Substrate recognition and selectivity in SARS-CoV-2 main protease: Unveiling the role of subsite interactions through dynamical nonequilibrium molecular dynamics simulations (preprint)

The main protease (Mpro) of the SARS-CoV-2 coronavirus employs a cysteine-histidine dyad in its active site to catalyse hydrolysis of the viral polyproteins. It is well established that binding of the substrate P1-Gln in the S1 subsite of Mpro active site is crucial for catalysis and this interaction has been employed to inform inhibitor design; however, how Mpro dynamically recognises and responds to substrate binding remains difficult to probe by experimental methods. We thus employed the dynamical nonequilibrium molecular dynamics (D-NEMD) approach to probe the response of Mpro to systematic substrate variations. The results emphasise the importance of P1-Gln for initiating a productive enzymatic reaction. Specifically, substituting P1-Gln with alanine disrupts the conformations of the Cys145 and His41 dyad, causing Cys145 to transition from the productive gauche conformation to the non-productive trans conformation. Importantly, our findings indicate that Mpro exhibits dynamic responses to substrate binding and likely to substrate-mimicking inhibitors within each of the S4-S2' subsites. The results inform on the substrate selectivity requirements and shed light on the observed variations in hydrolytic efficiencies of Mpro towards different substrates. Some interactions between substrate residues and enzyme subsites involve more induced fit than others, implying that differences in functional group flexibility may optimise the binding of a substrate or inhibitor in a particular subsite.

Studies on the selectivity of the SARS-CoV-2 papain-like protease reveal the importance of the P2' proline of the viral polyprotein (preprint)

The SARS-CoV-2 papain-like protease (PLpro) is an antiviral drug target that catalyzes the hydrolysis of the viral polyproteins pp1a/1ab, releasing the non-structural proteins (nsps) 1-3 that are essential for the coronavirus lifecycle. The LXGG{downarrow}X motif found in pp1a/1ab is crucial for recognition and cleavage by PLpro. We describe molecular dynamics, docking, and quantum mechanics/molecular mechanics (QM/MM) calculations to investigate how oligopeptide substrates derived from the viral polyprotein bind to PLpro. The results reveal how the substrate sequence affects the efficiency of PLpro-catalyzed hydrolysis. In particular, a proline at the P2'; position promotes catalysis, as validated by residue substitutions and mass spectrometry-based analyses. Analysis of PLpro catalyzed hydrolysis of LXGG motif-containing oligopeptides derived from human proteins suggests that factors beyond the LXGG motif and the presence of a proline residue at P2' contribute to catalytic efficiency, possibly reflecting the promiscuity of PLpro. The results will help in identifying PLpro substrates and guiding inhibitor design.

Dynamical nonequilibrium molecular dynamics simulations identify allosteric sites and positions associated with drug resistance in the SARS-CoV-2 main protease (preprint)

The SARS-CoV-2 main protease (Mpro) plays an essential role in the coronavirus lifecycle by catalysing hydrolysis of the viral polyproteins at specific sites. Mpro is the target of drugs, such as nirmatrelvir, though resistant mutants have emerged that threaten drug efficacy. Despite its importance, questions remain on the mechanism of how Mpro binds its substrates. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to evaluate structural and dynamical responses of Mpro to the presence and absence of a substrate. The results highlight communication between the Mpro dimer subunits and identify networks, including some far from the active site, that link the active site with a known allosteric inhibition site, or which are associated with nirmatrelvir resistance. They imply that some mutations enable resistance by altering the allosteric behaviour of Mpro. More generally, the results show the utility of the D-NEMD technique for identifying functionally relevant allosteric sites and networks including those relevant to resistance.

Accelerating Inhibitor Discovery for Multiple SARS-CoV-2 Targets with a Single, Sequence-Guided Deep Generative Framework (preprint)

The COVID-19 pandemic has highlighted the urgency for developing more efficient molecular discovery pathways. As exhaustive exploration of the vast chemical space is infeasible, discovering novel inhibitor molecules for emerging drug-target proteins is challenging, particularly for targets with unknown structure or ligands. We demonstrate the broad utility of a single deep generative framework toward discovering novel drug-like inhibitor molecules against two distinct SARS-CoV-2 targets -- the main protease (Mpro) and the receptor binding domain (RBD) of the spike protein. To perform target-aware design, the framework employs a target sequence-conditioned sampling of novel molecules from a generative model. Micromolar-level in vitro inhibition was observed for two candidates (out of four synthesized) for each target. The most potent spike RBD inhibitor also emerged as a rare non-covalent antiviral with broad-spectrum activity against several SARS-CoV-2 variants in live virus neutralization assays. These results show that a broadly deployable machine intelligence framework can accelerate hit discovery across different emerging drug-targets.

Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding (preprint)

The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mpro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mpro competitively. The combined results provide new insight useful for the development of Mpro inhibitors.

Characterisation of the SARS-CoV-2 ExoN (nsp14ExoN-nsp10) complex: implications for its role in viral genome stability and inhibitor identification (preprint)

The SARS-CoV-2 coronavirus (CoV) causes COVID-19, a current global pandemic. SARS-CoV-2 belongs to an order of Nidovirales with very large RNA genomes. It is proposed that the fidelity of CoV genome replication is aided by an RNA nuclease complex, formed of non-structural proteins 14 and 10 (nsp14-nsp10), an attractive target for antiviral inhibition. Here, we confirm that the SARS-CoV-2 nsp14-nsp10 complex is an RNase. Detailed functional characterisation reveals nsp14-nsp10 is a highly versatile nuclease capable of digesting a wide variety of RNA structures, including those with a blocked 3-terminus. We propose that the role of nsp14-nsp10 in maintaining replication fidelity goes beyond classical proofreading and purges the nascent replicating RNA strand of a range of potentially replication terminating aberrations. Using the developed assays, we identify a series of drug and drug-like molecules that potently inhibit nsp14-nsp10, including the known Sars-Cov-2 major protease (Mpro) inhibitor ebselen and the HIV integrase inhibitor raltegravir, revealing the potential for bifunctional inhibitors in the treatment of COVID-19.

Allosteric inhibition of the SARS-CoV-2 main protease - insights from mass spectrometry-based assays (preprint)

Following translation of the SARS-CoV-2 RNA genome into two viral polypeptides, the main protease Mpro cleaves at eleven sites to release non-structural proteins required for viral replication. MPro is an attractive target for antiviral therapies to combat the coronavirus-2019 disease (COVID-19). Here, we have used native mass spectrometry (MS) to characterize the functional unit of Mpro. Analysis of the monomer-dimer equilibria reveals a dissociation constant of Kd = 0.14 {+/-} 0.03 M, revealing MPro has a strong preference to dimerize in solution. Developing an MS-based kinetic assay we then characterized substrate turnover rates by following temporal changes in the enzyme-substrate complexes, which are effectively "flash-frozen" as they transition from solution to the gas phase. We screened small molecules, that bind distant from the active site, for their ability to modulate activity. These compounds, including one proposed to disrupt the catalytically active dimer, slow the rate of substrate processing by ~35%. This information was readily obtained and, together with analysis of the x-ray crystal structures of these enzyme-small molecule complexes, provides a starting point for the development of more potent molecules that allosterically regulate MPro activity.