Virtual Screening: An Overview on Methods and Applications

Virtual Screening: An Overview on Methods and Applications

Khaled H. Barakat (University of Alberta, Canada), Jonathan Y. Mane (University of Alberta, Canada) and Jack A. Tuszynski (University of Alberta, Canada)
DOI: 10.4018/978-1-60960-491-2.ch002

Abstract

Virtual screening, or VS, is emerging as a valuable tool in discovering new candidate inhibitors for many biologically relevant targets including the many chemotherapeutic targets that play key roles in cell signaling pathways. However, despite the great advances made in the field thus far, VS is still in constant development with a relatively low success rate that needs to be improved by parallel experimental validation methods. This chapter reviews the recent advances in VS, focusing on the range and type of computational methods and their successful applications in drug discovery. The chapter also discusses both the advantages and limitations of the various techniques used in VS and outlines a number of future directions in which the field may progress.
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Introduction

Once, a US General summarized his philosophy on warfare in just four concise statements, “The art of war is simple enough. Find out where your enemy is. Get at him as soon as you can. Strike him as hard as you can, and keep moving.” Although these overarching statements formed the basic premise of modern war strategies, the same concepts have been applied in designing new drugs aimed at combating a broad range of diseases. In this context, rational drug design (Mandal et al., 2009) has been established as an exciting research approach aimed at developing safer and more efficacious drugs. The ultimate goal of this research is to design small organic non-peptidic compounds that bind to a specific molecular target, and result in the inhibition (or less frequently, activation) of a particular protein or enzyme involved in a given cellular pathway. The development of such drugs has been recognized early on by the pharmaceutical industry as a principal foundation that provides it with the necessary return on investment to fuel further research and development (Szymkowski, 2005) leading to a discovery and development cycle.

Our understanding of cell mechanisms and pathways becomes deeper and clearer every day. This is largely due to the great efforts and hard work of genomic and proteomic research groups who add novel targets for drug intervention on a regular basis (Drews, 2000; Fishman & Porter, 2005; Hopkins & Groom, 2002). Thus far, several hundred proteins have been synthetically reproduced and many of them are currently evaluated for their druggability (Hopkins & Groom, 2002). These targets involve several families comprised of G-protein coupled receptors (GPCRs), ligand-gated ion channels (LGICs), cytoskeleton proteins, phosphatases, kinases, nuclear receptors (NRs) and DNA repair proteins. The growing list of potential drug targets encourages a bold question if it is in principle possible to restore any diseased cell to a healthy state by uncovering a drug for every potential druggable target? Certainly, if this dream is ever realized, many diseases will be cured and relegated to the dustbin of history in a manner similar to the effect of the discovery of vaccines in the 19th and early 20th century.

Without a doubt, developing a new drug is a highly structured and expensive route that begins with the identification of the target and concludes with a phase III clinical trial followed by marketing (Fishman & Porter, 2005). A candidate drug may never materialize into a safe and efficacious medicine due to its failure to comply with stringent requirements at any stage of the drug discovery process. The further a potential drug progresses in the development process, the more costly its failure becomes. Accordingly, it is important to reduce the probability of late-stage expensive failures by identifying a diversity of lead compounds that are suitable for structural optimizations. Throughout the last two decades, experimental high throughput screening (HTS) and combinatorial chemistry formed the principal source for lead identification. However, as these approaches are particularly expensive and require considerable resources in terms of equipment and skills of the highly qualified personnel (Lahana, 1999), it is vital to search for an alternative or a complementary low-cost technique that aids in the discovery of new bioactive compounds while maintaining the high yield and rapidity of HTS. More recently, a new trend was born which has been named computational virtual screening (VS) or in silico screening (Stahura & Bajorath, 2004; Zoete, Grosdidier, & Michielin, 2009).

Key Terms in this Chapter

Virtual Screening: Filtering chemical databases for bioactive molecules (usually inhibitors for a particular cellular pathway) using computational tools.

Molecular Dynamics Simulations: Integration of Newtown’s equations of motion for a particular system in order to predict its future dynamics.

Scoring Function: An additive function that includes representations of various interactions between a ligand (small molecule) and a target. These representations describe the electrostatic, hydrophobic, solvation and hydrogen bonding interactions between the two molecules. Scoring functions are used by docking programs for estimating the binding affinity between the interacting molecules as well as for predicting the native structure of the protein-ligand complex.

Inhibitor: A small molecule that binds to a specific binding site on the surface of a target (usually a protein). This binding process prevents the target from interacting with other molecules inside the cell, which in turn, reduce the activity of the cellular pathway that is associated with this target.

Binding Site: A pocket, a groove or a protrusion having an assortment of apparent hydrogen bond donors and acceptors, hydrophobic features and it can be associated with molecular adherence surfaces.

Pharmacophore: “A molecular framework that carries (phoros) the essential features responsible for a drug’s (pharmacon’s) biological activity” (Ehrlich, 1909).

Docking: A method for predicting the preferred orientation of one molecule when bound to a target to form a stable complex.

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