Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A perspective on multi-target drug discovery and design for complex diseases.

ABSTRACT: Diseases of infection, of neurodegeneration (such as Alzheimer's and Parkinson's diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clinically and biologically validated targets. This Perspective will focus on the molecular and computational approaches that underpin drug design by medicinal chemists to promote understanding and collaboration with clinical scientists.

SUBMITTER: Ramsay RR

PROVIDER: S-EPMC5770353 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A perspective on multi-target drug discovery and design for complex diseases.

Ramsay Rona R RR Popovic-Nikolic Marija R MR Nikolic Katarina K Uliassi Elisa E Bolognesi Maria Laura ML

Clinical and translational medicine 20180117 1

Diseases of infection, of neurodegeneration (such as Alzheimer's and Parkinson's diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clini ...[more]

PMID: 29340951

Similar Datasets

Drug discovery for neglected diseases: molecular target-based and phenotypic approaches.

Project description:Drug discovery for neglected tropical diseases is carried out using both target-based and phenotypic approaches. In this paper, target-based approaches are discussed, with a particular focus on human African trypanosomiasis. Target-based drug discovery can be successful, but careful selection of targets is required. There are still very few fully validated drug targets in neglected diseases, and there is a high attrition rate in target-based drug discovery for these diseases. Phenotypic screening is a powerful method in both neglected and non-neglected diseases and has been very successfully used. Identification of molecular targets from phenotypic approaches can be a way to identify potential new drug targets.

| S-EPMC3954685 | biostudies-other

LigBuilder V3: A Multi-Target de novo Drug Design Approach.

Project description:With the rapid development of systems-based pharmacology and poly-pharmacology, method development for rational design of multi-target drugs has becoming urgent. In this paper, we present the first de novo multi-target drug design program LigBuilder V3, which can be used to design ligands to target multiple receptors, multiple binding sites of one receptor, or various conformations of one receptor. LigBuilder V3 is generally applicable in de novo multi-target drug design and optimization, especially for the design of concise ligands for protein targets with large difference in binding sites. To demonstrate the utility of LigBuilder V3, we have used it to design dual-functional inhibitors targeting HIV protease and HIV reverse transcriptase with three different strategy, including multi-target de novo design, multi-target growing, and multi-target linking. The designed compounds were computational validated by MM/GBSA binding free energy estimation as highly potential multi-target inhibitors for both HIV protease and HIV reverse transcriptase. The LigBuilder V3 program can be downloaded at "http://www.pkumdl.cn/ligbuilder3/".

| S-EPMC7059350 | biostudies-literature

Sustainable Drug Discovery of Multi-Target-Directed Ligands for Alzheimer's Disease.

Project description:The multifactorial nature of Alzheimer's disease (AD) is a reason for the lack of effective drugs as well as a basis for the development of "multi-target-directed ligands" (MTDLs). As cases increase in developing countries, there is a need of new drugs that are not only effective but also accessible. With this motivation, we report the first sustainable MTDLs, derived from cashew nutshell liquid (CNSL), an inexpensive food waste with anti-inflammatory properties. We applied a framework combination of functionalized CNSL components and well-established acetylcholinesterase (AChE)/butyrylcholinesterase (BChE) tacrine templates. MTDLs were selected based on hepatic, neuronal, and microglial cell toxicity. Enzymatic studies disclosed potent and selective AChE/BChE inhibitors (5, 6, and 12), with subnanomolar activities. The X-ray crystal structure of 5 complexed with BChE allowed rationalizing the observed activity (0.0352 nM). Investigation in BV-2 microglial cells revealed antineuroinflammatory and neuroprotective activities for 5 and 6 (already at 0.01 μM), confirming the design rationale.

| S-EPMC8154578 | biostudies-literature

Multi-modal proteomic target discovery and orthogonol confirmation of preclinical diabetic retinopathy drug development biomarkers

Project description:The aim of this study was to identify proteomic alterations associated with functional dysregulation of the retina with diabetes that could eventually be used as surrogate endpoints in preclinical drug testing studies. A multi-modal approach of antibody (Luminex)-, electrophoresis (2-DIGE)-, and LC-MS (iTRAQ)-based quantitation methods was used to provide broad coverage of the retinal proteome. Transcriptional profiling through microarray analysis was also included to increase coverage and provide insight into potential regulation of protein expression changes at the mRNA level. The different technologies proved complementary, with limited coverage overlap between methods. Diabetes was induced in Sprague-Dawley male rats (Charles River Laboratories, Wilmington, MA) by intraperitoneal injection of 65 mg/kg streptozotocin (STZ) (Sigma-Aldrich, St. Louis, MO) in 10mM sodium citrate pH 4.5 vehicle. Control rats were injected with an equal dose of vehicle only. Rats had free access to food and water, and were maintained on a 12 hour light/dark cycle. Blood glucose level and body weight were measured 6 days post-STZ or vehicle injection, and biweekly throughout the experiment. Only rats with blood glucose levels >250 mg/dL at the time of the original test and throughout the experiment were included in the diabetic groups. At the time of retina harvest, rats were given a lethal dose of pentobarbital, 100 mg/kg, (Ovation Pharmaceuticals Inc., Deerfield, IL) by intraperitoneal injection and sacrificed by decapitation. Retinas were rapidly excised snap- frozen in liquid nitrogen for subsequent experimentation.

