scholarly journals Virtual screening strategies in drug design – methods and applications

2011 ◽  
Vol 3 ◽  
pp. 249-264 ◽  
Author(s):  
Ewa Bielska ◽  
Xavier Lucas ◽  
Anna Czerwoniec ◽  
Joanna M. Kasprzak ◽  
Katarzyna H. Kaminska ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Design Methods ◽  
Screening Strategies

scholarly journals Virtual Screening Strategies in Drug Design

2012 ◽  
Vol 4 (6) ◽  
Author(s):  
Ricardo P. Rodrigues ◽  
Susimaire P. Mantoani ◽  
Jonathan R. de Almeida ◽  
Flávio Roberto Pinsetta ◽  
Evandro P. Semighini ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Screening Strategies

Harnessing the Capability of CADD Methods in the Prediction of Anti-COVID Drug Likeliness

2021 ◽  
pp. 269-287
Author(s):  
Shubhra Chaturvedi ◽  
Vishaka Chaudhary ◽  
Tina Klauss ◽  
Philippe Barthélémy ◽  
Anil Kumar Mishra
Keyword(s):  
Psychological Distress ◽  
Virtual Screening ◽  
Drug Design ◽  
Ab Initio ◽  
Social Economic ◽  
Design Methods ◽  
Drug Molecule ◽  
Computer Aided Drug Design ◽  
The Social ◽  
Computer Aided

The COVID-19 pandemic has claimed many lives and added to the social, economic, and psychological distress. The contagious disease has quickly spread to almost 200 countries following the regional outbreak in China. As the number of infected populations increases exponentially, there is a pressing demand for anti-COVID drugs and vaccines. Virtual screening provides possible leads while extensively cutting down the time and resources required for ab-initio drug design. The chapter aims to highlight the various computer-aided drug design methods to predict an anti-COVID drug molecule.

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.

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

Design, Synthesis and In-Vitro Biological Activity of Some New 1,3-Thiazolidine-4-One Derivatives as Chemotherapeutic Agents Using Virtual Screening Strategies

2020 ◽  
Vol 16 ◽  
Author(s):  
Pragya Nayak ◽  
Monica Kachroo
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Virtual Screening ◽  
In Silico ◽  
Cancer Cell Line ◽  
Inhibitory Response ◽  
Chemotherapeutic Agents ◽  
Acceptor Site ◽  
Hydrogen Bond Acceptor ◽  
Screening Strategies

: A series of new heteroaryl thiazolidine-4-one derivatives were designed and subjected to in-silico prioritization using various virtual screening strategies. Two series of thiazolidinone derivatives were synthesized and screened for their in-vitro antitubercular, anticancer, antileishmanial and antibacterial (Staphylococcus aureus; Streptococcus pneumonia; Escherichia coli; Pseudomonas aeruginosa) activities. The compounds with electronegative substitutions exhibited positive antitubercular activity, the derivatives possessing a methyl substitution exhibited good inhibitory response against breast cancer cell line MCF-7 while the compounds possessing a hydrogen bond acceptor site like hydroxyl and methoxy substitution in their structures exhibited good in-vitro antileishmanial activity. Some compounds exhibited potent activity against gram positive bacteria Pseudomonas aeruginosa as compared to the standards. Altogether, the designed compounds exhibited good in-vitro anti-infective potential which was in good agreement with the in-silico predictions and they can be developed as important lead molecules for anti-infective and chemotherapeutic drug research.

Zoning in on Tankyrases: A Brief Review on the Past, Present and Prospective Studies

2020 ◽  
Vol 19 (16) ◽  
pp. 1920-1934
Author(s):  
Xylia Q. Peters ◽  
Thembeka H. Malinga ◽  
Clement Agoni ◽  
Fisayo A. Olotu ◽  
Mahmoud E.S. Soliman
Keyword(s):  
Drug Design ◽  
Small Molecule ◽  
Small Molecule Inhibitors ◽  
Design Methods ◽  
Selective Inhibitors ◽  
Computer Aided Drug Design ◽  
Cellular Processes ◽  
Conventional Drug ◽  
Computer Aided ◽  
Tankyrase 1

Background: Tankyrases are known for their multifunctionalities within the poly(ADPribose) polymerases family and playing vital roles in various cellular processes which include the regulation of tumour suppressors. Tankyrases, which exist in two isoforms; Tankyrase 1 and 2, are highly homologous and an integral part of the Wnt β -catenin pathway that becomes overly dysregulated when hijacked by pro-carcinogenic machineries. Methods: In this review, we cover the distinct roles of the Tankyrase isoforms and their involvement in the disease pathogenesis. Also, we provide updates on experimentally and computationally derived antagonists of Tankyrase whilst highlighting the precedence of integrative computer-aided drug design methods towards the discovery of selective inhibitors. Results: Despite the high prospects embedded in the therapeutic targeting and blockade of Tankyrase isoforms, the inability of small molecule inhibitors to achieve selective targeting has remained a major setback, even until date. This explains numerous incessant drug design efforts geared towards the development of highly selective inhibitors of the respective Tankyrase isoforms since they mediate distinct aberrancies in disease progression. Therefore, considering the setbacks of conventional drug design methods, can computer-aided approaches actually save the day? Conclusion: The implementation of computer-aided drug design techniques in Tankyrase research could help complement experimental methods and facilitate ligand/structure-based design and discovery of small molecule inhibitors with enhanced selectivity.

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