blood types, such as in myeloproliferative neoplasms (MPN) or the development of malignant leukemic stem cells (LSC) from pre-LSCs [4-7]. In the context of acute myeloid leukaemia (AML), the dysregulation of Bcl-2 and Mcl-1 anti-apoptotic proteins plays a critical role in disease progression and resistance to apoptosis. Bcl-2 and Mcl-1 are overexpressed in AML cells, enabling them to sequester pro-apoptotic proteins such as Bax, Bak, and BH3-only proteins like Bim, thereby preventing mitochondrial outer membrane permeabilization (MOMP) and subsequent apoptosis. This overexpression is often driven by oncogenic signalling pathways, including FLT3 mutations, which upregulate Mcl-1 and Bcl-XL while promoting the degradation of pro-apoptotic Bad. The imbalance between anti-apoptotic and pro-apoptotic Bcl-2 family members contributes to the survival and proliferation of AML cells. Therapeutic strategies targeting these proteins, such as BH3-mimetics (e.g., navitoclax, obatoclax) and agents that downregulate Mcl-1 (e.g., sorafenib, CDK9 inhibitors), have shown promise in preclinical studies, particularly in FLT3-mutated AML, by restoring apoptotic signalling and enhancing cell death. These findings underscore the importance of Bcl-2 and Mcl-1 in AML pathogenesis and highlight their potential as therapeutic targets [8]. Venetoclax, a potent and highly selective B-cell lymphoma-2 (BCL-2) inhibitor, has emerged as an important and widely used drug for treatment of acute myeloid leukaemia [9]. However, resistance to Venetoclax remains a challenge, especially in patients with high Mcl-1 levels. To counteract this, researchers are looking into drugs targeting Bcl-2 and Mcl-1 simultaneously. New drugs like BRD-810, BFC1108, and VU661013 could be used as dual inhibitors of the two proteins, to escape the resistance mechanisms. Other drugs in preclinical and early stages of clinical trials include A-1210477 and AZD5991. This could revitalize the sensitivity of the resistant AML cells to apoptosis, making it more feasible to treat the patient who has been resistant to the Bcl-2 inhibitor only [10,11].

From the belove figure, Venetoclax selectively inhibits Bcl-2, releasing Bax/Bak to induce mitochondrial outer membrane permeabilization (MOMP), cytochrome c release, and caspase-3 activation, triggering apoptosis. Resistance arises due to Mcl-1 upregulation. Novel Compounds (BRD-810, BFC1108, VU661013, A-1210477, AZD5991) These dual Bcl-2/Mcl-1 inhibitors overcome resistance by fully releasing Bax/Bak, enhancing MOMP, and promoting caspase-3 activation, restoring apoptosis in resistant cells. By restoring apoptosis in resistant AML cells, these compounds overcome treatment resistance, enabling the elimination of cancer cells that survive conventional therapies like Venetoclax. This enhances therapeutic efficacy and improves patient outcomes.

Fig 2: Structure of ligands

Fig 3: Structure of proteins

MATERIALS AND METHODS

Computational approaches were found to be the most reliable methods to start a research methodology. Hence, several computational tools were identified which rely on current research work for efficient strategies to develop novel compounds. The designed derivatives were studied using web tools to understand their physiochemical properties, biological activities and toxicological effects.

Table 1. Materials and Methodology

Prediction of Physicochemical and ADMET Properties

2.1 Molinspiration:
Molinspiration is employed to compute essential molecular properties, such as log P, polar surface area, and hydrogen bond donors/acceptors, while predicting bioactivity scores for key drug targets, including GPCRs, ion channels, and kinases, to support virtual screening and drug design [13].

2.2 SwissADME:
SwissADME is utilized to assess physicochemical properties, pharmacokinetic parameters, and drug-likeness of small molecules, enabling lead optimization and ADMET prediction during the drug discovery process [14].

2.3 PASS Studies:
PASS predicts a broad spectrum of biological activities, mechanisms, and toxicities (e.g., mutagenicity, carcinogenicity) for novel compounds using a comprehensive dataset of 26,000 bioactive molecules, aiding in early-stage drug development and risk assessment [15].

