Docking for EP4R antagonists active against inflammatory pain

Active Learning to Select the Most Suitable Reagents and One-Step Organic Chemistry Reactions for Prioritizing Target-Specific Hits from Ultralarge Chemical Spaces

Designing chemically novel and synthesizable ligands from the largest possible chemical space is a major issue in modern drug discovery to identify early hits that are easily amenable to medicinal chemistry optimization. Starting from the sole three-dimensional structure of a protein binding site, we herewith describe a fully automated active learning protocol to propose the commercial chemical reagents and one-step organic chemistry reactions necessary to enumerate target-specific primary hits from ultralarge chemical spaces. When applied in different scenarios (single transform and multiple transforms) addressing chemical spaces of various sizes (from 670 million to 4.5 billion compounds), the method was able to recover up to 98% of virtual hits discovered by an exhaustive docking-based approach while scanning only 5% of the full chemical space. It is therefore applicable to the structure-based screening of trillion-sized chemical spaces at a very high throughput with minimal computational resources.

SpaceHASTEN: A Structure-Based Virtual Screening Tool for Nonenumerated Virtual Chemical Libraries

Given the size of the relevant chemical space for drug discovery, working with fully enumerated compound libraries (especially in three-dimensional (3D)) is unfeasible. Nonenumerated virtual chemical spaces are a practical solution to this issue, where compounds are described as building blocks which are then connected by rules. One concrete example of such is the BioSolveIT chemical spaces file format (.space). Tools to search these space-files exist that are using ligand-based methods including two-dimensional (2D) fingerprint similarity, substructure matching, and fuzzier similarity metrics such as FTrees. However, there is no software available that enables the screening of these nonenumerated spaces using protein structure as the input query. Here, a hybrid ligand/structure-based virtual screening tool, called SpaceHASTEN, was developed on top of SpaceLight, FTrees, LigPrep, and Glide to allow efficient structure-based virtual screening of nonenumerated chemical spaces. SpaceHASTEN was validated using three public targets picked from the DUD-E data set. It was able to retrieve a large number of diverse and novel high-scoring compounds (virtual hits) from nonenumerated chemical spaces of billions of molecules, after docking a few million compounds. The software can be freely used and is available from http://github.com/TuomoKalliokoski/SpaceHASTEN.

Cartilage-targeting peptide-modified cerium oxide nanoparticles alleviate oxidative stress and cartilage damage in osteoarthritis

BACKGROUND

Osteoarthritis (OA) is a degenerative joint disease that leads to a substantial decline in the well-being of older individuals. Chondrocyte senescence and the resultant damage to cartilage tissue, induced by elevated levels of reactive oxygen species within the joint cavity, are significant causative factors in OA development. Cerium oxide nanoparticles (CeONPs) present a promising avenue for therapeutic investigation due to their exceptional antioxidant properties. However, the limited effectiveness of drugs in the joint cavity is often attributed to their rapid clearance by synovial fluid.

METHODS

Polyethylene glycol-packed CeONPs (PEG-CeONPs) were synthesized and subsequently modified with the cartilage-targeting peptide WYRGRLGK (WY-PEG-CeO). The antioxidant free radical activity and the mimetic enzyme activity of PEG-CeONPs and WY-PEG-CeO were detected. The impact of WY-PEG-CeO on chondrocytes oxidative stress, cellular senescence, and extracellular matrix degradation was assessed using in vitro assays. The cartilage targeting and protective effects were explored in animal models.

RESULTS

WY-PEG-CeO demonstrated significant efficacy in inhibiting oxidative stress, cellular senescence, and extracellular matrix degradation in OA chondrocytes. The underlying mechanism involves the inhibition of the PI3K/AKT and MAPK signaling pathways. Animal models further revealed that WY-PEG-CeO exhibited a prolonged residence time and enhanced penetration efficiency in cartilage tissue, leading to the attenuation of pathological changes in OA.

CONCLUSIONS

These findings suggest that WY-PEG-CeO exerts therapeutic effects in OA by inhibiting oxidative stress and suppressing the over-activation of PI3K/AKT and MAPK signaling pathways. This investigation served as a fundamental step towards the advancement of CeONPs-based interventions, providing potential strategies for the treatment of OA.

Docking‑based virtual screening of BRD4 (BD1) inhibitors: assessment of docking methods, scoring functions and in silico molecular properties

To enhance the accuracy of virtual screening for bromodomain-containing protein 4 (BRD4) inhibitors, two docking protocols and seven scoring functions were compared. A total of 73 crystal structures of BRD4 (BD1) complexes were selected for analysis. Firstly, docking was carried out using both the LibDock and CDOCKER methods. The CDOCKER protocol was shown to be more effective based on the root mean square deviation (RMSD) values (in Å) between the docking positions and the co-crystal structures, achieving a docking accuracy rate of 86.3%. Then, among the various scoring functions (LigScore1, LigScore2, PLP1, PLP2, PMF, PMF04 and Ludi3), PMF showed the highest correlation with inhibition constants (r2 = 0.614), while Ludi3 scored lowest (r2 = 0.266). Finally, using ligand descriptors from PubChem, a strong correlation (r2 > 0.5) with inhibition constants for heavy atom count was found. Based on these comprehensive evaluations, the PMF scoring function emerged as the best tool for docking-based virtual screening of potential BRD4 (BD1) inhibitors. And the correlation between molecular properties and BRD4 (BD1) ligands also provided information for future design strategies.

