A Novel Multi‐step Virtual Screening for the Identification ofHumanandMousemPGES‐1 Inhibitors

Abstract

We present here the development of a novel virtual screening protocol combining Structure-based and Ligand-based drug design approaches for the identification of mouse mPGES-1 inhibitors. We used the existing 3D structural data of the murine enzyme to hypothesize the inhibitors binding mode, which was the starting point for docking simulations, shape screening, and pharmacophore hypothesis screening. The protocol allowed the identification of 16 mouse mPGES-1 inhibitors with low micromolar activity, which, notably, also inhibit the human enzyme in the same concentration range. The inhibitors predicted binding mode is expected to be the base for the rational drug design of new potent dual species inhibitors of human and murine mPGES-1.

Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds

“…Virtual Screening is a widely used technique at the early stage of drug discovery that allows to identify potentially bioactive compounds at a high throughput [30]. In several prior projects, coalescing different virtual screening methods lead to the discovery of potent inhibitors [25][26][27]31]. Due to its speed and cost-effectiveness, it is a promising approach to identify potential drug candidates against the globally expanding SARS-CoV-2 virus, especially when time is of essence.…”

“…For our virtual screening efforts (Figure 2 and Figure S1, Supporting Information), we extracted a total of 606 million compounds from the ZINC database. First, all compounds in three-dimensional form were screened with respect to their shape similarity [25] against a pre-selected set of known and co-crystalized SARS-CoV and SARS-CoV-2 inhibitors. Such a coarse GPU-accelerated protocol allows for the rapid screening of large databases based on known binders as template.…”

“…In this study, we screened a large library of over 606 million compounds with the aim to discover novel inhibitors for the SARS-CoV-2 main protease. We designed a protocol consisting of a combination of intensively validated methods that were successfully applied in drug discovery programs either as standalone tools or in combination [25][26][27][28]. In a first step, we performed a shape-based screening with known binders for the SARS-CoV main protease and relevant substructures as template molecules.…”

Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery

“…In another study, shape-based virtual screening alone produced better hit rates than hierarchical combination of shape similarity and docking methods (Ballester et al, 2012 ). In numerous studies, shape similarity calculations along with molecular docking were complemented with other approaches such as 2D similarity search, pharmacophore modeling, electrostatic potential matching, machine learning and MM-PBSA method (Mochalkin et al, 2009 ; Alcaro et al, 2013 ; Poongavanam and Kongsted, 2013 ; Wiggers et al, 2013 ; Hamza et al, 2014a ; Kumar et al, 2014b ; Pala et al, 2014 ; Feng et al, 2015 ; Corso et al, 2016 ; Mangiatordi et al, 2017 ; Xia et al, 2017 ). The use of different virtual screening approaches in parallel has been previously suggested as different methods tend to identify different set of compounds and virtual screening hit rates could be improved by employing them in parallel manner (Sheridan and Kearsley, 2002 ).…”