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Marine Drug Discovery through Computer-Aided Approaches

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A special issue of Marine Drugs (ISSN 1660-3397).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 40658

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Dr. Susana P. Gaudencio

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Guest Editor

UCIBIO—Applied Biomolecular Sciences Unit, Chemistry Department, Blue Biotechnology and Biomedicine Lab, Nova School of Science and Technology, Nova University of Lisbon, Lisbon, Portugal
Interests: marine natural products; structure elucidation; secondary metabolites; blue biotechnology; bioactive compounds from actinomycetes; drug discovery and biotechnological applications
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Dr. Florbela Pereira

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Guest Editor

LAQV, Chemistry Department, NOVA Faculty of Sciences and Technology, NOVA University of Lisbon, 2819-516 Lisbon, Portugal
Interests: chemoinformatics; machine learning and data mining tecniques; quantitative structure–activity relationship (QSAR); quantitative structure–property relationship (QSPR); big data; DFT-calculated properties; marine natural products (MNPs); virtual screening; nuclear magnetic resonance (NMR); dereplication; drug discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer-Aided Ligand- and Structure-based methodologies are an evolving field in the discovery of Marine Drugs. Computational approaches and chemistry simulation methods, using bioinformatics and chemoinformatics tools, applications and databases, can be successfully used in the discovering, designing, and development of new chemical agents for therapeutic purposes, by assisting in the structure elucidation of secondary metabolites; repurposing known marine natural products (MNPs) for new therapeutic targets, identifying novel hits or leads against selected therapeutic targets, revealing mechanisms of action and supporting medicinal chemistry lead optimization programs.

This Special Issue of Marine Drugs entitled “Marine Drug Discovery through Computer-Aided Approaches” aims to provide a comprehensive overview of the great variety of existing and advanced Computer-Aided Approaches for the discovery and identification of molecular agents with added value and health-promoting properties for the development of biotechnological and medical applications.

As guest editors, we invite colleagues performing research on computer – aided drug discovery to contribute with your interesting papers to this Special Issue of Marine Drugs.

Dr. Susana P Gaudencio
Dr. Florbela Pereira
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Marine Drugs is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Chemoinformatics
Bioinformatics
Dereplication
Machine Learning Techniques
MNPs Databases
Chemical Space
Biological Space
Quantitative Structure–Activity Relationship (QSAR)
Molecular Docking
Computer-Aided Design Design (CADD)
Computer–Assisted Structure Elucidation (CASE)
Drug Discovery
Drug repurposing

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Related Special Issues

Virtual Screening of Marine Natural Products in Marine Drugs (3 articles)
Chemoinformatics for Marine Drug Discovery in Marine Drugs (1 article)

Published Papers (10 papers)

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Editorial

Jump to: Research

5 pages, 242 KiB

Open AccessEditorial

Marine Drug Discovery through Computer-Aided Approaches

by Susana P. Gaudêncio and Florbela Pereira

Mar. Drugs 2023, 21(8), 452; https://doi.org/10.3390/md21080452 - 17 Aug 2023

Cited by 1 | Viewed by 1755

Abstract

Besides the importance of our oceans as oxygen factories, food providers, shipping pathways, and tourism enablers, oceans hide an unprecedented wealth of opportunities [...] Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

Research

Jump to: Editorial

20 pages, 6386 KiB

Open AccessArticle

Predicting Antifouling Activity and Acetylcholinesterase Inhibition of Marine-Derived Compounds Using a Computer-Aided Drug Design Approach

