The third Critical Assessment of Computational Hit-finding Experiments (CACHE) challenged computational teams to identify chemically novel ligands targeting the macrodomain 1 of SARS-CoV-2 Nsp3, a promising coronavirus drug target. Twenty-three groups deployed diverse design strategies to collectively select 1739 ligand candidates. While over 85% of the designed molecules were chemically novel, the best experimentally confirmed hits were structurally similar to previously published compounds. Confirming a trend observed in CACHE #1 and #2, two of the best-performing workflows used compounds selected by physics-based computational screening methods to train machine learning models able to rapidly screen large chemical libraries, while four others used exclusively physics-based approaches. Three pharmacophore searches and one fragment growing strategy were also part of the seven winning workflows. While active molecules discovered by CACHE #3 participants largely mimicked the adenine ring of the endogenous substrate, ADP-ribose, preserving the canonical chemotype commonly observed in previously reported Nsp3-Mac1 ligands, they still provide novel structure-activity relationship insights that may inform the development of future antivirals. Collectively, these results show that multiple molecular design strategies can efficiently converge on similar potent molecules.

B-cell lymphoma 6 (BCL6) is a transcriptional repressor protein central to the development and maintenance of germinal centers (GCs) during the humoral immune response. BCL6 is often deregulated in diffuse large B-cell lymphoma (DLBCL), a type of non-Hodgkin's lymphoma, and inhibition of the protein-protein interaction between BCL6 and corepressors has been implicated as a therapeutic strategy. Based on a previously identified small molecule binding site on the BCL6 BTB domain, we carried out a virtual screen and identified a set of high micromolar screening hits. One series was advanced to a low micromolar confirmed hit via iterative rounds of compound optimization guided by structure activity relationships and co-crystal structures. Overall, we were able to use a rational, structure-based drug design approach to identify and advance a novel series of pyrrolopyrimidinone BCL6 BTB inhibitors.

Affinity-controlled release provides a versatile approach for the delivery of proteins from hydrogel systems by harnessing noncovalent interactions between a molecule of interest and a binding ligand. We present a strategy for the controlled release of native antibodies by leveraging affinity interactions with peptide ligands specific to the fragment crystallizable (Fc) region. Two Fc-binding ligands (FcLs) were engineered using distinct spacers, yielding different degrees of equilibrium dissociation constants (KD) for the Fc region of human IgG1: 2.54 ± 0.03 × 10-8 M (HWRGWV-GAKSKG; FcL1) and 3.01 ± 0.09 × 10-7 M (HWRGWV-K(PEG); FcLPEG). These ligands were immobilized within a chemically cross-linked hyaluronan-oxime hydrogel, where controlled release of bioactive bevacizumab was observed with FcL1 but not with the lower-affinity FcLPEG. To further explore the versatility of this approach, FcL1 was incorporated into a physically cross-linked hyaluronan-methylcellulose hydrogel, demonstrating tunable release of multiple IgG1 antibodies, including bevacizumab and adalimumab, each over a 7-day period. Together, this work demonstrates a broadly applicable strategy to tune antibody release.

Knowledge of protein-metabolite interactions can enhance mechanistic understanding and chemical probing of biochemical processes, but the discovery of endogenous ligands remains challenging. Here, we combined rapid affinity purification with precision mass spectrometry and high-resolution molecular docking to precisely map the physical associations of 296 chemically diverse small-molecule metabolite ligands with 69 distinct essential enzymes and 45 transcription factors in the gram-negative bacterium Escherichia coli. We then conducted systematic metabolic pathway integration, pan-microbial evolutionary projections, and independent in-depth biophysical characterization experiments to define the functional significance of ligand interfaces. This effort revealed principles governing functional crosstalk on a network level, divergent patterns of binding pocket conservation, and scaffolds for designing selective chemical probes. This structurally resolved ligand interactome mapping pipeline can be scaled to illuminate the native small-molecule networks of complete cells and potentially entire multi-cellular communities.

