scholarly journals Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein–Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

2021 ◽  
Vol 23 (1) ◽  
pp. 393
Author(s):  
Sebastjan Kralj ◽  
Marko Jukič ◽  
Urban Bren

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.

2016 ◽  
Vol 11 (10) ◽  
pp. 957-968 ◽  
Author(s):  
Leonardo G. Ferreira ◽  
Glaucius Oliva ◽  
Adriano D. Andricopulo

2017 ◽  
Vol 60 (2) ◽  
pp. 787-796 ◽  
Author(s):  
Matteo Incerti ◽  
Simonetta Russo ◽  
Donatella Callegari ◽  
Daniele Pala ◽  
Carmine Giorgio ◽  
...  

ALCHEMY ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 45
Author(s):  
Sandra Hermanto

Penapisan peptida bioaktif dari hidrolisat kasein susu kambing Etawa yang berpotensi sebagai obat antihipertensi berdasarkan kajian <em>in silico </em>telah dilakukan. Protein yang digunakan adalah α-S1-kasein prekursor [<em>Capra hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272624.1, α-S2-kasein prekursor [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272514.1, β-kasein [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: AAA30906.1 dan κ-kasein prekursor [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272516.1. Perancangan struktur peptida bioaktif dilakukan melalui simulasi hidrolisis enzimatik dengan menggunakan 3 jenis enzim proteolitik (tripsin, kimotripsin dan pepsin) dan dilanjutkan dengan preparasi struktur 3D ligan hasil pemotongan secara <em>in silico</em>. <em>Virtual screening</em> terhadap fragmen peptida dilakukan melalui penentuan nilai <em>drug likeness</em> dan <em>protease inhibitor.</em> Dari 104 fragmen peptida diperoleh 10 kandidat peptida bioaktif yang dilakukan simulasi <em>molecular docking</em> dengan mengeksplorasi daya inhibisi fragmen melalui perhitungan nilai (∆<em>G<sub>binding</sub></em>) dan interaksi antara kandidat peptida bioaktif dengan residu asam amino pada sisi aktif enzim ACE (<em>Angiotensin Converting Enzyme)</em>. Sebagai kontrol positif digunakan lisinopril yang merupakan inhibitor ACE komersil. Hasil penelitian menunjukkan dari 10 kandidat peptida bioaktif terdapat 6 peptida yang diduga bersifat antihipertensi dengan nilai ∆<em>G<sub>binding</sub></em><em></em><sub> </sub>yang lebih rendah dari kontrol positif (lisinopril). Keenam peptida tersebut diharapkan dapat berfungsi sebagai obat alternatif antihipertensi.


2018 ◽  
Vol 8 (5) ◽  
pp. 504-509 ◽  
Author(s):  
Surabhi Surabhi ◽  
BK Singh

Discovery and development of a new drug is generally known as a very complex process which takes a lot of time and resources. So now a day’s computer aided drug design approaches are used very widely to increase the efficiency of the drug discovery and development course. Various approaches of CADD are evaluated as promising techniques according to their need, in between all these structure-based drug design and ligand-based drug design approaches are known as very efficient and powerful techniques in drug discovery and development. These both methods can be applied with molecular docking to virtual screening for lead identification and optimization. In the recent times computational tools are widely used in pharmaceutical industries and research areas to improve effectiveness and efficacy of drug discovery and development pipeline. In this article we give an overview of computational approaches, which is inventive process of finding novel leads and aid in the process of drug discovery and development research. Keywords: computer aided drug discovery, structure-based drug design, ligand-based drug design, virtual screening and molecular docking


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