scholarly journals An Overview on Zika Virus and the Importance of Computational Drug Discovery

2018 ◽  
Vol 3 (2) ◽  
pp. 43-51 ◽  
Author(s):  
Umesh Panwar ◽  
Sanjeev Kumar Singh
Keyword(s):  
Drug Discovery ◽  
Zika Virus ◽  
Computational Drug Discovery

scholarly journals Computational drug discovery for the Zika virus

2018 ◽  
Vol 54 (spe) ◽  
Author(s):  
Melina Mottin ◽  
Joyce Villa Verde Bastos Borba ◽  
Cleber Camilo Melo-Filho ◽  
Bruno Junior Neves ◽  
Eugene Muratov ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Zika Virus ◽  
Computational Drug Discovery

A unified approach to computational drug discovery

2015 ◽  
Vol 20 (11) ◽  
pp. 1328-1336 ◽  
Author(s):  
Chih-Yuan Tseng ◽  
Jack Tuszynski
Keyword(s):  
Drug Discovery ◽  
Unified Approach ◽  
Computational Drug Discovery

scholarly journals Advances in the Treatment of Explicit Water Molecules in Docking and Binding Free Energy Calculations

2020 ◽  
Vol 26 (42) ◽  
pp. 7598-7622 ◽  
Author(s):  
Xiao Hu ◽  
Irene Maffucci ◽  
Alessandro Contini
Keyword(s):  
Drug Discovery ◽  
Binding Free Energy ◽  
Docking Studies ◽  
Free Energy Calculations ◽  
Binding Energies ◽  
New Drugs ◽  
Water Molecules ◽  
Open Questions ◽  
Dynamics Simulations ◽  
Computational Drug Discovery

Background: The inclusion of direct effects mediated by water during the ligandreceptor recognition is a hot-topic of modern computational chemistry applied to drug discovery and development. Docking or virtual screening with explicit hydration is still debatable, despite the successful cases that have been presented in the last years. Indeed, how to select the water molecules that will be included in the docking process or how the included waters should be treated remain open questions. Objective: In this review, we will discuss some of the most recent methods that can be used in computational drug discovery and drug development when the effect of a single water, or of a small network of interacting waters, needs to be explicitly considered. Results: Here, we analyse the software to aid the selection, or to predict the position, of water molecules that are going to be explicitly considered in later docking studies. We also present software and protocols able to efficiently treat flexible water molecules during docking, including examples of applications. Finally, we discuss methods based on molecular dynamics simulations that can be used to integrate docking studies or to reliably and efficiently compute binding energies of ligands in presence of interfacial or bridging water molecules. Conclusions: Software applications aiding the design of new drugs that exploit water molecules, either as displaceable residues or as bridges to the receptor, are constantly being developed. Although further validation is needed, workflows that explicitly consider water will probably become a standard for computational drug discovery soon.

scholarly journals Re-Designing Hazardous Chemicals with Target-Specific Toxicities by Learning from Structure-Based Drug Design

2018 ◽  
Author(s):  
Traci Clymer ◽  
Vanessa Vargas ◽  
Eric Corcoran ◽  
Robin Kleinberg ◽  
Jakub Kostal
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Adverse Effects ◽  
Environmental Health ◽  
In Silico ◽  
Adverse Outcomes ◽  
Design Stage ◽  
Hazardous Chemicals ◽  
Structure Based Drug Design ◽  
Computational Drug Discovery

Chemicals are the basis of our society and economy, yet many existing chemicals are known to have unintended adverse effects on human and environmental health. Testing all existing and new chemicals on animals is both economically and ethically unfeasible. In this paper, a new in silico framework is presented that affords redesign of existing hazardous chemicals in commerce based on specific molecular initiating events in their adverse outcomes pathways. Our approach is based on a successful methodology implemented in computational drug discovery, and promises to dramatically lower costs associated with new chemical development by synergistically addressing chemical function and safety at the design stage. <br>

In silico approaches to Zika virus drug discovery

2018 ◽  
Vol 13 (9) ◽  
pp. 825-835 ◽  
Author(s):  
Alessandro Sinigaglia ◽  
Silvia Riccetti ◽  
Marta Trevisan ◽  
Luisa Barzon
Keyword(s):  
Drug Discovery ◽  
Zika Virus ◽  
In Silico
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