Diffuse Large B-Cell Lymphoma (DLBCL) is one of the most aggressive forms of lymphoid malignancies. About 40 % of patients eventually relapse and succumb to the disease within 5 years after diagnosis, underscoring the need for new treatment modalities. B-Cell Lymphoma 6 protein (BCL6) is a repressive transcription factor that is dysregulated in about 40 % of DLBCLs. As a rationale for pursuing BCL6 as a drug target, disrupting complexes between this protein and its co-repressors is thought to mitigate the downstream oncogenic effects of this pathway. However, drugging transcription factors presents a formidable undertaking since targeting protein-protein interactions has historically been challenging. In this study, we used X-ray structures of BCL6-SMRT (a silencing mediator for retinoid or thyroid-hormone receptors, also known as the nuclear receptor co-repressor 2, NCOR2) peptide and compound 79-6 to conduct a virtual screen of a library of 5.2 million compounds. Through this exercise, we identified the pyrrolopyridone 3 as a viable hit, which in turn led to the identification of pyrrolopyrimidone lead compound 4. The X-ray crystal structure of 4 bound to the BTB (Broad-Complex, Tramtrack, and Bric à brac) domain of BCL6 revealed a large back pocket as well as a left-hand channel adjacent to the ligand that could be leveraged to optimize these compounds. Sulfonamide side chains were therefore introduced to target this space, leading to compounds 11d and 11e having sub-micromolar binding to the BTB domain of BCL6.

Human DCAF1 is a multidomain protein that plays a critical role in protein homeostasis. Its WDR domain functions as a substrate recruitment module for RING-type CRL4 and HECT family EDVP E3 ubiquitin ligases, enabling the ubiquitination and proteasomal degradation of specific substrates. DCAF1's activity has been implicated in cell proliferation and is documented to promote tumorigenesis. Additionally, the DCAF1 WDR domain is hijacked by lentiviral accessory proteins to induce the degradation of host antiviral factors, such as SAMHD1 and UNG2. These diverse roles make DCAF1 an attractive target for therapeutic development in oncology and antiviral strategies. It is also a promising candidate for use in targeted protein degradation. We previously reported a novel ligand, OICR-8268, that targets the DCAF1 WDR domain. In this study, we present the development of OICR-41103, a potent, selective, and cell-active small molecule chemical probe for DCAF1, derived from OICR-8268. The co-crystal structure of the DCAF1-OICR-41103 complex reveals the ligand's binding mode within the WDR central pocket, demonstrating its potential for PROTAC design and development. Notably, OICR-41103 effectively displaces the lentiviral Vpr protein from DCAF1 in both biochemical and cellular settings, highlighting its potential for the development of HIV therapeutics.

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson's disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Of the 1955 molecules predicted by participants in Round 1 of the challenge, 73 were found to bind to LRRK2 in an SPR assay with a KD lower than 150 μM. These 73 molecules were advanced to the Round 2 hit expansion phase, where computational teams each selected up to 50 analogs. Binding was observed in two orthogonal assays for seven chemically diverse series, with affinities ranging from 18 to 140 μM. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants adopted strikingly diverging screening strategies. Machine learning-accelerated methods achieved similar results to brute force (e.g., exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

Proteolysis-targeting chimeras (PROTACs) have been explored for the degradation of drug targets for more than two decades. However, only a handful of E3 ligase substrate receptors have been efficiently used. Downregulation and mutation of these receptors would reduce the effectiveness of such PROTACs. We recently developed potent ligands for DCAF1, a substrate receptor of EDVP and CUL4 E3 ligases. Here, we focus on DCAF1 toward the development of PROTACs for WDR5, a drug target in various cancers. We report four DCAF1-based PROTACs with endogenous and exogenous WDR5 degradation effects and high-resolution crystal structures of the ternary complexes of DCAF1-PROTAC-WDR5. The structures reveal detailed insights into the interaction of DCAF1 with various WDR5-PROTACs, indicating a significant role of DCAF1 loops in providing needed surface plasticity, and reflecting the mechanism by which DCAF1 functions as a substrate receptor for E3 ligases with diverse sets of substrates.

