Structural Comparison and Drug Screening of Spike Proteins of Ten SARS-CoV-2 Variants

Abstract

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has evolved many variants with stronger infectivity and immune evasion than the original strain, including Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Iota, Lambda, and 21H strains. Amino acid mutations are enriched in the spike protein of SARS-CoV-2, which plays a crucial role in cell infection. However, the impact of these mutations on protein structure and function is unclear. Understanding the pathophysiology and pandemic features of these SARS-CoV-2 variants requires knowledge of the spike protein structures. Here, we obtained the spike protein structures of 10 main globally endemic SARS-CoV-2 strains using AlphaFold2. The clustering analysis based on structural similarity revealed the unique features of the mainly pandemic SARS-CoV-2 Delta variants, indicating that structural clusters can reflect the current characteristics of the epidemic more accurately than those based on the protein sequence. The analysis of the binding affinities of ACE2-RBD, antibody-NTD, and antibody-RBD complexes in the different variants revealed that the recognition of antibodies against S1 NTD and RBD was decreased in the variants, especially the Delta variant compared with the original strain, which may induce the immune evasion of SARS-CoV-2 variants. Furthermore, by virtual screening the ZINC database against a high-accuracy predicted structure of Delta spike protein and experimental validation, we identified multiple compounds that target S1 NTD and RBD, which might contribute towards the development of clinical anti-SARS-CoV-2 medicines. Our findings provided a basic foundation for future in vitro and in vivo investigations that might speed up the development of potential therapies for the SARS-CoV-2 variants.

Caspase-1 and Gasdermin D Afford the Optimal Targets with Distinct Switching Strategies in NLRP1b Inflammasome-Induced Cell Death

“…Targeting pyroptosis or apoptosis induced by inflammasomes is suggested to be a promising strategy in COVID-19 and other disease treatment [ 1 , 13 , 20 , 40 ]. Focusing on exploring the efficient control strategy of the transducers is therefore a significant issue [ 41 ]. Our results clearly demonstrate that only the decrease of caspase-1 and GSDMD levels can individually switch death modes from pyroptosis to apoptosis ( Figure 3(b) ).…”

Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2

“…They have found that the AlphaFold2 models are entirely consistent with the experimental RDC data for most proteins. Yang et al have adopted AlphaFold2 to predict the structures of S proteins according to the sequences of the mutants and successfully predicted the S proteins of 10 major variants of SARS-CoV-2, including the Original, Alpha, Beta, Gamma, Delta, Epsilon, IOTA, Kappa, Lambda and 21H strains [56] . Gupta et al have combined the cryo-EM with AlphaFold2 to obtain the atomic model of full-length SARS-COV-2 non-structural protein 2 (NSP2) [57] , which reveals a highly-conserved zinc ion-binding site, suggesting a role for NSP2 in RNA binding.…”

Highly accurate protein structure prediction and drug screen of monkeypox virus proteome

“…The structures of most of the monkeypox virus proteins remain unknown, knowledge of which would significantly enhance our understanding of the molecular mechanisms underlying critical viral processes such as viral entry and replication. AlphaFold2 is a powerful open-source computational approach developed to help predict protein structures 3 , which has been used successfully in acquiring accurate protein structures of the human and SARS- CoV-2 proteomes 4 , 5 , 6 .…”

“…AlphaFold2 is a powerful open-source computational approach developed to help predict protein structures, 3 which has been used successfully in acquiring accurate protein structures of the human and SARS-CoV-2 proteomes. [4][5][6] Here, we used AlphaFold2 to predict the protein structures of the reference monkeypox virus proteome (Uniprot ID: UP101269 7 ), yielding a total of 186 highly accurate protein structures (Supplemental Table S1). The mean predicted Local Distance Difference Test (pLDDT) values of 156 of the 186 proteins are above the threshold of 70, which suggests that the predicted structures for these proteins are highly accurate ( Fig.…”