Marine Bioactive Compound Discovery by Combining Virtual with Actual Laboratory Experiments
A special issue of Marine Drugs (ISSN 1660-3397). This special issue belongs to the section "Marine Chemoecology for Drug Discovery".
Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 6168
Special Issue Editor
Interests: marine natural product; drug leads; pharmacological mechanism; marine microorganisms; cyanobacteria
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Discovering new marine bioactive compounds is a challenging and time-consuming process that involves multiple intricate steps. One approach to expedite the discovery of these compounds is integrating virtual experiments with actual laboratory experiments. In recent years, there has been an increasing interest in combining computational and experimental methods to accelerate the identification of novel marine bioactive compounds. This innovative strategy, known as "computational experimentation", harnesses the capabilities of advanced computational techniques, including molecular docking, molecular dynamics simulations, and machine learning algorithms, to efficiently and cost-effectively identify and prioritize potential bioactive compounds. Virtual experiments employ mathematical models and algorithms within computer simulations to predict compound properties and activities based on their chemical structures. Actual laboratory experiments involve performing physical tests to measure the effects of these compounds on biological targets, such as cells, enzymes, or organisms.
The integration of virtual and actual laboratory experiments presents a promising approach for the discovery of marine bioactive compounds, thereby enhancing the efficiency and effectiveness of the discovery process. This convergence can ultimately lead to the development of novel products with potential benefits for human health and well-being.
This Special Issue will focus on employing advances in all aspects of marine natural products (MNPs) for drug discovery and development by combining virtual and actual laboratory experiments, including the following aspects:
- Structurally novel and bioactive MNPs;
- Predictive models of structure and function of MNPs;
- Efficacy and pharmacological mechanisms of MNPs;
- Total synthesis, optimization, or biosynthesis of bioactive or novel MNPs;
- Research into marine medicinal biological resources.
Dr. Bin Yang
Guest Editor
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
- marine natural products
- biological activity
- biosynthetic pathway
- structure–activity relationships
- molecular docking
- network pharmacology
- experimental validation
- molecular networking
- molecular dynamics simulations
- machine learning algorithms
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