2010-06-01 | E-GEOD-20886 | biostudies-arrayexpress

Accelerating Drug Discovery by Early Protein Drug Target Prediction Based on a Multi-Fingerprint Similarity Search.

Project description:In this continuing work, we have updated our recently proposed Multi-fingerprint Similarity Search algorithm (MuSSel) by enabling the generation of dominant ionized species at a physiological pH and the exploration of a larger data domain, which included more than half a million high-quality small molecules extracted from the latest release of ChEMBL (version 24.1, at the time of writing). Provided with a high biological assay confidence score, these selected compounds explored up to 2822 protein drug targets. To improve the data accuracy, samples marked as prodrugs or with equivocal biological annotations were not considered. Notably, MuSSel performances were overall improved by using an object-relational database management system based on PostgreSQL. In order to challenge the real effectiveness of MuSSel in predicting relevant therapeutic drug targets, we analyzed a pool of 36 external bioactive compounds published in the Journal of Medicinal Chemistry from October to December 2018. This study demonstrates that the use of highly curated chemical and biological experimental data on one side, and a powerful multi-fingerprint search algorithm on the other, can be of the utmost importance in addressing the fate of newly conceived small molecules, by strongly reducing the attrition of early phases of drug discovery programs.

| S-EPMC6631269 | biostudies-literature

Rare variants in drug target genes contributing to complex diseases, phenome-wide.

Project description:The DrugBank database consists of ~800 genes that are well characterized drug targets. This list of genes is a useful resource for association testing. For example, loss of function (LOF) genetic variation has the potential to mimic the effect of drugs, and high impact variation in these genes can impact downstream traits. Identifying novel associations between genetic variation in these genes and a range of diseases can also uncover new uses for the drugs that target these genes. Phenome Wide Association Studies (PheWAS) have been successful in identifying genetic associations across hundreds of thousands of diseases. We have conducted a novel gene based PheWAS to test the effect of rare variants in DrugBank genes, evaluating associations between these genes and more than 500 quantitative and dichotomous phenotypes. We used whole exome sequencing data from 38,568 samples in Geisinger MyCode Community Health Initiative. We evaluated the results of this study when binning rare variants using various filters based on potential functional impact. We identified multiple novel associations, and the majority of the significant associations were driven by functionally annotated variation. Overall, this study provides a sweeping exploration of rare variant associations within functionally relevant genes across a wide range of diagnoses.

| S-EPMC5854600 | biostudies-literature

Network spectra for drug-target identification in complex diseases: new guns against old foes.

Project description:The fundamental understanding of altered complex molecular interactions in a diseased condition is the key to its cure. The overall functioning of these molecules is kind of jugglers play in the cell orchestra and to anticipate these relationships among the molecules is one of the greatest challenges in modern biology and medicine. Network science turned out to be providing a successful and simple platform to understand complex interactions among healthy and diseased tissues. Furthermore, much information about the structure and dynamics of a network is concealed in the eigenvalues of its adjacency matrix. In this review, we illustrate rapid advancements in the field of network science in combination with spectral graph theory that enables us to uncover the complexities of various diseases. Interpretations laid by network science approach have solicited insights into molecular relationships and have reported novel drug targets and biomarkers in various complex diseases.

| S-EPMC6297166 | biostudies-other

Multi-Target Drugs for Kidney Diseases.

Project description:Kidney diseases such as AKI, CKD, and GN can lead to dialysis and the need for kidney transplantation. The pathologies for kidney diseases are extremely complex, progress at different rates, and involve several cell types and cell signaling pathways. Complex kidney diseases require therapeutics that can act on multiple targets. In the past 10 years, in silico design of drugs has allowed for multi-target drugs to progress quickly from concept to reality. Several multi-target drugs have been made successfully to target AA pathways and transcription factors for the treatment of inflammatory, fibrotic, and metabolic diseases. Multi-target drugs have also demonstrated great potential to treat diabetic nephropathy and fibrotic kidney disease. These drugs act by decreasing renal TGF-β signaling, inflammation, mitochondrial dysfunction, and oxidative stress. There are several other recently developed multi-target drugs that have yet to be tested for their ability to combat kidney diseases. Overall, there is excellent potential for multi-target drugs that act on several cell types and signaling pathways to treat kidney diseases.

| S-EPMC8785794 | biostudies-literature

Perspective: Alchemical free energy calculations for drug discovery.

Project description:Computational techniques see widespread use in pharmaceutical drug discovery, but typically prove unreliable in predicting trends in protein-ligand binding. Alchemical free energy calculations seek to change that by providing rigorous binding free energies from molecular simulations. Given adequate sampling and an accurate enough force field, these techniques yield accurate free energy estimates. Recent innovations in alchemical techniques have sparked a resurgence of interest in these calculations. Still, many obstacles stand in the way of their routine application in a drug discovery context, including the one we focus on here, sampling. Sampling of binding modes poses a particular challenge as binding modes are often separated by large energy barriers, leading to slow transitions. Binding modes are difficult to predict, and in some cases multiple binding modes may contribute to binding. In view of these hurdles, we present a framework for dealing carefully with uncertainty in binding mode or conformation in the context of free energy calculations. With careful sampling, free energy techniques show considerable promise for aiding drug discovery.

| S-EPMC3537745 | biostudies-literature

Multi-modal proteomic target discovery and orthogonol confirmation of preclinical diabetic retinopathy drug development biomarkers

2010-06-01 | GSE20886 | GEO