Special Issue "A Systematic Development Method for Rational Drug Design"

Guest Editor
Dr. Dooil Kim
Korea Research Institute of Bioscience and Biotechnology, Systems Microbiology Research Center, Deajeon 305-806, South Korea
E-Mail:
Phone: +82 42 860 4135
Fax: +82 42 860 4597
Interests: bioinformatics; database development; comparative genomics; cheminformatics; molecular modeling; computer aided drug design

Dear Colleagues,

Traditionally drug discovery used to be a trial and error process, where chemical compounds from plant and other natural extracts were proposed for action against a disease and then tested for the compounds’ effectiveness in curing the disease on animal or tissue based models. Drug discovery process has now evolved into a much more scientific and rational process due to better understanding of the biological processes and the underlying chemistry, owing to the progress made due to advances in high throughput experimental techniques and availability of high performance computation resources. The process has matured to the stage where drugs are designed now rather than being discovered.

• drug design
• machine learning
• data mining
• high throughput screening

Type of Paper: Review
Title: Innovative Drug Designs Using Nucleic Acid-Recognizing Toll-Like Receptor Signaling Pathways against Virus Infections
Author: Jonathan P. Wong
Affiliation: Defence R&D Canada - Suffield, Ralston, AB, Canada; E-Mail: jonathan.wong@drdc-rddc.gc.ca
Abstract: During virus infections, nucleic acids of viral origin are signatory macromolecules which are recognized by endosomal membrane bound toll-like receptors.  These nucleic  acid-recognizing TLRs (TLR-3, -7, -8 and -9) play a critical role in innate immunity in appropriating inflammatory and antiviral immune responses to combat the invading virus particles. However, the detecting and recognizing of these viral nucleic acids may be too late for the body's immune defences to mount adequate antiviral responses, and some viruses have evolved mechanisms to evade them.  The review examined the role of exogenously administered nucleic acids specifically designed to trigger the TLR signaling pathways to potentiate the body's immune response to mount an effective and timely antiviral immunity.  These nucleic acids may have an important role to play as prophylactic and therapeutic agents which can be used as broad-spectrum antiviral agents. One example is Poly ICLC, a synthetic ds RNA, which acts as TLR-3 agonists, and in animal studies been shown to exert protective antiviral responses against such viruses as influenza (seasonal and pandemic), respiratory syncytial, SARS-CoV and alphaviruses.

Type of Paper: Review
Title: Systematic Approaches towards the Molecular Design of Novel Antiviral Drugs
Authors: Pahk Thepchatri ¹, Andrew Prussia ¹, James P. Snyder ¹ and Richard K. Plemper ^2,3
Affiliations: ¹ Department of Chemistry, Emory University, Atlanta, GA, USA
² Department of Pediatrics, Emory University, Atlanta, GA, USA; E-Mail: rplempe@emory.edu
³ Children’s Healthcare of Atlanta, USA
Abstract: Since the onset of antiviral therapy, viral resistance has compromised the clinical value of small-molecule drugs targeting pathogen components. As intracellular parasites, viruses complete their life cycle by hijacking a multitude of host-factors. Aiming at the latter rather than the pathogen directly, host-directed antiviral therapy has emerged as a concept to counteract evolution of viral resistance and develop broad-spectrum drug classes. This approach is propelled by system-wide bioinformatics screens that greatly enhance insights into the complex network of host-pathogen interactions and set the stage for a new era of rational identification of drug targets for host-directed antiviral therapies. With focus on three major human pathogens, human immunodeficiency virus, influenza virus and hepatitis C virus, we review the current status of screens employed to elucidate host-pathogen interactions and discuss the state of computational approaches applicable to complementary data mining with a therapeutic endpoint. The qualities of selected inhibitors are evaluated against those derived by traditional drug discovery strategies, and perspectives for bioinformatics-driven molecular design outlined.