2.4 Molecular Docking Studies:

In the course of developing new drugs, computational techniques are equally important and helpful resources. Computational tools make it easier to plan, search, evaluate, model, calculate binding energy, determine pharmacokinetic parameters and pharmacokinetic predictions, and optimize leads. One important online resource for structural biology and computer-aided drug design is computational molecular docking. Targeting a protein with a known three-dimensional molecular structure is the primary objective. Along with employing a scoring mechanism that would suitably rank potential dockings, high dimensional spaces are searched using effective molecular docking techniques.

2.4.1 Preparation of Protein: Proteins (6qbc and 6fbx) are downloaded from Protein data bank PDB [16] and saved in .pdb after removing hetero atoms and other bound ligands using biovia. The water molecules are deleted, polar hydrogens are added, kollman charges are introduced and ad4 type atoms are assigned using autodock and saved in .pdbqt format [17].

2.4.2 Preparation of Ligand: Ligands (Venetoclax, BRD-810, BFC1108, VU661013, A-1210477, AZD5991) drawn on chemDraw software and saved in mol format and converted to .pdb using biovia. Then converted to.pdbqt format using autodock [17].

2.4.3 Performing docking:

Molecular docking was performed with Autodock1.4.7. Preparation of ligand and the target protein was done by using Autodock vina tools. Molecular docking studies were performed to find the active binding site and their interaction with ligand molecules. Both ligand and protein were selected and the rigid grid box was attained. Blind docking studies were performed as the active binding site for the newly synthesized compound was not figured. The grid box dimension dimensions were then documented in the config file as text document and saved in separate file for each target and each ligand. To predict the binding scores of these ligands- target complex, command prompt was utilized. The desired syntax for the prediction and path for the results were given. Thus, scores were obtained in the output file in the folder. Scoring for all compounds for targets were obtained and tabulated [17].

2.5 Visualization:

Ligand target Molecular complex visualization is a significant aspect of the investigation and communication of modelling studies. It allows for a mechanistic understanding of a molecular structure to be visualized. BIOVIA Discovery Studio Visualizer is a free web tool, feature-rich modelling application for observing, allocation and analysing protein and other small molecular data. The output files obtained for every ligand were utilized separately in Biovia discovery studio where the best scoring output among conformers were visualized for their interactions of ligand molecules with amino acids of the targe, visualizing active sites and 2D interactions to know which atom is bonding with amino acid of target molecules. Thus, the visualized complexes were saved as image files [17].

RESULT AND DISCUSSION

3.1 Physicochemical properties results using Molinspiration: Pharmacokinetic properties were predicted using Molinspiration web tool which showed the following results listed in Table- 3.1 molecular formula and molecular weight were obtained and listed. Approved drug Venetoclax showed 3 violations for Lipinski rule i.e., all the other compounds have molecular weight greater than 500 except BFC1108 and number of hydrogen bond acceptors are also greater and equal to 5 except BFC1108. Log P values are also greater than 5 except BFC1108. Hence these compounds are considered to have apoptotic activity by inhibition of Bcl-2 and Mcl-1.

Table 3.1: ADMET properties of all compounds

3.2 Pharmacokinetic properties results using SwissADME:

Pharmacokinetic properties were predicted using SwissADME the properties are listed in the Table 3.2 Log Kp- skin permeability as all the compounds has shown value between -8.0 and -1.0 except A-1210477 they have good skin permeability. Compound 3 (BFC1108) only has good GI absorption all other compounds cannot be absorbed. None of the compound showed blood brain barrier permeability and has no neuroprotective effect. And shown various inhibitory interactions.

These properties are useful in predicting the biological activity and designing the dose and dosage from for the therapeutic agents.

Table- 3.2: Pharmacokinetic parameters of all compounds

3.3 PASS Results:

The pharmacological activity range was analyzed to identify the properties of biologically active compounds. The PASS (Prediction of Activity Spectra for Substances) online tool was utilized to predict over 300 pharmacological activities and biochemical mechanisms based on the structural or molecular formulas of the designed derivatives. It is effectively aided in identifying novel drug targets (mechanisms) for the newly developed derivatives. The pharmacological activities predicted by the PASS software for six compounds are detailed in the following tables.

