scholarly journals Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases

Marine Drugs ◽  
2022 ◽  
Vol 20 (1) ◽  
pp. 53
Author(s):  
Laura Llorach-Pares ◽  
Alfons Nonell-Canals ◽  
Conxita Avila ◽  
Melchor Sanchez-Martinez
Keyword(s):  
Natural Products ◽  
Drug Design ◽  
Therapeutic Potential ◽  
Marine Invertebrate ◽  
In Silico Analysis ◽  
New Drugs ◽  
Computer Aided Drug Design ◽  
Marine Habitats ◽  
Computer Aided ◽  
Promising Line

Computer-aided drug design (CADD) techniques allow the identification of compounds capable of modulating protein functions in pathogenesis-related pathways, which is a promising line on drug discovery. Marine natural products (MNPs) are considered a rich source of bioactive compounds, as the oceans are home to much of the planet’s biodiversity. Biodiversity is directly related to chemodiversity, which can inspire new drug discoveries. Therefore, natural products (NPs) in general, and MNPs in particular, have been used for decades as a source of inspiration for the design of new drugs. However, NPs present both opportunities and challenges. These difficulties can be technical, such as the need to dive or trawl to collect the organisms possessing the compounds, or biological, due to their particular marine habitats and the fact that they can be uncultivable in the laboratory. For all these difficulties, the contributions of CADD can play a very relevant role in simplifying their study, since, for example, no biological sample is needed to carry out an in-silico analysis. Therefore, the amount of natural product that needs to be used in the entire preclinical and clinical study is significantly reduced. Here, we exemplify how this combination between CADD and MNPs can help unlock their therapeutic potential. In this study, using a set of marine invertebrate molecules, we elucidate their possible molecular targets and associated therapeutic potential, establishing a pipeline that can be replicated in future studies.

scholarly journals Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

2021 ◽  
Vol 22 (9) ◽  
pp. 4688
Author(s):  
Mootaz M. Salman ◽  
Zaid Al-Obaidi ◽  
Philip Kitchen ◽  
Andrea Loreto ◽  
Roslyn M. Bill ◽  
...  
Keyword(s):  
Drug Design ◽  
Neurodegenerative Diseases ◽  
Docking Studies ◽  
New Drugs ◽  
Computer Aided Drug Design ◽  
Biological Assays ◽  
Advantages And Disadvantages ◽  
Computer Aided ◽  
Research Challenge ◽  
The Cost

Neurodegenerative diseases (NDs) including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

scholarly journals Integration of Cassandra and Spark in Computer Aided Drug Design

2021 ◽  
pp. 68-73
Author(s):  
Nitha V R
Keyword(s):  
Big Data ◽  
Molecular Modeling ◽  
Drug Design ◽  
Programming Languages ◽  
New Drugs ◽  
Java Virtual Machine ◽  
Management Tool ◽  
Computer Aided Drug Design ◽  
Modeling Tool ◽  
Computer Aided

The primary purpose of this paper is to provide feasibility study of Cassandra and spark in Computer Aided Drug Design (CADD). The Apache Cassandra database is a big data management tool which can be used to store huge amount of data in different file formats. A huge database can be designed with details of all known molecules or compounds that are existing on earth. The information regarding the compounds such as selectivity, solubility, synthetic viability, affinity, adverse reactions, metabolism and environmental toxicity along with the 3 D structure of molecule can be stored in this big database. A data analytics tool “spark” can be efficiently used in mining and managing huge data stored in the database. Integrating big data in CADD helps in identifying the candidate drugs within minutes, not years. It may take eight to fifteen years to develop a new drug traditionally. Spark is written in Scala Programming Language which runs on Java Virtual Machine (JVM) and it supports Scala, Java and Python Programming languages .Cassandra can provide connectors to different programming languages, hence it’s very easy to integrate any other molecular modeling tool with Spark. A python based molecular modeling tool called Pymol can be easily implemented with Spark. CADD helps in identifying new drugs by computational means thus eliminating unnecessary cost incurred in chemical testing of drugs.

