Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation

Comparison of chemical clustering methods using graph- and fingerprint-based similarity measures

This paper compares several published methods for clustering chemical structures, using both graph- and fingerprint-based similarity measures. The clusterings from each method were compared to determine the degree of cluster overlap. Each method was also evaluated on how well it grouped structures into clusters possessing a non-trivial substructural commonality. The methods which employ adjustable parameters were tested to determine the stability of each parameter for datasets of varying size and composition. Our experiments suggest that both graph- and fingerprint-based similarity measures can be used effectively for generating chemical clusterings; it is also suggested that the CAST and Yin–Chen methods, suggested recently for the clustering of gene expression patterns, may also prove effective for the clustering of 2D chemical structures

Development and characterization of an immunotherapeutic platform based on oncolytic Herpes simplex virus and aCTLA-4 antibodies

In the last decade, immunotherapy has emerged as a promising approach to treat cancer. Although encouraging results have been obtained with monotherapy treatments, a large percentage of patients still do not respond, opening therapeutic options to combination of immunotherapeutics (i.e., oncolytic viruses and mAbs targeting immune checkpoints). Unfortunately, despite combination therapies emerged as a valid option thanks to synergistic efficacy, the occurrence of systemic immune-related adverse events (irAEs) often leads to treatment interruption. The purpose of my thesis was to implement a platform of immunotherapeutics based on oncolytic HSV (oHSV) encoding vectored immunomodulators for local cancer treatment. Interleukin-12 and αCTLA-4 antibody were identified as promising payloads, to be encoded within oHSV genome. The efficacy of these oHSVs was evaluated in in vivo mouse model showing significant improvement in antitumor efficacy compared to oncolytics devoid of the selected immunotherapeutic cargoes. As viral vectored αCTLA-4 antibody resulted in significant improvement of antitumor efficacy, to facilitate preclinical to clinical translation, I isolated human/murine cross-reactive αCTLA-4 antibodies through a high throughput screening of a phage display library of scFvs by Next Generation Sequencing. Additional work will explore the potential ability of the THV_CTLA4 to reduce irAEs occurrence thanks to the antibody confined expression within the TME

Strain prioritization and genome mining for enediyne natural products

The enediyne family of natural products has had a profound impact on modern chemistry, biology, and medicine, and yet only 11 enediynes have been structurally characterized to date. Here we report a genome survey of 3,400 actinomycetes, identifying 81 strains that harbor genes encoding the enediyne polyketide synthase cassettes that could be grouped into 28 distinct clades based on phylogenetic analysis. Genome sequencing of 31 representative strains confirmed that each clade harbors a distinct enediyne biosynthetic gene cluster. A genome neighborhood network allows prediction of new structural features and biosynthetic insights that could be exploited for enediyne discovery. We confirmed one clade as new C-1027 producers, with a significantly higher C-1027 titer than the original producer, and discovered a new family of enediyne natural products, the tiancimycins (TNMs), that exhibit potent cytotoxicity against a broad spectrum of cancer cell lines. Our results demonstrate the feasibility of rapid discovery of new enediynes from a large strain collection. IMPORTANCE Recent advances in microbial genomics clearly revealed that the biosynthetic potential of soil actinomycetes to produce enediynes is underappreciated. A great challenge is to develop innovative methods to discover new enediynes and produce them in sufficient quantities for chemical, biological, and clinical investigations. This work demonstrated the feasibility of rapid discovery of new enediynes from a large strain collection. The new C-1027 producers, with a significantly higher C-1027 titer than the original producer, will impact the practical supply of this important drug lead. The TNMs, with their extremely potent cytotoxicity against various cancer cells and their rapid and complete cancer cell killing characteristics, in comparison with the payloads used in FDA-approved antibody-drug conjugates (ADCs), are poised to be exploited as payload candidates for the next generation of anticancer ADCs. Follow-up studies on the other identified hits promise the discovery of new enediynes, radically expanding the chemical space for the enediyne family

