Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance.

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

Natural therapeutics and nutraceuticals for lung diseases: Traditional significance, phytochemistry, and pharmacology.

BACKGROUND: Lung diseases including chronic obstructive pulmonary disease (COPD), infections like influenza, acute respiratory distress syndrome (ARDS), asthma and pneumonia lung cancer (LC) are common causes of sickness and death worldwide due to their remoteness, cold and harsh climatic conditions, and inaccessible health care facilities. PURPOSE: Many drugs have already been proposed for the treatment of lung diseases. Few of them are in clinical trials and have the potential to cure infectious diseases. Plant extracts or herbal products have been extensively used as Traditional Chinese Medicine (TCM) and Indian Ayurveda. Moreover, it has been involved in the inhibition of certain genes/protiens effects to promote regulation of signaling pathways. Natural remedies have been scientifically proven with remarkable bioactivities and are considered a cheap and safe source for lung disease. METHODS: This comprehensive review highlighted the literature about traditional plants and their metabolites with their applications for the treatment of lung diseases through experimental models in humans. Natural drugs information and mode of mechanism have been studied through the literature retrieved by Google Scholar, ScienceDirect, SciFinder, Scopus and Medline PubMed resources against lung diseases. RESULTS: In vitro, in vivo and computational studies have been explained for natural metabolites derived from plants (like flavonoids, alkaloids, and terpenoids) against different types of lung diseases. Probiotics have also been biologically active therapeutics against cancer, anti-inflammation, antiplatelet, antiviral, and antioxidants associated with lung diseases. CONCLUSION: The results of the mentioned natural metabolites repurposed for different lung diseases especially for SARS-CoV-2 should be evaluated more by advance computational applications, experimental models in the biological system, also need to be validated by clinical trials so that we may be able to retrieve potential drugs for most challenging lung diseases especially SARS-CoV-2.

Role of Phenolic Compounds in Human Disease: Current Knowledge and Future Prospects.

Inflammation is a natural protective mechanism that occurs when the body's tissue homeostatic mechanisms are disrupted by biotic, physical, or chemical agents. The immune response generates pro-inflammatory mediators, but excessive output, such as chronic inflammation, contributes to many persistent diseases. Some phenolic compounds work in tandem with nonsteroidal anti-inflammatory drugs (NSAIDs) to inhibit pro-inflammatory mediators' activity or gene expression, including cyclooxygenase (COX). Various phenolic compounds can also act on transcription factors, such as nuclear factor-κB (NF-κB) or nuclear factor-erythroid factor 2-related factor 2 (Nrf-2), to up-or downregulate elements within the antioxidant response pathways. Phenolic compounds can inhibit enzymes associated with the development of human diseases and have been used to treat various common human ailments, including hypertension, metabolic problems, incendiary infections, and neurodegenerative diseases. The inhibition of the angiotensin-converting enzyme (ACE) by phenolic compounds has been used to treat hypertension. The inhibition of carbohydrate hydrolyzing enzyme represents a type 2 diabetes mellitus therapy, and cholinesterase inhibition has been applied to treat Alzheimer's disease (AD). Phenolic compounds have also demonstrated anti-inflammatory properties to treat skin diseases, rheumatoid arthritis, and inflammatory bowel disease. Plant extracts and phenolic compounds exert protective effects against oxidative stress and inflammation caused by airborne particulate matter, in addition to a range of anti-inflammatory, anticancer, anti-aging, antibacterial, and antiviral activities. Dietary polyphenols have been used to prevent and treat allergy-related diseases. The chemical and biological contributions of phenolic compounds to cardiovascular disease have also been described. This review summarizes the recent progress delineating the multifunctional roles of phenolic compounds, including their anti-inflammatory properties and the molecular pathways through which they exert anti-inflammatory effects on metabolic disorders. This study also discusses current issues and potential prospects for the therapeutic application of phenolic compounds to various human diseases.