Development of a Targeted SN-38-Conjugate for the Treatment of Glioblastoma.

Glioblastoma (GBM) is the most aggressive and fatal brain tumor, with approximately 10,000 people diagnosed every year in the United States alone. The typical survival period for individuals with glioblastoma ranges from 12 to 18 months, with significant recurrence rates. Common therapeutic modalities for brain tumors are chemotherapy and radiotherapy. The main challenges with chemotherapy for the treatment of glioblastoma are high toxicity, poor selectivity, and limited accumulation of therapeutic anticancer agents in brain tumors as a result of the presence of the blood-brain barrier. To overcome these challenges, researchers have explored strategies involving the combination of targeting peptides possessing a specific affinity for overexpressed cell-surface receptors with conventional chemotherapy agents via the prodrug approach. This approach results in the creation of peptide drug conjugates (PDCs), which facilitate traversal across the blood-brain barrier (BBB), enable preferential accumulation of chemotherapy within the neoplastic microenvironment, and selectively target cancerous cells. This approach increases accumulation in tumors, thereby improving therapeutic efficiency and minimizing toxicity. Leveraging the affinity of the HAIYPRH (T7) peptide for the transferrin receptor (TfR) overexpressed on the blood-brain barrier and glioma cells, a novel T7-SN-38 peptide drug conjugate was developed. The T7-SN-38 peptide drug conjugate demonstrates about a 2-fold reduction in glide score (binding affinity) compared to T7 while maintaining a comparable orientation within the TfR target site using Schrödinger-2022-3 Maestro 13.3 for ligand preparation and Glide SP-Peptide docking. Additionally, SN-38 extends into a solvent-accessible region, enhancing its susceptibility to protease hydrolysis at the cathepsin B (Cat B) cleavable site. The SN-38-ether-peptide drug conjugate displayed high stability in buffer at physiological pH, and cleavage of the conjugate to release free cytotoxic SN-38 was observed in the presence of exogenous cathepsin B. The synthesized peptide drug conjugate exhibited potent cytotoxic activities in cellular models of glioblastoma in vitro. In addition, blocking transferrin receptors using the free T7 peptide resulted in a notable inhibition of cytotoxicity of the conjugate, which was reversed when exogenous cathepsin B was added to cells. This work demonstrates the potential for targeted drug delivery to the brain in the treatment of glioblastoma using the transferrin receptor-targeted T7-SN-38 conjugate.

Axially Chiral Cannabinoids: Design, Synthesis, and Cannabinoid Receptor Affinity.

The resorcinol-terpene phytocannabinoid template is a privileged scaffold for the development of diverse therapeutics targeting the endocannabinoid system. Axially chiral cannabinols (axCBNs) are unnatural cannabinols (CBNs) that bear an additional C10 substituent, which twists the cannabinol biaryl framework out of planarity creating an axis of chirality. This unique structural modification is hypothesized to enhance both the physical and biological properties of cannabinoid ligands, thus ushering in the next generation of endocannabinoid system chemical probes and cannabinoid-inspired leads for drug development. In this full report, we describe the philosophy guiding the design of axCBNs as well as several synthetic strategies for their construction. We also introduce a second class of axially chiral cannabinoids inspired by cannabidiol (CBD), termed axially chiral cannabidiols (axCBDs). Finally, we provide an analysis of axially chiral cannabinoid (axCannabinoid) atropisomerism, which spans two classes (class 1 and 3 atropisomers), and provide first evidence that axCannabinoids retain─and in some cases, strengthen─affinity and functional activity at cannabinoid receptors. Together, these findings present a promising new direction for the design of novel cannabinoid ligands for drug discovery and exploration of the complex endocannabinoid system.

Discovery of two novel (4-hydroxyphenyl) substituted polycyclic carbocycles as potent and selective estrogen receptor beta agonists.

