Browse
Submit Data
Databases
API
Help

Dataset Information

19 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Are 2D fingerprints still valuable for drug discovery?

ABSTRACT: Recently, molecular fingerprints extracted from three-dimensional (3D) structures using advanced mathematics, such as algebraic topology, differential geometry, and graph theory have been paired with efficient machine learning, especially deep learning algorithms to outperform other methods in drug discovery applications and competitions. This raises the question of whether classical 2D fingerprints are still valuable in computer-aided drug discovery. This work considers 23 datasets associated with four typical problems, namely protein-ligand binding, toxicity, solubility and partition coefficient to assess the performance of eight 2D fingerprints. Advanced machine learning algorithms including random forest, gradient boosted decision tree, single-task deep neural network and multitask deep neural network are employed to construct efficient 2D-fingerprint based models. Additionally, appropriate consensus models are built to further enhance the performance of 2D-fingerprint-based methods. It is demonstrated that 2D-fingerprint-based models perform as well as the state-of-the-art 3D structure-based models for the predictions of toxicity, solubility, partition coefficient and protein-ligand binding affinity based on only ligand information. However, 3D structure-based models outperform 2D fingerprint-based methods in complex-based protein-ligand binding affinity predictions.

SUBMITTER: Gao K

PROVIDER: S-EPMC7224332 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Aminoacyl-tRNA Synthetases as Valuable Targets for Antimicrobial Drug Discovery.

Project description:Aminoacyl-tRNA synthetases (aaRSs) catalyze the esterification of tRNA with a cognate amino acid and are essential enzymes in all three kingdoms of life. Due to their important role in the translation of the genetic code, aaRSs have been recognized as suitable targets for the development of small molecule anti-infectives. In this review, following a concise discussion of aaRS catalytic and proof-reading activities, the various inhibitory mechanisms of reported natural and synthetic aaRS inhibitors are discussed. Using the expanding repository of ligand-bound X-ray crystal structures, we classified these compounds based on their binding sites, focusing on their ability to compete with the association of one, or more of the canonical aaRS substrates. In parallel, we examined the determinants of species-selectivity and discuss potential resistance mechanisms of some of the inhibitor classes. Combined, this structural perspective highlights the opportunities for further exploration of the aaRS enzyme family as antimicrobial targets.

| S-EPMC7916415 | biostudies-literature

The Proteasome in Modern Drug Discovery: Second Life of a Highly Valuable Drug Target.

Project description:As the central figure of the cellular protein degradation machinery, the proteasome is critical for cell survival. Having been extensively targeted for inhibition, the constitutive proteasome has proven its role as a highly valuable drug target. However, recent advances in the protein homeostasis field suggest that additional chapters can be added to this successful story. For example, selective immunoproteasome inhibition promises high clinical efficacy for autoimmune disorders and inflammation, and proteasome inhibitors might serve as novel therapeutics for malaria or other microorganisms. Furthermore, utilizing the destructive force of the proteasome for selective degradation of essential drivers of human disorders has opened up a new and exciting area of drug discovery. Thus, the field of proteasome drug discovery still holds exciting questions to be answered and does not simply end with inhibiting the constitutive proteasome.

| S-EPMC5571462 | biostudies-literature

Control of asthma in real life: still a valuable goal?

Project description:Although studies show that control of asthma can be achieved in the majority of patients, surveys repeatedly show that this is not the case in real life. Important measures to implement in order to achieve asthma control are trained healthcare professionals, a good patient-doctor relationship, patient education, avoidance of exposure to triggers, personalised management and adherence to treatment. These measures help the majority of asthma patients but have not yet been widely implemented and there should be a concerted action for their implementation. Moreover, further and focused research is needed in severe/refractory asthma.

| S-EPMC9487814 | biostudies-literature

B-ALL Complexity: Is Targeted Therapy Still A Valuable Approach for Pediatric Patients?

Project description:B-cell acute lymphoblastic leukemia (B-ALL) is a hematologic malignancy that arises from the clonal expansion of transformed B-cell precursors and predominately affects childhood. Even though significant progresses have been made in the treatment of B-ALL, pediatric patients' outcome has to be furtherly increased and alternative targeted treatment strategies are required for younger patients. Over the last decade, novel approaches have been used to understand the genomic landscape and the complexity of the molecular biology of pediatric B-ALL, mainly next generation sequencing, offering important insights into new B-ALL subtypes, altered pathways, and therapeutic targets that may lead to improved risk stratification and treatments. Here, we will highlight the up-to-date knowledge of the novel B-ALL subtypes in childhood, with particular emphasis on altered signaling pathways. In addition, we will discuss the targeted therapies that showed promising results for the treatment of the different B-ALL subtypes.

| S-EPMC7760974 | biostudies-literature

PROTACs and Building Blocks: The 2D Chemical Space in Very Early Drug Discovery.

