Treasuring the computational approach in medicinal plant research

Enhancing Withanolide Production in the Withania Species: Advances in In Vitro Culture and Synthetic Biology Approaches

Withanolides are naturally occurring steroidal lactones found in certain species of the Withania genus, especially Withania somnifera (commonly known as Ashwagandha). These compounds have gained considerable attention due to their wide range of therapeutic properties and potential applications in modern medicine. To meet the rapidly growing demand for withanolides, innovative approaches such as in vitro culture techniques and synthetic biology offer promising solutions. In recent years, synthetic biology has enabled the production of engineered withanolides using heterologous systems, such as yeast and bacteria. Additionally, in vitro methods like cell suspension culture and hairy root culture have been employed to enhance withanolide production. Nevertheless, one of the primary obstacles to increasing the production of withanolides using these techniques has been the intricacy of the biosynthetic pathways for withanolides. The present article examines new developments in withanolide production through in vitro culture. A comprehensive summary of viable traditional methods for producing withanolide is also provided. The development of withanolide production in heterologous systems is examined and emphasized. The use of machine learning as a potent tool to model and improve the bioprocesses involved in the generation of withanolide is then discussed. In addition, the control and modification of the withanolide biosynthesis pathway by metabolic engineering mediated by CRISPR are discussed.

Isolation and Characterization of Antioxidant Peptides from Dairy Cow (Bos taurus) Placenta and Their Antioxidant Activities

Our preliminary study identified dairy cow placenta extract (CPE) as a mixture of peptides with potent antioxidant activity both in vivo and in vitro. However, the specific antioxidant peptides (AOPs) responsible for this activity were not yet identified. In the current study, we employed virtual screening and chromatography techniques to isolate two peptides, ANNGKQWAEVF (CP1) and QPGLPGPAG (CP2), from CPE. These peptides were found to be less stable under extreme conditions such as high temperature, strong acid, strong alkali, and simulated digestive conditions. Nevertheless, under normal physiological conditions, both CP1 and CP2 exhibited significant antioxidant properties, including free-radical scavenging, metal chelating, and the inhibition of lipid peroxidation. They also up-regulated the activities of intracellular antioxidant enzymes in response to hydrogen-peroxide-induced oxidative stress, resulting in reduced MDA levels, a decreased expression of the Keap1 gene and protein, and increased levels of the Nrf2 and HO-1 genes and proteins. Furthermore, CP1 demonstrated superior antioxidant activity compared to CP2. These findings suggest that CP1 and CP2 hold potential for mitigating oxidative stress in vitro and highlight the efficacy of virtual screening as a method for isolating AOPs within CPE.

Structure-based chemical ontology improves chemometric prediction of antibacterial essential oils

Plants are valuable resources for drug discovery as they produce diverse bioactive compounds. However, the chemical diversity makes it difficult to predict the biological activity of plant extracts via conventional chemometric methods. In this research, we propose a new computational model that integrates chemical composition data with structure-based chemical ontology. For a model validation, two training datasets were prepared from literature on antibacterial essential oils to classify active/inactive oils. Random forest classifiers constructed from the data showed improved prediction performance in both test datasets. Prior feature selection using hierarchical information criterion further improved the performance. Furthermore, an antibacterial assay using a standard strain of Staphylococcus aureus revealed that the classifier correctly predicted the activity of commercially available oils with an accuracy of 83% (= 10/12). The results of this study indicate that machine learning of chemical composition data integrated with chemical ontology can be a highly efficient approach for exploring bioactive plant extracts.

