Abstract

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein–protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Highlights

  • Since targeted libraries use a variety of different methods for data collection, we attempted to gain a better understanding of how libraries are designed and what they offer to the virtual screening process

  • We evaluated commercially available targeted libraries, which are often marketed by vendors to the scientific community

  • When we examined the processes behind the design of these libraries and evaluated them by using filtering and descriptor analysis, we could see that the library design is not transparent and that the exact steps on the way to focused libraries are not provided by the commercial vendors, nor are the references to the primary literature included

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Summary

Introduction

Extensive compound libraries representing the rich the hit rate (the at a given screening concentration appropriate chemical spacenumber are critical of for binding the successcompounds of (virtual) high-throughput the number of compounds tested experimentally) over classical screening me (vHTS or HTS) [10] This is a computational methodology used to differentiate between the molecules from a virtual library that bind to a potential target and those that do not, as well as to rank these molecules according to their predicted binding strength. This allows us to enrich the hit rate (the number of binding compounds at a given concentration divided by the number of compounds tested experimentally) over classical screening methods, such as the high-throughput screening (HTS) [11]. This review explores this topic as the first of its kind for the benefit of the medicinal chemistry community and refers the reader to the relevant resources and related reports in the scientific literature

In Silico Library Design for Medicinal Chemistry
Methods
Examples of Commercial Targeted Libraries
SARS-CoV-2- or COVID-19-Targeted Libraries
SARS-CoV-2COVID-19-Targeted
Enamine
Process algorithm for generating
Life Chemicals
TargetMol
Protease-Inhibitor-Focused
Protein–Protein-Interaction-Inhibitor-Focused Libraries
Findings
Discussion
Conclusions
Full Text
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