Project description:Targeted protein degradation by PROTACs has emerged as a new modality for the knockdown of a range of proteins, and, more recently, it has become increasingly clear that the PROTAC chemical space requires characterization through a pool of ad hoc physicochemical descriptors. In this study, a new database named PROTAC-DB that provides extensive information about PROTACs and building blocks was used to obtain the 2D chemical structures of about 1600 PROTACs, 60 E3 ligands, 800 linkers, and 202 warheads. For every structure, we calculated a pool of seven 2D descriptors carefully identified as informative for large and flexible structures. For comparison purposes, the same procedure was applied to a dataset of about 50 bRo5 approved drugs reported in the literature. Correlation matrices, PCAs, box plots, and other graphical tools were used to define and understand the chemical space covered by PROTACs and building blocks in relation to other compounds. Results show that linkers have different properties than E3 ligands and warheads. Polar descriptors additivity is not respected when passing from building blocks to degraders. Moreover, a very preliminary analysis based on three PROTACs with high, intermediate, and low permeability showed how the most permeable compounds seem to occupy a region closer to bRo5 drugs and, thus, exhibit different properties than impermeable compounds. Finally, a second database, PROTACpedia, was used to discuss the relevance of physicochemical descriptors on degradation activity.

| S-EPMC7865272 | biostudies-literature

iPSC-derived hepatocytes generated from NASH donors provide a valuable platform for disease modeling and drug discovery.

Project description:Non-alcoholic fatty liver disease (NAFLD) affects 30-40% of adults and 10% of children in the US. About 20% of people with NAFLD develop non-alcoholic steatohepatitis (NASH), which may lead to cirrhosis and liver cancer, and is projected to be a leading cause of liver transplantation in the near future. Human induced pluripotent stem cells (iPSC) from NASH patients are useful for generating a large number of hepatocytes for NASH modeling applications and identification of potential drug targets. We developed a novel defined in vitro differentiation process to generate cryopreservable hepatocytes using an iPSC panel of NASH donors and apparently healthy normal (AHN) controls. iPSC-derived hepatocytes displayed stage specific phenotypic markers, hepatocyte morphology, with bile canaliculi. Importantly, both fresh and cryopreserved definitive endoderm and hepatoblasts successfully differentiated to pure and functional hepatocytes with increased CYP3A4 activity in response to rifampicin and lipid accumulation upon fatty acid (FA) treatment. End-stage hepatocytes integrated into three-dimensional (3D) liver organoids and demonstrated increased levels of albumin secretion compared to aggregates consisting of hepatocytes alone. End-stage hepatocytes derived from NASH donors demonstrated spontaneous lipidosis without FA supplementation, recapitulating a feature of NASH hepatocytes in vivo Cryopreserved hepatocytes generated by this protocol across multiple donors will provide a critical cell source to facilitate the fundamental understanding of NAFLD/NASH biology and potential high throughput screening applications for preclinical evaluation of therapeutic targets.

| S-EPMC7758638 | biostudies-literature

Historeceptomic Fingerprints for Drug-Like Compounds.

Project description:Most drugs exert their beneficial and adverse effects through their combined action on several different molecular targets (polypharmacology). The true molecular fingerprint of the direct action of a drug has two components: the ensemble of all the receptors upon which a drug acts and their level of expression in organs/tissues. Conversely, the fingerprint of the adverse effects of a drug may derive from its action in bystander tissues. The ensemble of targets is almost always only partially known. Here we describe an approach improving upon and integrating both components: in silico identification of a more comprehensive ensemble of targets for any drug weighted by the expression of those receptors in relevant tissues. Our system combines more than 300,000 experimentally determined bioactivity values from the ChEMBL database and 4.2 billion molecular docking scores. We integrated these scores with gene expression data for human receptors across a panel of human tissues to produce drug-specific tissue-receptor (historeceptomics) scores. A statistical model was designed to identify significant scores, which define an improved fingerprint representing the unique activity of any drug. These multi-dimensional historeceptomic fingerprints describe, in a novel, intuitive, and easy to interpret style, the holistic, in vivo picture of the mechanism of any drug's action. Valuable applications in drug discovery and personalized medicine, including the identification of molecular signatures for drugs with polypharmacologic modes of action, detection of tissue-specific adverse effects of drugs, matching molecular signatures of a disease to drugs, target identification for bioactive compounds with unknown receptors, and hypothesis generation for drug/compound phenotypes may be enabled by this approach. The system has been deployed at drugable.org for access through a user-friendly web site.

| S-EPMC4683199 | biostudies-literature

Detection of drug-drug interactions by modeling interaction profile fingerprints.

Project description:Drug-drug interactions (DDIs) constitute an important problem in postmarketing pharmacovigilance and in the development of new drugs. The effectiveness or toxicity of a medication could be affected by the co-administration of other drugs that share pharmacokinetic or pharmacodynamic pathways. For this reason, a great effort is being made to develop new methodologies to detect and assess DDIs. In this article, we present a novel method based on drug interaction profile fingerprints (IPFs) with successful application to DDI detection. IPFs were generated based on the DrugBank database, which provided 9,454 well-established DDIs as a primary source of interaction data. The model uses IPFs to measure the similarity of pairs of drugs and generates new putative DDIs from the non-intersecting interactions of a pair. We described as part of our analysis the pharmacological and biological effects associated with the putative interactions; for example, the interaction between haloperidol and dicyclomine can cause increased risk of psychosis and tardive dyskinesia. First, we evaluated the method through hold-out validation and then by using four independent test sets that did not overlap with DrugBank. Precision for the test sets ranged from 0.4-0.5 with more than two fold enrichment factor enhancement. In conclusion, we demonstrated the usefulness of the method in pharmacovigilance as a DDI predictor, and created a dataset of potential DDIs, highlighting the etiology or pharmacological effect of the DDI, and providing an exploratory tool to facilitate decision support in DDI detection and patient safety.

| S-EPMC3592896 | biostudies-other

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

Project description:Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.

| S-EPMC4929472 | biostudies-other

Virtual drug screening for prion diseases: A valuable step?

Project description: Not available

| S-EPMC4972553 | biostudies-literature