iTAG an optimized IMiD-induced degron for targeted protein degradation in human and murine cells.

To address the limitation associated with degron based systems, we have developed iTAG, a synthetic tag based on IMiDs/CELMoDs mechanism of action that improves and addresses the limitations of both PROTAC and previous IMiDs/CeLMoDs based tags. Using structural and sequence analysis, we systematically explored native and chimeric degron containing domains (DCDs) and evaluated their ability to induce degradation. We identified the optimal chimeric iTAG(DCD23 60aa) that elicits robust degradation of targets across cell types and subcellular localizations without exhibiting the well documented "hook effect" of PROTAC-based systems. We showed that iTAG can also induce target degradation by murine CRBN and enabled the exploration of natural neo-substrates that can be degraded by murine CRBN. Hence, the iTAG system constitutes a versatile tool to degrade targets across the human and murine proteome.

Binding Mode Prediction and Virtual Screening Applications by Covalent Docking.

The mechanism of action of covalent drugs involves the formation of a bond between their electrophilic warhead group and a nucleophilic residue of the protein target. The recent advances in covalent drug discovery have accelerated the development of computational tools for the design and characterization of covalent binders. Covalent docking algorithms can predict the binding mode of covalent ligands by modeling the bonds and interactions formed at the reaction site. Their scoring functions can estimate the relative binding affinity of ligands towards the target of interest, thus allowing virtual screening of compound libraries. However, most of the scoring schemes have no specific terms for the bond formation, and therefore it prevents the direct comparison of warheads with different intrinsic reactivity. Herein, we describe a protocol for the binding mode prediction of covalent ligands, a typical virtual screening of compound sets with a single warhead chemistry, and an alternative approach to screen libraries that include various warhead types, as applied in recently validated studies.

WIDOCK: a reactive docking protocol for virtual screening of covalent inhibitors.

Here we present WIDOCK, a virtual screening protocol that supports the selection of diverse electrophiles as covalent inhibitors by incorporating ligand reactivity towards cysteine residues into AutoDock4. WIDOCK applies the reactive docking method (Backus et al. in Nature 534:570-574, 2016) and extends it into a virtual screening tool by introducing facile experimental or computational parametrization and a ligand focused evaluation scheme together with a retrospective and prospective validation against various therapeutically relevant targets. Parameters accounting for ligand reactivity are derived from experimental reaction kinetic data or alternatively from computed reaction barriers. The performance of this docking protocol was first evaluated by investigating compound series with diverse warhead chemotypes against KRASG12C, MurA and cathepsin B. In addition, WIDOCK was challenged on larger electrophilic libraries screened against OTUB2 and NUDT7. These retrospective analyses showed high sensitivity in retrieving experimental actives, by also leading to superior ROC curves, AUC values and better enrichments than the standard covalent docking tool available in AutoDock4 when compound collections with diverse warheads were investigated. Finally, we applied WIDOCK for the prospective identification of covalent human MAO-A inhibitors acting via a new mechanism by binding to Cys323. The inhibitory activity of several predicted compounds was experimentally confirmed and the labelling of Cys323 was proved by subsequent MS/MS measurements. These findings demonstrate the usefulness of WIDOCK as a warhead-sensitive, covalent virtual screening protocol.

DUckCov: a Dynamic Undocking-Based Virtual Screening Protocol for Covalent Binders.

Thanks to recent guidelines, the design of safe and effective covalent drugs has gained significant interest. Other than targeting non-conserved nucleophilic residues, optimizing the noncovalent binding framework is important to improve potency and selectivity of covalent binders toward the desired target. Significant efforts have been made in extending the computational toolkits to include a covalent mechanism of protein targeting, like in the development of covalent docking methods for binding mode prediction. To highlight the value of the noncovalent complex in the covalent binding process, here we describe a new protocol using tethered and constrained docking in combination with Dynamic Undocking (DUck) as a tool to privilege strong protein binders for the identification of novel covalent inhibitors. At the end of the protocol, dedicated covalent docking methods were used to rank and select the virtual hits based on the predicted binding mode. By validating the method on JAK3 and KRas, we demonstrate how this fast iterative protocol can be applied to explore a wide chemical space and identify potent targeted covalent inhibitors.

A road map for prioritizing warheads for cysteine targeting covalent inhibitors.

Targeted covalent inhibitors have become an integral part of a number of therapeutic protocols and are the subject of intense research. The mechanism of action of these compounds involves the formation of a covalent bond with protein nucleophiles, mostly cysteines. Given the abundance of cysteines in the proteome, the specificity of the covalent inhibitors is of utmost importance and requires careful optimization of the applied warheads. In most of the cysteine targeting covalent inhibitor programs the design strategy involves incorporating Michael acceptors into a ligand that is already known to bind non-covalently. In contrast, we suggest that the reactive warhead itself should be tailored to the reactivity of the specific cysteine being targeted, and we describe a strategy to achieve this goal. Here, we have extended and systematically explored the available organic chemistry toolbox and characterized a large number of warheads representing different chemistries. We demonstrate that in addition to the common Michael addition, there are other nucleophilic addition, addition-elimination, nucleophilic substitution and oxidation reactions suitable for specific covalent protein modification. Importantly, we reveal that warheads for these chemistries impact the reactivity and specificity of covalent fragments at both protein and proteome levels. By integrating surrogate reactivity and selectivity models and subsequent protein assays, we define a road map to help enable new or largely unexplored covalent chemistries for the optimization of cysteine targeting inhibitors.

Comparative Evaluation of Covalent Docking Tools.

Increased interest in covalent drug discovery led to the development of computer programs predicting binding mode and affinity of covalent inhibitors. Here we compare the performance of six covalent docking tools, AutoDock4, CovDock, FITTED, GOLD, ICM-Pro, and MOE, for reproducing experimental binding modes in an unprecedently large and diverse set of covalent complexes. It was found that 40-60% of the top scoring ligand poses are within 2.0 Å RMSD from the experimental binding mode. This rate showed program dependent increase and achieved 50-90% when the best RMSD among the top ten scoring poses was considered. This performance is comparable to that of noncovalent docking tools and therefore suggests that anchoring the ligand does not necessarily improve the accuracy of the prediction. The effect of various ligand and protein features on the docking performance was investigated. At the level of warhead chemistry, higher success rate was found for Michael additions, nucleophilic additions and nucleophilic substitutions than for ring opening reactions and disulfide formation. Increasing ligand size and flexibility generally affects pose predictions unfavorably, although AutoDock4, FITTED, and ICM-Pro were found to be less sensitive up to 35 heavy atoms. Increasing the accessibility of the target cysteine tends to result in improved binding mode predictions. Docking programs show protein dependent performance suggesting a target-dependent choice of the optimal docking tool. It was found that noncovalent docking into Cys/Ala mutated proteins by ICM-Pro and Glide reproduced experimental binding modes with only slightly lower performance and at a significantly lower computational expense than covalent docking did. Overall, our results highlight the key factors influencing the docking performance of the investigated tools and they give guidelines for selecting the optimal combination of warheads, ligands, and tools for the system investigated. Results also identify the most important aspects to be considered for developing improved protocols for docking and virtual screening of covalent ligands.