Current Drug Targets - Volume 22, Issue 6, 2021

Parkinson’s disease is one of the most common adult-onset, a chronic disorder involving neurodegeneration, which progressively leads to deprivation of dopaminergic neurons in substantia nigra, causing a subsequent reduction of dopamine levels in the striatum resulting in tremor, myotonia, and dyskinesia. Genetics and environmental factors are believed to be responsible for the onset of Parkinson’s disease. The exact pathogenesis of Parkinson's disease is quite complicated and the present anti-Parkinson's disease treatments appear to be clinically insufficient. Comprehensive researches have demonstrated the use of natural products such as ginseng, curcumin, ashwagandha, baicalein, etc. for the symptomatic treatment of this disease. The neuroprotective effects exhibited by these natural products are mainly due to their ability to increase dopamine levels in the striatum, manage oxidative stress, mitochondrial dysfunction, glutathione levels, clear the aggregation of α- synuclein, induce autophagy and decrease the pro-inflammatory cytokines and lipid peroxidation. This paper reviews various natural product studies conducted by scientists to establish the role of natural products (both metabolite extracts as well as pure metabolites) as adjunctive neuroprotective agents.

Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Machine Learning based tools, such as GOLD, Deep PVP, LIB SVM, etc. and the algorithms involved such as support vector machine (SVM), random forest (RF), decision tree and Artificial Neural Network (ANN), etc. at various stages of drug designing and development. These techniques can be employed in SNP discoveries, drug repurposing, ligand-based drug design (LBDD), Ligand-based Virtual Screening (LBVS) and Structure- based Virtual Screening (SBVS), Lead identification, quantitative structure-activity relationship (QSAR) modeling, and ADMET analysis. It is demonstrated that SVM exhibited better performance in indicating that the classification model will have great applications on human intestinal absorption (HIA) predictions. Successful cases have been reported which demonstrate the efficiency of SVM and RF models in identifying JFD00950 as a novel compound targeting against a colon cancer cell line, DLD-1, by inhibition of FEN1 cytotoxic and cleavage activity. Furthermore, a QSAR model was also used to predict flavonoid inhibitory effects on AR activity as a potent treatment for diabetes mellitus (DM), using ANN. Hence, in the era of big data, ML approaches have been evolved as a powerful and efficient way to deal with the huge amounts of generated data from modern drug discovery to model small-molecule drugs, gene biomarkers and identifying the novel drug targets for various diseases.

Pain is an unpleasant sensation that has complex and varying causative etiology. Modern drug discovery focuses on identifying potential molecules that target multiple pathways with a safer profile compared to those with a single target. The current treatment of pain and inflammation with the available therapeutics has a number of major side effects. Pain is one of the major clinical problems that need functional therapeutics which act on multiple targets and with low toxicity. Curcumin, a naturally occurring polyphenolic compound from Curcuma longa, has been used for years in Ayurvedic, Chinese, and in many other systems of traditional medicine. Pre-clinical data published thus far demonstrated that curcumin possesses multi-target biological functions, suggesting its potential use to cure different diseases. However, there is no or very brief systematic review of its potential use in pain and inflammation with underlying mechanisms for such activities. Accordingly, the aim of the current review was to update the pre-clinical data of curcumin and its multiple targeting pathways for analgesic and anti-inflammatory effects, and to further propose a molecular mechanism(s). A literature study was conducted using different known databases, including Pubmed, SciFinder, Google Scholar, and Science Direct. Available pre-clinical data suggest the ameliorating effect of curcumin in pain and inflammation is rendered through the modulation of pain pathways, including inhibition of a number of pro-inflammatory mediators, inhibition of oxidative stress and cyclooxygenase-2 (COX-2), down-regulation of Ca2+/calmodulin-depend protein kinase II (CaMKIIα) and calcium channels like transient receptor potential (TRP), modulation of metabotropic glutamate receptor-2 (mGlu2), modulation of monoamine system, inhibition of JAK2/STAT3 signaling pathway, remodeling of extracellular matrix proteins, inhibition of apoptosis, inhibition of JNK/MAPK and ERK/CREB signaling pathway, and activation of the opioid system. Taken all together, it is evident that curcumin is one of the promising, safe, and natural polyphenolic molecules that target multiple molecular pathways in pain and can be beneficial in the treatment and management of pain and inflammation.

Lack of adequate sleep is a major source of many harmful diseases related to heart, brain, psychological changes, high blood pressure, diabetes, weight gain, etc. 40 to 50% of the world’s population is suffering from poor or inadequate sleep. Insomnia is a sleep disorder in which an individual complaint of difficulties in starting/continuing sleep at least four weeks regularly. It is estimated that 70% of heart diseases are generated during insomnia sleep disorder. The main objective of this study is to determine all work conducted on insomnia detection and to make a database. We used two procedures including network visualization techniques on two databases including PubMed and Web of Science to complete this study. We found 169 and 36 previous publications of insomnia detection in the PubMed and the Web of Science databases, respectively. We analyzed 10 datasets, 2 databases, 21 genes, and 23 publications with 30105 subjects of insomnia detection. This work has revealed the future way and gap so far directed on insomnia detection and has also tried to provide objectives for the future work to be proficient in a scientific and significant manner.

Alzheimer’s disease is a common and most chronic neurological disorder (NDs) associated with cognitive dysfunction. Pathologically, Alzheimer’s disease (AD) is characterized by the presence of β-amyloid (Aβ) plaques, hyper-phosphorylated tau proteins, and neurofibrillary tangles, however, persistence oxidative-nitrative stress, endoplasmic reticulum stress, mitochondrial dysfunction, inflammatory cytokines, pro-apoptotic proteins along with altered neurotransmitters level are common etiological attributes in its pathogenesis. Rivastigmine, memantine, galantamine, and donepezil are FDA approved drugs for symptomatic management of AD, whereas tacrine has been withdrawn because of hepatotoxic profile. These approved drugs only exert symptomatic relief and exhibit poor patient compliance. In the current scenario, the number of published evidence shows the neuroprotective potential of naturally occurring bioactive molecules via their antioxidant, anti-inflammatory, antiapoptotic and neurotransmitter modulatory properties. Despite their potent therapeutic implications, concerns have arisen in context to their efficacy and probable clinical outcome. Thus, to overcome these glitches, many heterocyclic and cyclic hydrocarbon compounds inspired by natural sources have been synthesized and showed improved therapeutic activity. Computational studies (molecular docking) have been used to predict the binding affinity of these natural bioactive as well as synthetic compounds derived from natural sources for the acetylcholine esterase, α/β secretase Nuclear Factor kappa- light-chain-enhancer of activated B cells (NF-kB), Nuclear factor erythroid 2-related factor 2(Nrf2) and other neurological targets. Thus, in this review, we have discussed the molecular etiology of AD, focused on the pharmacotherapeutics of natural products, chemical and pharmacological aspects and multi-targeted designed ligands (MTDLs) of synthetic and semisynthetic molecules derived from the natural sources along with some important on-going clinical trials.