Design of Novel Coumarin Derivatives as NUDT5 Antagonists That Act by Restricting ATP Synthesis in Breast Cancer Cells

Disaggregation of amyloid-beta fibrils via natural metabolites using long timescale replica exchange molecular dynamics simulation studies

CONTEXT

Amyloid fibrils are self-assembled fibrous protein aggregates that are associated with several presently incurable diseases such as Alzheimer's. disease that is characterized by the accumulation of amyloid fibrils in the brain, which leads to the formation of plaques and the death of brain cells. Disaggregation of amyloid fibrils is considered a promising approach to cure Alzheimer's disease. The mechanism of amyloid fibril formation is complex and not fully understood, making it difficult to develop drugs that can target the process. Diacetonamine and cystathionine are potential lead compounds to induce disaggregation of amyloid fibrils.

METHODS

In the current research, we have used long timescale molecular simulation studies and replica exchange molecular dynamics (REMD) for 1000 ns (1 μs) to examine the mechanisms by which natural metabolites can disaggregate amyloid-beta fibrils. Molecular docking was carried out using Glide and with prior protein minimization and ligand preparation. We focused on a screening a database of natural metabolites, as potential candidates for disaggregating amyloid fibrils. We used Desmond with OPLS 3e as a force field. MM-GBSA calculations were performed. Blood-brain barrier permeability, SASA, and radius of gyration parameters were calculated.

BRCA1/TP53 tumor proteins inhibited by novel analogues of curcumin - Insight from computational modelling, dynamic simulation and experimental validation

The current study aimed to design novel curcumin analogue inhibitors with antiproliferative and antitumor activity towards BRCA1 and TP53 tumor proteins and to study their therapeutic potential by computer-aided molecular designing and experimental investigations. Four curcumin analogues were computationally designed and their drug-likeness and pharmacokinetic properties were predicted. The binding of these analogues against six protein targets belonging to BRCA1 and TP53 tumor proteins were modelled by molecular docking and their binding energies were compared with that of curcumin and the standard drug cyclophosphamide and its validated target. The stabilities of selected docked complexes were confirmed by molecular dynamic simulation (MDS) and MMGBSA calculations. The best-docked analogue was chemically synthesized, characterized, and used for in vitro cytotoxic screening using DLA, EAC, and C127I cell lines. In vivo antitumor studies were carried out in Swiss Albino Mice. The study revealed that the designed analogues satisfied drug-likeness and pharmacokinetic properties and demonstrated better binding affinity to the selected targets than curcumin. Among the analogues, NLH demonstrated significant interaction with the BRCA1-BRCT-c domain (TG3; binding energy -8.3 kcal/mol) when compared to the interaction of curcumin (binding energy -6.19 kcal) and cyclophosphamide (binding energy -3.8 kcal/mol) and its usual substrate (TG7). The MDS and MM/GBSA studies revealed that the binding free energy of the NLH-TG3 complex (-61.24 kcal/mol) was better when compared to that of the cyclophosphamide-TG7 complex (-21.67 kcal/mol). In vitro, cytotoxic studies showed that NLH demonstrated significant antiproliferative activities against tumor cell lines. The in vivo study depicted NLH possesses the potential for tumor inhibition. Thus, the newly synthesized curcumin analogue is probably used to develop novel therapeutic agents against breast cancer.

Stearyl palmitate a multi-target inhibitor against breast cancer: in-silico, in-vitro & in-vivo approach

Multi-target inhibitors are currently trending in the pharmaceutical research, as they possess increased efficacy and reduced toxicity. In this study multi-target inhibitors for breast cancer are explored from a curated list of natural products, i.e. 4,670 phytochemicals belonging to 360 medicinal plants. In-silico screening of phytochemicals using SeeSAR and AutoDock Vina resulted in identification of Stearyl Palmitate as a potential drug molecule that inhibits three drug targets, i.e. HER-2, MEK-1 and PARP-1 proteins. Molecular Dynamics Simulation for 100 ns each for these three protein-ligand complexes using Desmond, Maestro platform also confirmed the prediction of multi-target inhibition by Stearyl Palmitate. Further in-vitro MTT assay demonstrated that Stearyl Palmitate has a significant IC50 value of 40 µM against MCF-7 cells and >1000 µM against L929 cells. This confirmed that Stearyl Palmitate is having selective cytotoxicity towards breast cancer cells in comparison to non-cancerous cells. Fluorescence staining and flow cytometry analysis confirmed that, Stearyl Palmitate is inducing apoptosis in MCF-7 cells at IC50 concentration. Finally, in-vivo efficacy and toxicity studies were performed using zebrafishes (Danio rerio). It was observed that the fishes treated with IC50 concentration of Stearyl Palmitate demonstrated 2x folds reduction in tumour size, while double dose resulted in 4x folds reduction in tumour size. Stearyl Palmitate did not demonstrate any toxicity or side effects in the zebrafishes. It is concluded that, Stearyl Palmitate, a phytochemical reported to be present in Althea officinalis is a potential anti-breast cancer agent, with ability to inhibit multiple targets such as HER-2, MEK-1 and PARP-2 proteins.Communicated by Ramaswamy H. Sarma.