DCAF1 is a substrate receptor of two distinct E3 ligases (CRL4DCAF1 and EDVP), plays a critical physiological role in protein degradation, and is considered a drug target for various cancers. Antagonists of DCAF1 could be used toward the development of therapeutics for cancers and viral treatments. We used the WDR domain of DCAF1 to screen a 114-billion-compound DNA encoded library (DEL) and identified candidate compounds using similarity search and machine learning. This led to the discovery of a compound (Z1391232269) with an SPR KD of 11 μM. Structure-guided hit optimization led to the discovery of OICR-8268 (26e) with an SPR KD of 38 nM and cellular target engagement with EC50 of 10 μM as measured by cellular thermal shift assay (CETSA). OICR-8268 is an excellent tool compound to enable the development of next-generation DCAF1 ligands toward cancer therapeutics, further investigation of DCAF1 functions in cells, and the development of DCAF1-based PROTACs.

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.org/. Since many targets had multiple chains and a number of ligands, several templates, and some manual interventions were required. In a few cases, no templates were found, and we had to use direct docking using the Glide program. Nevertheless, ligTBM was shown to be a very useful tool, and by any ranking criteria, our group was ranked among the top five best-performing teams. In fact, all the best groups used template-based docking methods. Thus, it appears that the AlphaFold2-generated models, despite the high accuracy of the predicted backbone, have local differences from the x-ray structure that make the use of direct docking methods more challenging. The results of CASP15 confirm that this limitation can be frequently overcome by homology-based docking.

The design of PROteolysis-TArgeting Chimeras (PROTACs) requires bringing an E3 ligase into proximity with a target protein to modulate the concentration of the latter through its ubiquitination and degradation. Here, we present a method for generating high-accuracy structural models of E3 ligase-PROTAC-target protein ternary complexes. The method is dependent on two computational innovations: adding a "silent" convolution term to an efficient protein-protein docking program to eliminate protein poses that do not have acceptable linker conformations and clustering models of multiple PROTACs that use the same E3 ligase and target the same protein. Results show that the largest consensus clusters always have high predictive accuracy and that the ensemble of models can be used to predict the dissociation rate and cooperativity of the ternary complex that relate to the degrading activity of the PROTAC. The method is demonstrated by applications to known PROTAC structures and a blind test involving PROTACs against BRAF mutant V600E. The results confirm that PROTACs function by stabilizing a favorable interaction between the E3 ligase and the target protein but do not necessarily exploit the most energetically favorable geometry for interaction between the proteins.

B cell lymphoma 6 (BCL6), a highly regulated transcriptional repressor, is deregulated in several forms of non-Hodgkin lymphoma (NHL), most notably in diffuse large B-cell lymphoma (DLBCL). The activities of BCL6 are dependent on protein-protein interactions with transcriptional co-repressors. To find new therapeutic interventions addressing the needs of patients with DLBCL, we initiated a program to identify BCL6 inhibitors that interfere with co-repressor binding. A virtual screen hit with binding activity in the high micromolar range was optimized by structure-guided methods, resulting in a novel and highly potent inhibitor series. Further optimization resulted in the lead candidate 58 (OICR12694/JNJ-65234637), a BCL6 inhibitor with low nanomolar DLBCL cell growth inhibition and an excellent oral pharmacokinetic profile. Based on its overall favorable preclinical profile, OICR12694 is a highly potent, orally bioavailable candidate for testing BCL6 inhibition in DLBCL and other neoplasms, particularly in combination with other therapies.

