Current Topics in Medicinal Chemistry - Volume 23, Issue 29, 2023

Background: Nitric oxide is a free radical bioregulator controlling homeostasis, vasodilation, and inhibition of platelet aggregation, significantly implicated in the nervous and immune system functionality. In vivo it is produced by nitric oxide synthases (NOSs).Objective: Overproduction of nitric oxide is linked to several inflammatory, immunological, and neurodegenerative diseases and for that, various compounds have be Read More

Background: Quantitative Structure-Activity Relationship (QSAR) studies describing the correlations between biological activity as dependent parameters and physicochemical and structural descriptors, including topological indices (TIs) as independent parameters, play an important role in drug discovery research. The emergence of graph theory in exploring the structural attributes of the chemical space has led to the evol Read More

Quantitative Structure-activity Relationship (QSAR) studies gained a foothold in the mid-1960s to rationalise the biological activity of medicinally important compounds. Since then, the advancements in computer hardware and software added many new techniques and areas to this field of study. Molecular dynamics (MD) simulations are one such technique in direct drug design approaches. MD simulations have a special pla Read More

Multi-target drug development (MTDD) is the demand of the recent era, especially in the case of multi-factorial conditions such as cancer, depression, neurodegenerative diseases (NDs), etc. The MTDD approaches have many advantages; avoidance of drug-drug interactions, predictable pharmacokinetic profile, and less drug resistance. The wet lab practice in MTDD is very challenging for the researchers, and Read More

Quantitative structure - activity relationship (QSAR) modelling is widely used in medicinal chemistry and regulatory decision making. The large amounts of data collected in recent years in materials and life sciences projects provide a solid foundation for data-driven modelling approaches that have fostered the development of machine learning and artificial intelligence tools. An overview and discussion of the principles of Read More