A Remote Arene-Binding Site on Prostate Specific Membrane Antigen Revealed by Antibody-Recruiting Small Molecules

Prostate specific membrane antigen (PSMA) is a membrane-bound glutamate carboxypeptidase overexpressed in many forms of prostate cancer. Our laboratory has recently disclosed a class of small molecules, called ARM-Ps (antibody-recruiting molecule targeting prostate cancer) that are capable of enhancing antibody-mediated immune recognition of prostate cancer cells. Interestingly, during the course of these studies, we found ARM-Ps to exhibit extraordinarily high potencies toward PSMA, compared to previously reported inhibitors. Here, we report in-depth biochemical, crystallographic, and computational investigations which elucidate the origin of the observed affinity enhancement. These studies reveal a previously unreported arene-binding site on PSMA, which we believe participates in an aromatic stacking interaction with ARMs. Although this site is composed of only a few amino acid residues, it drastically enhances small molecule binding affinity. These results provide critical insights into the design of PSMA-targeted small molecules for prostate cancer diagnosis and treatment; more broadly, the presence of similar arene-binding sites throughout the proteome could prove widely enabling in the optimization of small-molecule–protein interactions

Comparative Structure Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor

HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms which makes the conventional homology modeling less reliable. AlphaFold is a neural network machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However the fact that AlphaFold models are predicted in absence of small molecules and ions/cofactors complicate their utilization for drug design. Previously we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 µM for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 µM concentration. In addition we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery

Continuous Fluorescent Sirtuin Activity Assay Based on Fatty Acylated Lysines

Lysine deacetylases, like histone deacetylases (HDACs) and sirtuins (SIRTs), are involved in many regulatory processes such as control of metabolic pathways, DNA repair, and stress responses. Besides robust deacetylase activity, sirtuin isoforms SIRT2 and SIRT3 also show demyristoylase activity. Interestingly, most of the inhibitors described so far for SIRT2 are not active if myristoylated substrates are used. Activity assays with myristoylated substrates are either complex because of coupling to enzymatic reactions or time-consuming because of discontinuous assay formats. Here we describe sirtuin substrates enabling direct recording of fluorescence changes in a continuous format. Fluorescence of the fatty acylated substrate is different when compared to the deacylated peptide product. Additionally, the dynamic range of the assay could be improved by the addition of bovine serum albumin, which binds the fatty acylated substrate and quenches its fluorescence. The main advantage of the developed activity assay is the native myristoyl residue at the lysine side chain avoiding artifacts resulting from the modified fatty acyl residues used so far for direct fluorescence-based assays. Due to the extraordinary kinetic constants of the new substrates (KM values in the low nM range, specificity constants between 175,000 and 697,000 M−1s−1) it was possible to reliably determine the IC50 and Ki values for different inhibitors in the presence of only 50 pM of SIRT2 using different microtiter plate formats

Targeting Prostate Cancer Using Bispecific T‑Cell Engagers against Prostate-Specific Membrane Antigen

Prostate cancer (PCa) tops the list of cancer-related deaths in men worldwide. Prostate-specific membrane antigen (PSMA) is currently the most prominent PCa biomarker, as its expression levels are robustly enhanced in advanced stages of PCa. As such, PSMA targeting is highly efficient in PCa imaging as well as therapy. For the latter, PSMA-positive tumors can be targeted directly by using small molecules or macromolecules with cytotoxic payloads or indirectly by engaging the immune system of the host. Here we describe the engineering, expression, purification, and biological characterization of bispecific T-cell engagers (BiTEs) that enable targeting PSMA-positive tumor cells by host T lymphocytes. To this end, we designed the 5D3-αCD3 BiTE as a fusion of single-chain fragments of PSMA-specific 5D3 and anti-CD3 antibodies. Detailed characterization of BiTE was performed by a combination of size-exclusion chromatography, differential scanning fluorimetry, and flow cytometry. Expressed in insect cells, BiTE was purified in monodisperse form and retained thermal stability of both functional parts and nanomolar affinity to respective antigens. 5D3-αCD3’s efficiency and specificity were further evaluated in vitro using PCa-derived cell lines together with peripheral blood mononuclear cells isolated from human blood. Our data revealed that T-cells engaged via 5D3-αCD3 can efficiently eliminate tumor cells already at an 8 pM BiTE concentration in a highly specific manner. Overall, the data presented here demonstrate that the 5D3-αCD3 BiTE is a candidate molecule of high potential for further development of immuno­therapeutic modalities for PCa treatment

Histone Deacetylase 11 Is a Fatty-Acid Deacylase

Histone deacetylase 11 (HDAC11) is a sole member of the class IV HDAC subfamily with negligible intrinsic deacetylation activity. Here, we report <i>in vitro</i> profiling of HDAC11 deacylase activities, and our data unequivocally show that the enzyme efficiently removes acyl moieties spanning 8–18 carbons from the side chain nitrogen of the lysine residue of a peptidic substrate. Additionally, N-linked lipoic acid and biotin are removed by the enzyme, although with lower efficacy. Catalytic efficiencies toward dodecanoylated and myristoylated peptides were 77 700 and 149 000 M^–1 s^–1, respectively, making HDAC11 the most proficient fatty-acid deacylase of the HDAC family. Interestingly, HDAC11 is strongly inhibited by free myristic, palmitic, and stearic acids with inhibition constants of 6.5, 0.9, and 1.6 μM, respectively. At the same time, its deacylase activity is stimulated more than 2.5-fold by both palmitoyl-coenzyme A and myristoyl-coenzyme A, pointing toward metabolic control of the enzymatic activity by fatty-acid metabolites. Our data reveal novel enzymatic activity of HDAC11 that can, in turn, facilitate the uncovering of additional biological functions of the enzyme as well as the design of isoform-specific HDAC inhibitors

Utilization of an Optimized AlphaFold Protein Model for Structure-Based Design of a Selective HDAC11 Inhibitor with Anti-neuroblastoma Activity

AlphaFold is an artificial intelligence approach for predicting the 3D structures of proteins with atomic accuracy. One challenge that limits the use of AlphaFold models for drug discovery is the correct prediction of folding in the absence of ligands and cofactors, which compromises their direct use. We have previously described the optimization and use of the HDAC11-AlphaFold model for the docking of selective inhibitors such as FT895 and SIS17. Based on the predicted binding mode of FT895 in the optimized HDAC11 AlphaFold model, a new scaffold for HDAC11 inhibitors was designed, and the resulting compounds were tested in vitro against various HDAC isoforms. Compound 5a proved to be the most active compound with an IC50 of 365 nM and was able to selectively inhibit HDAC11. 5a also showed promising activity with an EC50 of 3.6 µM on neuroblastoma cells. Furthermore, we supported our study by comparative docking and MD simulations