Metabolic diseases are increasing at staggering rates globally. The peroxisome proliferator-activated receptors (PPARα/γ/δ) are fatty acid sensors that help mitigate imbalances between energy uptake and utilization. Herein, we report compounds derived from phenolic lipids present in cashew nut shell liquid (CNSL), an abundant waste byproduct, in an effort to create effective, accessible, and sustainable drugs. Derivatives of anacardic acid and cardanol were tested for PPAR activity in HEK293 cell co-transfection assays, primary hepatocytes, and 3T3-L1 adipocytes. In vivo studies using PPAR-expressing zebrafish embryos identified CNSL derivatives with varying tissue-specific activities. LDT409 (23) is an analogue of cardanol with partial agonist activity for PPARα and PPARγ. Pharmacokinetic profiling showed that 23 is orally bioavailable with a half-life of 4 h in mice. CNSL derivatives represent a sustainable source of selective PPAR modulators with balanced intermediate affinities (EC50 ∼ 100 nM to 10 μM) that provide distinct and favorable gene activation profiles for the treatment of diabetes and obesity.

While coronavirus disease 2019 (COVID-19) begins as a respiratory infection, it progresses as a systemic disease involving multiorgan microthromboses that underly the pathology. SARS-CoV-2 enters host cells via attachment to the angiotensin-converting enzyme 2 (ACE2) receptor. ACE2 is widely expressed in a multitude of tissues, including the lung (alveolar cells), heart, intestine, kidney, testis, gallbladder, vasculature (endothelial cells), and immune cells. Interference in ACE2 signaling could drive the aforementioned systemic pathologies, such as endothelial dysfunction, microthromboses, and systemic inflammation, that are typically seen in patients with severe COVID-19. ACE2 is a component of the renin-angiotensin system (RAS) and is intimately associated with the plasma kallikrein-kinin system (KKS). As many papers are published on the role of ACE and ACE2 in COVID-19, we will review the role of bradykinin, and more broadly the KSS, in SARS-CoV-2-induced vascular dysfunction. Furthermore, we will discuss the possible therapeutic interventions that are approved and in development for the following targets: coagulation factor XII (FXII), tissue kallikrein (KLK1), plasma kallikrein (KLKB1), bradykinin (BK), plasminogen activator inhibitor (PAI-1), bradykinin B1 receptor (BKB1R), bradykinin B2 receptor (BKB2R), ACE, furin, and the NLRP3 inflammasome. Understanding these targets may prove of value in the treatment of COVID-19 as well as in other virus-induced coagulopathies in the future.

RBBP4 is a nuclear WD40 motif-containing protein widely implicated in various cancers and a putative drug target. It interacts with multiple proteins within diverse complexes such as nucleosome remodeling and deacetylase (NuRD) complex and polycomb repressive complex 2 (PRC2), as well as histone H3 and H4 through two distinct binding sites. B-cell lymphoma/leukemia 11A (BCL11A), friend of GATA-1 (FOG-1), plant homeodomain finger protein 6 (PHF6) and histone H3 bind to the top of the donut-shaped seven-bladed β-propeller fold of RBBP4, while suppressor of zeste 12 (SUZ12), metastasis associated protein 1 (MTA1) and histone H4 bind to a pocket on the side of the WD40 repeats of this protein. Here, we report the discovery of the first small molecule antagonists of the RBBP4 top pocket, competing with interacting peptides from proteins such as BCL11A and histone H3. We also determined the first crystal structure of RBBP4 in complex with a small molecule (OICR17251), paving the path for structure-guided design and optimization towards more potent antagonists.

