Design and Evaluation of PROTACs Targeting Acyl Protein Thioesterase 1.

PROTAC linker design remains mostly an empirical task. We employed the PRosettaC computational software in the design of sulfonyl-fluoride-based PROTACs targeting acyl protein thioesterase 1 (APT1). The software efficiently generated ternary complex models from empirically-designed PROTACs and suggested alkyl linkers to be the preferred type of linker to target APT1. Western blotting analysis revealed efficient degradation of APT1 and activity-based protein profiling showed remarkable selectivity of an alkyl linker-based PROTAC amongst serine hydrolases. Collectively, our data suggests that combining PRosettaC and chemoproteomics can effectively assist in triaging PROTACs for synthesis and providing early data on their potency and selectivity.

Pep-Whisperer: Inhibitory peptide design.

Designing peptides for protein-protein interaction inhibition is of significant interest in computer-aided drug design. Such inhibitory peptides could mimic and compete with the binding of the partner protein to the inhibition target. Experimental peptide design is a laborious, time consuming, and expensive multi-step process. Therefore, in silico peptide design can be beneficial for achieving this task. We present a novel algorithm, Pep-Whisperer, which aims to design inhibitory peptides for protein-protein interaction. The desirable peptides would have a relatively high predicted binding affinity to the target protein in a given protein-protein complex. The algorithm outputs linear peptides which are based on an initial template. The template could either be a peptide which is retrieved from the interaction site, or a patch of nonconsecutive amino acids from the protein-protein interface which is completed to a linear peptide by short polyalanine linkers. In addition, the algorithm takes into consideration the conservation of the amino acids in the ligand-protein binding site by using evolutionary information for choosing the preferred amino acids in each position of the designed peptide. Our algorithm was able to design peptides with high predicted binding affinity to the target protein. The method is fully automated and available as a web server at http://bioinfo3d.cs.tau.ac.il/PepWhisperer/.

An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor.

Designing covalent inhibitors is increasingly important, although it remains challenging. Here, we present covalentizer, a computational pipeline for identifying irreversible inhibitors based on structures of targets with non-covalent binders. Through covalent docking of tailored focused libraries, we identify candidates that can bind covalently to a nearby cysteine while preserving the interactions of the original molecule. We found âˆ¼11,000 cysteines proximal to a ligand across 8,386 complexes in the PDB. Of these, the protocol identified 1,553 structures with covalent predictions. In a prospective evaluation, five out of nine predicted covalent kinase inhibitors showed half-maximal inhibitory concentration (IC50) values between 155 nM and 4.5 µM. Application against an existing SARS-CoV Mpro reversible inhibitor led to an acrylamide inhibitor series with low micromolar IC50 values against SARS-CoV-2 Mpro. The docking was validated by 12 co-crystal structures. Together these examples hint at the vast number of covalent inhibitors accessible through our protocol.

Sulfopin is a covalent inhibitor of Pin1 that blocks Myc-driven tumors in vivo.

The peptidyl-prolyl isomerase, Pin1, is exploited in cancer to activate oncogenes and inactivate tumor suppressors. However, despite considerable efforts, Pin1 has remained an elusive drug target. Here, we screened an electrophilic fragment library to identify covalent inhibitors targeting Pin1's active site Cys113, leading to the development of Sulfopin, a nanomolar Pin1 inhibitor. Sulfopin is highly selective, as validated by two independent chemoproteomics methods, achieves potent cellular and in vivo target engagement and phenocopies Pin1 genetic knockout. Pin1 inhibition had only a modest effect on cancer cell line viability. Nevertheless, Sulfopin induced downregulation of c-Myc target genes, reduced tumor progression and conferred survival benefit in murine and zebrafish models of MYCN-driven neuroblastoma, and in a murine model of pancreatic cancer. Our results demonstrate that Sulfopin is a chemical probe suitable for assessment of Pin1-dependent pharmacology in cells and in vivo, and that Pin1 warrants further investigation as a potential cancer drug target.

Tunable Methacrylamides for Covalent Ligand Directed Release Chemistry.

