Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design.

Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism. However, the models from these studies are often linear regression equations and can have limitations associated with their usage. Applications of machine learning (ML) models to predict covalent warhead reactivities with QM descriptors are not extensively seen in the literature. This study uses QM descriptors, calculated at different levels of theory, to train ML models to predict reactivities of covalent acrylamide warheads. The QM/ML models are compared with linear regression models built upon the same QM descriptors and with ML models trained on structure-based features like Morgan fingerprints and RDKit descriptors. Experiments show that the QM/ML models outperform the linear regression models and the structure-based ML models, and literature test sets demonstrate the power of the QM/ML models to predict reactivities of unseen acrylamide warhead scaffolds. Ultimately, these QM/ML models are effective, computationally feasible tools that can expedite the design of new covalent inhibitors.

Martini 3 Force Field Parameters for Protein Lipidation Post-Translational Modifications.

Protein lipidations are vital co/post-translational modifications that tether lipid tails to specific protein amino acids, allowing them to anchor to biological membranes, switch their subcellular localization, and modulate association with other proteins. Such lipidations are thus crucial for multiple biological processes including signal transduction, protein trafficking, and membrane localization and are implicated in various diseases as well. Examples of lipid-anchored proteins include the Ras family of proteins that undergo farnesylation; actin and gelsolin that are myristoylated; phospholipase D that is palmitoylated; glycosylphosphatidylinositol-anchored proteins; and others. Here, we develop parameters for cysteine-targeting farnesylation, geranylgeranylation, and palmitoylation, as well as glycine-targeting myristoylation for the latest version of the Martini 3 coarse-grained force field. The parameters are developed using the CHARMM36m all-atom force field parameters as reference. The behavior of the coarse-grained models is consistent with that of the all-atom force field for all lipidations and reproduces key dynamical and structural features of lipid-anchored peptides, such as the solvent-accessible surface area, bilayer penetration depth, and representative conformations of the anchors. The parameters are also validated in simulations of the lipid-anchored peripheral membrane proteins Rheb and Arf1, after comparison with independent all-atom simulations. The parameters, along with mapping schemes for the popular martinize2 tool, are available for download at 10.5281/zenodo.7849262 and also as supporting information.

Membrane Composition and Raf[CRD]-Membrane Attachment Are Driving Forces for K-Ras4B Dimer Stability.

Ras proteins are membrane-anchored GTPases that regulate key cellular signaling networks. It has been recently shown that different anionic lipid types can affect the properties of Ras in terms of dimerization/clustering on the cell membrane. To understand the effects of anionic lipids on key spatiotemporal properties of dimeric K-Ras4B, we perform all-atom molecular dynamics simulations of the dimer K-Ras4B in the presence and absence of Raf[RBD/CRD] effectors on two model anionic lipid membranes: one containing 78% mol DOPC, 20% mol DOPS, and 2% mol PIP2 and another one with enhanced concentration of anionic lipids containing 50% mol DOPC, 40% mol DOPS, and 10% mol PIP2. Analysis of our results unveils the orientational space of dimeric K-Ras4B and shows that the stability of the dimer is enhanced on the membrane containing a high concentration of anionic lipids in the absence of Raf effectors. This enhanced stability is also observed in the presence of Raf[RBD/CRD] effectors although it is not influenced by the concentration of anionic lipids in the membrane, but rather on the ability of Raf[CRD] to anchor to the membrane. We generate dominant K-Ras4B conformations by Markov state modeling and yield the population of states according to the K-Ras4B orientation on the membrane. For the membrane containing anionic lipids, we observe correlations between the diffusion of K-Ras4B and PIP2 and anchoring of anionic lipids to the Raf[CRD] domain. We conclude that the presence of effectors with the Raf[CRD] domain anchoring on the membrane as well as the membrane composition both influence the conformational stability of the K-Ras4B dimer, enabling the preservation of crucial interface interactions.

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease.

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of Mpro, a cysteine protease, have been determined, facilitating structure-based drug design. Mpro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, Mpro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nucleophile Cys145 have been debated in previous studies of SARS-CoV Mpro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 Mpro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of Mpro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 Mpro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease.

The main protease (M pro ) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of M pro , a cysteine protease, have been determined, facilitating structure-based drug design. M pro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, M pro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nu-cleophile Cys145 have been debated in previous studies of SARS-CoV M pro , but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 M pro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of M pro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α -ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α -ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 M pro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Implications of Dynamic Occupancy, Binding Kinetics, and Channel Gating Kinetics for hERG Blocker Safety Assessment and Mitigation.

Blockade of the hERG potassium channel prolongs the ventricular action potential (AP) and QT interval, and triggers early after depolarizations (EADs) and torsade de pointes (TdP) arrhythmia. Opinions differ as to the causal relationship between hERG blockade and TdP, the relative weighting of other contributing factors, definitive metrics of preclinical proarrhythmicity, and the true safety margin in humans. Here, we have used in silico techniques to characterize the effects of channel gating and binding kinetics on hERG occupancy, and of blockade on the human ventricular AP. Gating effects differ for compounds that are sterically compatible with closed channels (becoming trapped in deactivated channels) versus those that are incompatible with the closed/closing state, and expelled during deactivation. Occupancies of trappable blockers build to equilibrium levels, whereas those of non-trappable blockers build and decay during each AP cycle. Occupancies of ~83% (non-trappable) versus ~63% (trappable) of open/inactive channels caused EADs in our AP simulations. Overall, we conclude that hERG occupancy at therapeutic exposure levels may be tolerated for nontrappable, but not trappable blockers capable of building to the proarrhythmic occupancy level. Furthermore, the widely used Redfern safety index may be biased toward trappable blockers, overestimating the exposure-IC50 separation in nontrappable cases.

