Search

Cardiovascular diseases (CVDs) comprise a group of diseases and disorders of the heart and blood vessels, which together are the number one cause of death worldwide, being associated with multiple genetic and modifiable risk factors, and that may directly arise from different etiologies. For a long time, the search for cardiovascular drugs was based on the old paradigm "one compound - one target", aiming to obtain a highly potent and selective molecule with only one desired molecular target. Although historically successful in the last decades, this approach ignores the multiple causes and the multifactorial nature of CVDs. Thus, over time, treatment strategies for cardiovascular diseases have changed, and, currently, pharmacological therapies for CVD are mainly based on the association of two or more drugs to control symptoms and reduce cardiovascular death. In this context, the development of multitarget drugs, i.e., compounds having the ability to act simultaneously at multiple sites, is an attractive and relevant strategy that can be even more advantageous to achieve predictable pharmacokinetic and pharmacodynamics correlations as well as better patient compliance. In this review, we aim to highlight the efforts and rational pharmacological bases for the design of some promising multitargeted compounds to treat important cardiovascular diseases like heart failure, atherosclerosis, acute myocardial infarction, pulmonary arterial hypertension, and arrhythmia., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background/objective: Knowledge of protein subcellular localization is vitally important for both basic research and drug development. Facing the avalanche of protein sequences emerging in the post-genomic age, it is urgent to develop computational tools for timely and effectively identifying their subcellular localization based on the sequence information alone. Recently, a predictor called "pLoc-mVirus" was developed for identifying the subcellular localization of virus proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems in which some proteins, known as "multiplex proteins", may simultaneously occur in, or move between two or more subcellular location sites. Despite the fact that it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mVirus was trained by an extremely skewed dataset in which some subset was over 10 times the size of the other subsets. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset., Methods: Using the Chou's general PseAAC (Pseudo Amino Acid Composition) approach and the IHTS (Inserting Hypothetical Training Samples) treatment to balance out the training dataset, we have developed a new predictor called "pLoc_bal-mVirus" for predicting the subcellular localization of multi-label virus proteins., Results: Cross-validation tests on exactly the same experiment-confirmed dataset have indicated that the proposed new predictor is remarkably superior to pLoc-mVirus, the existing state-of-theart predictor for the same purpose., Conclusion: Its user-friendly web-server is available at http://www.jci-bioinfo.cn/pLoc_balmVirus/, by which the majority of experimental scientists can easily get their desired results without the need to go through the detailed complicated mathematics. Accordingly, pLoc_bal-mVirus will become a very useful tool for designing multi-target drugs and in-depth understanding of the biological process in a cell., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Metabolic disorders are a major cause of illness and death worldwide. Metabolism is the process by which the body makes energy from proteins, carbohydrates, and fats; chemically breaking these down in the digestive system towards sugars and acids which constitute the human body's fuel for immediate use, or to store in body tissues, such as the liver, muscles, and body fat., Objective: The efficiency of treatments for multifactor diseases has not been proved. It is accepted that to manage multifactor diseases, simultaneous modulation of multiple targets is required leading to the development of new strategies for discovery and development of drugs against metabolic disorders., Methods: In silico studies are increasingly being applied by researchers due to reductions in time and costs for new prototype synthesis; obtaining substances that present better therapeutic profiles., Discussion: In the present work, in addition to discussing multi-target drug discovery and the contributions of in silico studies to rational bioactive planning against metabolic disorders such as diabetes and obesity, we review various in silico study contributions to the fight against human metabolic pathologies., Conclusion: In this review, we have presented various studies involved in the treatment of metabolic disorders; attempting to obtain hybrid molecules with pharmacological activity against various targets and expanding biological activity by using different mechanisms of action to treat a single pathology., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The smallest unit of life is a cell, which contains numerous protein molecules. Most of the functions critical to the cell's survival are performed by these proteins located in its different organelles, usually called ''subcellular locations". Information of subcellular localization for a protein can provide useful clues about its function. To reveal the intricate pathways at the cellular level, knowledge of the subcellular localization of proteins in a cell is prerequisite. Therefore, one of the fundamental goals in molecular cell biology and proteomics is to determine the subcellular locations of proteins in an entire cell. It is also indispensable for prioritizing and selecting the right targets for drug development. Unfortunately, it is both timeconsuming and costly to determine the subcellular locations of proteins purely based on experiments. