Recent global outbreak of the pandemic caused by coronavirus (COVID-19) emphasizes the urgent need for novel antiviral therapeutics. It can be supplemented by utilization of efficient and validated ...drug discovery approaches such as drug repurposing/repositioning. The well reported and clinically used anti-malarial aminoquinoline drugs (chloroquine and hydroxychloroquine) have shown potential to be repurposed to control the present pandemic by inhibition of COVID-19. The review elaborates the mechanism of action, safety (side effects, adverse effects, toxicity) and details of clinical trials for chloroquine and hydroxychloroquine to benefit the clinicians, medicinal chemist, pharmacologist actively involved in controlling the pandemic and to provide therapeutics for the treatment of COVID-19 infection.
We combine quantum chemical and molecular docking techniques to provide new insights into how piperine molecule in various forms of pepper enhances bioavailability of a number of drugs including ...curcumin in turmeric for which it increases its bioavailability by a 20-fold. We have carried out docking studies of quantum chemically optimized piperine structure binding to curcumin, CYP3A4 in cytochrome P450, p-Glycoprotein and UDP-glucuronosyltransferase (UGT), the enzyme responsible for glucuronosylation, which increases the solubility of curcumin. All of these studies establish that piperine binds to multiple sites on the enzymes and also intercalates with curcumin forming a hydrogen bonded complex with curcumin. The conjugated network of double bonds and the presence of multiple charge centers of piperine offer optimal binding sites for piperine to bind to enzymes such as UDP-GDH, UGT, and CYP3A4. Piperine competes for curcumin's intermolecular hydrogen bonding and its stacking propensity by hydrogen bonding with enolic proton of curcumin. This facilitates its metabolic transport, thereby increasing its bioavailability both through intercalation into curcumin layers through intermolecular hydrogen bonding, and by inhibiting enzymes that cause glucuronosylation of curcumin.
In the design and discovery of anticancer drugs, various natural heterocyclic scaffolds have attracted considerable interest as privileged structures. For rational drug design, some of the natural ...scaffolds such as chromones have exhibited wide acceptability due to their drug‐like properties. Among the approved anticancer drugs, the scaffolds with high selectivity for a small group of closely related targets are of importance. In the development of selective anticancer agents, the natural, as well as synthetic, can generate highly selective compounds toward cancer targets. The present manuscript includes more particularly the development of cancer inhibitors incorporating the chromone scaffold, with a strong emphasis on their molecular interactions in the anticancer mechanism. It also includes the structure‐activity relationship studies and related examples of lead optimization.
In the design and discovery of anticancer drugs, various natural heterocyclic scaffolds have attracted considerable interest as privileged structures. In the development of selective anticancer agents, the natural, as well as synthetic chromones, can be utilized to generate highly selective compounds towards cancer targets.
Pexidartinib is an orally active small molecule inhibitor of tyrosine kinase. It is selective towards the colony-stimulating factor 1 receptor (CSF1R) and has been approved by FDA for the clinical ...use in tenosynovial giant cell tumor (TGCT). CSF1R is over expressed in various types of solid tumors and facilitates monocyte differentiation and survival of tumor-associated macrophages. TGCT is rare and has over expressed CSF1. Based on the phase III clinical reports, pexidartinib has been approved. To make the treatment economical and for patients’ safety, studies are ongoing to improve synthetic efficiency as well as to reduce associated toxicity. Based on the reported preclinical data, clinical studies are ongoing for various other types of solid tumors. Studies focusing on the use of pexidartinib, a CSF1R inhibitor as potential anticancer therapeutics against different types of solid tumor will play a significant role in the discovery of anticancer agents as well as for the management of other disease conditions.
•Mutation informatics study on RBD of SARS-CoV-2 variants.•Discussion of small molecules targeting the RBD/ACE2 interface.•Ideation to design novel inhibitors against wild and mutant strains.
Severe ...acute respiratory syndrome coronavirus 2 (SARS-CoV-2) undergoes mutations at a high rate and with frequent genetic reassortment (antigenic drift/shift), leading to variability in targets. The receptor-binding domain (RBD) of the spike (S) protein has a major role in the binding of SARS-CoV-2 with human angiotensin-converting enzyme 2 (ACE2). Mutations at the RBD influence the binding interaction at the SARS-CoV-2 S–ACE2 interface and impact viral pathogenicity. Here, we discuss different reported mutations of concern in RBD, physicochemical characteristic changes resulting from mutated amino acids and their effect on binding between the RBD and ACE2. Along with mutation informatics, we highlight recently developed small-molecule inhibitors of RBD and the ACE2 interface. This information provides a rational basis for the design of inhibitors against the multivariant strains of SARS-CoV-2.
Throughout the ages, compounds collected and/or isolated from natural sources have been the basic source of medicinal agents against a variety of diseases. The data generated from the extensive ...experimentation conducted in research labs from all over the world has diversity and complexity, and the challenging task for database creators is to store, represent, and exchange this data. The natural product database is required to be easily accessible for supporting drug discovery efforts. A possible solution for this is provided by chemical databases based on bio- and chem-informatic approaches. Some of the anti-cancer natural product databases, along with the tools required for creating and accessing the information, are discussed here.
This study aimed at studying various types of gynecological cancers and the available therapeutics to investigate safe and effective drugs.
Cancer is the most common cause of mortality throughout the ...world. When the statistics are being considered for gynecological cancers, ovarian, cervical, and uterine cancers are among the most prevalent types. They have the worst prognosis and the highest mortality rate and by the year 2040 significant increase in mortality rate is predicted.
The major limitation with the development of anti-cancer therapeutics for gynecological cancers is the safety of the therapeutics for the developing fetus as well as the mother. Various medicinal classes of natural to synthetic therapeutics have been reported including kinase inhibitors as the most promising category of anti-cancer drugs.
A dataset of kinase inhibitors clinically approved as anticancer agents was derived through a literature review. A QSAR based approach i.e. VEGAQSAR has been applied to evaluate the reproductive and developmental toxicity for the selected class of kinase inhibitors.
In the present work, the promising category of anticancer kinase inhibitors has been investigated for its toxicity potential with the help of in silico approach. The anti-cancer kinase inhibitors were categorized based on the found non-toxic or toxic properties towards reproductive and developmental toxicity.
Early prediction of the available or proposed anti-cancer therapeutics for their contribution towards developmental and reproductive toxicity is an important criterion for their use in pregnancy-associated cancers. The investigation of the toxicity profile of available anti-cancer kinase therapeutics will be helpful to design and develop novel and safe anti-cancer drugs in the near future. The study outcomes will benefit the current anticancer drug development efforts.
Alzheimer's disease (AD) is one of the neurodegenerative diseases and has been hypothesized to be a protein misfolding disease. In the generation of AD, β-secretase, γ-secretase, and tau protein play ...an important role. A literature search reflects ever increasing interest in the design and development of anti-AD drugs targeting β-secretase, γ-secretase, and tau protein.
The objective is to explore the structural aspects and role of β-secretase, γ-secretase, and tau protein in AD and the efforts made to exploit them for the design of effective anti-AD drugs.
The manuscript covers the recent studies on design and development of anti-AD drugs exploiting amyloid and cholinergic hypotheses.
Based on amyloid and cholinergic hypotheses, effective anti-AD drugs have been searched out in which non-peptidic BACE1 inhibitors have been most prominent.
Further exploitation of the structural aspects and the inhibition mechanism for β-secretase, γ-secretase, and tau protein and the use of cholinergic hypothesis may lead still more potent anti-AD drugs.
CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs ...is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer’s and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.
Graphical abstract
PDF