A computational odyssey: uncovering classical β-lactamase inhibitors in dry fruits

In the antibacterial arsenal, β-lactams have held a prominent position, but increasing resistance due to unauthorized use and genetic factors requires new strategies. Combining β-lactamase inhibitors with broad-spectrum β-lactams proves effective in combating this resistance. ESBL producers demand new inhibitors, leading to the exploration of plant-derived secondary metabolites for potent β-lactam antibiotics or alternative inhibitors. Using virtual screening, molecular docking, ADMET analysis, and molecular dynamic simulation, this study actively analyzed the inhibitory activity of figs, cashews, walnuts, and peanuts against SHV-1, NDM-1, KPC-2, and OXA-48 β-lactamases. Using AutoDock Vina, the docking affinities of various compounds for target enzymes were initially screened, revealing 12 bioactive compounds with higher affinities for the target enzymes compared to Avibactam and Tazobactam. Top-scoring metabolites, including Oleanolic acid, Protocatechuic acid, and Tannin, were subjected to MD simulation studies to further analyze the stability of the docked complexes using WebGro. The simulation coordinates, in terms of RMSD, RMSF, SASA, Rg, and hydrogen bonds formed, showed that these phytocompounds are stable enough to retain in the active sites at various orientations. The PCA and FEL analysis also showed the stability of the dynamic motion of Cα residues of phytochemical-bound enzymes. The pharmacokinetic analysis of the top phytochemicals was performed to analyze their bioavailability and toxicity. This study provides new insights into the therapeutic potential of phytochemicals of selected dry fruits and contributes to future experimental studies to identify βL inhibitors from plants.Communicated by Ramaswamy H. Sarma.

Identifying novel therapeutic inhibitors to target FMS-like tyrosine kinase-3 (FLT3) against acute myeloid leukemia: a molecular docking, molecular dynamics, and DFT study

Around 30% of acute myeloid leukemia (AML) patients have triggering mutations in Feline McDonough Sarcoma (FMS)-like tyrosine kinase 3 (FLT3), which has been suggested as a possible therapeutic candidate for AML therapy. Many tyrosine kinase inhibitors are available and have a wide variety of applications in the treatment of cancer by inhibiting subsequent steps of cell proliferation. Therefore, our study aims to identify effective antileukemic agents against FLT3 gene. Initially, well-known antileukemic drug candidates have been chosen to generate a structure-based pharmacophore model to assist the virtual screening of 217,77,093 compounds from the Zinc database. The final hits compounds were retrieved and evaluated by docking against the target protein, where the top four compounds have been selected for the analysis of ADMET. Based on the density functional theory (DFT), the geometry optimization, frontier molecular orbital (FMO), HOMO-LUMO, and global reactivity descriptor values have been evaluated that confirming a satisfactory profile and reactivity order for the selected candidates. In comparison to control compounds, the docking results revealed that the four compounds had substantial binding energies (-11.1 to -11.5 kcal/mol) with FLT3. The physicochemical and ADMET (adsorption, distribution, metabolism, excretion, toxicity) prediction results corresponded to the bioactive and safe candidates. Molecular dynamics (MD) confirmed the better binding affinity and stability compared to gilteritinib as a potential FLT3 inhibitor. In this study, a computational approach has been performed that found a better docking and dynamics score against target proteins, indicating potent and safe antileukemic agents, furthermore in-vivo and in-vitro investigations are recommended.Communicated by Ramaswamy H. Sarma.

Annonaceous acetogenins as promising DNA methylation inhibitors to prevent and treat leukemogenesis - an in silico approach

Leukemia is a haematological malignancy affecting blood and bone marrow, ranking 10th among the other common cancers. DNA methylation is an epigenetic dysregulation that plays a critical role in leukemogenesis. DNA methyltransferases (DNMTs) such as DNMT1, DNMT3A and DNMT3B are the key enzymes catalysing DNA methylation. Inhibition of DNMT1 with secondary metabolites from medicinal plants helps reverse DNA methylation. The present study focuses on inhibiting DNMT1 protein (PDB ID: 3PTA) with annonaceous acetogenins through in-silico studies. The docking and molecular dynamic (MD) simulation study was carried out using Schrödinger Maestro and Desmond, respectively. These compounds' drug likeliness, ADMET properties and bioactivity scores were analysed. About 76 different acetogenins were chosen for this study, among which 17 showed the highest binding energy in the range of -8.312 to -10.266 kcal/mol. The compounds with the highest negative binding energy were found to be annohexocin (-10.266 kcal/mol), isoannonacinone (-10.209 kcal/mol) and annonacin (-9.839 kcal/mol). MD simulation results reveal that annonacin remains stable throughout the simulation time of 100 ns and also binds to the catalytic domain of DNMT1 protein. From the above results, it can be concluded that annonacin has the potential to inhibit the DNA methylation process and prevent leukemogenesis.Communicated by Ramaswamy H. Sarma.