Development of new, potent NAPRT inhibitors by CADD

Nicotinate phosphoribosyltransferase (NAPRT) is the rate-limiting enzyme of the Preiss-Handler NAD biosynthetic pathway. NAPRT is widely distributed across healthy mammalian tissues where the enzyme supports the production of NAD, an essential pyridine nucleotide that acts as redox cofactor in multiple metabolic pathways key for bioenergetics and as substrate for several critical cellular processes. Recently, NAPRT has emerged as a novel therapeutic target against cancer owing to its recognition as a biomarker for the success of NAMPT inhibitors in cancer treatment. Indeed, the lack of objective tumor response to NAMPT inhibitors in clinical trials might reflect NAPRT-mediated resistance to these agents. Interestingly, NAPRT displays marked tumor specificity in terms of expression and its regulation mechanisms. Some tumors show NAPRT gene promoter hypermethylation and therefore do not express the enzyme. An insightful study found that NAPRT is frequently upregulated in ovarian, prostate, pancreatic, and breast cancers. In addition, high protein levels of NAPRT were shown to confer resistance to NAMPT inhibitors in several tumor types whereas the simultaneous inhibition of NAMPT and NAPRT resulted in marked anti-tumor effects both in vitro and in vivo. While numerous potent NAMPT inhibitors are available, the few reported NAPRT inhibitors (NAPRTi) have a low affinity for the enzyme. In this work, computer-aided drug design (CADD) efforts to identify putative NAPRT inhibitors were coupled to state-of-the-art in vitro testing of the compounds to study their capacity to inhibit NAPRT and to sensitize the NAPRT-proficient OVCAR-5 cell line to the NAMPTi FK866. Starting from the crystal structure of NAPRT several structure-based drug design (SBDD) experiments based on molecular docking and molecular dynamics simulations were carried out. In the process, large compound libraries of diverse and drug-like small molecules were virtually screened against the NAPRT structure. The selected in silico hits were subsequently tested through cell-based assays in the NAPRT-proficient OVCAR-5 ovarian carcinoma cell line and on the recombinant NAPRT enzyme. We found different chemotypes that efficiently inhibit the enzyme in the micromolar range concentration and for which direct engagement with the target was verified by differential scanning fluorimetry. Of note, the therapeutic potential of these compounds was evidenced by a synergistic interaction between the NAMPT inhibitor FK866 and the new NAPRTi in terms of decreasing OVCAR-5 intracellular NAD+ levels and cell viability. For example, compound IM 29 can potentiate the effect of FK866 of more than two-fold in reducing intracellular NAD+ levels. These results pave the way for the development of a new generation of potent NAPRT inhibitors with anticancer activity

Exploring DNA Topoisomerase I Ligand Space in Search of Novel Anticancer Agents

DNA topoisomerase I (Top1) is over-expressed in tumour cells and is an important target in cancer chemotherapy. It relaxes DNA torsional strain generated during DNA processing by introducing transient single-strand breaks and allowing the broken strand to rotate around the intermediate Top1 – DNA covalent complex. This complex can be trapped by a group of anticancer agents interacting with the DNA bases and the enzyme at the cleavage site, preventing further topoisomerase activity. Here we have identified novel Top1 inhibitors as potential anticancer agents by using a combination of structure- and ligand-based molecular modelling methods. Pharmacophore models have been developed based on the molecular characteristics of derivatives of the alkaloid camptothecin (CPT), which represent potent antitumour agents and the main group of Top1 inhibitors. The models generated were used for in silico screening of the National Cancer Institute (NCI, USA) compound database, leading to the identification of a set of structurally diverse molecules. The strategy is validated by the observation that amongst these molecules are several known Top1 inhibitors and agents cytotoxic against human tumour cell lines. The potential of the untested hits to inhibit Top1 activity was further evaluated by docking into the binding site of a Top1 – DNA complex, resulting in a selection of 10 compounds for biological testing. Limited by the compound availability, 7 compounds have been tested in vitro for their Top1 inhibitory activity, 5 of which display mild to moderate Top1 inhibition. A further compound, found by similarity search to the active compounds, also shows mild activity. Although the tested compounds display only low in vitro antitumour activity, our approach has been successful in the identification of structurally novel Top1 inhibitors worthy of further investigation as potential anticancer agents

Benzimidazoles: From Antiproliferative to Multitargeted Anticancer Agents

Benzimidazole derivatives are known to act against a range of biological targets and thus gained clinical applications in a wide spectrum of diseases. Few examples of multitargeted benzimidazole derivatives that were reported during the last decade will be described in this chapter. Multitargeting agents for serving the polypharmacology approach to combat shortcomings of the main one-drug-one target main dogma will be briefly explored. In that context, the multitargeting benzimidazole derivatives gain a special attention. This includes discovery (hit-to-lead), structure-activity relationship (SAR), and binding mode of at least one lead (or hit) in each group. Special attention will be given to two structures dovitinib and AT9283 that are reported to exhibit potent in vitro and in vivo activities against a group of kinases and non-kinase target (as shown recently for dovitinib)

A Multi-Objective Approach for Anti-Osteosarcoma Cancer Agents Discovery through Drug Repurposing

[Abstract] Osteosarcoma is the most common type of primary malignant bone tumor. Although nowadays 5-year survival rates can reach up to 60–70%, acute complications and late effects of osteosarcoma therapy are two of the limiting factors in treatments. We developed a multi-objective algorithm for the repurposing of new anti-osteosarcoma drugs, based on the modeling of molecules with described activity for HOS, MG63, SAOS2, and U2OS cell lines in the ChEMBL database. Several predictive models were obtained for each cell line and those with accuracy greater than 0.8 were integrated into a desirability function for the final multi-objective model. An exhaustive exploration of model combinations was carried out to obtain the best multi-objective model in virtual screening. For the top 1% of the screened list, the final model showed a BEDROC = 0.562, EF = 27.6, and AUC = 0.653. The repositioning was performed on 2218 molecules described in DrugBank. Within the top-ranked drugs, we found: temsirolimus, paclitaxel, sirolimus, everolimus, and cabazitaxel, which are antineoplastic drugs described in clinical trials for cancer in general. Interestingly, we found several broad-spectrum antibiotics and antiretroviral agents. This powerful model predicts several drugs that should be studied in depth to find new chemotherapy regimens and to propose new strategies for osteosarcoma treatment.Universidad de Las Américas (Quito, Ecuador); ENF.RCA.18.01Gobierno Vasco; IT1045-16)-2016–202