Current Pharmaceutical Design - Volume 28, Issue 33, 2022

Due to the heap of data sets available for drug discovery, modern drug discovery has taken the shape of big data. Usage of Artificial intelligence (AI) can help to modify drug discovery based on big data to precised, knowledgeable data. The pharmaceutical companies have already geared their departments for this and started a race to search for new novel drugs. The AI helps to predict the molecular structure of the compound and its in-vivo vs. in-vitro characteristics without hampering life, thus saving time and economic loss. Clinical studies, electronic records, and images act as a helping hand for the development. The data mining and curation techniques help explore the data with a single click. AI in big data analysis has paved the red carpet for future rational drug development and optimization. This review's objective is to familiarise readers with various advances in the AI field concerning software, firms, and other tools working in easing out the labor of the drug discovery journey.

Background: Cancer is a leading risk of death globally. According to the World Health Organization, it is presently the second most important disease that causes death in both developing and developed countries. Remarkable progress has been made in the war against cancer with the development of numerous novel chemotherapy agents. However, it remains an immense challenge to discover new efficient therapeutic potential candidates to combat cancer. Objectives: The majority of the currently used anticancer drugs are of natural origins, such as curcumin, colchicine, vinca alkaloid, paclitaxel, bergenin, taxols, and combretastatin. Concerning this, this review article presents the structure of the most potent molecules along with IC50 values, structure-activity relationships, mechanistic studies, docking studies, in silico studies of phytomolecules, and important key findings on human cancer cell lines. Methods: A viewpoint of drug design and development of antiproliferative agents from natural phytomolecules has been established by searching peer-reviewed literature from Google Scholar, PubMed, Scopus, Springer, Science Direct, and Web of Science over the past few years. Results: Our analysis revealed that this article would assist chemical biologists and medicinal chemists in industry and academia in gaining insights into the anticancer potential of phytomolecules. Conclusion: In vitro and in silico studies present phytomolecules, such as curcumin, colchicine, vinca alkaloids, colchicine, bergenin, combretastatin, and taxol encompassing anticancer agents, offerings abundant sanguinity and capacity in the arena of drug discovery to inspire the investigators towards the continual investigations on these phytomolecules. It is extremely expected that efforts in this track will strengthen and grant some budding cancer therapeutics candidates in the near future.

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disorder worldwide. The symptoms of PD are characterized not only by motor alterations but also by a spectrum of nonmotor symptoms. Some of these are psychiatric manifestations such as sleep disorders; depression; cognitive difficulties that can evolve into dementia; and symptoms of psychosis, which include hallucinations, illusions, and delusions. Parkinson’s disease psychosis (PDP) occurs in 18-50% of patients with PD. Treating PDP is challenging because antipsychotic drugs tend to be inefficient or may even worsen the disease's motor symptoms. Objective: This review aims to summarize the current understanding of the molecular mechanisms involved in PDP and recent innovative alternatives for its treatment. Methods: This is a narrative review in which an extensive literature search was performed on the Scopus, EMBASE, PubMed, ISI Web of Science, and Google Scholar databases from inception to August 2021. The terms “Parkinson’s disease psychosis”, “Parkinson psychosis,” “neurodegenerative psychosis”, and “dopamine psychosis” were among the keywords used in the search. Results: Recently, views on the etiology of hallucinations and illusions have evolved remarkably. PDP has been cemented as a multifactorial entity dependent on extrinsic and novel intrinsic mechanisms, including genetic factors, neurostructural alterations, functional disruptions, visual processing disturbances, and sleep disorders. Consequently, innovative pharmacological and biological treatments have been proposed. Pimavanserin, a selective 5-HT2A inverse agonist, stands out after its approval to treat PDP-associated hallucinations and illusions. Conclusion: Future results from upcoming clinical trials should further characterize the role of this drug in the management of PDP as well as other treatment options with novel mechanisms of action, such as saracatinib, SEP-363856, cannabidiol, electroconvulsive therapy, and transcranial magnetic stimulation.

