In silico hit optimization toward AKT inhibition: fragment-based approach, molecular docking and molecular dynamics study

Designing a novel drug-drug conjugate as a prodrug for breast cancer therapy: in silico insights

Breast cancer (BC) poses a significant global health threat, necessitating innovative therapeutic approaches. The ribosomal s6 kinase 2 (RSK2) has emerged as a promising target due to its roles in cell proliferation and survival. This study proposes a drug-drug conjugate prodrug comprising Methotrexate (hydrophobic) and Capecitabine (hydrophilic) for BC treatment. In silico approaches, including Molecular Docking, Molecular Dynamics Simulations, MM-PBSA, ADME, and DFT calculations were employed to evaluate the prodrug's potential. The designed MET-CAP ligand exhibits a robust docking score (-8.980 kcal/mol), superior binding affinity (-53.16 kcal/mol), and stable dynamic behavior (0.62 nm) compared to native ligands. The DFT results reveal intramolecular charge transfer in MET-CAP (HLG = 0.09 eV), indicating its potential as a BC inhibitor. ADME analysis suggests satisfactory pharmaceutically relevant properties. The results indicate that the conjugated MET-CAP ligand exhibits favorable binding characteristics, stability, and pharmaceutically relevant properties, making it a potential RSK2 inhibitor for BC therapy. The multifaceted approach provides insights into binding interactions, stability, and pharmacokinetic properties, laying the foundation for further experimental validation and potential clinical development.

Revealing Molecular Mechanisms of the Bioactive Saponins from Edible Root of Platycodon grandiflorum in Combating Obesity

Obesity has emerged as a significant health concern, as it is a disease linked to metabolic disorders in the body and is characterized by the excessive accumulation of lipids. As a plant-derived food, Platycodon grandiflorum (PG) was reported by many studies, indicating that the saponins from PG can improve obesity effectively. However, the anti-obesity saponins from PG and its anti-obesity mechanisms have not been fully identified. This study identified the active saponins and their molecular targets for treating obesity. The TCMSP database was used to obtain information on 18 saponins in PG. The anti-obesity target of the PG saponins was 115 targets and 44 core targets. GO and KEGG analyses using 44 core anti-obesity genes and targets of PG-active saponins screened from GeneCards, OMIM, Drugbank, and DisGeNet showed that the PI3K-Akt pathway, the JAK-STAT pathway, and the MAPK pathway were the major pathways involved in the anti-obesity effects of PG saponins. BIOVIA Discovery Studio Visualizer and AutoDock Vina were used to perform molecular docking and process the molecular docking results. The molecular docking results showed that the active saponins of PG could bind to the major therapeutic obesity targets to play an obesity-inhibitory role. The results of this study laid the foundation for further research on the anti-obesity saponins in PG and their anti-obesity mechanism and provided a new direction for the development of functional plant-derived food. This research studied the molecular mechanism of PG saponins combating obesity through various signaling pathways, and prosapogenin D can be used to develop as a new potential anti-obesity drug.

Investigation of the inhibitory behavior of XFE and mitoxantrone molecules in interaction with AKT1 protein: a molecular dynamics simulation study

The PI3K/Akt/mTOR pathway is one of the important pathways in many cancers. Akt is a serine-threonine kinase protein identified as a drug target for cancer treatment. Therefore, anticancer drugs are essential therapeutic targets for this pathway. In the current study, the inhibitory effect of two anticancer molecules, XFE and mitoxantrone, on AKT1 protein that can impact the activity of the AKT1 protein was investigated by using molecular docking and molecular dynamics (MD) simulations. The molecular docking results presented a relatively higher binding affinity of the mitoxantrone molecule in interaction with AKT1 than the XFE molecule. These results were validated by the MM/PBSA technique that was performed on obtained trajectories of 25 ns MD simulations. The mitoxantrone molecule has an intense binding energy of - 880.536 kcal/mol with AKT1 protein, while the XFE molecule shows a binding energy value of - 83.569 kcal/mol. Our findings from molecular dynamics simulations indicated that both molecules have favorite interactions with AKT1 protein. Other analyses, such as RMSF and hydrogen binding on trajectories obtained from MD simulations, indicated that the mitoxantrone molecule could be a relatively potent inhibitor for AKT1. Based on the results of this study and the structure of mitoxantrone, it is expected to be a good candidate for cancer treatment as a (PI3K)/Akt/mTOR inhibitor.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

BACKGROUND

Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).

