Molecular Mechanism of Labelling Functional Cysteines by Heterocyclic Thiones.

Heterocyclic thiones have recently been identified as reversible covalent warheads, consistent with their mild electrophilic nature. Little is known so far about their mechanism of action in labelling nucleophilic sidechains, especially cysteines. The vast number of tractable cysteines promotes a wide range of target proteins to examine; however, our focus was put on functional cysteines. We chose the main protease of SARS-CoV-2 harboring Cys145 at the active site that is a structurally characterized and clinically validated target of covalent inhibitors. We screened an in-house, cysteine-targeting covalent inhibitor library which resulted in several covalent fragment hits with benzoxazole, benzothiazole and benzimidazole cores. Thione derivatives and Michael acceptors were selected for further investigations with the objective of exploring the mechanism of inhibition of the thiones and using the thoroughly characterized Michael acceptors for benchmarking our studies. Classical and hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations were carried out that revealed a new mechanism of covalent cysteine labelling by thione derivatives, which was supported by QM and free energy calculations and by a wide range of experimental results. Our study shows that the molecular recognition step plays a crucial role in the overall binding of both sets of molecules.

Molecular Dynamics Simulations and Diversity Selection by Extended Continuous Similarity Indices.

Molecular dynamics (MD) is a core methodology of molecular modeling and computational design for the study of the dynamics and temporal evolution of molecular systems. MD simulations have particularly benefited from the rapid increase of computational power that has characterized the past decades of computational chemical research, being the first method to be successfully migrated to the GPU infrastructure. While new-generation MD software is capable of delivering simulations on an ever-increasing scale, relatively less effort is invested in developing postprocessing methods that can keep up with the quickly expanding volumes of data that are being generated. Here, we introduce a new idea for sampling frames from large MD trajectories, based on the recently introduced framework of extended similarity indices. Our approach presents a new, linearly scaling alternative to the traditional approach of applying a clustering algorithm that usually scales as a quadratic function of the number of frames. When showcasing its usage on case studies with different system sizes and simulation lengths, we have registered speedups of up to 2 orders of magnitude, as compared to traditional clustering algorithms. The conformational diversity of the selected frames is also noticeably higher, which is a further advantage for certain applications, such as the selection of structural ensembles for ligand docking. The method is available open-source at https://github.com/ramirandaq/MultipleComparisons.

Mechanistic and thermodynamic characterization of oxathiazolones as potent and selective covalent immunoproteasome inhibitors.

The ubiquitin-proteasome system is responsible for the degradation of proteins and plays a critical role in key cellular processes. While the constitutive proteasome (cPS) is expressed in all eukaryotic cells, the immunoproteasome (iPS) is primarily induced during disease processes, and its inhibition is beneficial in the treatment of cancer, autoimmune disorders and neurodegenerative diseases. Oxathiazolones were reported to selectively inhibit iPS over cPS, and the inhibitory activity of several oxathiazolones against iPS was experimentally determined. However, the detailed mechanism of the chemical reaction leading to irreversible iPS inhibition and the key selectivity drivers are unknown, and separate characterization of the noncovalent and covalent inhibition steps is not available for several compounds. Here, we investigate the chemical reaction between oxathiazolones and the Thr1 residue of iPS by quantum mechanics/molecular mechanics (QM/MM) simulations to establish a plausible reaction mechanism and to determine the rate-determining step of covalent complex formation. The modelled binding mode and reaction mechanism are in line with the selective inhibition of iPS versus cPS by oxathiazolones. The kinact value of several ligands was estimated by constructing the potential of mean force of the rate-determining step by QM/MM simulations coupled with umbrella sampling. The equilibrium constant Ki of the noncovalent complex formation was evaluated by classical force field-based thermodynamic integration. The calculated Ki and kinact values made it possible to analyse the contribution of the noncovalent and covalent steps to the overall inhibitory activity. Compounds with similar intrinsic reactivities exhibit varying selectivities for iPS versus cPS owing to subtle differences in the binding modes that slightly affect Ki, the noncovalent affinity, and importantly alter kinact, the covalent reactivity of the bound compounds. A detailed understanding of the inhibitory mechanism of oxathiazolones is useful in designing iPS selective inhibitors with improved drug-like properties.

Affinity and Selectivity Assessment of Covalent Inhibitors by Free Energy Calculations.

Covalent inhibitors have been gaining increased attention in drug discovery due to their beneficial properties such as long residence time, high biochemical efficiency, and specificity. Optimization of covalent inhibitors is a complex task that involves parallel monitoring of the noncovalent recognition elements and the covalent reactivity of the molecules to avoid potential idiosyncratic side effects. This challenge calls for special design protocols, including a variety of computational chemistry methods. Covalent inhibition proceeds through multiple steps, and calculating free energy changes of the subsequent binding events along the overall binding process would help us to better control the design of drug candidates. Inspired by the recent success of free energy calculations on reversible binders, we developed a complex protocol to compute free energies related to the noncovalent and covalent binding steps with thermodynamic integration and hybrid quantum mechanical/molecular mechanical (QM/MM) potential of mean force (PMF) calculations, respectively. In optimization settings, we examined two therapeutically relevant proteins complexed with congeneric sets of irreversible cysteine targeting covalent inhibitors. In the selectivity paradigm, we studied the irreversible binding of covalent inhibitors to phylogenetically close targets by a mutational approach. The results of the calculations are in good agreement with the experimental free energy values derived from the inhibition and kinetic constants (Ki and kinact) of the enzyme-inhibitor binding. The proposed method might be a powerful tool to predict the potency, selectivity, and binding mechanism of irreversible covalent inhibitors.

Catalytic Mechanism and Covalent Inhibition of UDP-N-Acetylglucosamine Enolpyruvyl Transferase (MurA): Implications to the Design of Novel Antibacterials.

UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) catalyzes the first step in the biosynthesis of the bacterial cell wall. This pathway is essential for the growth of bacteria but missing in mammals, that nominates MurA as an attractive antibacterial target. MurA has a flexible loop whose conformational change is known to be part of the activation mechanism of the enzyme. We have shown that the loop closed conformation makes the proton transfer from Cys115 to His394 possible by a low barrier exothermic process. QM/MM MD simulations revealed that the activated thiolate is able to react with phosphoenolpyruvate (PEP), the natural substrate of MurA. The binding free energy profile of several covalent inhibitors with various warheads reacting with the activated Cys115 was calculated by QM/MM MD simulations and confirmed that reaction barrier heights tend to separate active from inactive compounds. Our results give new insight into the catalytic mechanism and covalent inhibition of MurA and suggest that QM/MM MD simulations are able to support ligand design by providing sensible relative free energy barriers for covalent inhibitors with various warheads reacting with thiolate nucleophiles.