In recent years, tools for the development of new drugs have been dramatically improved. These include genomic and proteomic research, numerous biophysical methods, combinatorial chemistry and screening technologies. In addition, early ADMET studies are employed in order to significantly reduce the failure rate in the development of drug candidates. As a consequence, the lead finding, lead optimization and development process has gained marked enhancement in speed and efficiency. In parallel to this development, major pharma companies are increasingly outsourcing many components of drug discovery research to biotech companies. All these measures are designed to address the need for a faster time to market. New screening methodologies have contributed significantly to the efficiency of the drug discovery process. The conventional screening of single compounds or compound libraries has been dramatically accelerated by high throughput screening methods. In addition, in silico screening methods allow the evaluation of virtual compounds. A wide range of new lead finding and lead optimization opportunities result from novel screening methods by NMR, which are the topic of this review article.

Drug Discovery Today

This study aims to identify and isolate the secondary metabolites of Zingiber officinale using GC-MS, preparative TLC, and LC-MS/MS methods, to evaluate the inhibitory potency on SARS-CoV-2 3 chymotrypsin-like protease enzyme, as well as to study the molecular interaction and stability by using docking and molecular dynamics simulations. GC-MS analysis suggested for the isolation of terpenoids compounds as major compounds on methanol extract of pseudostems and rhizomes. Isolation and LC-MS/MS analysis identified 5-hydro-7, 8, 2′-trimethoxyflavanone (9), (E)-hexadecyl-ferulate (1), isocyperol (2), N-isobutyl-(2E,4E)-octadecadienamide (3), and nootkatone (4) from the rhizome extract, as well as from the leaves extract with the absence of 9. Three known steroid compounds, i.e., spinasterone (7), spinasterol (8), and 24-methylcholesta-7-en-3β-on (6), were further identified from the pseudostem extract. Molecular docking showed that steroids compounds 7, 8, and 6 have lower predictive binding energies (MMGBSA) than other metabolites with binding energy of −87.91, −78.11, and −68.80 kcal/mole, respectively. Further characterization on the single isolated compound by NMR showed that 6 was identified and possessed 75% inhibitory activity on SARS-CoV-2 3CL protease enzyme that was slightly different with the positive control GC376 (77%). MD simulations showed the complex stability with compound 6 during 100 ns simulation time.

GC-MS, LC-MS/MS, Docking and Molecular Dynamics Approaches to Identify Potential SARS-CoV-2 3-Chymotrypsin-Like Protease Inhibitors from Zingiber officinale Roscoe.

Chronic dietary ingestion of suitable phytochemicals may assist with limiting or negating neurodegenerative decline. Current therapeutics used to treat Alzheimer disease elicit broad adverse drug reactions, and alternative sources of cholinesterase inhibitors (ChEIs) are required. Herein, we screened methanolic extracts from seven commonly cultivated plants for their nutraceutical potential; ability to inhibit acetylcholinesterase (AChE) and butyryl-cholinesterase (BuChE), and provision of antioxidant activity through their 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical scavenging capabilities. Potential neurotoxicity of plant extracts was examined via application to SHSY-5Y neuroblastoma cells and quantitation of cell viability. Methanolic extracts of Citrus limon (Lemon), Bombax ceiba (Red silk-cotton), Lawsonia inermis (Henna), Eucalyptus globulus (Eucalyptus), Ocimum basilicum (Basil), Citrus reticulata (Mandarin orange), and Mentha spicata (Spearmint) all displayed concentration-dependent inhibition of AChE and BuChE. The majority of extracts inhibited AChE and BuChE to near equipotency, with Henna and Eucalyptus extracts the two most potent ChEIs. All plant extracts were able to scavenge free radicals in a concentration-dependent manner, with Eucalyptus the most potent antioxidant. Toxicity of plant extracts to neuronal cells was concentration dependent, with Eucalyptus also the most toxic extract. Fractionation of plant extracts and analysis by mass spectrometry identified a number of plant polyphenols that might have contributed to the cholinesterase inhibition: 3-caffeoylquinic acid, methyl 4-caffeoylquinate, kaempferol-acetyl-glycoside, quercetin 3-rutinoside, quercetin-acetyl-glycoside, kaempferol 3-O-glucoside, and quercetin 3-O-glucoside. In silico molecular modeling of these polyphenols demonstrated their improved AChE and BuChE binding affinities compared to the current FDA-approved dual ChEI, galantamine. Collectively, all the plant extracts contained nutraceutical agents as antioxidants and ChEIs and, therefore, their chronic consumption may prove beneficial to combat the pathological deficits that accrue in Alzheimer disease.