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods for rapidly and effectively identifying the subcellular locations of uncharacterized proteins based on their sequences information alone. Actually, considerable progresses have been achieved in this regard. This review is focused on those methods, which have the capacity to deal with multi-label proteins that may simultaneously exist in two or more subcellular location sites. Protein molecules with this kind of characteristic are vitally important for finding multi-target drugs, a current hot trend in drug development. Focused in this review are also those methods that have use-friendly web-servers established so that the majority of experimental scientists can use them to get the desired results without the need to go through the detailed mathematics involved., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Nitroproston is a novel prostaglandin-based compound modified by NOdonating groups with potential application in obstructive respiratory diseases such as asthma and obstructive bronchitis. Nitroproston has been extensively studied using various pharmacological models. Its biological stability is still uncertain., Objective: The aim of the present study was to evaluate Nitroproston stability in vitro, as well as to identify and characterize its major biodegradation products., Methods: The principal biodegradation products of Nitroproston were identified in vitro using liquid chromatography/ion trap - time-of-flight mass-spectrometry. The postulated structure of metabolites was confirmed using authentic reference standards. Rat, rabbit and human plasma and human whole blood samples were used for comparative in vitro degradation study. Nitroproston and its biodegradation products in biological samples were measured by liquid chromatography/triple -stage quadrupole mass spectrometry., Results: Nitroproston is rapidly hydrolyzed in rat plasma to generate glycerol-1,3-dinitrate and prostaglandin E2. The latter can undergo conversion to cyclopentenone prostaglandins A2 and B2. Thereby less than 5% of the parent compound was observed in rat plasma at the first moment of incubation. A similar pattern was observed for rabbit plasma where half-life (T1/2) of Nitroproston was about 2.0 minutes. Nitroproston biodegradation rate for human plasma was the slowest (T1/2 = 2.1 h) among tested species, occurred more rapidly in whole blood (T1/2 = 14.8 min)., Conclusion: It was found that Nitroproston is rapidly hydrolyzed in rodent compared to human plasma incubations. Whereas Nitroproston is relatively stable in human plasma an enhanced hydrolytic activity was observed in whole human blood incubations. Extensive metabolism of Nitroproston in human whole blood was mainly associated with red blood cells. The observed interspecies variability highlights the need of suitable animal model selection for Nitroproston follow-up PK/PD studies., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis, which has high levels of mortality worldwide and has already gained resistance to first- and second-line drugs. The study by new chemical entities with promising activities becomes paramount to broaden the therapeutic strategies in the cure of the patients affected with this disease. In this context, in this review we report the discovery of 3 classes of compounds that can simultaneously interact with more than one target of Mycobacterium tuberculosis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder. Several hallmarks such as β-amyloid (Aβ) aggregation underlying amyloid plaque formation, τ-hyperphosphorylation leading to production of neurofibrillary tangles, and decline in the number of cholinergic neurons appear to be fundamental in the pathophysiology of the disease. Other evidence points also to the involvement of oxidative stress, biometal dyshomeostasis, inflammation, and cell cycle regulatory failure. Taking into account such premises, many attractive targets for the development of anti-AD drugs have emerged. Specifically, the multifactorial nature of AD calls for multi-target-directed ligands (MTDLs) which can be beneficial by providing interactions with multiple targets. Tacrine (THA), the first clinically effective acetylcholinesterase inhibitor, was approved for the treatment of mild to moderate AD. Unfortunately, frequent adverse effects including peripheral cholinergic effects and hepatotoxicity limited its therapeutic potential. Based on the numerous biological systems involved in AD progression, this review covers THA-incorporated hybrids possessing a neuroprotective profile. In particular, it focuses on THA hybrids capable of scavenging reactive oxygen species (ROS), and derivatives which reduce the formation of Aβ-plaques either directly by confronting the Aβ1-42 selfaggregation process or indirectly by inhibiting the BACE-1 enzyme or AChE-induced Aβ1-40 aggregation. Particular interest is also addressed to THA hybrids with suppressed hepatotoxicity., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

The most basic principle of drug action is found in the lock and key model, where the highest possible affinity for a target that also avoids side effects is desired. For many years this was understood as being "one drug, for one target, for one disease", however researchers began to observe that certain diseases are best treated with multi-target drugs. In recent years, studies have sought out polypharmacological compounds acting on multiple targets against complex (multifactorial) diseases, such as cancer, neurodegenerative disease, and certain infections. One of the computational tools used in research for multifunctional drugs is Molecular Docking. Through this methodology of Computer-Aided Drug Design, we observe complexes formed between ligands and interesting targets (often many), for a particular disease. This review reports on docking studies as used in investigations of new multi-target compounds; it also shows the various ways that such studies are used in the search for multifunctional compounds., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)