This reference summarizes information about pharmaceuticals that can target infectious strains of coronaviruses to neutralize infections. Chapters focus on SARS-CoV-2, drug discovery methods and ...natural methods to combat the virus, which is a causative agent of COVID-19. Specifically, the book presents 5 chapters written by expert scholar on the following topics: Structure-Based Drug Discovery Approaches Applied to SARS-CoV-2 (the causative agent COVID- 19)Potential Antiviral Medicinal Plants against Novel SARS-CoV-2Infections Caused by SARS Coronaviruses: Main Characteristics, Targets And Inhibitors Natural Sourced Traditional Indian and Chinese Medicines to Combat COVID- 19Peptidomimetic and Peptide-Derived Agents Against 3CLpro from Coronaviruses The book contents present both conventional drug design and traditional approaches to discovering relevant drugs in an easy-to-read approach, which is supplemented by bibliographic references. It is intended as a reference for students (pharmacology, pharmacy) and researchers (virology) who are seeking information about antiviral drugs that can be used against coronaviruses.
Secondary metabolites are plant products that occur usually in differentiated cells, generally not being necessary for the cells themselves, but likely useful for the plant as a whole. ...Neurodegeneration can be found in many different levels in the neurons, it always begins at the molecular level and progresses toward the systemic levels. Usually, alterations are observed such as decreasing cholinergic impulse, toxicity related to reactive oxygen species (ROS, inflammatory "amyloid plaque" related processes, catecholamine disequilibrium, etc. Computer aided drug design (CADD has become relevant in the drug discovery process; technological advances in the areas of molecular structure characterization, computational science, and molecular biology have contributed to the planning of new drugs against neurodegenerative diseases. This review discusses scientific CADD studies of the secondary metabolites. Flavonoids, alkaloids, and xanthone compounds have been studied by various researchers (as inhibitory ligands in molecular docking; mainly with three enzymes: acetylcholinesterase (AChE; EC 3.1.1.7, butyrylcholinesterase (BChE; EC 3.1.1.8, and monoamine oxidase (MAO; EC 1.4.3.4. In addition, we have applied ligand-based-virtual screening (using Random Forest, associated with structure-based- virtual screening (docking of a small dataset of 469 alkaloids of the Apocynaceae family from an in-house data bank to select structures with potential inhibitory activity against human AChE. This computer-aided drug design study selected certain alkaloids that might be useful in further studies for the treatment of neurological disorders such as Alzheimer's and Parkinson's disease.
MACHINE LEARNING APLLIED TO QSAR. Over the years the study of the quantitative structure-activity relationship (QSAR) has transformed from a simple regression analysis to the implementation of ...machine learning (ML) with multiple statistics. Today ML-based QSAR models are quite important and play a notable role in drug design and screening, property prediction, biological activity, etc. ML methods applied to QSAR build classification or regression models to describe/predict the complex relationships between the chemical structure of molecules and biological activity. Even with the increase in scientific publications addressing this topic written in Portuguese, there is still a shortage of scientific articles explaining ML techniques applied to QSAR, how to build models, the types of models, algorithms, for the Brazilian scientific community. And to fill this need, we intend to approach the subject in a simple and didactic way for students and researchers who are starting in this very promising and important area. We will describe the fully explained theory of machine learning by applying QSAR, abstracting the complexity, and well-illustrated.