Two (4-hydroxyphenyl) substituted polycyclic carbocycles were prepared and assayed for estrogen receptor activity. 4-(4-Hydroxyphenyl)tricyclo[3.3.1.13,7]decane-1-methanol (5a/b) and 7-(4-hydroxyphenyl)spiro[3.5]nonan-2-ol ((±)-11) were found to be potent ERß agonists (1.9 ± 0.4 nM and 6.2 ± 1.4 nM respectively) in a cell-based functional assay. Furthermore, both 5a/b and 11 were highly selective for ERß over ERα (377 and 1,100-fold selective respectively). While neither compound inhibited CYP2D6 or CYP3A4 at concentrations up to 62.5 µM, 5a/b did have weak binding to CYP2C9 with an IC50 of 10 ± 0.5 µM. Computational assessment of 5a/b and 11 predicted the most probable site of metabolism would be ortho to the phenolic hydroxyl group.

Utilizing in silico and in vitro methods to identify possible binding sites of a novel ligand against Pseudomonas aeruginosa phospholipase toxin ExoU.

Multi-drug resistant infections caused by the opportunistic pathogen, Pseudomonas aeruginosa (P. aeruginosa), are a continuing problem that contribute to morbidity and mortality in immunocompromised hosts such as cystic fibrosis (CF), wound and burn patients. The bacterial toxin ExoU is one of four potent toxins that P. aeruginosa secretes into the epithelial cells of hosts. In this study, NMR Saturation Transfer Difference (STD) and in silico Schrödinger Computational Modeling were used to identify a possible binding site of a novel ligand methoctramine targeting ExoU. Future project goals will be to design a structure activity relationship (SAR) study of methoctramine and ExoU and lead to a new drug solving ExoU toxicity P. aeruginosa exerts in the clinical environment.

Potential of Flavonoid-Inspired Phytomedicines against COVID-19.

Flavonoids are widely used as phytomedicines. Here, we report on flavonoid phytomedicines with potential for development into prophylactics or therapeutics against coronavirus disease 2019 (COVID-19). These flavonoid-based phytomedicines include: caflanone, Equivir, hesperetin, myricetin, and Linebacker. Our in silico studies show that these flavonoid-based molecules can bind with high affinity to the spike protein, helicase, and protease sites on the ACE2 receptor used by the severe acute respiratory syndrome coronavirus 2 to infect cells and cause COVID-19. Meanwhile, in vitro studies show potential of caflanone to inhibit virus entry factors including, ABL-2, cathepsin L, cytokines (IL-1ß, IL-6, IL-8, Mip-1α, TNF-α), and PI4Kiiiß as well as AXL-2, which facilitates mother-to-fetus transmission of coronavirus. The potential for the use of smart drug delivery technologies like nanoparticle drones loaded with these phytomedicines to overcome bioavailability limitations and improve therapeutic efficacy are discussed.

Interactions of the effector ExoU from Pseudomonas aeruginosa with short-chain phosphatidylinositides provide insights into ExoU targeting to host membranes.

Pseudomonas aeruginosa is an opportunistic multidrug-resistant pathogen and a common cause of infection in cystic fibrosis and ventilator-associated pneumonia and in burn and wound patients. P. aeruginosa uses its type III secretion system to secrete various effector proteins directly into mammalian host cells. ExoU is a potent type III secretion system effector that, after secretion, localizes to the inner cytoplasmic membrane of eukaryotic cells, where it exerts its phospholipase A2 activity upon interacting with ubiquitin and/or ubiquitinated proteins. In this study, we used site-directed spin-labeling electron paramagnetic resonance spectroscopy to examine the interaction of ExoU with soluble analogs of phosphatidylinositol (4,5)-bisphosphate (PI(4,5)P2). We found that dioctanoyl PI(4,5)P2 binds to and induces conformational changes in a C-terminal four-helix bundle (4HB) domain of ExoU implicated previously in membrane binding. Other soluble phosphoinositides also interacted with the 4HB but less effectively. Molecular modeling and ligand docking studies indicated the potential for numerous hydrogen bond interactions within and between interhelical loops of the 4HB and suggested several potential interaction sites for PI(4,5)P2 Site-directed mutagenesis experiments confirmed that the side chains of Gln-623 and Arg-661 play important roles in mediating PI(4,5)P2-induced conformational changes in ExoU. These results support a mechanism in which direct interactions with phosphatidylinositol-containing lipids play an essential role in targeting ExoU to host membrane bilayers. Molecules or peptides that block this interaction may prove useful in preventing the cytotoxic effects of ExoU to mitigate the virulence of P. aeruginosa strains that express this potent phospholipase toxin.

Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

Chemokine receptors (CRs) have long been druggable targets for the treatment of inflammatory diseases and HIV-1 infection. As a powerful technique, virtual screening (VS) has been widely applied to identifying small molecule leads for modern drug targets including CRs. For rational selection of a wide variety of VS approaches, ligand enrichment assessment based on a benchmarking data set has become an indispensable practice. However, the lack of versatile benchmarking sets for the whole CRs family that are able to unbiasedly evaluate every single approach including both structure- and ligand-based VS somewhat hinders modern drug discovery efforts. To address this issue, we constructed Maximal Unbiased Benchmarking Data sets for human Chemokine Receptors (MUBD-hCRs) using our recently developed tools of MUBD-DecoyMaker. The MUBD-hCRs encompasses 13 subtypes out of 20 chemokine receptors, composed of 404 ligands and 15756 decoys so far and is readily expandable in the future. It had been thoroughly validated that MUBD-hCRs ligands are chemically diverse while its decoys are maximal unbiased in terms of "artificial enrichment", "analogue bias". In addition, we studied the performance of MUBD-hCRs, in particular CXCR4 and CCR5 data sets, in ligand enrichment assessments of both structure- and ligand-based VS approaches in comparison with other benchmarking data sets available in the public domain and demonstrated that MUBD-hCRs is very capable of designating the optimal VS approach. MUBD-hCRs is a unique and maximal unbiased benchmarking set that covers major CRs subtypes so far.

Cheminfomatic-based Drug Discovery of Human Tyrosine Kinase Inhibitors.

Receptor Tyrosine Kinases (RTKs) are essential components for regulating cell-cell signaling and communication events in cell growth, proliferation, differentiation, survival and metabolism. Deregulation of RTKs and their associated signaling pathways can lead to a wide variety of human diseases such as immunodeficiency, diabetes, arterosclerosis, psoriasis and cancer. Thus RTKs have become one of the most important drug targets families in recent decade. Pharmaceutical companies have dedicated their research efforts towards the discovery of small-molecule inhibitors of RTKs, many of which had been approved by the U.S. Food and Drug Administration (US FDA) or are currently in clinical trials. The great successes in the development of small-molecule inhibitors of RTKs are largely attributed to the use of modern cheminformatic approaches to identifying lead scaffolds. Those include the quantitative structure-activity relationship (QSAR) modeling, as well as the structure-, and ligand-based pharmacophore modeling techniques in this case. Herein we inspected the literature thoroughly in an effort to conduct a comparative analysis of major findings regarding the essential structure-activity relationships (SARs)/pharmacophore features of known active RTK inhibitors, most of which were collected from cheminformatic modeling approaches.

Discovery of Natural Product-Derived 5-HT1A Receptor Binders by Cheminfomatics Modeling of Known Binders, High Throughput Screening and Experimental Validation.

The human 5-hydroxytryptamine receptor subtype 1A (5-HT1A) is highly expressed in the raphe nuclei region and limbic structures; for that reason 5-HT1A has served as a promising target for treating human mood disorders and neurodegenerative diseases. We have developed binary quantitative structure-activity relationship (QSAR) models for 5- HT1A binding using data retrieved from the WOMBAT database and the k-Nearest Neighbor (kNN) machine learning method. A rigorous QSAR modeling and screening workflow had been followed, with extensive internal and external validation processes. The models' classification accuracies to discriminate 5-HT1A binders from the non-binders are as high as 96% for the external validation. These models were employed further to mine two major natural products screening libraries, i.e. TimTec Natural Product Library (NPL) and Natural Derivatives Library (NDL). In the end five screening hits were tested by radioligand binding assays with a success rate of 40%, and two Library compounds were confirmed to be binders at the µM concentration against the human 5-HT1A receptor. The combined application of rigorous QSAR modeling and model-based virtual screening presents a powerful means for profiling natural products compounds with important biomedical activities.