AIM

The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.

METHODOLOGY

Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.

RESULT

MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.

CONCLUSION

Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

Molecular dynamics simulation, free energy landscape and binding free energy computations in exploration the anti-invasive activity of amygdalin against metastasis

BACKGROUND AND OBJECTIVE

Historically, amygdalin has been used as alternative medicine or in vitro and in vivo studies, but no single study exists which discusses the structural mechanism of amygdalin at a molecular level. This paper inquiries into the inhibitory actions of amygdalin on the selected targets: AKT1, FAK, and ILK, which are regulators for various mediated signaling pathways, and are associated with cell adhesion, migration, and differentiation. In order to get details at the molecular level of amygdalin's inhibitory activities against chosen proteins, molecular modeling and simulation techniques including double docking, molecular dynamics simulation, free energy landscape analysis, and binding free energy calculation were exerted.

METHODS

To get molecular level details of amygdalin inhibitory effects against the relevant proteins; here the utilized tools are the following: the double docking, molecular dynamics simulation, free energy landscape analysis, g_mmpbsa, and interaction entropy were used to evaluate the inhibitory activity against targeted proteins.

RESULTS

The computational calculations revealed that amygdalin inhibits the selected targets via block the ATP-binding pocket of AKT1, FAK, and ILK by forming stable hydrogen bonds. Moreover, free energy landscape, FEL exposed that amygdalin stabilized the global conformations of both FAK and ILK proteins to the minimum global energy besides it reduced the essential dynamics of FAK and ILK proteins. MMPBSA computations provided further evidence for amygdalin's stability inside the ATP-binding pocket of AKT1, FAK, and ILK with a binding free energy of 45.067, -13.033, 13.109 kJ/mol, respectively. The binding free energies are lastly consistent with the hydrogen bonding and pairs within 0.35 nm results. The decomposition of binding energy shows the pivotal amino acid residues responsible for the stability of amygdalin's interactions inside the ATP-binding sites by forming hydrogen bonds.

CONCLUSIONS

Before this work, it was enigmatic to make predictions about how amygdalin inhibits metastasis of cancer. But the computational results contribute in several ways to our understanding of amygdalin activity and provide a basic insight into the activity of amygdalin as a multi-target drug in the metastasis and invasion of cancer.

Atranorin, an antimicrobial metabolite from lichen Parmotrema rampoddense exhibited in vitro anti-breast cancer activity through interaction with Akt activity

Atranorin (ATR), lichenized secondary metabolite and depside molecule with several biological potentials such as antimicrobial, anticancer, anti-inflammatory, antinociceptive, wound healing and photoprotective activities. Cytotoxic reports of ATR are documented in several cancer cells and in vivo models but its molecular interaction studies are poorly understood. Therefore, in this present investigation, we have used the in silico studies with biological validation of the molecular targets for the anti-breast cancer mechanism of ATR. The molecular docking studies with the breast cancer oncoproteins such as Bcl-2, Bax, Akt, Bcl-w and Bcl-xL revealed the highest interaction was observed with the Akt followed by Bax, Bcl-xL and Bcl-2 & least with the Bcl-w proteins. The cytotoxicity studies showed ATR selectively inhibited MDA MB-231 and MCF-7 breast cancer cells in differential and dose-dependent manner with the IC₅₀ concentration of 5.36 ± 0.85 μM and 7.55 ± 1.2 μM respectively. Further mechanistic investigations revealed that ATR significantly inhibited ROS production and significantly down-regulated the anti apoptotic Akt than Bcl-2, Bcl-xL and Bcl-w proteins with a significant increase in the Bax level and caspases-3 activity in the breast cancer cells when comparison with Akt inhibitor, ipatasertib. In vitro biological activities well correlated with the molecular interaction data suggesting that atranorin had higher interaction with Akt than Bax and Bcl-2 but weak interaction with Bcl-w and Bcl-xL. In this present study, the first time we report the interactions of atranorin with molecular targets for anti-breast cancer potential. Hence, ATR represents the nature-inspired molecule for pharmacophore moiety for design in targeted therapy.Communicated by Ramaswamy H. Sarma.

