Bioactive Extracts: Strategies to generate Diversified Natural Product Like Libraries

2022 ◽  
Vol 18 ◽  
Author(s):  
Meenu Aggarwal ◽  
Raman Singh ◽  
Priyanka Ahlawat ◽  
Kuldeep Singh
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Structural Diversity ◽  
New Drugs ◽  
The Novel ◽  
Chemical Derivatization ◽  
Molecular Fragments ◽  
Reverse Phase ◽  
Great Capacity ◽  
Compound Libraries

Abstract: Natural products have stimulated chemists owing to their abundant structural diversity and complexity. Indeed, natural products have performed an essential role, particularly in the cure of cancerous and infectious diseases, thereby posing medicinal researchers with a scope of unexplored chemotypes for the innovation of new drugs. Fusion of chemical derivatization and combinatorial synthesis forms the basis of the concept of chemo diversification of plants. Diverse libraries of natural product analogs are constructed through existing biological and chemical approaches using unique schemes to expand natural product frameworks. This review aims to present several approaches employed to offer innovative opportunities to synthesize NP-inspired compound libraries. Reactive molecular fragments present in most natural products are chemically converted to chemically engineered extracts (CEEs) or semisynthetic compounds constituting distinct libraries. Bio-guided isolation for natural products required vital tools like reverse phase chromatography and bioautographic assays. Different established strategies from DTS, BIOS, CtD, FOS, FBDD to Late-stage diversification facilitate the expansion of molecules with physicochemical properties. In particular, fragment-like natural products with novel skeletons may be used as preliminary points for chemical biology and medicinal chemistry programs with great capacity. In this review, we sum up how NPs have proven fruitful for the novel methodologies responsible for the diversification of complex natural products; thereby, it is worthy of going over the upcoming integration of natural products with combinatorial chemistry.

scholarly journals Cheminformatics Analysis of Natural Product Scaffolds: Comparison of Scaffolds Produced by Animals, Plants, Fungi and Bacteria

2020 ◽  
Author(s):  
Peter Ertl ◽  
Tim Schuhmann
Keyword(s):  
Natural Products ◽  
Natural Selection ◽  
Natural Product ◽  
Selection Process ◽  
Structural Features ◽  
New Drugs ◽  
Large Database ◽  
Biologically Relevant ◽  
Different Types ◽  
Selection Of

AbstractNatural products (NPs) have evolved over a very long natural selection process to form optimal interactions with biologically relevant macromolecules. NPs are therefore an extremely useful source of inspiration for the design of new drugs. In the present study we report the results of a cheminformatics analysis of a large database of NP structures focusing on their scaffolds. First, general differences between NP scaffolds and scaffolds from synthetic molecules are discussed, followed by a comparison of the properties of scaffolds produced by different types of organisms. Scaffolds produced by plants are the most complex and those produced by bacteria differ in many structural features from scaffolds produced by other organisms. The results presented here may be used as a guidance in selection of scaffolds for the design of novel NP-like bioactive structures or NP-inspired libraries.

scholarly journals Multiplexed screening of thousands of natural products for protein-ligand binding in native mass spectrometry

2021 ◽  
Author(s):  
Giang Nguyen ◽  
Jack Bennett ◽  
Sherrie Liu ◽  
Sarah Hancock ◽  
Daniel Winter ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Natural Products ◽  
Drug Discovery ◽  
Small Molecules ◽  
Natural Product ◽  
Drug Targets ◽  
Structural Diversity ◽  
Native Mass Spectrometry ◽  
Protein Targets ◽  
Rapid Measurement

The structural diversity of natural products offers unique opportunities for drug discovery, but challenges associated with their isolation and screening can hinder the identification of drug-like molecules from complex natural product extracts. Here we introduce a mass spectrometry-based approach that integrates untargeted metabolomics with multistage, high-resolution native mass spectrometry to rapidly identify natural products that bind to therapeutically relevant protein targets. By directly screening crude natural product extracts containing thousands of drug-like small molecules using a single, rapid measurement, novel natural product ligands of human drug targets could be identified without fractionation. This method should significantly increase the efficiency of target-based natural product drug discovery workflows.

scholarly journals Natural product drug discovery in the artificial intelligence era

2022 ◽  
Author(s):  
Fernanda I Saldivar-Gonzalez ◽  
Victor Daniel Aldas-Bulos ◽  
José Luis Medina-Franco ◽  
Fabien Plisson
Keyword(s):  
Artificial Intelligence ◽  
Natural Products ◽  
Drug Discovery ◽  
Natural Product ◽  
Drug Targets ◽  
Structural Diversity ◽  
Protein Drug ◽  
Privileged Structures

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even...

scholarly journals Natural Product Scores and Fingerprints Extracted from Artificial Neural Networks.