Discovery of a Novel HDAC2 Inhibitor by a Scaffold-Merging Hybrid Query.

Histone deacetylases (HDACs) are part of a vast family of enzymes with crucial roles in numerous biological processes, largely through their repressive influence on transcription, with serious implications in a variety of human diseases. Among different isoforms, human HDAC2 in particular draws attention as a promising target for the treatment of cancer and memory deficits associated with neurodegenerative diseases. Now the challenge is to obtain a compound that is structurally novel and truly selective to HDAC2 because most current HDAC2 inhibitors do not show isoforms selectivity and suffer from metabolic instability. In order to identify novel, and isoform-selective inhibitors for human HDAC2, we designed a shape-based hybrid query from multiple scaffolds of known chemical classes and validated it to be a more effective approach to discover diverse scaffolds than single-molecule query. The hybrid query-based screening rendered a hit compound with the N-benzylaniline scaffold which showed moderate inhibitory activity against HDAC2, and its chemical structure is diverse compared to known HDAC2 inhibitors. Notably, this compound shows the selectivity against the HDAC6, a Class II enzyme, thus has the potential to further develop into the class- and isoform-selective inhibitors. Our present study supplies an useful approach to identifying novel HDAC2 inhibitors, and can be extended to the inquires of other important biomedical targets as well.

Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of "artificial enrichment" and "analogue bias". We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the "2D bias" and "LBVS favorable" effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/ .

Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. "analogue bias", "artificial enrichment" and "false negative". In addition, we introduce our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylases (HDACs) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The leave-one-out cross-validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased as measured by property matching, ROC curves and AUCs.

Predictive in silico studies of human 5-hydroxytryptamine receptor subtype 2B (5-HT2B) and valvular heart disease.

Serotonin (5-hydroxytryptamine, 5-HT) receptors are neuromodulator neurotransmitter receptors which when activated trigger a signal transduction cascade within cells resulting in cell-cell communication. 5-hydroxytryptamine receptor 2B (5-HT2B) is a subtype of the seven members of 5-hydroxytrytamine receptors family which is the largest member of the super family of 7-transmembrane G-protein coupled receptors (GPCRs). Not only do 5-HT receptors play physiological roles in the cardiovascular system, gastrointestinal and endocrine function as well as the central nervous system, but they also play a role in behavioral functions. In particular 5-HT2B receptor is widely spread with regards to its distribution throughout bodily tissues and is expressed at high levels in the lungs, peripheral tissues, liver, kidneys and prostate, just to name a few. Hence 5-HT2B participates in multiple biological functions including CNS regulation, regulation of gastrointestinal motality, cardiovascular regulation and 5-HT transport system regulation. While 5-HT2B is a viable drug target and has therapeutic indications for treating obesity, psychosis, Parkinson's disease etc. there is a growing concern regarding adverse drug reactions, specifically valvulopathy associated with 5-HT2B agonists. Due to the sequence homology experienced by 5-HT2 subtypes there is also a concern regarding the off-target effects of 5-HT2A and 5-HT2C agonists. The concepts of sensitivity and subtype selectivity are of paramount importance and now can be tackled with the aid of in silico studies, especially cheminformatics, to develop models to predict valvulopathy associated toxicity of drug candidates prior to clinical trials. This review has highlighted three in silico approaches thus far that have been successful in either predicting 5-HT2B toxicity of molecules or identifying important interactions between 5-HT2B and drug molecules that bring about valvulopathy related toxicities.