Table- 3.3.1: PASS Biological activity data of Venetoclax

Table- 3.3.2: PASS Biological activity data of BRD-810

Table- 3.3.3: PASS Biological activity data of BFC1108:

Table-3.3.4: PASS Biological activity data VU661013:

Table-3.3.5: PASS Biological activity data A-1210477:

Table-3.3.6: PASS Biological activity data AZD5991:

3.4 MOLECULAR DOCKING RESULTS:

All the 6 compounds were docked against two targets (6qbc and 6fbx) using Auto-Dock  and the results are listed in the following tables.

Table-3.4.1: Molecular docking results of all compounds with 6qbc:

Table-3.4.2: Molecular docking results of all compounds with 6fbx:

3.5 VISUALIZATION:

The highest scoring compounds were visualized for their interactions with the two protein targets and their interactions and 2D interaction images were displayed in the below tables.

Table-3.5.1: Interaction of compounds with 6qbc target

Table-3.5.2: Interaction of molecules with 6fbx target:

In this study, we explored the potential of novel inhibitors targeting both BCL-2 and MCL-1 to overcome resistance to Venetoclax. Using computational tools such as Molinspiration and SwissADME, we predicted the physicochemical and pharmacokinetic properties of five promising compounds: AZD5991, BRD-810, BFC1108, VU661013, and A-1210477. The results indicated that most of the compounds, except BFC1108, violated Lipinski’s Rule of Five, which typically suggests issues with oral bioavailability. However, these violations did not preclude the compounds from showing significant apoptotic activity, as their ability to inhibit BCL-2 and MCL-1 suggests they can effectively engage the apoptotic machinery.

The pharmacokinetic analysis revealed that all compounds, except A-1210477, exhibited good skin permeability, which could be advantageous for topical formulations or drug delivery systems targeting the skin. Notably, BFC1108 demonstrated excellent gastrointestinal absorption, which suggests that it might be suitable for oral administration. However, none of the compounds showed significant blood-brain barrier permeability, indicating that these inhibitors might not have neuroprotective effects, which could be important for therapies targeting central nervous system involvement in leukaemia.

Molecular docking studies revealed that AZD5991 has a binding affinity to MCL1 comparable to Venetoclax affinity for BCL-2, suggesting that AZD5991 may be an effective MCL-1 inhibitor for overcoming Venetoclax resistance. On the other hand, A-1210477 showed superior binding affinity to BCL-2 compared to Venetoclax, indicating that it might be a more potent alternative or complement to Venetoclax in AML therapies. The other compounds, BRD-810, BFC1108, and VU661013, showed strong binding to both BCL-2 and MCL-1, indicating that they may serve as dual inhibitors, offering an advantage in overcoming the functional redundancy of these anti-apoptotic proteins in AML cells.

The results of this study strongly suggest that targeting both BCL-2 and MCL-1 may provide a more effective therapeutic strategy for AML, particularly in cases where Venetoclax resistance has developed. The combination of these inhibitors could circumvent the compensatory survival mechanisms that allow leukaemia cells to escape apoptosis. Furthermore, the favourable physicochemical properties of these inhibitors, including skin permeability and gastrointestinal absorption, suggest that they could be developed into viable oral or topical therapeutic agents.

CONCLUSION

This study identifies AZD5991, BRD-810, BFC1108, VU661013, and A-1210477 as promising candidates for the treatment of AML, especially in cases where resistance to BCL-2 inhibitors like Venetoclax has developed. These compounds show the potential to simultaneously target BCL-2 and MCL-1, offering a dual approach to overcome therapeutic resistance. Further in vitro and clinical investigations are necessary to validate the therapeutic potential and optimize the use of these inhibitors in AML treatment strategies.

ACKNOWLEDGEMENT

We acknowledge the help of G. Pulla Reddy College of Pharmacy, Hyderabad, in providing the required infrastructure and facilities to conduct this in silico research study. We thank the Department of Pharmacology and the Department of Pharmaceutical Chemistry for their technical support and guidance during the work. We further acknowledge the informative feedback and inspiration provided by S. Apporva, Assistant Professor, Department of Pharmaceutical Chemistry, and Dr. Veeresh B., Professor and Head, Department of Pharmacology, as our corresponding authors.

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