Fragment-Based Ligand Discovery Applied to the Mycolic Acid Methyltransferase Hma (MmaA4) from Mycobacterium tuberculosis: A Crystallographic and Molecular Modelling Study

The mycolic acid biosynthetic pathway represents a promising source of pharmacological targets in the fight against tuberculosis. In Mycobacterium tuberculosis, mycolic acids are subject to specific chemical modifications introduced by a set of eight S-adenosylmethionine dependent methyltransferases. Among these, Hma (MmaA4) is responsible for the introduction of oxygenated modifications. Crystallographic screening of a library of fragments allowed the identification of seven ligands of Hma. Two mutually exclusive binding modes were identified, depending on the conformation of residues 147–154. These residues are disordered in apo-Hma but fold upon binding of the S-adenosylmethionine (SAM) cofactor as well as of analogues, resulting in the formation of the short η1-helix. One of the observed conformations would be incompatible with the presence of the cofactor, suggesting that allosteric inhibitors could be designed against Hma. Chimeric compounds were designed by fusing some of the bound fragments, and the relative binding affinities of initial fragments and evolved compounds were investigated using molecular dynamics simulation and generalised Born and Poisson–Boltzmann calculations coupled to the surface area continuum solvation method. Molecular dynamics simulations were also performed on apo-Hma to assess the structural plasticity of the unliganded protein. Our results indicate a significant improvement in the binding properties of the designed compounds, suggesting that they could be further optimised to inhibit Hma activity.

Processing binding data using an open-source workflow

The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (FBLD) to detect protein–ligand interactions. By comparing the thermal stability of a target protein in the presence and absence of a ligand, potential binders can be identified. The technique is easy to set up, has low protein consumption, and can be run on most real-time polymerase chain reaction (PCR) instruments. While data analysis is straightforward in principle, it becomes cumbersome and time-consuming when the screens involve multiple 96- or 384-well plates. There are several approaches that aim to streamline this process, but most involve proprietary software, programming knowledge, or are designed for specific instrument output files. We therefore developed an analysis workflow implemented in the Konstanz Information Miner (KNIME), a free and open-source data analytics platform, which greatly streamlined our data processing timeline for 384-well plates. The implementation is code-free and freely available to the community for improvement and customization to accommodate a wide range of instrument input files and workflows. Graphical Abstract

CSIG-05. DISSOCIATION OF THE INTRAMOLECULARLY CLEAVED N- AND C-TERMINAL FRAGMENTS OF ADHESION G PROTEIN-COUPLED RECEPTOR GPR133 (ADGRD1) INCREASES ITS CANONICAL SIGNALING IN GLIOBLASTOMA

We previously demonstrated that GPR133 (ADGRD1), an adhesion GPCR that signals via cytosolic cAMP increase, is de novo expressed in glioblastoma (GBM) and enriched in patient-derived glioblastoma stem cells. Knockdown of GPR133 reduces GBM cell proliferation and tumorsphere formation, and abolishes orthotopic xenograft initiation in vivo. GPR133’s requirement for GBM growth and its absence in non-malignant brain suggest its therapeutic potential, yet its mechanisms of action and activation remained unclear. Here, we demonstrate in patient-derived GBM cultures and HEK293T cells that GPR133 gets intramolecularly cleaved into N-terminal and C-terminal fragments (NTF and CTF) right after synthesis in the endoplasmic reticulum. The resulting NTF and CTF remain non-covalently bound to each other, until the mature receptor reaches the plasma membrane, where we observe dissociation of the extracellular NTF from the transmembrane-spanning CTF. While cleavage is not required for correct subcellular trafficking, the cleaved wild-type GPR133 generates significantly higher cytosolic cAMP levels than an uncleavable point mutant GPR133 (H543R), suggesting that cleavage and dissociation are involved in receptor activation. To test this hypothesis in a more controllable proxy system, we generated a fusion of the CTF of GPR133 and the N-terminus of human protease-activated receptor 1 (hPAR1). Indeed, acute thrombin-induced cleavage and shedding of the hPAR1 NTF increases intracellular cAMP levels generated by the GPR133 CTF. These results support a model wherein dissociation of the NTF from the CTF at the plasma membrane promotes GPR133 activation and downstream signaling. To test whether extracellular binding proteins could influence NTF shedding and/or GPR133 signaling activation, we conducted ligand discovery screens and indeed found a new GPR133 binding protein in GBM cells, which is capable of influencing receptor signaling. Together, these findings provide critical insights into GPR133’s mechanism of activation, that will guide future approaches of therapeutic targeting of GPR133 in GBM.

Rational design of ASCT2 inhibitors using an integrated experimental-computational approach

ASCT2 (SLC1A5) is a sodium-dependent neutral amino acid transporter that controls amino acid homeostasis in peripheral tissues. In cancer, ASCT2 is up-regulated where it modulates intracellular glutamine levels, fueling cell proliferation. Nutrient deprivation via ASCT2 inhibition provides a potential strategy for cancer therapy. Here, we rationally designed stereospecific inhibitors exploiting specific subpockets in the substrate binding site using computational modeling and cryo-electron microscopy (cryo-EM). The final structures combined with molecular dynamics simulations reveal multiple pharmacologically relevant conformations in the ASCT2 binding site as well as a previously unknown mechanism of stereospecific inhibition. Furthermore, this integrated analysis guided the design of a series of unique ASCT2 inhibitors. Our results provide a framework for future development of cancer therapeutics targeting nutrient transport via ASCT2, as well as demonstrate the utility of combining computational modeling and cryo-EM for solute carrier ligand discovery.

Ligands of Adrenergic Receptors: A Structural Point of View

Adrenergic receptors are G protein-coupled receptors for epinephrine and norepinephrine. They are targets of many drugs for various conditions, including treatment of hypertension, hypotension, and asthma. Adrenergic receptors are intensively studied in structural biology, displayed for binding poses of different types of ligands. Here, we summarized molecular mechanisms of ligand recognition and receptor activation exhibited by structure. We also reviewed recent advances in structure-based ligand discovery against adrenergic receptors.

An automated platform for structural analysis of membrane proteins through serial crystallography

Membrane proteins are central to many pathophysiological processes yet remain very difficult to analyze at a structural level. Moreover, high-throughput structure-based drug discovery has not yet been exploited for membrane proteins due to lack of automation. Here, we present a facile and versatile platform for in meso membrane protein crystallization, enabling rapid atomic structure determination at both cryogenic and room temperature and in a single support. We apply this approach to two human integral membrane proteins, which allowed us to capture different conformational states of intramembrane enzyme-product complexes and analyze the structural dynamics of the ADIPOR2 integral membrane protein. Finally, we demonstrate an automated pipeline combining high-throughput microcrystal soaking, automated laser-based harvesting and serial crystallography enabling screening of small molecule libraries with membrane protein crystals grown in meso. This approach brings badly needed automation for this important class of drug targets and enables high-throughput structure-based ligand discovery with membrane proteins.