Natural polyphenols: a promising bioactive compounds for skin care and cosmetics

The physiological and morphological aspects of skin suffer from frequent change. Numerous internal and external factors have direct impact on inducing various skin problems like inflammation, aging, cancer, oxidative stress, hyperpigmentation etc. The use of plant polyphenols as a photo-ecting agent is gaining popularity nowadays. Polyphenols are known to enhance endogenic antioxidant system of skin thereby preventing various skin diseases. The biological activity of plant polyphenols is dependent on their physicochemical properties for overcoming the epidermal barriers to reach the specific receptor. Several evidences have reported the vital role polyphenols in mitigating adverse skin problems and reverting back the healthy skin condition. The interest in plant derived skin care products is emerging due to the changing notion of people to shift their focus towards use of plant-based products. The present review draws an attention to uncover the protective role of polyphenols in prevention of various skin problems. Several in vitro and in vivo studies have been summarized that claims the efficacious nature of plant extract having dermatological significance.

Prediction of In vitro organogenesis of Bacopa monnieri using artificial neural networks and regression models

This study was conducted to determine if artificial neural networks (ANN) can be used to accurately predict in vitro organogenesis of Bacopa monnieri compared with statistical regression. Prediction models were developed for shoot and root organogenesis (outputs) on two culture media (Murashige and Skoog and Gamborg B5) affected by two explant types (leaf and node) and two cytokinins (6-Benzylaminopurine and Thidiazuron at 1.0, 5.0, and 10.0 μM levels) with and without the addition of auxin (1-Naphthaleneacetic acid 0.1 μM) (inputs). Categorical data were encoded in numeric form using one-hot encoding technique. Backpropagation (BP) and Kalman filter (KF) learning algorithms were used to develop nonparametric models between inputs and outputs. Correlations between predicted and observed outputs (validation dataset) were similar in both ANN-BP (R values = 0.77, 0.71, 0.68, and 0.48), and ANN-KF (R values = 0.79, 0.68, 0.75, and 0.49), and were higher than regression (R values = 0.13, 0.48, 0.39, and 0.37) models for shoots and roots from leaf and node explants, respectively. Because ANN models have the ability to interpolate from unseen data, they could be used as an effective tool in accurately predicting the in vitro growth kinetics of Bacopa cultures.

Structural-Guided Identification of Small Molecule Inhibitor of UHRF1 Methyltransferase Activity

Ubiquitin-like containing plant homeodomain Ring Finger 1 (UHRF1) protein is recognized as a cell-cycle-regulated multidomain protein. UHRF1 importantly manifests the maintenance of DNA methylation mediated by the interaction between its SRA (SET and RING associated) domain and DNA methyltransferase-1 (DNMT1)-like epigenetic modulators. However, overexpression of UHRF1 epigenetically responds to the aberrant global methylation and promotes tumorigenesis. To date, no potential molecular inhibitor has been studied against the SRA domain. Therefore, this study focused on identifying the active natural drug-like candidates against the SRA domain. A comprehensive set of in silico approaches including molecular docking, molecular dynamics (MD) simulation, and toxicity analysis was performed to identify potential candidates. A dataset of 709 natural compounds was screened through molecular docking where chicoric acid and nystose have been found showing higher binding affinities to the SRA domain. The MD simulations also showed the protein ligand interaction stability of and in silico toxicity analysis has also showed chicoric acid as a safe and nontoxic drug. In addition, chicoric acid possessed a longer interaction time and higher LD50 of 5000 mg/kg. Moreover, the global methylation level (%5 mC) has been assessed after chicoric acid treatment was in the colorectal cancer cell line (HCT116) at different doses. The result showed that 7.5 µM chicoric acid treatment reduced methylation levels significantly. Thus, the study found chicoric acid can become a possible epidrug-like inhibitor against the SRA domain of UHRF1 protein.

