Multitarget Compounds for Neglected Diseases: A Review.

Neglected diseases are a group of infectious diseases, many of them parasitic, that mainly affect the poorest populations with limited access to health services, especially those living in remote rural areas and slums. According to the World Health Organization (WHO), neglected diseases put the lives of more than 200 million people at risk, and treatment is made difficult by the occurrence of resistance to existing medications, as well as the high level of toxicity. In this way, the potential of multitarget compounds is highlighted, defined as compounds designed to modulate multiple targets of relevance to disease, with the overall goal of enhancing efficacy and/or improving safety. Thus, the objective of our study is to evaluate existing multi-target compound approaches for neglected diseases, with an emphasis on Leishmaniasis, Chagas Disease, and Arboviruses. A literature review was performed by searching the database "Web of Sciences". In relation to the diseases covered in this work, Leishmaniasis, individually, was the one that presented the largest number of articles (11) that dealt with the topic, which can be justi-fied by the high prevalence of this disease in the world, the second most common disease was Dengue, followed by Chagas disease, Chikungunya virus, and Zika virus. Furthermore, the multi-target potential of phenolic compounds was observed in all diseases under study, with the mecha-nisms related to the nucleus and transcription being the most reported mechanisms. From this per-spective, it is worth highlighting the effectiveness of approaches related to multitarget drugs in discovering new therapeutic agents for neglected diseases.

Computer Aided Drug Design Methodologies with Natural Products in the Drug Research Against Alzheimer's Disease.

Natural products are compounds isolated from plants that provide a variety of lead structures for the development of new drugs by the pharmaceutical industry. The interest in these substances increases because of their beneficial effects on human health. Alzheimer's disease (AD) affects occur in about 80% of individuals aged 65 years. AD, the most common cause of dementia in elderly people, is characterized by progressive neurodegenerative alterations, as decrease of cholinergic impulse, increased toxic effects caused by reactive oxygen species and the inflammatory process that the amyloid plaque participates. In silico studies is relevant in the process of drug discovery; through technological advances in the areas of structural characterization of molecules, computational science and molecular biology have contributed to the planning of new drugs used against neurodegenerative diseases. Considering the social impairment caused by an increased incidence of disease and that there is no chemotherapy treatment effective against AD; several compounds are studied. In the researches for effective neuroprotectants as potential treatments for Alzheimer's disease, natural products have been extensively studied in various AD models. This study aims to carry out a literature review with articles that address the in silico studies of natural products aimed at potential drugs against Alzheimer's disease (AD) in the period from 2015 to 2021.

Recent Studies on Neglected Drug Design.

BACKGROUND: Neglected diseases require special attention when looking for new therapeutic alternatives, as these are diseases of extreme complexity and severity that affect populations belonging to lower social classes who lack access to basic rights, such as sanitation. INTRODUCTION: Among the alternatives available for obtaining new drugs is Medicinal Chemistry, which is responsible for the discovery, identification, invention, and preparation of prototypes. In this perspective, the present work aims to make a bibliographic review on the recent studies of Medicinal Chemistry applied to neglected diseases. METHODS: A literature review was carried out by searching the "Web of Sciences" database, including recent articles published on the Neglected Drug Design. RESULTS: In general, it was noticed that the most studied neglected diseases corresponded to Chagas disease and leishmaniasis, with studies on organic synthesis, optimization of structures, and molecular hybrids being the most used strategies. It is also worth mentioning the growing number of computationally developed studies, providing speed and optimization of costs in the procurement process. CONCLUSION: The CADD approach and organic synthesis studies, when applied in the area of Medicinal Chemistry, have proven to be important in the research and discovery of drugs for Neglected Diseases, both in terms of planning the experimental methodology used to obtain it and in the selection of compounds with higher activity potential.

Machine Learning, Molecular Modeling, and QSAR Studies on Natural Products Against Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is a very common neurodegenerative disorder in individuals over 65 years of age; however, younger individuals can also be affected due to brain damage. INTRODUCTION: The general symptoms of this disease include progressive loss of memory, changes in behavior, deterioration of thinking, and gradual loss of ability to perform daily activities. According to the World Health Organization, dementia has affected more than 50 million people worldwide, and it is estimated that there are 10 million new cases per year, of which 70% are due to AD. METHODS: This paper reported a review of scientific articles available on the internet which discuss in silico analyzes such as molecular docking, molecular dynamics, and quantitative structure-activity relationship (QSAR) of different classes of natural products and their derivatives published from 2016 onwards. In addition, this work reports the potential of fermented papaya preparation against oxidative stress in AD. RESULTS: This research reviews the most recent studies on AD, computational analysis methods used in proposing new bioactive compounds and their possible molecular targets, and finally, the molecules or classes of natural products involved in each study. CONCLUSION: Thus, studies like this can orientate new research works on neurodegenerative diseases, especially AD.

Ligand and Structure-based Virtual Screening of Lamiaceae Diterpenes with Potential Activity against a Novel Coronavirus (2019-nCoV).

BACKGROUND: The emergence of a new coronavirus (CoV), named 2019-nCoV, as an outbreak originated in the city of Wuhan, China, has resulted in the death of more than 3,400 people this year alone and has caused worldwide an alarming situation, particularly following previous CoV epidemics, including the Severe Acute Respiratory Syndrome (SARS) in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012. Currently, no exists for infections caused by CoVs; however, some natural products may represent potential treatment resources, such as those that contain diterpenes. OBJECTIVE: This study aimed to use computational methods to perform a virtual screening (VS) of candidate diterpenes with the potential to act as CoV inhibitors. METHODS: 1,955 diterpenes, derived from the Nepetoideae subfamily (Lamiaceae), were selected using the SistematX tool (https://sistematx.ufpb.br), which were used to make predictions. From the ChEMBL database, 3 sets of chemical structures were selected for the construction of predictive models. RESULTS: The chemical structures of molecules with known activity against SARS CoV, two of which were tested for activity against specific viral proteins and one of which was tested for activity against the virus itself, were classified according to their pIC50 values [-log IC50 (mol/l)]. CONCLUSION: In the consensus analysis approach, combining both ligand- and structure-based VSs, 19 compounds were selected as potential CoV inhibitors, including isotanshinone IIA (01), tanshinlactone (02), isocryptotanshinone (03), and tanshinketolactone (04), which did not present toxicity within the evaluated parameters.