by Susana P. Gaudêncio and Florbela Pereira

Mar. Drugs 2022, 20(2), 129; https://doi.org/10.3390/md20020129 - 8 Feb 2022

Cited by 12 | Viewed by 4316

Abstract

Biofouling is the undesirable growth of micro- and macro-organisms on artificial water-immersed surfaces, which results in high costs for the prevention and maintenance of this process (billion €/year) for aquaculture, shipping and other industries that rely on coastal and off-shore infrastructure. To date, there are still no sustainable, economical and environmentally safe solutions to overcome this challenging phenomenon. A computer-aided drug design (CADD) approach comprising ligand- and structure-based methods was explored for predicting the antifouling activities of marine natural products (MNPs). In the CADD ligand-based method, 141 organic molecules extracted from the ChEMBL database and literature with antifouling screening data were used to build the quantitative structure–activity relationship (QSAR) classification model. An overall predictive accuracy score of up to 71% was achieved with the best QSAR model for external and internal validation using test and training sets. A virtual screening campaign of 14,492 MNPs from Encinar’s website and 14 MNPs that are currently in the clinical pipeline was also carried out using the best QSAR model developed. In the CADD structure-based approach, the 125 MNPs that were selected by the QSAR approach were used in molecular docking experiments against the acetylcholinesterase enzyme. Overall, 16 MNPs were proposed as the most promising marine drug-like leads as antifouling agents, e.g., macrocyclic lactam, macrocyclic alkaloids, indole and pyridine derivatives. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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18 pages, 2806 KiB

Open AccessArticle

Uncovering the Bioactive Potential of a Cyanobacterial Natural Products Library Aided by Untargeted Metabolomics

by Leonor Ferreira, João Morais, Marco Preto, Raquel Silva, Ralph Urbatzka, Vitor Vasconcelos and Mariana Reis

Mar. Drugs 2021, 19(11), 633; https://doi.org/10.3390/md19110633 - 12 Nov 2021

Cited by 18 | Viewed by 4996

Abstract

The Blue Biotechnology and Ecotoxicology Culture Collection (LEGE-CC) holds a vast number of cyanobacteria whose chemical richness is still largely unknown. To expedite its bioactivity screening we developed a natural products library. Sixty strains and four environmental samples were chromatographed, using a semiautomatic HPLC system, yielding 512 fractions that were tested for their cytotoxic activity against 2D and 3D models of human colon carcinoma (HCT 116), and non-cancerous cell line hCMEC/D3. Six fractions showed high cytotoxicity against 2D and 3D cell models (group A), and six other fractions were selected by their effects on 3D cells (group B). The metabolome of each group was organized and characterized using the MolNetEnhancer workflow, and its processing with MetaboAnalyst allowed discrimination of the mass features with the highest fold change, and thus the ones that might be bioactive. Of those, mass features without precedented identification were mostly found in group A, indicating seven possible novel bioactive molecules, alongside in silico putative annotation of five cytotoxic compounds. Manual dereplication of group B tentatively identified nine pheophytin and pheophorbide derivatives. Our approach enabled the selection of 7 out of 60 cyanobacterial strains for anticancer drug discovery, providing new data concerning the chemical composition of these cyanobacteria. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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39 pages, 11624 KiB

Open AccessEditor’s ChoiceArticle

Application of Networking Approaches to Assess the Chemical Diversity, Biogeography, and Pharmaceutical Potential of Verongiida Natural Products

by James Lever, Robert Brkljača, Colin Rix and Sylvia Urban

Mar. Drugs 2021, 19(10), 582; https://doi.org/10.3390/md19100582 - 18 Oct 2021

Cited by 6 | Viewed by 3791

Abstract

This study provides a review of all isolated natural products (NPs) reported for sponges within the order Verongiida (1960 to May 2020) and includes a comprehensive compilation of their geographic and physico-chemical parameters. Physico-chemical parameters were used in this study to infer pharmacokinetic properties as well as the potential pharmaceutical potential of NPs from this order of marine sponge. In addition, a network analysis for the NPs produced by the Verongiida sponges was applied to systematically explore the chemical space relationships between taxonomy, secondary metabolite and drug score variables, allowing for the identification of differences and correlations within a dataset. The use of scaffold networks as well as bipartite relationship networks provided a platform to explore chemical diversity as well as the use of chemical similarity networks to link pharmacokinetic properties with structural similarity. This study paves the way for future applications of network analysis procedures in the field of natural products for any order or family. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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16 pages, 5172 KiB