2021 ◽  
Author(s):  
Janosch Menke ◽  
Joana Massa ◽  
Oliver Koch
Keyword(s):  
Neural Networks ◽  
Natural Products ◽  
Artificial Neural Networks ◽  
Virtual Screening ◽  
Natural Product ◽  
Recent Work ◽  
The Novel ◽  
Multi Layer Perceptron ◽  
Output Layer ◽  
Depth Analysis

<div>Due to its desirable properties, natural products are an important ligand class for medicinal chemists. However, due to their structural distinctiveness, traditional cheminformatic approaches, like ligand-based virtual screening, often perform worse for natural products. Based on our recent work, we evaluated the ability of neural networks to generate fingerprints more appropriate for the use with natural products. A manually curated dataset of natural products and synthetic decoys was used to train a multi-layer perceptron network and an autoencoder-like network. An in-depth analysis showed that the extracted natural product specific neural fingerprints outperforms traditional as well as natural product specific fingerprints on three datasets. Further, we explore how the activation from the output layer of a network can work as a novel natural product likeness score. Overall two natural product specific datasets were generated, which are publicly available together with the code to create the fingerprints and the novel natural product likeness score.<br></div>

Multiplexed screening of thousands of natural products for protein-ligand binding in native mass spectrometry

2021 ◽  
Author(s):  
Giang Nguyen ◽  
Jack Bennett ◽  
Sherrie Liu ◽  
Sarah Hancock ◽  
Daniel Winter ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Natural Products ◽  
Drug Discovery ◽  
Small Molecules ◽  
Natural Product ◽  
Drug Targets ◽  
Structural Diversity ◽  
Native Mass Spectrometry ◽  
Protein Targets ◽  
Rapid Measurement

The structural diversity of natural products offers unique opportunities for drug discovery, but challenges associated with their isolation and screening can hinder the identification of drug-like molecules from complex natural product extracts. Here we introduce a mass spectrometry-based approach that integrates untargeted metabolomics with multistage, high-resolution native mass spectrometry to rapidly identify natural products that bind to therapeutically relevant protein targets. By directly screening crude natural product extracts containing thousands of drug-like small molecules using a single, rapid measurement, novel natural product ligands of human drug targets could be identified without fractionation. This method should significantly increase the efficiency of target-based natural product drug discovery workflows.

scholarly journals Structure-Based Identification of Potent Natural Product Chemotypes as Cannabinoid Receptor 1 Inverse Agonists

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2630 ◽  
Author(s):  
Pankaj Pandey ◽  
Kuldeep Roy ◽  
Haining Liu ◽  
Guoyi Ma ◽  
Sara Pettaway ◽  
...  
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Binding Affinity ◽  
Cannabinoid Receptor ◽  
New Drugs ◽  
In Vitro Screening ◽  
Cannabinoid Receptor 1 ◽  
Cardiometabolic Disorders ◽  
Cb1 Antagonists

Natural products are an abundant source of potential drugs, and their diversity makes them a rich and viable prospective source of bioactive cannabinoid ligands. Cannabinoid receptor 1 (CB1) antagonists are clinically established and well documented as potential therapeutics for treating obesity, obesity-related cardiometabolic disorders, pain, and drug/substance abuse, but their associated CNS-mediated adverse effects hinder the development of potential new drugs and no such drug is currently on the market. This limitation amplifies the need for new agents with reduced or no CNS-mediated side effects. We are interested in the discovery of new natural product chemotypes as CB1 antagonists, which may serve as good starting points for further optimization towards the development of CB1 therapeutics. In search of new chemotypes as CB1 antagonists, we screened the in silico purchasable natural products subset of the ZINC12 database against our reported CB1 receptor model using the structure-based virtual screening (SBVS) approach. A total of 18 out of 192 top-scoring virtual hits, selected based on structural diversity and key protein–ligand interactions, were purchased and subjected to in vitro screening in competitive radioligand binding assays. The in vitro screening yielded seven compounds exhibiting >50% displacement at 10 μM concentration, and further binding affinity (Ki and IC50) and functional data revealed compound 16 as a potent and selective CB1 inverse agonist (Ki = 121 nM and EC50 = 128 nM) while three other compounds—2, 12, and 18—were potent but nonselective CB1 ligands with low micromolar binding affinity (Ki). In order to explore the structure–activity relationship for compound 16, we further purchased compounds with >80% similarity to compound 16, screened them for CB1 and CB2 activities, and found two potent compounds with sub-micromolar activities. Most importantly, these bioactive compounds represent structurally new natural product chemotypes in the area of cannabinoid research and could be considered for further structural optimization as CB1 ligands.

