Chemical space of naturally occurring compounds

2018 ◽  
Vol 4 (5) ◽  
Author(s):  
Fernanda I. Saldívar-González ◽  
B. Angélica Pilón-Jiménez ◽  
José L. Medina-Franco
Keyword(s):  
Data Mining ◽  
Natural Products ◽  
Small Molecules ◽  
Chemical Space ◽  
Chemical Diversity ◽  
Diversity Analysis ◽  
Naturally Occurring ◽  
Systematic Exploration ◽  
Chemical Descriptors ◽  
Different Sources

AbstractThe chemical space of naturally occurring compounds is vast and diverse. Other than biologics, naturally occurring small molecules include a large variety of compounds covering natural products from different sources such as plant, marine, and fungi, to name a few, and several food chemicals. The systematic exploration of the chemical space of naturally occurring compounds have significant implications in many areas of research including but not limited to drug discovery, nutrition, bio- and chemical diversity analysis. The exploration of the coverage and diversity of the chemical space of compound databases can be carried out in different ways. The approach will largely depend on the criteria to define the chemical space that is commonly selected based on the goals of the study. This chapter discusses major compound databases of natural products and cheminformatics strategies that have been used to characterize the chemical space of natural products. Recent exemplary studies of the chemical space of natural products from different sources and their relationships with other compounds are also discussed. We also present novel chemical descriptors and data mining approaches that are emerging to characterize the chemical space of naturally occurring compounds.

scholarly journals Computational Approaches to Identify Natural Products as Inhibitors of DNA Methyltransferases

2018 ◽  
Author(s):  
Fernanda I. Saldívar-González ◽  
Alejandro Gómez-García ◽  
Norberto Sánchez-Cruz ◽  
Javier Ruiz-Rios ◽  
B. Angélica Pilón-Jiménez ◽  
...  
Keyword(s):  
Natural Products ◽  
Molecular Modeling ◽  
Small Molecules ◽  
Chemical Space ◽  
Pharmacophore Modeling ◽  
Dna Methyltransferases ◽  
Computational Approaches ◽  
Naturally Occurring ◽  
Epigenetic Drug ◽  
Different Sources

Naturally occurring small molecules include a large variety of natural products from different sources that have confirmed activity against epigenetic targets. In this work we review chemoinformatic, molecular modeling and other computational approaches that have been used to uncover natural products as inhibitors of DNA metiltransferases, a major family of epigenetic targets with significant potential for the treatment of cancer and several other diseases. Examples of these computational approaches include docking, similarity-based virtual screening, and pharmacophore modeling. It is also commented the chemoinformatic-based exploration of the chemical space of naturally occurring compounds as epigenetic modulators which may have significant implications in epigenetic drug discovery and nutriepigenetics.

scholarly journals Chemical Diversity of Plant Cyanogenic Glycosides: An Overview of Reported Natural Products

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 719
Author(s):  
Meri Yulvianti ◽  
Christian Zidorn
Keyword(s):  
Natural Products ◽  
Plant Species ◽  
Chemical Diversity ◽  
Cyanogenic Glycosides ◽  
Sugar Moiety ◽  
Plant Natural Products ◽  
Naturally Occurring

Cyanogenic glycosides are an important and widespread class of plant natural products, which are however structurally less diverse than many other classes of natural products. So far, 112 naturally occurring cyanogenic glycosides have been described in the phytochemical literature. Currently, these unique compounds have been reported from more than 2500 plant species. Natural cyanogenic glycosides show variations regarding both the aglycone and the sugar part of the molecules. The predominant sugar moiety is glucose but many substitution patterns of this glucose moiety exist in nature. Regarding the aglycone moiety, four different basic classes can be distinguished, aliphatic, cyclic, aromatic, and heterocyclic aglycones. Our overview covers all cyanogenic glycosides isolated from plants and includes 33 compounds with a non-cyclic aglycone, 20 cyclopentane derivatives, 55 natural products with an aromatic aglycone, and four dihydropyridone derivatives. In the following sections, we will provide an overview about the chemical diversity known so far and mention the first source from which the respective compounds had been isolated. This review will serve as a first reference for researchers trying to find new cyanogenic glycosides and highlights some gaps in the knowledge about the exact structures of already described compounds.

scholarly journals Analysis of a large food chemical database: chemical space, diversity, and complexity