Sensory nerve EP4 facilitates heterotopic ossification by regulating angiogenesis-coupled bone formation

Objective

Heterotopic ossification (HO) refers to the abnormal development of bone in soft tissue rather than within bone itself. Previous research has shown that sensory nerve prostaglandin E2 receptor 4 (EP4) signaling not only governs pain perception but also influences bone formation. However, the relationship between sensory nerve EP4 and the pathogenesis of HO in the Achilles tendon remains unclear. This study aims to investigate this relationship and the underlying mechanisms.

Methods

We generated sensory nerve EP4-specific knockout mice, with the genotype of Avil-CreEP4fl/fl, was propagated. Transcriptome sequencing and bioinformatics analysis techniques were used to identify the potential molecular pathways involving with sensory nerve EP4. Additionally, a neurectomy mouse model was created by transecting the sciatic nerve transection, to examine the effects and mechanisms of peripheral innervation on HO in vivo. Micro-CT, immunofluorescence (IF), Hematoxylin and Eosin (H&E) Staining, Safranin O-Fast Green staining and western blotting were used to analyze changes in cellular and tissue components.

Results

We here observed an increase in sensory nerve EP4 and H-type vessels during the pathogenesis of HO in both human subjects and mice. Proximal neurectomy through sciatic nerve transection or the targeted knockout of EP4 in sensory nerves hindered angiogenesis-dependent bone formation and the development of HO at the traumatic site of the Achilles tendon. Furthermore, we identified the Efnb2 (Ephrin-B2)/Dll4 (Delta-like ligand 4) axis as a potential downstream element influenced by sensory nerve EP4 in the regulation of HO. Notably, administration of an EP4 inhibitor demonstrated the ability to alleviate HO. Based on these findings, sensory nerve EP4 emerges as an innovative and promising approach for managing HO.

Conclusion

Our findings demonstrate that the sensory nerve EP4 promotes ectopic bone formation by modulating angiogenesis-associated osteogenesis during HO.

The translational potential of this article

Our results provide a mechanistic rationale for targeting sensory nerve EP4 as a promising candidate for HO therapy.

GPCRSPACE: A New GPCR Real Expanded Library Based on Large Language Models Architecture and Positive Sample Machine Learning Strategies

The quest for novel therapeutics targeting G protein-coupled receptors (GPCRs), essential in numerous physiological processes, is crucial in drug discovery. Despite the abundance of GPCR-targeting drugs, many receptors lack selective modulators, indicating a significant untapped therapeutic potential. To bridge this gap, we introduce GPCRSPACE, a novel GPCR-focused purchasable real chemical library developed using the G protein-coupled receptors large language models (GPCR LLM) architecture. Different from traditional machine learning models, GPCR LLM uses a positive sample machine learning strategy for training and does not need to construct any negative samples. This not only reduces false negatives but also reduces the time to label negative samples. GPCR LLM accelerates the identification and screening of potential GPCR-interactive compounds by learning the chemical space of GPCR-targeting molecules. GPCRSPACE, built on GPCR LLM, outperforms existing chemical data sets in synthesizability, structural diversity, and GPCR-likeness, making it a valuable tool for GPCR drug discovery.

Neural and immune roles in osteoarthritis pain: Mechanisms and intervention strategies

Pain is the leading symptom for most individuals with osteoarthritis (OA), a complex condition marked by joint discomfort. Recently, the dynamic interplay between the nervous and immune systems has become a focal point for understanding pain regulation. Despite this, there is still a substantial gap in our comprehensive understanding of the neuroimmune interactions and their effects on pain in OA. This review examines the bidirectional influences between immune cells and nerves in OA progression. It explores current approaches that target neuroimmune pathways, including promoting M2 macrophage polarization and specific neuronal receptor targeting, for effective pain reduction.

Translational potential statement

This review provides a comprehensive overview of the mechanisms underlying the interplay between the immune system and nervous system during the progression of OA, as well as their contributions to pain. Additionally, it compiles existing intervention strategies targeting neuroimmunity for the treatment of OA pain. This information offers valuable insights for researchers seeking to address the challenge of OA pain.

