Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.     

Identification of Novel Fragments Binding to the PDZ1-2 Domain of PSD-95

Inhibition of PSD-95 has emerged as a promising strategy for the treatment of ischemic stroke, as shown with peptide-based compounds that target the PDZ domains of PSD-95. In contrast, developing potent and drug-like small molecules against the PSD-95 PDZ domains has so far been unsuccessful. Here, we explore the druggability of the PSD-95 PDZ1-2 domain and use fragment screening to investigate if this protein is prone to binding small molecules. We screened 2500 fragments by fluorescence polarization (FP) and validated the hits by surface plasmon resonance (SPR), including an inhibition counter-test, and found four promising fragments. Three ligand efficient fragments were shown by ¹H,¹⁵N HSQC NMR to bind in the small hydrophobic P⁰ pockets of PDZ1-2, and one of them underwent structure-activity relationship (SAR) studies. Overall, we demonstrate that fragment screening can successfully be applied to PDZ1-2 of PSD-95 and disclose novel fragments that can serve as starting points for optimization towards small-molecule PDZ domain inhibitors.     

Scanning Protein Surfaces with DNA-Encoded Libraries

Understanding the ligandability of a target protein, defined as the capability of a protein to bind drug-like compounds on any site, can give important stimuli to drug-development projects. For instance, inhibition of protein–protein interactions usually depends on the identification of protein surface binders. DNA-encoded chemical libraries (DELs) allow scanning of protein surfaces with large chemical space. Encoded library selection screens uncovered several protein–protein interaction inhibitors and compounds binding to the surface of G protein-coupled receptors (GPCRs) and kinases. The protein surface-binding chemotypes from DELs are predominantly chemically modified and cyclized peptides, and functional small-molecule peptidomimetics. Peptoid libraries and structural peptidomimetics have been less studied in the DEL field, hinting at hitherto less populated chemical space and suggesting alternative library designs. Roughly a third of bioactive molecules evolved from smaller, target-focused libraries. They showcase the potential of encoded libraries to identify more potent molecules from weak, for example, fragment-like, starting points.     

Native Mass Spectrometry for the Study of PROTAC GNE-987-Containing Ternary Complexes

PRO teolysis TA rgeting C himeras (PROTACs) promote the degradation, rather than inhibition, of a drug target as a mechanism for therapeutic treatment. Bifunctional PROTAC molecules allow simultaneous binding of both the target protein and an E3-Ubiquitin ligase, bringing the two proteins into close spatial proximity to allow ubiquitinylation and degradation of the target protein via the cell's endogenous protein degradation pathway. We utilized native mass spectrometry (MS) to study the ternary complexes promoted by the previously reported PROTAC GNE-987 between Brd4 bromodomains 1 and 2, and Von Hippel Lindeau E3-Ubiquitin Ligase. Native MS at high resolution allowed us to measure ternary complex formation as a function of PROTAC concentration to provide a measure of complex affinity and stability, whilst simultaneously measuring other intermediate protein species. Native MS provides a high-throughput, low sample consumption, direct screening method to measure ternary complexes for PROTAC development.     

Inhibition of RANKL-Induced Osteoclastogenesis by Novel Mutant RANKL

Background: Recently, it was reported that leucine-rich repeat-containing G-protein-coupled receptor 4 (LGR4, also called GPR48) is another receptor for RANKL and was shown to compete with RANK to bind RANKL and suppress canonical RANK signaling during osteoclast differentiation. The critical role of the protein triad RANK–RANKL in osteoclastogenesis has made their binding an important target for the development of drugs against osteoporosis. In this study, point-mutations were introduced in the RANKL protein based on the crystal structure of the RANKL complex and its counterpart receptor RANK, and we investigated whether LGR4 signaling in the absence of the RANK signal could lead to the inhibition of osteoclastogenesis.; Methods: The effects of point-mutated RANKL (mRANKL-MT) on osteoclastogenesis were assessed by tartrate-resistant acid phosphatase (TRAP), resorption pit formation, quantitative real-time polymerase chain reaction (qPCR), western blot, NFATc1 nuclear translocation, micro-CT and histomorphological assay in wild type RANKL (mRANKL-WT)-induced in vitro and in vivo experimental mice model. Results: As a proof of concept, treatment with the mutant RANKL led to the stimulation of GSK-3β phosphorylation, as well as the inhibition of NFATc1 translocation, mRNA expression of TRAP and OSCAR, TRAP activity, and bone resorption, in RANKL-induced mouse models; and Conclusions: The results of our study demonstrate that the mutant RANKL can be used as a therapeutic agent for osteoporosis by inhibiting RANKL-induced osteoclastogenesis via comparative inhibition of RANKL. Moreover, the mutant RANKL was found to lack the toxic side effects of most osteoporosis treatments.     