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 993 ◽  
Author(s):  
J. Jesús Naveja ◽  
Mariel P. Rico-Hidalgo ◽  
José L. Medina-Franco
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Structural Complexity ◽  
Chemical Diversity ◽  
Chemical Structures ◽  
Novel Approach ◽  
Chemical Database ◽  
Protein Interactome ◽  
Limited Basis ◽  
Future Direction

Background: Food chemicals are a cornerstone in the food industry. However, its chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related databases were done up to 2,200 molecules. The goal of this work was to quantify the chemical diversity of chemical compounds stored in FooDB, a database with nearly 24,000 food chemicals. Methods: The visual representation of the chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of chemical satellites. The large food chemical database was profiled based on physicochemical properties, molecular complexity and scaffold content. The global diversity of FooDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other databases. Conclusions: To the best of our knowledge, this is the first analysis of the chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the chemical structures of the molecules in FooDB with other compound databases, for instance, drug-like databases and natural products collections. An additional future direction of this work is to use the list of 3,228 polyphenolic compounds identified in this work to enhance the on-going polyphenol-protein interactome studies.

scholarly journals Bioactivity descriptors for uncharacterized compounds

2020 ◽  
Author(s):  
Martino Bertoni ◽  
Miquel Duran-Frigola ◽  
Pau Badia-i-Mompel ◽  
Eduardo Pauls ◽  
Modesto Orozco-Ruiz ◽  
...  
Keyword(s):  
Small Molecules ◽  
Cellular Response ◽  
Chemical Space ◽  
Biological Properties ◽  
Experimental Information ◽  
Substantial Improvement ◽  
Biologically Relevant ◽  
Chemical Structures ◽  
Chemical Descriptors ◽  
Physicochemical And Structural Properties

AbstractChemical descriptors encode the physicochemical and structural properties of small molecules, and they are at the core of chemoinformatics. The broad release of bioactivity data has prompted enriched representations of compounds, reaching beyond chemical structures and capturing their known biological properties. Unfortunately, ‘bioactivity descriptors’ are not available for most small molecules, which limits their applicability to a few thousand well characterized compounds. Here we present a collection of deep neural networks able to infer bioactivity signatures for any compound of interest, even when little or no experimental information is available for them. Our ‘signaturizers’ relate to bioactivities of 25 different types (including target profiles, cellular response and clinical outcomes) and can be used as drop-in replacements for chemical descriptors in day-to-day chemoinformatics tasks. Indeed, we illustrate how inferred bioactivity signatures are useful to navigate the chemical space in a biologically relevant manner, unveiling higher-order organization in natural product collections, and to enrich mostly uncharacterized chemical libraries for activity against the drug-orphan target Snail1. Moreover, we implement a battery of signature-activity relationship (SigAR) models and show a substantial improvement in performance, with respect to chemistry-based classifiers, across a series of biophysics and physiology activity prediction benchmarks.

Dihydroresveratrol Type Dihydrostilbenoids: Chemical Diversity, Chemosystematics, and Bioactivity

2018 ◽  
Vol 25 (10) ◽  
pp. 1194-1240 ◽  
Author(s):  
Sara Vitalini ◽  
Serhat S. Cicek ◽  
Sebastian Granica ◽  
Christian Zidorn
Keyword(s):  
Natural Products ◽  
Anticancer Activity ◽  
Biological Activities ◽  
Wide Spectrum ◽  
Pathogenic Fungi ◽  
Chemical Diversity ◽  
Limited Information ◽  
Lead Compounds ◽  
Naturally Occurring

Background: Dihydrostilbenoids, a diverse class of natural products differing from stilbenoids by the missing double bond in the ethylene chain linking the aromatic moieties, have been reported from fungi, mosses, ferns, and flowering plants. Objective: Occurrence, structure, and bioactivity of naturally occurring dihydroresveratrol type dihydrostilbenoids are discussed in this review. Method: A Reaxys database search for dihydroresveratrol derivatives with possible substitutions on all atoms, but excluding non-natural products and compounds featuring additional rings involving the ethyl connecting chain, was performed. Results: Structures include simple dihydroresveratrol derivatives, compounds substituted with complex side chains composed of acyl moieties and sugars, and compounds containing polycyclic cores attached to dihydrostilbenoid units. Dihydrostilbenoids have a wide spectrum of bioactivities ranging from expectable antioxidant and anti-inflammatory activities to interesting neuroprotective and anticancer activity. The anticancer activity in particular is very pronounced for some plant-derived dihydrostilbenoids and makes them interesting lead compounds for drug development. Apart from some reports on dihydroresveratrol derivatives as phytoalexins against plant-pathogenic fungi, only very limited information is available on the ecological role of these compounds for the organisms producing them. Conclusion: Dihydrostilbenoids are a class of natural products possessing significant biological activities; their scattered but not ubiquitous occurrence throughout the kingdoms of plants and fungi is not easily explained. We are convinced that future studies will identify new sources of dihydrostilbenoids, and we hope that the present review will inspire such studies and will help in directing such efforts to suitable source organisms and towards promising bioactivities.

