Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery

2015 ◽  
Vol 18 (6) ◽  
pp. 528-543 ◽  
Author(s):  
Muthukumarasamy Karthikeyan ◽  
Renu Vyas
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Open Source

scholarly journals InterLig: a fast and accurate software for ligand-based virtual screening

2019 ◽  
Author(s):  
Claudio Mirabello ◽  
Björn Wallner
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Small Molecules ◽  
Open Source ◽  
Computational Methods ◽  
New Method ◽  
Scaffold Hopping ◽  
Protein Target ◽  
The Past ◽  
3D Methods

AbstractIn the past few years, drug discovery processes have been relying more and more on computational methods to sift out the most promising molecules before time and resources are spent to test them in experimental settings. Whenever the protein target of a given disease is not known, it becomes fundamental to have accurate methods for ligand-based Virtual Screening, which compare known active molecules against vast libraries of candidate compounds. Recently, 3D-based similarity methods have been developed that are capable of scaffold-hopping and to superimpose matching molecules. Here, we present InterLig, a new method for the comparison and superposition of small molecules based on 3D, topologically-independent alignments of atoms. We test InterLig on a standard benchmark and show that it compares favorably to the best currently available 3D methods.InterLig is open source and is available to everyone at: http://wallnerlab.org/interlig.

Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors

2015 ◽  
pp. 318-353
Author(s):  
Khac-Minh Thai ◽  
Quoc-Hiep Dong ◽  
Thi-Thanh-Lan Nguyen ◽  
Duy-Phong Le ◽  
Minh-Tri Le ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Viral Replication ◽  
Quantitative Structure Activity Relationship ◽  
Computational Approaches ◽  
Ns5b Polymerase ◽  
Replication Activity

Nonstructural 5B (NS5B) polymerase and Nonstructural 3/4A (NS3/4A) protease have proven to be promising targets for the development of anti-HCV (Hepatitis C Virus) agents. The NS5B polymerase is of paramount importance in HCV viral replication; therefore, employing NS5B inhibitors was considered an effective way for the treatment of HCV. Identifying inhibitors against NS3/4A serine protease represents another attractive approach applied in anti-HCV drug discovery, which is evidenced by its crucial role of in the biogenesis of the viral replication activity. In this chapter, many different computational approaches including Quantitative Structure-Activity Relationship (QSAR) and virtual screening in anti-HCV drug discovery were considered and discussed in detail. Virtual Screening (VS) techniques, including ligand-based and structure-based, and QSAR have been utilized for the discovery of NS5B inhibitors. Moreover, using various in silico protocols and workflows, a number of studies have been conducted with an aim of identifying potential NS3/4A blockage agents.

Computational Approaches for the Discovery of Novel Hepatitis C Virus NS3/4A and NS5B Inhibitors

Oncology ◽  
2017 ◽  
pp. 482-518 ◽  
Author(s):  
Khac-Minh Thai ◽  
Quoc-Hiep Dong ◽  
Thi-Thanh-Lan Nguyen ◽  
Duy-Phong Le ◽  
Minh-Tri Le ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Viral Replication ◽  
Quantitative Structure Activity Relationship ◽  
Computational Approaches ◽  
Ns5b Polymerase ◽  
Replication Activity

Nonstructural 5B (NS5B) polymerase and Nonstructural 3/4A (NS3/4A) protease have proven to be promising targets for the development of anti-HCV (Hepatitis C Virus) agents. The NS5B polymerase is of paramount importance in HCV viral replication; therefore, employing NS5B inhibitors was considered an effective way for the treatment of HCV. Identifying inhibitors against NS3/4A serine protease represents another attractive approach applied in anti-HCV drug discovery, which is evidenced by its crucial role of in the biogenesis of the viral replication activity. In this chapter, many different computational approaches including Quantitative Structure-Activity Relationship (QSAR) and virtual screening in anti-HCV drug discovery were considered and discussed in detail. Virtual Screening (VS) techniques, including ligand-based and structure-based, and QSAR have been utilized for the discovery of NS5B inhibitors. Moreover, using various in silico protocols and workflows, a number of studies have been conducted with an aim of identifying potential NS3/4A blockage agents.