Open AccessArticle

Investigation of Marine-Derived Natural Products as Raf Kinase Inhibitory Protein (RKIP)-Binding Ligands

by Shraddha Parate, Vikas Kumar, Jong Chan Hong and Keun Woo Lee

Mar. Drugs 2021, 19(10), 581; https://doi.org/10.3390/md19100581 - 18 Oct 2021

Cited by 5 | Viewed by 3514

Abstract

Raf kinase inhibitory protein (RKIP) is an essential regulator of the Ras/Raf-1/MEK/ERK signaling cascade and functions by directly interacting with the Raf-1 kinase. The abnormal expression of RKIP is linked with numerous diseases including cancers, Alzheimer’s and diabetic nephropathy. Interestingly, RKIP also plays an indispensable role as a tumor suppressor, thus making it an attractive therapeutic target. To date, only a few small molecules have been reported to modulate the activity of RKIP, and there is a need to explore additional scaffolds. In order to achieve this objective, a pharmacophore model was generated that explores the features of locostatin, the most potent RKIP modulator. Correspondingly, the developed model was subjected to screening, and the mapped compounds from Marine Natural Products (MNP) library were retrieved. The mapped MNPs after ensuing drug-likeness filtration were escalated for molecular docking, where locostatin was regarded as a reference. The MNPs exhibiting higher docking scores than locostatin were considered for molecular dynamics simulations, and their binding affinity towards RKIP was computed via MM/PBSA. A total of five molecules revealed significantly better binding free energy scores than compared to locostatin and, therefore, were reckoned as hits. The hits from the present in silico investigation could act as potent RKIP modulators and disrupt interactions of RKIP with its binding proteins. Furthermore, the identification of potent modulators from marine natural habitat can act as a future drug-discovery source. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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9 pages, 1774 KiB

Open AccessArticle

Saliniquinone Derivatives, Saliniquinones G−I and Heraclemycin E, from the Marine Animal-Derived Nocardiopsis aegyptia HDN19-252

by Luning Zhou, Xuedong Chen, Chunxiao Sun, Yimin Chang, Xiaofei Huang, Tianjiao Zhu, Guojian Zhang, Qian Che and Dehai Li

Mar. Drugs 2021, 19(10), 575; https://doi.org/10.3390/md19100575 - 14 Oct 2021

Cited by 8 | Viewed by 2573

Abstract

Four new anthraquinone derivatives, namely saliniquinones G−I (1–3) and heraclemycin E (4), were obtained from the Antarctic marine-derived actinomycete Nocardiopsis aegyptia HDN19-252, guided by the Global Natural Products Social (GNPS) molecular networking platform. Their structures, including absolute configurations, were elucidated by extensive NMR, MS, and ECD analyses. Compounds 1 and 2 showed promising inhibitory activity against six tested bacterial strains, including methicillin-resistant coagulase-negative staphylococci (MRCNS), with MIC values ranging from 3.1 to 12.5 μM. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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30 pages, 4545 KiB

Open AccessArticle

Efficacy of Chondroprotective Food Supplements Based on Collagen Hydrolysate and Compounds Isolated from Marine Organisms

by Thomas Eckert, Mahena Jährling-Butkus, Helen Louton, Monika Burg-Roderfeld, Ruiyan Zhang, Ning Zhang, Karsten Hesse, Athanasios K. Petridis, Tibor Kožár, Jürgen Steinmeyer, Roland Schauer, Peter Engelhard, Anna Kozarova, John W. Hudson and Hans-Christian Siebert