Drug delivery to central nervous system (CNS) diseases is one of the most challenging tasks. The innate blood-brain barrier (BBB) and the blood-cerebrospinal fluid (BCSF) barrier create an obstacle to effective systemic drug delivery to the CNS, by limiting the access of drugs to the brain. Nanotechnology-based drug delivery platform offers a potential therapeutic approach for the treatment of neurological disorders. Several studies have shown that nanomaterials have great potential to be used for the treatment of CNS diseases. The nanocarriers have simplified the targeted delivery of therapeutics into the brain by surpassing the BBB and actively inhibiting the disease progression of CNS disorders. The review is an overview of the recent developments in nanotechnology-based drug delivery approaches for major CNS diseases like Alzheimer's disease, Parkinson's disease, ischemic stroke, and Glioblastoma. This review discusses the disease biology of major CNS disorders describing various nanotechnology-based approaches to overcome the challenges associated with CNS drug delivery, focussing on nanocarriers in preclinical and clinical studies for the same. The review also sheds light on the challenges during clinical translation of nanomedicine from bench to bedside. Conventional therapeutic agents used for the treatment of CNS disorders are inadequate due to their inability to cross BBB or BCSF, higher efflux from BBB, related toxicity, and poor pharmacokinetics. The amalgamation of nanotechnology with conventional therapeutic agents can greatly ameliorate the pharmacokinetic problems and at the same time assist in efficient delivery to the CNS.

Background: Epigallocatechin gallate (EGCG) is the main component of rhubarb tannin, with antioxidant, anti-angiogenic, anti-cancer and antiviral activities. Diabetes mellitus (DM) is a high blood sugar and protein metabolism disorder syndrome, which is caused by absolute or relative factors, such as deficiency of insulin and oxidative stress. Diabetes cardiomyopathy (DCM) is one of the most frequent complications of DM. Objective: This study aims to explore whether EGCG can improve diabetic complication, myocardial fibrosis, in diabetic rats with an intraperitoneal injection of streptozotocin (STZ) through the transforming growth factor β1 (TGF-β1)/C-Jun N -terminal kinase (JNK) signaling pathway. Methods: 50 male SD rats were randomly divided into five groups, including the control group, model group, and EGCG drug groups (10 mg/kg, 20 mg/kg, 40 mg/kg), with 10 rats in each group. Rats, except for the control group, were intraperitoneally injected with STZ (65 mg/kg) to induce the diabetic rats model. EGCG drug groups were given distilled water according to the dose, while the control group and model group were given the same volume of distilled water for 12 weeks. The levels of glucose (GLU), triglyceride (TG), cholesterol (CHO), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) in serum were detected by ELISA of all rats. Myocardial function was observed by HE, Masson staining and Sirius red staining in DCM rats. Immunohistochemistry was used to detect the expression of Collagen I (COL-I) and Collagen III (COL-III), and detect the degree of myocardial fibrosis of DM rats. Western blot was used to detect the expression of matrix metalloproteinases (MMPs), tissue inhibitor of matrix metalloproteinase (TIMPs), TGF-β1, JNK and p-JNK in the myocardium. Results: Compared to the model group, the levels of GLU, TG, CHO, and LDL in serum were decreased while the level of HDL in serum was increased in EGCG groups rats; cardiac index and left ventricular mass index were decreased while heart function was improved in EGCG groups rats; the expressions of the COL-I and COL-III were decreased in EGCG groups, and the high dose group was the best; the expressions of TGF-β1, JNK, p-JNK, and TIMP-1 were down-regulated, and the expression of MMP-9 was up-regulated in EGCG groups. Conclusion: The results demonstrated that EGCG could improve STZ-induced diabetic complication, i.e., myocardial fibrosis, in diabetic rats, and protect their heart through TGF-β1/JNK signaling pathway.