Targeted covalent inhibitors are an important class of drugs and chemical probes. However, relatively few electrophiles meet the criteria for successful covalent inhibitor design. Here we describe α-substituted methacrylamides as a new class of electrophiles suitable for targeted covalent inhibitors. While typically α-substitutions inactivate acrylamides, we show that hetero α-substituted methacrylamides have higher thiol reactivity and undergo a conjugated addition-elimination reaction ultimately releasing the substituent. Their reactivity toward thiols is tunable and correlates with the pKa/pKb of the leaving group. In the context of the BTK inhibitor ibrutinib, these electrophiles showed lower intrinsic thiol reactivity than the unsubstituted ibrutinib acrylamide. This translated to comparable potency in protein labeling, in vitro kinase assays, and functional cellular assays, with improved selectivity. The conjugate addition-elimination reaction upon covalent binding to their target cysteine allows functionalizing α-substituted methacrylamides as turn-on probes. To demonstrate this, we prepared covalent ligand directed release (CoLDR) turn-on fluorescent probes for BTK, EGFR, and K-RasG12C. We further demonstrate a BTK CoLDR chemiluminescent probe that enabled a high-throughput screen for BTK inhibitors. Altogether we show that α-substituted methacrylamides represent a new and versatile addition to the toolbox of targeted covalent inhibitor design.

Conserved interactions required for inhibition of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The COVID-19 pandemic caused by the SARS-CoV-2 requires a fast development of antiviral drugs. SARS-CoV-2 viral main protease (Mpro, also called 3C-like protease, 3CLpro) is a potential target for drug design. Crystal and co-crystal structures of the SARS-CoV-2 Mpro have been solved, enabling the rational design of inhibitory compounds. In this study we analyzed the available SARS-CoV-2 and the highly similar SARS-CoV-1 crystal structures. We identified within the active site of the Mpro, in addition to the inhibitory ligands' interaction with the catalytic C145, two key H-bond interactions with the conserved H163 and E166 residues. Both H-bond interactions are present in almost all co-crystals and are likely to occur also during the viral polypeptide cleavage process as suggested from docking of the Mpro cleavage recognition sequence. We screened in silico a library of 6900 FDA-approved drugs (ChEMBL) and filtered using these key interactions and selected 29 non-covalent compounds predicted to bind to the protease. Additional screen, using DOCKovalent was carried out on DrugBank library (11,414 experimental and approved drugs) and resulted in 6 covalent compounds. The selected compounds from both screens were tested in vitro by a protease activity inhibition assay. Two compounds showed activity at the 50 µM concentration range. Our analysis and findings can facilitate and focus the development of highly potent inhibitors against SARS-CoV-2 infection.

PRosettaC: Rosetta Based Modeling of PROTAC Mediated Ternary Complexes.

Proteolysis-targeting chimeras (PROTACs), which induce degradation by recruitment of an E3 ligase to a target protein, are gaining much interest as a new pharmacological modality. However, designing PROTACs is challenging. Formation of a ternary complex between the protein target, the PROTAC, and the recruited E3 ligase is considered paramount for successful degradation. A structural model of this ternary complex could in principle inform rational PROTAC design. Unfortunately, only a handful of structures are available for such complexes, necessitating tools for their modeling. We developed a combined protocol for the modeling of a ternary complex induced by a given PROTAC. Our protocol alternates between sampling of the protein-protein interaction space and the PROTAC molecule conformational space. Application of this protocol-PRosettaC-to a benchmark of known PROTAC ternary complexes results in near-native predictions, with often atomic accuracy prediction of the protein chains, as well as the PROTAC binding moieties. It allowed the modeling of a CRBN/BTK complex that recapitulated experimental results for a series of PROTACs. PRosettaC generated models may be used to design PROTACs for new targets, as well as improve PROTACs for existing targets, potentially cutting down time and synthesis efforts. To enable wide access to this protocol, we have made it available through a web server (https://prosettac.weizmann.ac.il/).

Identification of a potent and selective covalent Pin1 inhibitor.

Peptidyl-prolyl cis/trans isomerase NIMA-interacting 1 (Pin1) is commonly overexpressed in human cancers, including pancreatic ductal adenocarcinoma (PDAC). While Pin1 is dispensable for viability in mice, it is required for activated Ras to induce tumorigenesis, suggesting a role for Pin1 inhibitors in Ras-driven tumors, such as PDAC. We report the development of rationally designed peptide inhibitors that covalently target Cys113, a highly conserved cysteine located in the Pin1 active site. The inhibitors were iteratively optimized for potency, selectivity and cell permeability to give BJP-06-005-3, a versatile tool compound with which to probe Pin1 biology and interrogate its role in cancer. In parallel to inhibitor development, we employed genetic and chemical-genetic strategies to assess the consequences of Pin1 loss in human PDAC cell lines. We demonstrate that Pin1 cooperates with mutant KRAS to promote transformation in PDAC, and that Pin1 inhibition impairs cell viability over time in PDAC cell lines.