/pdf/potential-nutraceutical-properties-of-leaves-from-several-1a2w01tn1e.pdf

Potential Nutraceutical Properties of Leaves from Several Commonly Cultivated Plants

In the quest to effectively diagnose and treat the diseases that afflict mankind, the development of a tool capable of simultaneous detection and treatment would provide a significant cornerstone for the survival and control of these diseases. Theranostics denotes a portmanteau of therapeutics and diagnostics which simultaneously detect and treat ailments. Research advances have initiated the advent of theranostics in modern medicine. Overall, theranostics are drug delivery systems with molecular or targeted imaging agents integrated into their structure. The application of theranostics is rising exponentially due to the urgent need for treatments that can be utilized for diagnostic imaging as an aid in precision and personalised medicine. Subsequently, the emergence of nanobiotechnology and the green synthesis of metallic nanoparticles (MNPs) has provided one such avenue for nanoscale development and research. Of interest is the drastic rise in the use of medicinal plants in the synthesis of MNPs which have been reported to be potentially effective in the diagnosis and treatment of diseases. At present, medicinal plant-derived MNPs have been cited to have broad pharmacological applications and have been studied for their potential use in the treatment and management of cancer, malaria, microbial and cardiovascular diseases. The subject of this article regards the role of medicinal plants in the synthesis of MNPs and the potential role of MNPs in the field of theranostics.

/pdf/the-use-of-medicinal-plant-derived-metallic-nanoparticles-in-20f24imz.pdf

The Use of Medicinal Plant-Derived Metallic Nanoparticles in Theranostics

Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was time consuming and expensive. Computational methods such as Molecular Docking, Molecular Dynamic Simulation and Artificial intelligence are significant Insilico tools in medicinal plant research. Molecular docking approach exploits the mechanism of potential phytochemicals into the target active site to elucidate its interactions and biological therapeutic properties. MD simulation illuminates the dynamic behavior of biomolecules at atomic level with fine quality representation of biomolecules. Dramatical advancement in computer science is illustrating the biological mechanism via these tools in different diseases treatment. The advancement comprises speed, the system configuration, and other software upgradation to insights into the structural explanation and optimization of biomolecules. A probable shift from simulation to artificial intelligence has in fact accelerated the art of scientific study to a sky high. The most upgraded algorithm in artificial intelligence such as Artificial Neural Networks, Deep Neural Networks, Neuro-fuzzy Logic has provided a wide opportunity in easing the time required in classical experimental strategy. The notable progress in computer science technology has paved a pathway for understanding the pharmacological functions and creating a roadmap for drug design and development and other achievement in the field of medicinal plants research. This review focus on the development and overview in computational research moving from static molecular docking method to a range of dynamic simulation and an advanced artificial intelligence such as machine learning.

Treasuring the computational approach in medicinal plant research.

The discovery of medicinal plants is crucial for drug development. Eucalyptus globulus leaves are used as a traditional medicine in many areas of world due to herbicidal and insecticidal activity. While natural products are difficult to be separated and activity assayed, a new approach is needed to predict the active ingredients therein. In this study, a new method for screening active compounds extracted from E. globulus leaves was developed by GC-MS/MS and UPLC-MS/MS combined with molecular docking technology. Predicted compounds with high activity were proposed. Firstly, 35 volatile compounds and 34 aqueous extracted compounds were extracted from E. globulus leaves, and identified by GC-MS/MS and UPLC-MS/MS. The herbicidal receptor (1BX9) was then docked with the identified compounds by docking software, evaluated by docking models and seven scoring functions. The results showed that gallic acid had a strong inhibitory activity of 1BX9, which was speculated to be the main reason for the inhibitory effect of E. globulus leaves. Finally, allelopathic tests of gallic acid, citric acid, and isopulegol were carried out on grass seeds to verify its inhibitory activity against herbicide receptor 1BX9. The results show that the method can screen compounds with specific activity from a complex system of medicinal plants, which is very important for the screening of new active ingredients, confirmation of new medicinal ingredients, and the in-depth development of animal and plant medicines.

A Strategy Based on GC-MS/MS, UPLC-MS/MS and Virtual Molecular Docking for Analysis and Prediction of Bioactive Compounds in Eucalyptus Globulus Leaves.

Prediction and confirmation of active ingredients in Eucalyptus globulus Labill leaves

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A Strategy Based on GC-MS/MS, UPLC-MS/MS and Virtual Molecular Docking for Analysis and Prediction of Bioactive Compounds in Eucalyptus Globulus Leaves.

Prediction and confirmation of active ingredients in Eucalyptus globulus Labill leaves