Computer-Aided Drug Design of Bioactive Natural Products

2015 ◽  
Vol 15 (18) ◽  
pp. 1780-1800 ◽  
Author(s):  
Veda Prachayasittikul ◽  
Apilak Worachartcheewan ◽  
Watshara Shoombuatong ◽  
Napat Songtawee ◽  
Saw Simeon ◽  
...  
Keyword(s):  
Natural Products ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Bioactive Natural Products ◽  
Computer Aided

From Natural Products to Drugs for Epimutation Computer-Aided Drug Design

2013 ◽  
Vol 170 (1) ◽  
pp. 164-175 ◽  
Author(s):  
Naveed A. Chikan ◽  
V. Bhavaniprasad ◽  
K. Anbarasu ◽  
Nadeem Shabir ◽  
Trupti N. Patel
Keyword(s):  
Natural Products ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Computer Aided

scholarly journals In Silico Research of New Therapeutics Rotenoids Derivatives Against Leishmania Amazonensis Infection

2021 ◽  
Author(s):  
Adrián Vicente-Barrueco ◽  
Ángel Carlos Román ◽  
Trinidad Ruiz-Téllez ◽  
Francisco Centeno
Keyword(s):  
Drug Design ◽  
In Silico ◽  
Combinatorial Library ◽  
Leishmania Amazonensis ◽  
New Drugs ◽  
Ethnobotanical Knowledge ◽  
Computer Aided Drug Design ◽  
Computer Aided ◽  
Key Enzyme ◽  
The One

Yearly, 1,500,000 cases of leishmaniasis are diagnosed, causing thousands of deaths. To advance in its therapy, we present an interdisciplinary protocol that unifies ethnobotanical knowledge of natural compounds and the latest bioinformatics advances to respond to an orphan disease such as leishmaniasis and specifically the one caused by Leishmania amazonensis. The use of ethnobotanical information serves as a basis for the development of new drugs, a field in which computer-aided drug design (CADD) has been a revolution. Taking this information from Amazonian communities, located in the area with the highest prevalence of this disease, a protocol has been designed to verify new leads. Moreover, a method has been developed that allows the evaluation of lead molecules, and the improvement of their affinity and specificity against therapeutic targets. Through this approach, deguelin has been identified as a good lead to treat the infection due to its potential as an ornithine decarboxylase (ODC) inhibitor, a key enzyme in Leishmania development. Using an in silico-generated combinatorial library followed by docking approaches, we have found deguelin derivatives with better affinity and specificity against ODC than the original compound, suggesting that this approach could be adapted for developing new drugs against leishmaniasis.

Computer Aided Drug Design Approaches for Identification of Novel Autotaxin (ATX) Inhibitors

2016 ◽  
Vol 23 (17) ◽  
pp. 1708-1724 ◽  
Author(s):  
Eleni Vrontaki ◽  
Georgia Melagraki ◽  
Eleanna Kaffe ◽  
Thomas Mavromoustakos ◽  
George Kokotos ◽  
...  
Keyword(s):  
Drug Design ◽  
Computer Aided Drug Design ◽  
Computer Aided

Prospects for Discovering the Secondary Metabolites of Cordyceps Sensu Lato by the Integrated Strategy

2020 ◽  
Vol 17 (2) ◽  
pp. 97-120
Author(s):  
Shabana Bibi ◽  
Yuan-Bing Wang ◽  
De-Xiang Tang ◽  
Mohammad Amjad Kamal ◽  
Hong Yu
Keyword(s):  
Drug Design ◽  
Biological Activities ◽  
Design Methods ◽  
Chinese Herbs ◽  
Active Metabolites ◽  
Computer Aided Drug Design ◽  
Design Concepts ◽  
Conventional Drug ◽  
Computer Aided ◽  
Design Techniques

: Some species of Cordyceps sensu lato are famous Chinese herbs with significant biological activities, often used as edible food and traditional medicine in China. Cordyceps represents the largest entomopathogenic group of fungi, including 40 genera and 1339 species in three families and incertae sedis of Hypocreales. Objective: Most of the Cordyceps-derivatives have been approved clinically for the treatment of various diseases such as diabetes, cancers, inflammation, cardiovascular, renal and neurological disorders and are used worldwide as supplements and herbal drugs, but there is still need for highly efficient Cordyceps-derived drugs for fatal diseases with approval of the U.S. Food and Drug Administration. Methods: Computer-aided drug design concepts could improve the discovery of putative Cordyceps- derived medicine within less time and low budget. The integration of computer-aided drug design methods with experimental validation has contributed to the successful discovery of novel drugs. Results: This review focused on modern taxonomy, active metabolites, and modern drug design techniques that could accelerate conventional drug design and discovery of Cordyceps s. l. Successful application of computer-aided drug design methods in Cordyceps research has been discussed. Conclusion: It has been concluded that computer-aided drug design techniques could influence the multiple target-focused drug design, because each metabolite of Cordyceps has shown significant activities for the various diseases with very few or no side effects.

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