Overcoming insecticide resistance through computational inhibitor design.

Insecticides allow control of agricultural pests and disease vectors and are vital for global food security and health. The evolution of resistance to insecticides, such as organophosphates (OPs), is a serious and growing concern. OP resistance often involves sequestration or hydrolysis of OPs by carboxylesterases. Inhibiting carboxylesterases could, therefore, restore the effectiveness of OPs for which resistance has evolved. Here, we use covalent virtual screening to produce nano-/picomolar boronic acid inhibitors of the carboxylesterase αE7 from the agricultural pest Lucilia cuprina as well as a common Gly137Asp αE7 mutant that confers OP resistance. These inhibitors, with high selectivity against human acetylcholinesterase and low to no toxicity in human cells and in mice, act synergistically with the OPs diazinon and malathion to reduce the amount of OP required to kill L. cuprina by up to 16-fold and abolish resistance. The compounds exhibit broad utility in significantly potentiating another OP, chlorpyrifos, against the common pest, the peach-potato aphid (Myzus persicae). These compounds represent a solution to OP resistance as well as to environmental concerns regarding overuse of OPs, allowing significant reduction of use without compromising efficacy.

Rapid Covalent-Probe Discovery by Electrophile-Fragment Screening.

Covalent probes can display unmatched potency, selectivity, and duration of action; however, their discovery is challenging. In principle, fragments that can irreversibly bind their target can overcome the low affinity that limits reversible fragment screening, but such electrophilic fragments were considered nonselective and were rarely screened. We hypothesized that mild electrophiles might overcome the selectivity challenge and constructed a library of 993 mildly electrophilic fragments. We characterized this library by a new high-throughput thiol-reactivity assay and screened them against 10 cysteine-containing proteins. Highly reactive and promiscuous fragments were rare and could be easily eliminated. In contrast, we found hits for most targets. Combining our approach with high-throughput crystallography allowed rapid progression to potent and selective probes for two enzymes, the deubiquitinase OTUB2 and the pyrophosphatase NUDT7. No inhibitors were previously known for either. This study highlights the potential of electrophile-fragment screening as a practical and efficient tool for covalent-ligand discovery.

Novel K-Ras G12C Switch-II Covalent Binders Destabilize Ras and Accelerate Nucleotide Exchange.

The success of targeted covalent inhibitors in the global pharmaceutical industry has led to a resurgence of covalent drug discovery. However, covalent inhibitor design for flexible binding sites remains a difficult task due to a lack of methodological development. Here, we compared covalent docking to empirical electrophile screening against the highly dynamic target K-RasG12C. While the overall hit rate of both methods was comparable, we were able to rapidly progress a docking hit to a potent irreversible covalent binder that modifies the inactive, GDP-bound state of K-RasG12C. Hydrogen-deuterium exchange mass spectrometry was used to probe the protein dynamics of compound binding to the switch-II pocket and subsequent destabilization of the nucleotide-binding region. SOS-mediated nucleotide exchange assays showed that, contrary to prior switch-II pocket inhibitors, these new compounds appear to accelerate nucleotide exchange. This study highlights the efficiency of covalent docking as a tool for the discovery of chemically novel hits against challenging targets.

Protein-Peptide Interaction Design: PepCrawler and PinaColada.

In this chapter we present two methods related to rational design of inhibitory peptides: PepCrawler: A tool to derive binding peptides from protein-protein complexes and the prediction of protein-peptide complexes. Given an initial protein-peptide complex, the method detects improved predicted peptide binding conformations which bind the protein with higher affinity. This program is a robotics motivated algorithm, representing the peptide as a robotic arm moving among obstacles and exploring its conformational space in an efficient way. PinaColada: A peptide design program for the discovery of novel peptide candidates that inhibit protein-protein interactions. PinaColada uses PepCrawler while introducing sequence mutations, in order to find novel inhibitory peptides for PPIs. It uses the ant colony optimization approach to explore the peptide's sequence space, while using PepCrawler in the refinement stage.

PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm.

MOTIVATION: Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. RESULTS: In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ([Formula: see text]) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. AVAILABILITY AND IMPLEMENTATION: An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. CONTACT: danielza@post.tau.ac.il; wolfson@tau.ac.il.