Theoretical, antioxidant, antidiabetic and in silico molecular docking and pharmacokinetics studies of heteroleptic oxovanadium(IV) complexes of thiosemicarbazone-based ligands and diclofenac

A series of new heteroleptic oxovanadium(IV) complexes with the general formula [VOL1-6(Dcf)] (1-6), where L1-6 = thiosemicarbazone (TSC)-based ligands and Dcf = diclofenac have been synthesized and characterized. The spectral studies along with the density functional theory calculations evidenced the distorted square-pyramidal geometry around oxovanadium(IV) ion through imine nitrogen and thione sulfur atoms of TSC moiety, and two asymmetric carboxylate oxygen atoms of diclofenac drug. The complexes were evaluated for in vitro antioxidant activity using 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), 2,2'-diphenyl-1-picrylhydrazyl (DPPH), hydrogen peroxide (H2O2) and superoxide radical scavenging assays with respect to the standard antioxidant drugs butylated hydroxyanisole (BHA) and rutin. The in vitro antidiabetic activity of the complexes was tested with enzymes such as α-amylase, α-glucosidase and glucose-6-phosphatase. The complexes containing methyl substituent showed higher activity than that containing the nitro substituent due to the electron-donating effect of methyl group. The in silico molecular docking studies of the oxovanadium(IV) complexes with α-amylase and α-glucosidase enzymes showed strong interaction via hydrogen bonding and hydrophobic interactions. The dynamic behavior of the proposed complexes was analyzed by molecular dynamics (MDs) simulations, which revealed the stability of docked structures with α-amylase and α-glucosidase enzymes. The in silico physicochemical and pharmacokinetics parameters, such as Lipinski's 'rule of five', Veber's rule and absorption, distribution, metabolism and excretion (ADME) properties predicted non-toxic, non-carcinogenic and safe oral administration of the synthesized complexes.Communicated by Ramaswamy H. Sarma.

De Novo Design of Anti-COVID Drugs Using Machine Learning-Based Equivariant Diffusion Model Targeting the Spike Protein

The drug discovery and research for an anti-COVID-19 drug has been ongoing despite repurposed drugs in the market. Over time, these drugs were discontinued due to side effects. The search for effective drugs is still under process. The role of Machine Learning (ML) is critical in the search for novel drug compounds. In the current work, using the equivariant diffusion model, we built novel compounds targeting the spike protein of SARS-CoV-2. Using the ML models, 196 de novo compounds were generated which had no hits on any major chemical databases. These novel compounds fulfilled all the criteria of ADMET properties to be lead-like and drug-like compounds. Of the 196 compounds, 15 were docked with high confidence in the target. These compounds were further subjected to molecular docking, the best compound having an IUPAC name of (4aS,4bR,8aS,8bS)-4a,8a-dimethylbiphenylene-1,4,5,8(4aH,4bH,8aH,8bH)-tetraone and a binding score of -6.930 kcal/mol. The principal compound is labeled as CoECG-M1. Density Function Theory (DFT) and Quantum optimization was carried out along with the study of ADMET properties. This suggests that the compound has potential drug-like properties. The docked complex was further subjected to MD simulations, GBSA, and metadynamics simulations to gain insights into the stability of binding. The model can be in the future modified to improve the positive docking rate.

Carboxymuconolactone decarboxylase is a prospective molecular target for multi-drug resistant Acinetobacter baumannii-computational modeling, molecular docking and dynamic simulation studies

Multidrug-resistant Acinetobacter baumannii (MDRAb), a priority-I pathogen declared by the World Health Organization, became a potential healthcare concern worldwide with a high mortality rate. Thus, the identification of putative molecular targets and potential lead molecules is an important concern in healthcare. The present study aimed to screen a prospective molecular target and effectual binders for the drug discovery of MDRAb by computational virtual screening approach. Based on the functional role, γ-carboxymuconolactone decarboxylase (CMD) was prioritized as the target and its three-dimensional (3D) structure was computationally modeled. Based on the availability of the 3D structure, twenty-five herbal molecules were selected by database search, and their drug-likeliness, pharmacokinetic, and toxicity features were predicted. The effectual binding of the selected molecules towards CMD was predicted by molecular docking. The stability of the best-docked complexes was predicted by molecular dynamics (MD) simulation for 100 ns and binding energy calculations were carried out by molecular mechanics generalized Born and surface area solvation (MM/GBSA) method. Out of twenty-five molecules screened, hirsutine (an indole alkaloid of Uncaria rhynchophylla) and thymoquinone (a phytochemical of Nigella sativa) were qualified for drug likeliness, pharmacokinetic, and toxicity features and demonstrated significant effectual binding to CMD when compared with the binding of co-crystallized inhibitor and CMD (control). The docked complexes of hirsutine and thymoquinone, and CMD were stabilized by the binding energies of -8. 30 and -8. 46 kcal/mol respectively. These molecules were qualified in terms of ideal drug likeliness, ADME, and toxicity properties. MD simulation studies showed that the ligand-protein complexes were stable throughout the simulation. The binding free energies of the complexes by MMGBSA were estimated to be -42.08157745 kcal/mol and -36.58618242 kcal/mol for hirsutine and thymoquinone respectively when compared with the calculated binding free energy of the control (-28.75032666 kcal/mol). This study concluded that hirsutine and thymoquinone can act as potential lead molecules against CMD and the present hypothesis can be scaled up to develop potential inhibitors against MDRAb.