The nuclear receptor peroxisome proliferator-activated receptor alpha (PPARα) is emerging as an important target in the brain for the treatment or prevention of cognitive disorders. The identification of high-affinity ligands for brain PPARα may reveal the mechanisms underlying the synaptic effects of this receptor and facilitate drug development. Here, using an affinity purification–untargeted mass spectrometry (AP-UMS) approach, we identified an endogenous, selective PPARα ligand, 7( S )-hydroxy-docosahexaenoic acid [7( S )-HDHA]. Results from mass spectrometric detection of 7( S )-HDHA in mouse and rat brain tissues, time-resolved FRET analyses, and thermal shift assays collectively revealed that 7( S )-HDHA potently activated PPARα with an affinity greater than that of other ligands identified to date. We also found that 7( S )-HDHA activation of PPARα in cultured mouse cortical neurons stimulated neuronal growth and arborization, as well as the expression of genes associated with synaptic plasticity. The findings suggest that this DHA derivative supports and enhances neuronal synaptic capacity in the brain.

Activating mutations in the epidermal growth factor receptor (EGFR) are common driver mutations in non-small cell lung cancer (NSCLC). First, second and third generation EGFR tyrosine kinase inhibitors (TKIs) are effective at inhibiting mutant EGFR NSCLC, however, acquired resistance is a major issue, leading to disease relapse. Here, we characterize a small molecule, EMI66, an analog of a small molecule which we previously identified to inhibit mutant EGFR signalling via a novel mechanism of action. We show that EMI66 attenuates receptor tyrosine kinase (RTK) expression and signalling and alters the electrophoretic mobility of Coatomer Protein Complex Beta 2 (COPB2) protein in mutant EGFR NSCLC cells. Moreover, we demonstrate that EMI66 can alter the subcellular localization of EGFR and COPB2 within the early secretory pathway. Furthermore, we find that COPB2 knockdown reduces the growth of mutant EGFR lung cancer cells, alters the post-translational processing of RTKs, and alters the endoplasmic reticulum (ER) stress response pathway. Lastly, we show that EMI66 treatment also alters the ER stress response pathway and inhibits the growth of mutant EGFR lung cancer cells and organoids. Our results demonstrate that targeting of COPB2 with EMI66 presents a viable approach to attenuate mutant EGFR signalling and growth in NSCLC.

Both previous and additional genetic knockdown studies reported herein implicate G protein-coupled receptor kinase 6 (GRK6) as a critical kinase required for the survival of multiple myeloma (MM) cells. Therefore, we sought to develop a small molecule GRK6 inhibitor as an MM therapeutic. From a focused library of known kinase inhibitors, we identified two hits with moderate biochemical potencies against GRK6. From these hits, we developed potent (IC50 < 10 nM) analogues with selectivity against off-target kinases. Further optimization led to the discovery of an analogue (18) with an IC50 value of 6 nM against GRK6 and selectivity against a panel of 85 kinases. Compound 18 has potent cellular target engagement and antiproliferative activity against MM cells and is synergistic with bortezomib. In summary, we demonstrate that targeting GRK6 with small molecule inhibitors represents a promising approach for MM and identify 18 as a novel, potent, and selective GRK6 inhibitor.

There are currently no effective chemotherapeutic drugs approved for the treatment of diffuse intrinsic pontine glioma (DIPG), an aggressive pediatric cancer resident in the pons region of the brainstem. Radiation therapy is beneficial but not curative, with the condition being uniformly fatal. Analysis of the genomic landscape surrounding DIPG has revealed that activin receptor-like kinase-2 (ALK2) constitutes a potential target for therapeutic intervention given its dysregulation in the disease. We adopted an open science approach to develop a series of potent, selective, orally bioavailable, and brain-penetrant ALK2 inhibitors based on the lead compound LDN-214117. Modest structural changes to the C-3, C-4, and C-5 position substituents of the core pyridine ring afforded compounds M4K2009, M4K2117, and M4K2163, each with a superior potency, selectivity, and/or blood-brain barrier (BBB) penetration profile. Robust in vivo pharmacokinetic (PK) properties and tolerability mark these inhibitors as advanced preclinical compounds suitable for further development and evaluation in orthotopic models of DIPG.