Modulating the interaction between CDK2 and cyclin A with a quinoline-based inhibitor.

A new class of quinoline-based kinase inhibitors has been discovered that both disrupt cyclin dependent 2 (CDK2) interaction with its cyclin A subunit and act as ATP competitive inhibitors. The key strategy for discovering this class of protein-protein disrupter compounds was to screen the monomer CDK2 in an affinity-selection/mass spectrometry-based technique and to perform secondary assays that identified compounds that bound only to the inactive CDK2 monomer and not the active CDK2/cyclin A heterodimer. Through a series of chemical modifications the affinity (Kd) of the original hit improved from 1 to 0.005µM.

LMX1B mutations cause hereditary FSGS without extrarenal involvement.

LMX1B encodes a homeodomain-containing transcription factor that is essential during development. Mutations in LMX1B cause nail-patella syndrome, characterized by dysplasia of the patellae, nails, and elbows and FSGS with specific ultrastructural lesions of the glomerular basement membrane (GBM). By linkage analysis and exome sequencing, we unexpectedly identified an LMX1B mutation segregating with disease in a pedigree of five patients with autosomal dominant FSGS but without either extrarenal features or ultrastructural abnormalities of the GBM suggestive of nail-patella-like renal disease. Subsequently, we screened 73 additional unrelated families with FSGS and found mutations involving the same amino acid (R246) in 2 families. An LMX1B in silico homology model suggested that the mutated residue plays an important role in strengthening the interaction between the LMX1B homeodomain and DNA; both identified mutations would be expected to diminish such interactions. In summary, these results suggest that isolated FSGS could result from mutations in genes that are also involved in syndromic forms of FSGS. This highlights the need to include these genes in all diagnostic approaches to FSGS that involve next-generation sequencing.

Thermodynamics of nucleotide and inhibitor binding to wild-type and ispinesib-resistant forms of human kinesin spindle protein.

Current antimitotic cancer chemotherapy based on vinca alkaloids and taxanes target tubulin, a protein required not only for mitotic spindle formation but also for the overall structural integrity of terminally differentiated cells. Among many innovations targeting specific mitotic events, inhibition of motor enzymes including KSP (or Eg5) has been validated as a highly productive approach. Many reported KSP inhibitors bind to an induced allosteric site near the site of ATP hydrolysis, and some have been tested in clinical trials with varying degrees of success. This allosteric site was defined in detail by X-ray crystallography of inhibitor complexes, yet complementary information on binding thermodynamics is still lacking. Using two model ATP-uncompetitive inhibitors, monastrol and ispinesib, we report here the results of thermal denaturation and isothermal titration calorimetric studies. These binding studies were conducted with the wild-type KSP motor domain as well as two ispinesib mutants (D130V and A133D) identified to confer resistance to ispinesib treatment. The thermodynamic parameters obtained were placed in the context of the available structural information and corresponding models of the two ispinesib-resistant mutants. The resulting overall information formed a strong basis for future structure-based design of inhibitors of KSP and related motor enzymes.

Recent advances on structure-informed drug discovery of cyclin-dependent kinase-2 inhibitors.

Serine and threonine kinases play an important role in signal-transduction pathways. Within this kinase family, cyclin-dependent kinase (CDK)2 is an attractive target for oncology involved in cell cycle regulation. In recent years, kinase inhibition has become a major area for therapeutic involvement. As we discuss here, these efforts have resulted in a considerable increase in the number of available high-resolution structures of CDK2-inhibitor complexes. A large amount of structural-based and computational work has allowed the identification of novel chemical scaffolds and structural motifs to design potent CDK2 inhibitors. Of any kinase, CDK2 has the most structures available from the protein databank, averaging 22 new structures per year since 2002. A protein-ligand interaction fingerprint analysis of the available CDK2 protein-ligand complexes indicates that structural diversity is attainable from the structure-based design of CDK2 inhibitors. Since the first CDK2 structure was published in 1996, seven new chemical entities (NCEs) have been advanced to clinical stages. To date, only three of these NCEs have had their complexes published in the protein databank. This review summarizes the structurally informed efforts in the field of CDK2 inhibitor design.

The active site of a zinc-dependent metalloproteinase influences the computed pK(a) of ligands coordinated to the catalytic zinc ion.

TNF-alpha converting enzyme (TACE) is a multidomain, membrane-anchored protein that includes a Zn-dependent protease domain. It releases the soluble form of cytokine tumor necrosis factor-alpha (TNF-alpha) from its membrane-bound precursor. TACE is a metalloprotease containing a catalytic glutamic acid, Glu-406, and a Zn(2+) ion ligated to three imidazoles. The protonation states of the active site glutamic acid and inhibitors are important factors in understanding the potency of inhibitors with acidic zinc-ligating groups such as hydroxamic and carboxylic acids. Density functional methods were utilized to compute pK(a) values using a model of the catalytic site of TACE and to predict a concomitant mechanism of binding, consistent with lowering the pK(a) of the bound ligand and raising the pK(a) of the active site Glu-406. Weak acids, such as hydroxamic acids, bind in their neutral form and then transfer an acidic proton to Glu-406. Stronger acids, such as carboxylic acids, bind in their anionic form and require preprotonation of Glu-406. Similar binding events would be expected for other zinc-dependent proteases.