Computational Methodologies in the Exploration of Marine Natural Product Leads

Abstract

Computational methodologies are assisting the exploration of marine natural products (MNPs) to make the discovery of new leads more efficient, to repurpose known MNPs, to target new metabolites on the basis of genome analysis, to reveal mechanisms of action, and to optimize leads. In silico efforts in drug discovery of NPs have mainly focused on two tasks: dereplication and prediction of bioactivities. The exploration of new chemical spaces and the application of predicted spectral data must be included in new approaches to select species, extracts, and growth conditions with maximum probabilities of medicinal chemistry novelty. In this review, the most relevant current computational dereplication methodologies are highlighted. Structure-based (SB) and ligand-based (LB) chemoinformatics approaches have become essential tools for the virtual screening of NPs either in small datasets of isolated compounds or in large-scale databases. The most common LB techniques include Quantitative Structure–Activity Relationships (QSAR), estimation of drug likeness, prediction of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, similarity searching, and pharmacophore identification. Analogously, molecular dynamics, docking and binding cavity analysis have been used in SB approaches. Their significance and achievements are the main focus of this review.

Free Marine Natural Products Databases for Biotechnology and Bioengineering

“…Compound dereplication is one of the big hurdles in the discovery of MNPs. To achieve a simpler, faster, and more effective compound dereplication, the collected data in these databases include computational data from bioinformatics, compound curation and compilation, and experimental data from UV spectroscopy, mass spectroscopy, and nuclear magnetic resonance (NMR) . These databases deliver crucial information to the scientific community to discover new MNPs.…”

“…When these databases are available for download, the compounds are commonly available in various formats suitable for bioprospecting studies, where data are used in data mining, cheminformatics, computational chemistry, and big data analysis. The most common computational applications are in molecular docking, molecular dynamics simulations, high‐throughput virtual screening, and other cheminformatics’ tools to extract and calculate useful data …”

“…MNP databases are currently of utmost importance in blue biotechnology, mainly in compound dereplication . Notwithstanding, the enormous potential of using these databases in discovering new compounds of economic interest is still underexploited in biotechnology and bioengineering, but already extensively used in the pharmaceutical industry.…”

“…MNPs have already been proved successful as drugs, with eight approved drugs currently in the market and at least 12 in clinical trials . MNP research for bioactive compounds is very fruitful and from 1985 to 2012 at least 4196 bioactive compounds were described .…”

“…Data could be applied not only to the discovery of new bioactive compounds but also to new materials and high‐value molecules, e.g., pigments from microalgae . An important issue that could be attenuated with more accessible marine product databases is MNP bioprospecting and dereplication . Dereplication is a fundamental step in compound identification as it is crucial to understand which compounds are new or have been already found in other organisms, and to prevent reisolation and recharacterization of known bioactive compounds .…”