Mar. Drugs 2021, 19(10), 542; https://doi.org/10.3390/md19100542 - 26 Sep 2021

Cited by 18 | Viewed by 5309

Abstract

Osteoarthritis belongs to the most common joint diseases in humans and animals and shows increased incidence in older patients. The bioactivities of collagen hydrolysates, sulfated glucosamine and a special fatty acid enriched dog-food were tested in a dog patient study of 52 dogs as potential therapeutic treatment options in early osteoarthritis. Biophysical, biochemical, cell biological and molecular modeling methods support that these well-defined substances may act as effective nutraceuticals. Importantly, the applied collagen hydrolysates as well as sulfated glucosamine residues from marine organisms were strongly supported by both an animal model and molecular modeling of intermolecular interactions. Molecular modeling of predicted interaction dynamics was evaluated for the receptor proteins MMP-3 and ADAMTS-5. These proteins play a prominent role in the maintenance of cartilage health as well as innate and adapted immunity. Nutraceutical data were generated in a veterinary clinical study focusing on mobility and agility. Specifically, key clinical parameter (MMP-3 and TIMP-1) were obtained from blood probes of German shepherd dogs with early osteoarthritis symptoms fed with collagen hydrolysates. Collagen hydrolysate, a chondroprotective food supplement was examined by high resolution NMR experiments. Molecular modeling simulations were used to further characterize the interaction potency of collagen fragments and glucosamines with protein receptor structures. Potential beneficial effects of collagen hydrolysates, sulfated glycans (i.e., sulfated glucosamine from crabs and mussels) and lipids, especially, eicosapentaenoic acid (extracted from fish oil) on biochemical and physiological processes are discussed here in the context of human and veterinary medicine. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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14 pages, 3203 KiB

Open AccessArticle

Solid-Phase Extraction Embedded Dialysis (SPEED), an Innovative Procedure for the Investigation of Microbial Specialized Metabolites

by Phuong-Y. Mai, Géraldine Le Goff, Erwan Poupon, Philippe Lopes, Xavier Moppert, Bernard Costa, Mehdi A. Beniddir and Jamal Ouazzani

Mar. Drugs 2021, 19(7), 371; https://doi.org/10.3390/md19070371 - 26 Jun 2021

Cited by 3 | Viewed by 3264

Abstract

Solid-phase extraction embedded dialysis (SPEED technology) is an innovative procedure developed to physically separate in-situ, during the cultivation, the mycelium of filament forming microorganisms, such as actinomycetes and fungi, and the XAD-16 resin used to trap the secreted specialized metabolites. SPEED consists of an external nylon cloth and an internal dialysis tube containing the XAD resin. The dialysis barrier selects the molecular weight of the trapped compounds, and prevents the aggregation of biomass or macromolecules on the XAD beads. The external nylon promotes the formation of a microbial biofilm, making SPEED a biofilm supported cultivation process. SPEED technology was applied to the marine Streptomyces albidoflavus 19-S21, isolated from a core of a submerged Kopara sampled at 20 m from the border of a saltwater pond. The chemical space of this strain was investigated effectively using a dereplication strategy based on molecular networking and in-depth chemical analysis. The results highlight the impact of culture support on the molecular profile of Streptomyces albidoflavus 19-S21 secondary metabolites. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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18 pages, 3392 KiB

Open AccessArticle

Potency- and Selectivity-Enhancing Mutations of Conotoxins for Nicotinic Acetylcholine Receptors Can Be Predicted Using Accurate Free-Energy Calculations

by Dana Katz, Michael A. DiMattia, Dan Sindhikara, Hubert Li, Nikita Abraham and Abba E. Leffler