Screening of Natural Lead Molecules Against Putative Molecular Targets of Drug-resistant Cryptococcus spp: An Insight from Computer-aided Molecular Design

2019 ◽  
Vol 18 (31) ◽  
pp. 2681-2701
Author(s):  
Meghna Manjunath ◽  
Sinosh Skariyachan
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Drug Targets ◽  
Medicinal Chemistry ◽  
Fungal Infections ◽  
Limited Information ◽  
New Paradigm ◽  
Effective Prevention ◽  
Computer Aided

Cryptococcosis is one of the major invasive fungal infections distributed worldwide with high mortality rate. C. neoformans and C. gattii are the major organisms that cause various types of infections. Anti-fungal resistances exhibited by the mentioned species of Cryptococcus threaten their effective prevention and treatment. There is limited information available on human to human transmission of the pathogen and virulent factors that are responsible for Cryptococcus mediated infections. Hence, there is high scope for understanding the mechanism, probable drug targets and scope of developing natural therapeutic agents that possess high relevance to pharmaceutical biotechnology and medicinal chemistry. The proposed review illustrates the role of computer-aided virtual screening for the screening of probable drug targets and identification of natural lead candidates as therapeutic remedies. The review initially focuses on the current perspectives on cryptococcosis, major metabolic pathways responsible for the pathogenesis, conventional therapies and associated drug resistance, challenges and scope of structure-based drug discovery. The review further illustrates various approaches for the prediction of unknown drug targets, molecular modeling works, screening of natural compounds by computational virtual screening with ideal drug likeliness and pharmacokinetic features, application of molecular docking studies and simulation. Thus, the present review probably provides AN insight into the role of medicinal chemistry and computational drug discovery to combat Cryptococcus infections and thereby open a new paradigm for the development of novel natural therapeutic against various drug targets for cryptococcal infections.

The Role of QSAR and Virtual Screening Studies in Type 2 Diabetes Drug Discovery

2017 ◽  
Vol 13 (8) ◽  
Author(s):  
Simone Q. Pantaleao ◽  
Drielli G.V. Fujii ◽  
Vinicius G. Maltarollo ◽  
Danielle da C. Silva ◽  
Gustavo H.G. Trossini ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Diabetes Drug

scholarly journals Open Source Drug Discovery with Bioclipse

2013 ◽  
Vol 12 (18) ◽  
pp. 1980-1986
Author(s):  
Ola Spjuth ◽  
Jonathan Alvarsson ◽  
Egon Willighagen ◽  
Lars Carlsson ◽  
Valentin Georgiev ◽  
...  
Keyword(s):  
Decision Support ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Knowledge Discovery ◽  
Open Source ◽  
Chemical Structures ◽  
Related Information ◽  
Computational Pharmacology ◽  
Qspr Modeling ◽  
Discovery And Integration

We present the open source components for drug discovery that has been developed and integrated into the graphical workbench Bioclipse. Building on a solid open source cheminformatics core, Bioclipse has advanced functionality for managing and visualizing chemical structures and related information. The features presented here include QSAR/QSPR modeling, various predictive solutions such as decision support for chemical liability assessment, site-ofmetabolism prediction, virtual screening, and knowledge discovery and integration. We demonstrate the utility of the described tools with examples from computational pharmacology, toxicology, and ADME. Bioclipse is used in both academia and industry, and is a good example of open source leading to new solutions for drug discovery.

Dose COVID-19 Uncovered a New Feature of Metronidazole Drug?

2020 ◽  
Author(s):  
Mohammad Seyedhamzeh ◽  
Bahareh Farasati Far ◽  
Mehdi Shafiee Ardestani ◽  
Shahrzad Javanshir ◽  
Fatemeh Aliabadi ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Active Sites ◽  
Initial Plasma ◽  
New Feature ◽  
Metronidazole Benzoate ◽  
Global Health Problem ◽  
A Current ◽  
Pro Inflammatory Cytokines

Studies of coronavirus disease 2019 (COVID-19) as a current global health problem shown the initial plasma levels of most pro-inflammatory cytokines increased during the infection, which leads to patient countless complications. Previous studies also demonstrated that the metronidazole (MTZ) administration reduced related cytokines and improved treatment in patients. However, the effect of this drug on cytokines has not been determined. In the present study, the interaction of MTZ with cytokines was investigated using molecular docking as one of the principal methods in drug discovery and design. According to the obtained results, the IL12-metronidazole complex is more stable than other cytokines, and an increase in the surface and volume leads to prevent to bind to receptors. Moreover, ligand-based virtual screening of several libraries showed metronidazole phosphate, metronidazole benzoate, 1-[1-(2-Hydroxyethyl)-5- nitroimidazol-2-yl]-N-methylmethanimine oxide, acyclovir, and tetrahydrobiopterin (THB or BH4) like MTZ by changing the surface and volume prevents binding IL-12 to the receptor. Finally, the inhibition of the active sites of IL-12 occurred by modifying the position of the methyl and hydroxyl functional groups in MTZ. <br>

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