scholarly journals Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

2021 ◽  
Vol 9 ◽  
Author(s):  
Kauê Santana ◽  
Lidiane Diniz do Nascimento ◽  
Anderson Lima e Lima ◽  
Vinícius Damasceno ◽  
Claudio Nahum ◽  
...  
Keyword(s):  
Natural Products ◽  
Virtual Screening ◽  
Bioactive Compounds ◽  
Chemical Space ◽  
Structural Diversity ◽  
Industrial Applications ◽  
Bioactive Molecules ◽  
Natural Sources ◽  
Compound Libraries ◽  
Pharmacokinetic Properties

Natural products are continually explored in the development of new bioactive compounds with industrial applications, attracting the attention of scientific research efforts due to their pharmacophore-like structures, pharmacokinetic properties, and unique chemical space. The systematic search for natural sources to obtain valuable molecules to develop products with commercial value and industrial purposes remains the most challenging task in bioprospecting. Virtual screening strategies have innovated the discovery of novel bioactive molecules assessing in silico large compound libraries, favoring the analysis of their chemical space, pharmacodynamics, and their pharmacokinetic properties, thus leading to the reduction of financial efforts, infrastructure, and time involved in the process of discovering new chemical entities. Herein, we discuss the computational approaches and methods developed to explore the chemo-structural diversity of natural products, focusing on the main paradigms involved in the discovery and screening of bioactive compounds from natural sources, placing particular emphasis on artificial intelligence, cheminformatics methods, and big data analyses.

scholarly journals Exploring novel secondary metabolites from natural products using pre-processed mass spectral data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyun Woo Kim ◽  
Seong Yeon Choi ◽  
Hyeon Seok Jang ◽  
Byeol Ryu ◽  
Sang Hyun Sung ◽  
...  
Keyword(s):  
Natural Products ◽  
Secondary Metabolites ◽  
Natural Product ◽  
Spectral Data ◽  
Structural Diversity ◽  
Natural Material ◽  
Natural Sources ◽  
Mass Spectral ◽  
Aerial Parts ◽  
Similar Chemical

AbstractMany natural product chemists are working to identify a wide variety of novel secondary metabolites from natural materials and are eager to avoid repeatedly discovering known compounds. Here, we developed liquid chromatography/mass spectrometry (LC/MS) data-processing protocols for assessing high-throughput spectral data from natural sources and scoring the novelty of unknown metabolites from natural products. This approach automatically produces representative MS spectra (RMSs) corresponding to single secondary metabolites in natural sources. In this study, we used the RMSs of Agrimonia pilosa roots and aerial parts as models to reveal the structural similarities of their secondary metabolites and identify novel compounds, as well as isolation of three types of nine new compounds including three pilosanidin- and four pilosanol-type molecules and two 3-hydroxy-3-methylglutaryl (HMG)-conjugated chromones. Furthermore, we devised a new scoring system, the Fresh Compound Index (FCI), which grades the novelty of single secondary metabolites from a natural material using an in-house database constructed from 466 representative medicinal plants from East Asian countries. We expect that the FCIs of RMSs in a sample will help natural product chemists to discover other compounds of interest with similar chemical scaffolds or novel compounds and will provide insights relevant to the structural diversity and novelty of secondary metabolites in natural products.

scholarly journals Guided by evolution: from biology oriented synthesis to pseudo natural products

2020 ◽  
Vol 37 (11) ◽  
pp. 1497-1510 ◽  
Author(s):  
Gregor S. Cremosnik ◽  
Jie Liu ◽  
Herbert Waldmann
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Historical Context ◽  
Compound Libraries ◽  
Synthetic Methodologies

This review provides an overview and historical context to two concepts for the design of natural product-inspired compound libraries and highlights the used synthetic methodologies.

scholarly journals Coupling Mass Spectral and Genomic Information to Improve Bacterial Natural Product Discovery Workflows

Marine Drugs ◽  
2021 ◽  
Vol 19 (3) ◽  
pp. 142 ◽  
Author(s):  
Max Crüsemann
Keyword(s):  
Mass Spectrometry ◽  
Natural Products ◽  
Natural Product ◽  
Large Scale ◽  
Genome Mining ◽  
Structural Diversity ◽  
Gene Clusters ◽  
Genomic Information ◽  
Mass Spectral ◽  
Natural Product Discovery

Bacterial natural products possess potent bioactivities and high structural diversity and are typically encoded in biosynthetic gene clusters. Traditional natural product discovery approaches rely on UV- and bioassay-guided fractionation and are limited in terms of dereplication. Recent advances in mass spectrometry, sequencing and bioinformatics have led to large-scale accumulation of genomic and mass spectral data that is increasingly used for signature-based or correlation-based mass spectrometry genome mining approaches that enable rapid linking of metabolomic and genomic information to accelerate and rationalize natural product discovery. In this mini-review, these approaches are presented, and discovery examples provided. Finally, future opportunities and challenges for paired omics-based natural products discovery workflows are discussed.

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