Mar. Drugs 2021, 19(7), 367; https://doi.org/10.3390/md19070367 - 25 Jun 2021

Cited by 12 | Viewed by 5896

Abstract

Nicotinic acetylcholine receptor (nAChR) subtypes are key drug targets, but it is challenging to pharmacologically differentiate between them because of their highly similar sequence identities. Furthermore, α-conotoxins (α-CTXs) are naturally selective and competitive antagonists for nAChRs and hold great potential for treating nAChR disorders. Identifying selectivity-enhancing mutations is the chief aim of most α-CTX mutagenesis studies, although doing so with traditional docking methods is difficult due to the lack of α-CTX/nAChR crystal structures. Here, we use homology modeling to predict the structures of α-CTXs bound to two nearly identical nAChR subtypes, α3β2 and α3β4, and use free-energy perturbation (FEP) to re-predict the relative potency and selectivity of α-CTX mutants at these subtypes. First, we use three available crystal structures of the nAChR homologue, acetylcholine-binding protein (AChBP), and re-predict the relative affinities of twenty point mutations made to the α-CTXs LvIA, LsIA, and GIC, with an overall root mean square error (RMSE) of 1.08 ± 0.15 kcal/mol and an R² of 0.62, equivalent to experimental uncertainty. We then use AChBP as a template for α3β2 and α3β4 nAChR homology models bound to the α-CTX LvIA and re-predict the potencies of eleven point mutations at both subtypes, with an overall RMSE of 0.85 ± 0.08 kcal/mol and an R² of 0.49. This is significantly better than the widely used molecular mechanics—generalized born/surface area (MM-GB/SA) method, which gives an RMSE of 1.96 ± 0.24 kcal/mol and an R² of 0.06 on the same test set. Next, we demonstrate that FEP accurately classifies α3β2 nAChR selective LvIA mutants while MM-GB/SA does not. Finally, we use FEP to perform an exhaustive amino acid mutational scan of LvIA and predict fifty-two mutations of LvIA to have greater than 100X selectivity for the α3β2 nAChR. Our results demonstrate the FEP is well-suited to accurately predict potency- and selectivity-enhancing mutations of α-CTXs for nAChRs and to identify alternative strategies for developing selective α-CTXs. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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20 pages, 4464 KiB

Open AccessArticle

In Vitro and In Silico Characterization of G-Protein Coupled Receptor (GPCR) Targets of Phlorofucofuroeckol-A and Dieckol

by Pradeep Paudel, Su Hui Seong, Se Eun Park, Jong Hoon Ryu, Hyun Ah Jung and Jae Sue Choi

Mar. Drugs 2021, 19(6), 326; https://doi.org/10.3390/md19060326 - 4 Jun 2021

Cited by 7 | Viewed by 3421

Abstract

Phlorotannins are polyphenolic compounds in marine alga, especially the brown algae. Among numerous phlorotannins, dieckol and phlorofucofuroeckol-A (PFF-A) are the major ones and despite a wider biological activity profile, knowledge of the G protein-coupled receptor (GPCR) targets of these phlorotannins is lacking. This study explores prime GPCR targets of the two phlorotannins. In silico proteocheminformatics modeling predicted twenty major protein targets and in vitro functional assays showed a good agonist effect at the α2C adrenergic receptor (α_2CAR) and an antagonist effect at the adenosine 2A receptor (A_2AR), δ-opioid receptor (δ-OPR), glucagon-like peptide-1 receptor (GLP-1R), and 5-hydroxytryptamine 1A receptor (5-TH_1AR) of both phlorotannins. Besides, dieckol showed an antagonist effect at the vasopressin 1A receptor (V_1AR) and PFF-A showed a promising agonist effect at the cannabinoid 1 receptor and an antagonist effect at V_1AR. In silico molecular docking simulation enabled us to investigate and identify distinct binding features of these phlorotannins to the target proteins. The docking results suggested that dieckol and PFF-A bind to the crystal structures of the proteins with good affinity involving key interacting amino acid residues comparable to reference ligands. Overall, the present study suggests α_2CAR, A_2AR, δ-OPR, GLP-1R, 5-TH_1AR, CB₁R, and V_1AR as prime receptor targets of dieckol and PFF-A. Full article

(This article belongs to the Special Issue Marine Drug Discovery through Computer-Aided Approaches)

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