Structure-based discovery of inhibitors of Mac1 domain of nonstructural protein-3 of SARS-CoV-2 by machine learning-augmented screening of chemical space

Abstract

Significant efforts have been recently dedicated to the discovery of small molecule inhibitors against the Macrodomain 1 (Mac1) of nonstructural protein 3 (NSP3) as potential antivirals for SARS-CoV-2. Thus, Mac1 has also been selected as the target for the Critical Assessment of Hit-finding Experiments (CACHE) challenge #3. As contestants in that challenge, we developed a computational strategy that ranked on the top among all 23 participants in the competition and resulted in the discovery of a novel chemical series of non-charged Mac1 inhibitors. Those have been identified through the combination of machine learning-accelerated virtual screening of Enamine REAL Diversity Subset of approximately 25 million compounds and consequent hit expansion into the entire Enamine REAL Space library. In particular, the initially identified hit compound CACHE3-HI_1706_56 (K_D = 20 μM) was explored by probing 17 close analogues from a library of 44 billion molecules from the Enamine REAL. All those analogues effectively displaced the Mac1-binding ADP-ribose peptide, and 12 were confirmed to engage with Mac1 by the Surface Plasmon Resonance experiments, revealing a new chemical series of compounds for hit-to-lead optimization. The structure of the CACHE3-HI_1706_56-Mac1 complex was further determined at high resolution with crystallography, confirming initial computational predictions. Our results illustrate the effectiveness of ML-accelerated docking to rapidly identify novel chemical series and provide a strong foundation for the development of SARS-CoV-2 NSP3 Mac1 inhibitors.

Keywords: CACHE challenge; Mac1; SARS-CoV-2; Virtual screening; machine learning.

Figure 1.. Chemical structures of SARS-CoV-2 NSP3 Mac1 inhibitors

a) best anionic inhibitor, Z8539_0072 b) Best neutral inhibitor, LHR-0003.

Figure 2.. Binding site and virtual screening schematics

a) X-ray binding pose of LHR-0003 bound to SARS-CoV-2 NSP3 Mac1 (PDB 5SRY), the complex that was chosen as the target structure for virtual screening b) Multi-step structure-based virtual screening workflow to investigate the Enamine REAL Diversity Subset against Mac1.

Figure 3.. Experimental confirmation of the Round 1 hit

a) Chemical structure and HTRF results demonstrating inhibition of binding of the ADP-ribose peptide to Mac1 by CACHE3-HI_1706_56 b) Biophysical confirmation of Mac1-CACH3-HI_1706_56 binding with SPR c) Docking-predicted binding pose of CACHE3-HI_1706_56, with hydrogen bonds represented in red dashed lines d) a) Comparison between docked (ligand in blue, Mac1 in light green) and crystallographic (ligand in pink, Mac1 in yellow) Mac1-CACHE3-HI_1706_56 complexes; ligand binding induced a conformational change from the closed conformation of Phe132 (P132_d) used for docking and observed also in the apo-structure of Mac1 to the solvent-exposed one revealed by crystallography (P132_c). Only one of the two alternative conformations of CACHE3-HI_1706_56 is showed.

Figure 4.. Binding pose and biophysical characterization of best hit analogues

a) Docking poses of CACHE3-HO _1706_4 (cyan) and CACHE3-HO _1706_7 (pink) to Mac1 pocket, represented as a molecular surface (green: hydrophobic regions, purple: polar regions, red: solvent exposed) b) Structure and biophysical confirmation of Mac1-CACHE3-HO _1706_4 binding with SPR c) Structure and biophysical confirmation of Mac1-CACHE3-HO _1706_7 binding with SPR.