From Traditional Ethnopharmacology to Modern Natural Drug Discovery: A Methodology Discussion and Specific Examples

Ethnopharmacology, through the description of the beneficial effects of plants, has provided an early framework for the therapeutic use of natural compounds. Natural products, either in their native form or after crude extraction of their active ingredients, have long been used by different populations and explored as invaluable sources for drug design. The transition from traditional ethnopharmacology to drug discovery has followed a straightforward path, assisted by the evolution of isolation and characterization methods, the increase in computational power, and the development of specific chemoinformatic methods. The deriving extensive exploitation of the natural product chemical space has led to the discovery of novel compounds with pharmaceutical properties, although this was not followed by an analogous increase in novel drugs. In this work, we discuss the evolution of ideas and methods, from traditional ethnopharmacology to in silico drug discovery, applied to natural products. We point out that, in the past, the starting point was the plant itself, identified by sustained ethnopharmacological research, with the active compound deriving after extensive analysis and testing. In contrast, in recent years, the active substance has been pinpointed by computational methods (in silico docking and molecular dynamics, network pharmacology), followed by the identification of the plant(s) containing the active ingredient, identified by existing or putative ethnopharmacological information. We further stress the potential pitfalls of recent in silico methods and discuss the absolute need for in vitro and in vivo validation as an absolute requirement. Finally, we present our contribution to natural products' drug discovery by discussing specific examples, applying the whole continuum of this rapidly evolving field. In detail, we report the isolation of novel antiviral compounds, based on natural products active against influenza and SARS-CoV-2 and novel substances active on a specific GPCR, OXER1.

Licania rigida leaf extract: Protective effect on oxidative stress, associated with cytotoxic, mutagenic and preclinical aspects

Brazilian plant biodiversity is a rich alternative source of bioactive compounds since plant-derived extracts and/or their secondary metabolites exhibit potential properties to treat several diseases. In this context, Licania rigida Benth (Chrysobalanaceae Family), a large evergreen tree distributed in Brazilian semi-arid regions, deserves attention for its widespread use in popular medicine, although its biological properties are still poorly studied. The aim of this study was to examine (1) acute and sub-chronic oral toxicity at 2000 mg/kg dose; (2) in vitro cytotoxicity at 0.1; 1; 10; 100 or 1000 µg/ml; (3) in vivo mutagenicity at 5, 10 or 20 mg/ml, and (4) potential antioxidant protective effect of L. rigida aqueous leaf extract of (AELr). No marked apparent toxic and genotoxic effects were observed using in vitro and in vivo assays after in vitro treatment of Chinese hamster ovary cell line (CHO-K1) with AELr or in vivo exposure of Wistar rats and Drosophila melanogaster to different extract concentrations. Concerning the antioxidant effect, the extract exhibited a protective effect by decreasing lipid peroxidation as determined by malondialdehyde levels. No significant changes were observed for glutathione (GSH) levels and activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx). Data demonstrate the beneficial potential of AELr to be employed for therapeutic purposes. However, further studies are required to validate the pharmacological application of this plant extract to develop as a phytotherapeutic formulation.

Computational Identification of Druggable Bioactive Compounds from Catharanthus roseus and Avicennia marina against Colorectal Cancer by Targeting Thymidylate Synthase