Structure-based virtual screening of vast chemical space as a starting point for drug discovery

Structure-based virtual screening aims to find molecules forming favorable interactions with a biological macromolecule using computational models of complexes. The recent surge of commercially available chemical space provides the opportunity to search for ligands of therapeutic targets among billions of compounds. This review offers a compact overview of structure-based virtual screens of vast chemical spaces, highlighting successful applications in early drug discovery for therapeutically important targets such as G protein-coupled receptors and viral enzymes. Emphasis is placed on strategies to explore ultra-large chemical libraries and synergies with emerging machine learning techniques. The current opportunities and future challenges of virtual screening are discussed, indicating that this approach will play an important role in the next-generation drug discovery pipeline.

Generation of multimillion chemical space based on the parallel Groebke-Blackburn-Bienaymé reaction

Parallel Groebke-Blackburn-Bienaymé reaction was evaluated as a source of multimillion chemically accessible chemical space. Two most popular classical protocols involving the use of Sc(OTf)3 and TsOH as the catalysts were tested on a broad substrate scope, and prevalence of the first method was clearly demonstrated. Furthermore, the scope and limitations of the procedure were established. A model 790-member library was obtained with 85% synthesis success rate. These results were used to generate a 271-Mln. readily accessible (REAL) heterocyclic chemical space mostly containing unique chemotypes, which was confirmed by comparative analysis with commercially available compound collections. Meanwhile, this chemical space contained 432 compounds that already showed biological activity according to the ChEMBL database.

Structure-based discovery of CFTR potentiators and inhibitors

The cystic fibrosis transmembrane conductance regulator (CFTR) is a crucial ion channel whose loss of function leads to cystic fibrosis, whereas its hyperactivation leads to secretory diarrhea. Small molecules that improve CFTR folding (correctors) or function (potentiators) are clinically available. However, the only potentiator, ivacaftor, has suboptimal pharmacokinetics and inhibitors have yet to be clinically developed. Here, we combine molecular docking, electrophysiology, cryo-EM, and medicinal chemistry to identify CFTR modulators. We docked ∼155 million molecules into the potentiator site on CFTR, synthesized 53 test ligands, and used structure-based optimization to identify candidate modulators. This approach uncovered mid-nanomolar potentiators, as well as inhibitors, that bind to the same allosteric site. These molecules represent potential leads for the development of more effective drugs for cystic fibrosis and secretory diarrhea, demonstrating the feasibility of large-scale docking for ion channel drug discovery.

The impact of Library Size and Scale of Testing on Virtual Screening

Virtual libraries for ligand discovery have recently increased 10,000-fold, and this is thought to have improved hit rates and potencies from library docking. This idea has not, however, been experimentally tested in direct comparisons of larger-vs-smaller libraries. Meanwhile, though libraries have exploded, the scale of experimental testing has little changed, with often only dozens of high-ranked molecules investigated, making interpretation of hit rates and affinities uncertain. Accordingly, we docked a 1.7 billion molecule virtual library against the model enzyme AmpC β-lactamase, testing 1,521 new molecules and comparing the results to the same screen with a library of 99 million molecules, where only 44 molecules were tested. Encouragingly, the larger screen outperformed the smaller one: hit rates improved by two-fold, more new scaffolds were discovered, and potency improved. Overall, 50-fold more inhibitors were found, supporting the idea that there are many more compounds to be discovered than are being tested. With so many compounds evaluated, we could ask how the results vary with number tested, sampling smaller sets at random from the 1521. Hit rates and affinities were highly variable when we only sampled dozens of molecules, and it was only when we included several hundred molecules that results converged. As docking scores improved, so too did the likelihood of a molecule binding; hit rates improved steadily with docking score, as did affinities. This also appeared true on reanalysis of large-scale results against the σ2 and dopamine D4 receptors. It may be that as the scale of both the virtual libraries and their testing grows, not only are better ligands found but so too does our ability to rank them.

Revisiting prostaglandin E2: A promising therapeutic target for osteoarthritis

Osteoarthritis (OA) is a complex disease characterized by cartilage degeneration and persistent pain. Prostaglandin E2 (PGE2) plays a significant role in OA inflammation and pain. Recent studies have revealed the significant role of PGE2-mediated skeletal interoception in the progression of OA, providing new insights into the pathogenesis and treatment of OA. This aspect also deserves special attention in this review. Additionally, PGE2 is directly involved in pathologic processes including aberrant subchondral bone remodeling, cartilage degeneration, and synovial inflammation. Therefore, celecoxib, a commonly used drug to alleviate inflammatory pain through inhibiting PGE2, serves not only as an analgesic for OA but also as a potential disease-modifying drug. This review provides a comprehensive overview of the discovery history, synthesis and release pathways, and common physiological roles of PGE2. We discuss the roles of PGE2 and celecoxib in OA and pain from skeletal interoception and multiple perspectives. The purpose of this review is to highlight PGE2-mediated skeletal interoception and refresh our understanding of celecoxib in the pathogenesis and treatment of OA.