A chemoinformatics approach to the discovery of lead-like molecules from marine and microbial sources en route to antitumor and antibiotic drugs.

Florbela Pereira,Diogo A R S Latino,Susana P Gaudêncio

doi:10.3390/md12020757

Florbela Pereira, Diogo A R S Latino + Show 1 more

Open Access

https://doi.org/10.3390/md12020757

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Abstract

The comprehensive information of small molecules and their biological activities in the PubChem database allows chemoinformatic researchers to access and make use of large-scale biological activity data to improve the precision of drug profiling. A Quantitative Structure–Activity Relationship approach, for classification, was used for the prediction of active/inactive compounds relatively to overall biological activity, antitumor and antibiotic activities using a data set of 1804 compounds from PubChem. Using the best classification models for antibiotic and antitumor activities a data set of marine and microbial natural products from the AntiMarin database were screened—57 and 16 new lead compounds for antibiotic and antitumor drug design were proposed, respectively. All compounds proposed by our approach are classified as non-antibiotic and non-antitumor compounds in the AntiMarin database. Recently several of the lead-like compounds proposed by us were reported as being active in the literature.

Highlights

Small organic molecules have proven to be important tools for biological systems research, but there is still much to learn from their use
We explored the application of machine learning (ML) techniques to exploit lead-like molecules en route to antitumor and antibiotic drugs from 1192 Marine Natural Products (MNPs) and MbNPs
The selected 16 lead antitumor MNPs and MbNPs from the AntiMarin database using the Random Forests (RFs) antitumor model. We proposed these MNPs as lead antitumor compounds no antitumor activity was recorded in the AntiMarin database

Summary

Introduction

Small organic molecules have proven to be important tools for biological systems research, but there is still much to learn from their use. From the 150,000 structures in the CRC Dictionary of Natural Products (NPs) only approximately 1% of them have at least one biological test results described in the MDL Drug Data Report database (MDDR) [1], which has been compiled by. The future seems very promising for this new branch since MNP chemists have already elucidated the chemical structure of over 22,000 novel compounds [3]. The success rate of drug discovery from the marine world is 1 drug per 3140 natural products described. This rate is approximately 1.7- to 3.3-fold better than the industry average (1 in 5000–10,000 tested compounds) [5]

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