Computational investigation on the effect of Oleuropein aglycone on the α-synuclein aggregation

Parkinson's disease (PD) is considered to be the second most common progressive neurodegenerative brain disorder after Alzheimer's disease, which is caused by misfolding and aggregation of Alpha-synuclein (α-synuclein). It is characterized by distinct aggregated fibrillary form of α-synuclein known as the Lewy bodies and Lewy neurites. The most promising approach to combat PD is to prevent the misfolding and subsequent aggregation of α-synuclein. Recently, Oleuropein aglycone (OleA) has been reported to stabilize the monomeric structure of α-synuclein, subsequently favoring the growth of nontoxic aggregates. Therefore, understanding the conformational dynamics of α-synuclein monomer in the presence of OleA is significant. Here, we have investigated the effect of OleA on the conformational dynamics and the aggregation propensity of α-synuclein using molecular dynamics simulation. From molecular dynamics trajectory analysis, we noticed that when OleA is bound to α-synuclein, the intramolecular distance between non-amyloid-β component domain and C-terminal domain of α-synuclein was increased, whereas long-range hydrophobic interactions between the two region were reduced. Oleuropein aglycone was found to interact with the N-terminal domain of α-synuclein, making this region unavailable for interaction with membranes and lipids for the formation of cellular toxic aggregates. From the binding-free energy analysis, we found binding affinity between α-synuclein and OleA to be indeed high (ΔG_bind = -12.56 kcal mol^-1 from MM-PBSA and ΔG_bind = -27.41 kcal mol^-1from MM-GBSA). Our findings in this study thus substantiate the effect of OleA on the structure and stabilization of α-synuclein monomer that subsequently favors the growth of stable and nontoxic aggregates.Communicated by Ramaswamy H. Sarma.

Effect of CTerm of human albumin on the aggregation propensity of Aβ1-42 peptide: a potential of mean force study

Alzheimer's disease (AD) is the most common progressive neurodegenerative brain disorder. It is characterized by the presence of extracellular aggregated fibrillary form of amyloid beta (Aβ) peptide and intraneuronal neurofibrillary tangles caused by the hyperphosphorylation of tau protein. Monomeric form of Aβ peptide in α-conformation is not toxic but it can undergo self-aggregation to form β-conformation which is neurotoxic. The most promising approach to combat AD is to prevent the self-aggregation of Aβ peptide. Recently, it has been reported that C-terminal (CTerm) of human albumin (HA) binds to the Aβ_1-42 peptide and impairs the Aβ_1-42 aggregation and promotes disassembly of Aβ_1-42 aggregates. In this work, using potential of mean force (PMF) and binding free energy (BFE) calculations, we have demonstrated the effect of CTerm of HA on the dimerization of Aβ_1-42 peptide. From the PMF profile, we noticed Aβ_1-42-CTerm Heterodimer (10.99 kcal mol - 1) complex to have higher disassociation energy than Aβ_1-42-Aβ_1-42 homodimer (2.23 kcal mol - 1) complex. And also from the BFE calculations, we found that the binding affinity between Aβ_1-42 peptide and CTerm (ΔG_bind = -32.27 kcal mol - 1 from MM-GBSA and ΔG_bind = -2.83 kcal mol - 1 from MM-PBSA (molecular mechanics-Poisson - Boltzmann surface area)) to be stronger than the Aβ_1-42 peptide and another Aβ_1-42 peptide (ΔG_bind = -16.20 kcal mol - 1 from MM-GBSA and ΔG_bind = -1.95 kcal mol - 1 from MM-PBSA). In this study, our findings from PMF and BFE analysis of the two complexes provide salient structural, binding and unbinding features and thermodynamics that support the ability of CTerm of HA in affecting the dimerization of Aβ_1-42. Communicated by Ramaswamy H. Sarma.