Colorectal cancer (CRC) is the second most common cause of death worldwide, affecting approximately 1.9 million individuals in 2020. Therapeutics of the disease are not yet available and discovering a novel anticancer drug candidate against the disease is an urgent need. Thymidylate synthase (TS) is an important enzyme and prime precursor for DNA biosynthesis that catalyzes the methylation of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP) that has emerged as a novel drug target against the disease. Elevated expression of TS in proliferating cells promotes oncogenesis as well as CRC. Therefore, this study aimed to identify potential natural anticancer agents that can inhibit the activity of the TS protein, subsequently blocking the progression of colorectal cancer. Initially, molecular docking was implied on 63 natural compounds identified from Catharanthus roseus and Avicennia marina to evaluate their binding affinity to the desired protein. Subsequently, molecular dynamics (MD) simulation, ADME (Absorption, Distribution, Metabolism, and Excretion), toxicity, and quantum chemical-based DFT (density-functional theory) approaches were applied to evaluate the efficacy of the selected compounds. Molecular docking analysis initially identified four compounds (PubChem CID: 5281349, CID: 102004710, CID: 11969465, CID: 198912) that have better binding affinity to the target protein. The ADME and toxicity properties indicated good pharmacokinetics (PK) and toxicity ability of the selected compounds. Additionally, the quantum chemical calculation of the selected molecules found low chemical reactivity indicating the bioactivity of the drug candidate. The global descriptor and HOMO-LUMO energy gap values indicated a satisfactory and remarkable profile of the selected molecules. Furthermore, MD simulations of the compounds identified better binding stability of the compounds to the desired protein. To sum up, the phytoconstituents from two plants showed better anticancer activity against TS protein that can be further developed as an anti-CRC drug.

Potential Anti-Mycobacterium tuberculosis Activity of Plant Secondary Metabolites: Insight with Molecular Docking Interactions

Tuberculosis (TB) is a recurrent and progressive disease, with high mortality rates worldwide. The drug-resistance phenomenon of Mycobacterium tuberculosis is a major obstruction of allelopathy treatment. An adverse side effect of allelopathic treatment is that it causes serious health complications. The search for suitable alternatives of conventional regimens is needed, i.e., by considering medicinal plant secondary metabolites to explore anti-TB drugs, targeting the action site of M. tuberculosis. Nowadays, plant-derived secondary metabolites are widely known for their beneficial uses, i.e., as antioxidants, antimicrobial agents, and in the treatment of a wide range of chronic human diseases (e.g., tuberculosis), and are known to “thwart” disease virulence. In this regard, in silico studies can reveal the inhibitory potential of plant-derived secondary metabolites against Mycobacterium at the very early stage of infection. Computational approaches based on different algorithms could play a significant role in screening plant metabolites against disease virulence of tuberculosis for drug designing.

Molecular modeling piloted analysis for semicarbazone derivative of curcumin as a potent Abl-kinase inhibitor targeting colon cancer

The human Abl kinases comprise a family of proteins that are known to be key stimulus drivers in the signaling pathways modulating cell growth, cell survival, cell adhesion, and apoptosis. Recent collative studies have indicated the role of activation of Abl and Abl-related genes in solid tumors; further terming the Abl kinases as molecular switches which promote proliferation, tumorigenesis, and metastasis. The up-regulated Abl-kinase expression in colorectal cancer (CRC) and the role of Abl tyrosine kinase activity in the Matrigel invasion of CRC cells have cemented its significance in CRC advancement. Therefore, the requisite of identifying small molecules which serve as Abl selective inhibitors and designing anti-Abl therapies, particularly for CRC tumors, has driven this study. Curcumin has been touted as an effective inhibitor of cancer cells; however, it is limited by its physicochemical inadequacies. Hence, we have studied the behavior of heterocyclic derivatives of curcumin via computational tools such as pharmacophore-based virtual screening, molecular docking, free-energy binding, and ADME profiling. The most actively docked molecule, 3,5-bis(4-hydroxy-3-methylstyryl)-1H-pyrazole-1-carboxamide, was comparatively evaluated against Curcumin via molecular dynamics simulation using Desmond, Schrödinger. The study exhibited the improved stability of the derivative as compared to Curcumin in the tested protein pocket and displayed the interaction bonds with the contacted key amino acids. To further establish the claim, the derivatives were synthesized via the mechanism of cyclization of Curcumin and screened in vitro using SRB assay against human CRC cell line, HCT 116. The active derivative indicated an IC₅₀ value of 5.85 µM, which was sevenfold lower as compared to Curcumin’s IC₅₀ of 35.40 µM. Hence, the results base the potential role of the curcumin derivative in modulating Abl-kinase activity and in turn may have potential therapeutic value as a lead for CRC therapy.