Novel Siglec-15-Sia axis inhibitor leads to colorectal cancer cell death by targeting miR-6715b-3p and oncogenes.

Siglecs are well known immunotherapeutic targets in cancer. Current checkpoint inhibitors have exhibited limited efficacy, prompting a need for novel therapeutics for targets such as Siglec-15. Presently, small molecule inhibitors targeting Siglec-15 are not explored alongside characterised regulatory mechanisms involving microRNAs in CRC progression. Therefore, a small molecule inhibitor to target Siglec-15 was elucidated in vitro and microRNA mediated inhibitor effects were investigated. Our research findings demonstrated that the SHG-8 molecule exerted significant cytotoxicity on cell viability, migration, and colony formation, with an IC50 value of approximately 20µM. SHG-8 exposure induced late apoptosis in vitro in SW480 CRC cells. Notably, miR-6715b-3p was the most upregulated miRNA in high-throughput sequencing, which was also validated via RT-qPCR. MiR-6715b-3p may regulate PTTG1IP, a potential oncogene which was validated via RT-qPCR and in silico analysis. Additionally, molecular docking studies revealed SHG-8 interactions with the Siglec-15 binding pocket with the binding affinity of -5.4 kcal/mol, highlighting its role as a small molecule inhibitor. Importantly, Siglec-15 and PD-L1 are expressed on mutually exclusive cancer cell populations, suggesting the potential for combination therapies with PD-L1 antagonists.

Zinc-dependent multimerization of mutant calreticulin is required for MPL binding and MPN pathogenesis.

Calreticulin (CALR) is mutated in the majority of JAK2/MPL-unmutated myeloproliferative neoplasms (MPNs). Mutant CALR (CALRdel52) exerts its effect by binding to the thrombopoietin receptor MPL to cause constitutive activation of JAK-STAT signaling. In this study, we performed an extensive mutagenesis screen of the CALR globular N-domain and revealed 2 motifs critical for CALRdel52 oncogenic activity: (1) the glycan-binding lectin motif and (2) the zinc-binding domain. Further analysis demonstrated that the zinc-binding domain was essential for formation of CALRdel52 multimers, which was a co-requisite for MPL binding. CALRdel52 variants incapable of binding zinc were unable to homomultimerize, form CALRdel52-MPL heteromeric complexes, or stimulate JAK-STAT signaling. Finally, treatment with zinc chelation disrupted CALRdel52-MPL complexes in hematopoietic cells in conjunction with preferential eradication of cells expressing CALRdel52 relative to cells expressing other MPN oncogenes. In addition, zinc chelators exhibited a therapeutic effect in preferentially impairing growth of CALRdel52-mutant erythroblasts relative to unmutated erythroblasts in primary cultures of MPN patients. Together, our data implicate zinc as an essential cofactor for CALRdel52 oncogenic activity by enabling CALRdel52 multimerization and interaction with MPL, and suggests that perturbation of intracellular zinc levels may represent a new approach to abrogate the oncogenic activity of CALRdel52 in the treatment of MPNs.

Integrating molecular modelling methods to advance influenza A virus drug discovery.

Since the discovery of the anti-influenza drugs oseltamivir and zanamivir using computer-aided drug design methods, there have been significant applications of molecular modelling methodologies applied to influenza A virus drug discovery, such as molecular dynamics (MD) simulation, molecular docking, and virtual screening (VS). In this review, we provide a brief general introduction to molecular modelling in the context of drug discovery and then focus on the advances and impact of integrating these methods with specific reference to potential influenza A antiviral drug targets.

Prediction of ligands to universally conserved binding sites of the influenza a virus nuclear export protein.

The nuclear export protein (NEP) of the influenza A virus exports viral ribonucleoproteins to the host cell cytoplasm following nuclear transcription. In this work conservation analysis of 3000 protein sequences and molecular modelling of full-length NEP identified ligand binding sites overlapping with high sequence conservation. Two binding hot spots were identified close to the first nuclear export signal and several hot spots overlapped with highly conserved amino acids such as Arg42, Asp43, Lys39, Ile80, Gln101 and Val109. Virtual screening with ~43,000 compounds against a binding site showed affinities of up to -8.95 kcal/mol, while ~1700 approved drugs showed affinities of up to -8.31 kcal/mol. A drug-like compounds predicted was ZINC01564229 that could be used as probe to investigate NEP function or as a new drug lead. The approved drugs Nandrolone phenylpropionate and Estropipate were predicted to bind with high affinity and may be investigated for repurposing as anti-influenza drugs. IMPORTANCE: The influenza A virus causes respiratory illness in humans and farm animals annually across the world. Antigenic shifts and drifts in the surface proteins lead to genome diversity and unpredictable pandemics and epidemics. The high evolution rate of the RNA genome can also limit the effectiveness of antivirals and is the cause of emerging resistance. From a human health perspective, it is important that compounds identified as potential influenza replication inhibitors remain effective long-term. This work presents results which are based on computational predictions that reveal interactions between available compounds and regions of the influenza A nuclear export protein which display high conservation. Due to a low probability of highly conserved regions undergoing genomic changes, these compounds may serve as ideal leads for new antivirals.

Evolutionary conservation of influenza A PB2 sequences reveals potential target sites for small molecule inhibitors.

The influenza A basic polymerase protein 2 (PB2) functions as part of a heterotrimer to replicate the viral RNA genome. To investigate novel PB2 antiviral target sites, this work identified evolutionary conserved regions across the PB2 protein sequence amongst all sub-types and hosts, as well as ligand binding hot spots which overlap with highly conserved areas. Fifteen binding sites were predicted in different PB2 domains; some of which reside in areas of unknown function. Virtual screening of ~50,000 drug-like compounds showed binding affinities of up to -10.3kcal/mol. The highest affinity molecules were found to interact with conserved residues including Gln138, Gly222, Ile529, Asn540 and Thr530. A library containing 1738 FDA approved drugs was screened additionally and revealed Paliperidone as a top hit with a binding affinity of -10kcal/mol. Predicted ligands are ideal leads for new antivirals as they were targeted to evolutionary conserved binding sites.

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated.

Recent discoveries of influenza A drug target sites to combat virus replication.

Sequence variations in the binding sites of influenza A proteins are known to limit the effectiveness of current antiviral drugs. Clinically, this leads to increased rates of virus transmission and pathogenicity. Potential influenza A inhibitors are continually being discovered as a result of high-throughput cell based screening studies, whereas the application of computational tools to aid drug discovery has further increased the number of predicted inhibitors reported. This review brings together the aspects that relate to the identification of influenza A drug target sites and the findings from recent antiviral drug discovery strategies.