Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm

Skinnider, Michael A.; Dejong, Chris A.; Franczak, Brian C.; McNicholas, Paul D.; Magarvey, Nathan A.

doi:10.1186/s13321-017-0234-y

Cited by 39 publications

(28 citation statements)

References 52 publications

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“…NP are considered complex due to their number of asymmetric centers, their number of Sp3 carbon ratio in rings, and their number of ring junctions. Indeed, NP display in general more chiral centers than drugs, although their number of chiral centers to number to carbon atoms ratio may be lower (Gu et al, 2013;Skinnider et al, 2017). Although there is no clear evidence that this complexity is necessary for their biological activity (Firn and Jones, 2003), it greatly impacts their specificity (Clemons et al, 2011).…”

Section: Limitations Related To the Need Of Market-compatible Amountsmentioning

confidence: 99%

Unraveling Plant Natural Chemical Diversity for Drug Discovery Purposes

Lautie

Russo

Ducrot³

2020

Front. Pharmacol.

164

120

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The screening and testing of extracts against a variety of pharmacological targets in order to benefit from the immense natural chemical diversity is a concern in many laboratories worldwide. And several successes have been recorded in finding new actives in natural products, some of which have become new drugs or new sources of inspiration for drugs. But in view of the vast amount of research on the subject, it is surprising that not more drug candidates were found. In our view, it is fundamental to reflect upon the approaches of such drug discovery programs and the technical processes that are used, along with their inherent difficulties and biases. Based on an extensive survey of recent publications, we discuss the origin and the variety of natural chemical diversity as well as the strategies to having the potential to embrace this diversity. It seemed to us that some of the difficulties of the area could be related with the technical approaches that are used, so the present review begins with synthetizing some of the more used discovery strategies, exemplifying some key points, in order to address some of their limitations. It appears that one of the challenges of natural product-based drug discovery programs should be an easier access to renewable sources of plant-derived products. Maximizing the use of the data together with the exploration of chemical diversity while working on reasonable supply of natural product-based entities could be a way to answer this challenge. We suggested alternative ways to access and explore part of this chemical diversity with in vitro cultures. We also reinforced how important it was organizing and making available this worldwide knowledge in an "inventory" of natural products and their sources. And finally, we focused on strategies based on synthetic biology and syntheses that allow reaching industrial scale supply. Approaches based on the opportunities lying in untapped natural plant chemical diversity are also considered.

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Section: Limitations Related To the Need Of Market-compatible Amountsmentioning

confidence: 99%

Unraveling Plant Natural Chemical Diversity for Drug Discovery Purposes

Lautie

Russo

Ducrot³

2020

Front. Pharmacol.

164

120

View full text Add to dashboard Cite

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“…Duplicates were removed based on the InChIKey strings. It was reported that GRAPE/GARLIC algorithm and circular fingerprint (especially the FCFP6) show better performance than conventional fingerprint algorithms in natural product similarity search ( 35 , 36 ). Given that there is no open-accessed software for calculating GRAPE/GARLIC fingerprints, the FCFP6 fingerprint was used to code compounds for similarity calculation.…”

Section: Data Collection and Processingmentioning

confidence: 99%

NPASS: natural product activity and species source database for natural product research, discovery and tool development

Zeng

Zhang

et al. 2017

Nucleic Acids Research

195

120

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There has been renewed interests in the exploration of natural products (NPs) for drug discovery, and continuous investigations of the therapeutic claims and mechanisms of traditional and herbal medicines. In-silico methods have been employed for facilitating these studies. These studies and the optimization of in-silico algorithms for NP applications can be facilitated by the quantitative activity and species source data of the NPs. A number of databases collectively provide the structural and other information of ∼470 000 NPs, including qualitative activity information for many NPs, but only ∼4000 NPs are with the experimental activity values. There is a need for the activity and species source data of more NPs. We therefore developed a new database, NPASS (Natural Product Activity and Species Source) to complement other databases by providing the experimental activity values and species sources of 35 032 NPs from 25 041 species targeting 5863 targets (2946 proteins, 1352 microbial species and 1227 cell-lines). NPASS contains 446 552 quantitative activity records (e.g. IC50, Ki, EC50, GI50 or MIC mainly in units of nM) of 222 092 NP-target pairs and 288 002 NP-species pairs. NPASS, http://bidd2.nus.edu.sg/NPASS/, is freely accessible with its contents searchable by keywords, physicochemical property range, structural similarity, species and target search facilities.

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“…Library for the Enumeration of MOdular Natural Structures (LEMONS) is a software package originally designed to enumerate hypothetical modular natural product structures [25]. However, in this study, we utilized LEMONS to compare the structure similarity between two compounds based on Functional-Class Fingerprint (FCFP).…”

Section: Repurposing Processmentioning

confidence: 99%

A novel drug repurposing approach for non-small cell lung cancer using deep learning

Li¹,

Dai²,

Wang³

et al. 2020

PLoS ONE

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Drug repurposing is an attractive and pragmatic way offering reduced risks and development time in the complicated process of drug discovery. In the past, drug repurposing has been largely accidental and serendipitous. The most successful examples so far have not involved a systematic approach. Nowadays, remarkable advances in drugs, diseases and bioinformatic knowledge are offering great opportunities for designing novel drug repurposing approach through comprehensive understanding of drug information. In this study, we introduced a novel drug repurposing approach based on transcriptomic data and chemical structures using deep learning. One strong candidate for repurposing has been identified. Pimozide is an anti-dyskinesia agent that is used for the suppression of motor and phonic tics in patients with Tourette's Disorder. However, our pipeline proposed it as a strong candidate for treating non-small cell lung cancer. The cytotoxicity of pimozide against A549 cell lines has been validated.

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Comparative analysis of chemical similarity methods for modular natural products with a hypothetical structure enumeration algorithm

Cited by 39 publications

References 52 publications

Unraveling Plant Natural Chemical Diversity for Drug Discovery Purposes

Unraveling Plant Natural Chemical Diversity for Drug Discovery Purposes

NPASS: natural product activity and species source database for natural product research, discovery and tool development

A novel drug repurposing approach for non-small cell lung cancer using deep learning

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