3,4-Dihydroisocoumarins, Interesting Natural Products: Isolation, Organic Syntheses and Biological Activities

2019 ◽  
Vol 16 (1) ◽  
pp. 112-129 ◽  
Author(s):  
Aurelio Ortiz ◽  
Miriam Castro ◽  
Estibaliz Sansinenea
Keyword(s):  
Natural Products ◽  
Biological Activities ◽  
Natural Compounds ◽  
Biologically Active ◽  
Bacterial Strains ◽  
Drug Candidates ◽  
Heterocyclic Molecules ◽  
Naturally Occurring ◽  
Wide Range ◽  
Different Sources

Background:3,4-dihydroisocoumarins are an important small group belonging to the class of naturally occurring lactones isolated from different bacterial strains, molds, lichens, and plants. The structures of these natural compounds show various types of substitution in their basic skeleton and this variability influences deeply their biological activities. These lactones are structural subunits of several natural products and serve as useful intermediates in the synthesis of different heterocyclic molecules, which exhibit a wide range of biological activities, such as anti-inflammatory, antiplasmodial, antifungal, antimicrobial, antiangiogenic and antitumoral activities, among others. Their syntheses have attracted attention of many researchers reporting many synthetic strategies to achieve 3,4-dihydroisocoumarins and other related structures. </P><P> Objective: In this context, the isolation of these natural compounds from different sources, their syntheses and biological activities are reviewed, adding the most recent advances and related developments.Conclusion:This review aims to encourage further work on the isolation and synthesis of this class of natural products. It would be beneficial for synthetic as well as the medicinal chemists to design selective, optimized dihydroisocoumarin derivatives as potential drug candidates, since dihydroisocoumarin scaffolds have significant utility in the development of therapeutically relevant and biologically active compounds.

Case studies on computer-based identification of natural products as lead molecules

2020 ◽  
Vol 5 (10) ◽  
Author(s):  
Conrad V. Simoben ◽  
Fidele Ntie-Kang ◽  
Dina Robaa ◽  
Wolfgang Sippl
Keyword(s):  
Natural Products ◽  
Virtual Screening ◽  
Experimental Validation ◽  
Chemical Space ◽  
Chemical Diversity ◽  
Computer Aided Drug Design ◽  
Drug Molecules ◽  
Success Stories ◽  
Computer Based ◽  
Experimental Approaches

AbstractThe development and application of computer-aided drug design/discovery (CADD) techniques (such as structured-base virtual screening, ligand-based virtual screening and neural networks approaches) are on the point of disintermediation in the pharmaceutical drug discovery processes. The application of these CADD methods are standing out positively as compared to other experimental approaches in the identification of hits. In order to venture into new chemical spaces, research groups are exploring natural products (NPs) for the search and identification of new hits and more efficient leads as well as the repurposing of approved NPs. The chemical space of NPs is continuously increasing as a result of millions of years of evolution of species and these data are mainly stored in the form of databases providing access to scientists around the world to conduct studies using them. Investigation of these NP databases with the help of CADD methodologies in combination with experimental validation techniques is essential to identify and propose new drug molecules. In this chapter, we highlight the importance of the chemical diversity of NPs as a source for potential drugs as well as some of the success stories of NP-derived candidates against important therapeutic targets. The focus is on studies that applied a healthy dose of the emerging CADD methodologies (structure-based, ligand-based and machine learning).

scholarly journals Bioactivity descriptors for uncharacterized chemical compounds