Patient-Derived Organoids as a Model for Cancer Drug Discovery

In the search for the ideal model of tumours, the use of three-dimensional in vitro models is advancing rapidly. These are intended to mimic the in vivo properties of the tumours which affect cancer development, progression and drug sensitivity, and take into account cell–cell interactions, adhesion and invasiveness. Importantly, it is hoped that successful recapitulation of the structure and function of the tissue will predict patient response, permitting the development of personalized therapy in a timely manner applicable to the clinic. Furthermore, the use of co-culture systems will allow the role of the tumour microenvironment and tissue–tissue interactions to be taken into account and should lead to more accurate predictions of tumour development and responses to drugs. In this review, the relative merits and limitations of patient-derived organoids will be discussed compared to other in vitro and ex vivo cancer models. We will focus on their use as models for drug testing and personalized therapy and how these may be improved. Developments in technology will also be considered, including the use of microfluidics, 3D bioprinting, cryopreservation and circulating tumour cell-derived organoids. These have the potential to enhance the consistency, accessibility and availability of these models.     

Nacre-Inspired,Liquid Metal-Based Ultrasensitive Electronic Skin by Spatially Regulated Cracking Strategy

The realization of liquid metal-based wearable systems will be a milestone toward high-performance, integrated electronic skin. However, despite the revolutionary progress achieved in many other components of electronic skin, liquid metal-based flexible sensors still suffer from poor sensitivity due to the insufficient resistance change of liquid metal to deformation. Herein, a nacre-inspired architecture composed of a biphasic pattern (liquid metal with Cr/Cu underlayer) as “bricks” and strain-sensitive Ag film as “mortar” is developed, which breaks the long-standing sensitivity bottleneck of liquid metal-based electronic skin. With 2 orders of magnitude of sensitivity amplification while maintaining wide (>85%) working range, for the first time, liquid metal-based strain sensors rival the state-of-art counterparts. This liquid metal composite features spatially regulated cracking behavior. On the one hand, hard Cr cells locally modulate the strain distribution, which avoids premature cut-through cracks and prolongs the defect propagation in the adjacent Ag film. On the other hand, the separated liquid metal cells prevent unfavorable continuous liquid-metal paths and create crack-free regions during strain. Demonstrated in diverse scenarios, the proposed design concept may spark more applications of ultrasensitive liquid metal-based electronic skins, and reveals a pathway for sensor development via crack engineering.     

Single image dehazing using a new color channel

Images with hazy scene suffer from low-contrast, which reduces the visible quality of the scene, thus making object detection a more challenging task. Low-contrast can result from foggy weather conditions during image acquisition. Dehazing is a process of removal of haze from the photography of a hazy scene. Single-image dehazing based on dark channel priors are well-known techniques in this field. However, the performance of such techniques is limited to priors or constraints. Moreover, this type of method fails when images have sky-region. So, a method is proposed, which can restore the visibility of hazy images. First, a hazy image is divided into blocks of size 32 × 32, then the score of each block is calculated to select a block having the highest score. Atmospheric light is calculated from the selected block. A new color channel is considered to remove atmospheric scattering, obtained channel value and atmospheric light are then used to calculate the transmission map in the second step. Third, radiance is computed using a transmission map and atmospheric light. The illumination scaling factor is adopted to enhance the quality of a dehazed image in the final step. Experiments are performed on six datasets namely, I-HAZE, O-HAZE, BSDS500, FRIDA, RESIDE dataset and natural images from Google. The proposed method is compared against 11 state-of-the-art methods. The performance is analyzed using fourteen quantitative evaluation metrics. All the results demonstrate that the proposed method outperforms 11 state-of-the-art methods in most of the cases.