Abstract

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry—many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry–virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

Highlights

  • Drug development included the individual synthesis and biological evaluation of hundreds of organic compounds with the intention of characterizing their biological activity, selectivity, bioavailability, and toxicity

  • We review the methodologies used to carry out the virtual screening of combinatorial libraries and non-combinatorial databases

  • The design of virtual combinatorial libraries (VCLs) is a critical part in the early phases of the drug discovery process as these libraries are used in lead generation projects to identify series of analogues around hit and lead compounds to explore structure–activity relationships (SARs) [14]

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Summary

Introduction

Drug development included the individual synthesis and biological evaluation of hundreds of organic compounds with the intention of characterizing their biological activity, selectivity, bioavailability, and toxicity. The emergence of VCC, along with the publication of many databases with hundreds or thousands of compounds, has propelled the development of computational methods designed to analyze the rapidly increasing amounts of chemical information that is being generated [5]. These libraries or databases were analyzed using High-Throughput Screening (HTS), which involved the experimental screening of entire compound collections. LBVS methods use the structural and biological data from a set of known active compounds to identify promising candidates for experimental screening [8] These chemical data can be based on either 2D or 3D representations of the molecules. The third part includes examples and applications of the aforementioned methodologies in the discovery and development of new drugs

Virtual Combinatorial Library Creation
Types of Combinatorial Libraries
Generation of Combinatorial Libraries
Virtual Screening
Methods Used in Virtual Screening
Applications and Current Trends
Conclusions
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