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Martino Bertoni ◽  
Miquel Duran-Frigola ◽  
Pau Badia-i-Mompel ◽  
Eduardo Pauls ◽  
Modesto Orozco-Ruiz ◽  
...  
Keyword(s):  
Small Molecules ◽  
Cellular Response ◽  
Chemical Space ◽  
Biological Properties ◽  
Experimental Information ◽  
Substantial Improvement ◽  
Biologically Relevant ◽  
Chemical Structures ◽  
Chemical Descriptors ◽  
Physicochemical And Structural Properties

AbstractChemical descriptors encode the physicochemical and structural properties of small molecules, and they are at the core of chemoinformatics. The broad release of bioactivity data has prompted enriched representations of compounds, reaching beyond chemical structures and capturing their known biological properties. Unfortunately, bioactivity descriptors are not available for most small molecules, which limits their applicability to a few thousand well characterized compounds. Here we present a collection of deep neural networks able to infer bioactivity signatures for any compound of interest, even when little or no experimental information is available for them. Our signaturizers relate to bioactivities of 25 different types (including target profiles, cellular response and clinical outcomes) and can be used as drop-in replacements for chemical descriptors in day-to-day chemoinformatics tasks. Indeed, we illustrate how inferred bioactivity signatures are useful to navigate the chemical space in a biologically relevant manner, unveiling higher-order organization in natural product collections, and to enrich mostly uncharacterized chemical libraries for activity against the drug-orphan target Snail1. Moreover, we implement a battery of signature-activity relationship (SigAR) models and show a substantial improvement in performance, with respect to chemistry-based classifiers, across a series of biophysics and physiology activity prediction benchmarks.

Natural Products as Potential Anti-Alzheimer Agents

2020 ◽  
Vol 27 (35) ◽  
pp. 5887-5917 ◽  
Author(s):  
Siva S. Panda ◽  
Nancy Jhanji
Keyword(s):  
Natural Products ◽  
Cognitive Function ◽  
Secondary Metabolites ◽  
Chemical Substances ◽  
Complex Chemical ◽  
Naturally Occurring ◽  
Beta Secretase ◽  
Β Amyloid ◽  
Prevention And Cure ◽  
Different Sources

Medicinal plants have curative properties due to the presence of various complex chemical substances of different composition, which are found as secondary metabolites in one or more parts of the plant. The diverse secondary metabolites play an important role in the prevention and cure of various diseases including neurodegenerative diseases like Alzheimer’s disease. Naturally occurring compounds such as flavonoids, polyphenols, alkaloids, and glycosides found in various parts of the plant and/or marine sources may potentially protect neurodegeneration as well as improve memory and cognitive function. Many natural compounds show anti-Alzheimer activity through specific pharmacological mechanisms like targeting β-amyloid, Beta-secretase 1 and Acetylcholinesterase. In this review, we have compiled more than 130 natural products with a broad diversity in the class of compounds, which were isolated from different sources showing anti- Alzheimer properties.

scholarly journals Recapitulation of the evolution of biosynthetic gene clusters reveals hidden chemical diversity on bacterial genomes

2015 ◽  
Author(s):  
Pablo Cruz-Morales ◽  
Christian E. Martínez-Guerrero ◽  
Marco A. Morales-Escalante ◽  
Luis Yáñez-Guerra ◽  
Johannes Florian Kopp ◽  
...  
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Streptomyces Coelicolor ◽  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Chemical Diversity ◽  
Biosynthetic Gene ◽  
Bacterial Genomes ◽  
Biosynthetic Gene Clusters

AbstractNatural products have provided humans with antibiotics for millennia. However, a decline in the pace of chemical discovery exerts pressure on human health as antibiotic resistance spreads. The empirical nature of current genome mining approaches used for natural products research limits the chemical space that is explored. By integration of evolutionary concepts related to emergence of metabolism, we have gained fundamental insights that are translated into an alternative genome mining approach, termed EvoMining. As the founding assumption of EvoMining is the evolution of enzymes, we solved two milestone problems revealing unprecedented conversions. First, we report the biosynthetic gene cluster of the ‘orphan’ metabolite leupeptin in Streptomyces roseus. Second, we discover an enzyme involved in formation of an arsenic-carbon bond in Streptomyces coelicolor and Streptomyces lividans. This work provides evidence that bacterial chemical repertoire is underexploited, as well as an approach to accelerate the discovery of novel antibiotics from bacterial genomes.

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