Development of Anti-Viral Agents Using Molecular Modeling and Virtual Screening Techniques

Author(s): Johannes Kirchmair, Simona Distinto, Klaus Roman Liedl, Patrick Markt, Judith Maria Rollinger, Daniela Schuster, Gudrun Maria Spitzer, Gerhard Wolber

Journal Name: Infectious Disorders - Drug Targets
Formerly Current Drug Targets - Infectious Disorders

Volume 11 , Issue 1 , 2011

Become EABM
Become Reviewer
Call for Editor


Computational chemistry has always played a key role in anti-viral drug development. The challenges and the quickly rising public interest when a virus is becoming a threat has significantly influenced computational drug discovery. The most obvious example is anti-AIDS research, where HIV protease and reverse transcriptase have triggered enormous efforts in developing and improving computational methods. Methods applied to anti-viral research include (i) ligandbased approaches that rely on known active compounds to extrapolate biological activity, such as machine learning techniques or classical QSAR, (ii) structure-based methods that rely on an experimentally determined 3D structure of the targets, such as molecular docking or molecular dynamics, and (iii) universal approaches that can be applied in a structure- or ligand-based way, such as 3D QSAR or 3D pharmacophore elucidation. In this review we summarize these molecular modeling approaches as they were applied to fight anti-viral diseases and highlight their importance for anti-viral research. We discuss the role of computational chemistry in the development of small molecules as agents against HIV integrase, HIV-1 protease, HIV-1 reverse transcriptase, the influenza virus M2 channel protein, influenza virus neuraminidase, the SARS coronavirus main proteinase and spike protein, thymidine kinases of herpes viruses, hepatitis C virus proteins and other flaviviruses as well as human rhinovirus coat protein and proteases, and other picornaviridae. We highlight how computational approaches have helped in discovering anti-viral activities of natural products and give an overview on polypharmacology approaches that help to optimize drugs against several viruses or help to optimize the metabolic profile of and anti-viral drug.

Keywords: Activity profiling, computational chemistry, docking, drugs from natural sources, fingerprints, HCV NS3/4A serine protease, HCV NS5B RNA-dependent RNA-polymerase, hepatitis C virus, herpes, HIV, HIV integrase, HIV-1 protease, HIV-1 reverse transcriptase, homology modeling, HRV capsid protein, HRV protease 2A, HRV protease 3C, HSV, human -glucosidase, influenza virus, inverse screening, lead structure development, M2 channel protein, molecular dynamics simula-tion, molecular interaction fields, molecular modeling, natural compounds, neuraminidase, parallel screening, pharmacophore modeling, QSAR, SARS-CoV, similarity-based screening, thymidine kinase, viral disease, virtual screening, virus

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2011
Page: [64 - 93]
Pages: 30
DOI: 10.2174/187152611794407782
Price: $65

Article Metrics

PDF: 115