Discovery of a First-in-Class Small-Molecule Ligand for WDR91 Using DNA-Encoded Chemical Library Selection Followed by Machine Learning.

WD40 repeat-containing protein 91 (WDR91) regulates early-to-late endosome conversion and plays vital roles in endosome fusion, recycling, and transport. WDR91 was recently identified as a potential host factor for viral infection. We employed DNA-encoded chemical library (DEL) selection against the WDR domain of WDR91, followed by machine learning to predict ligands from the synthetically accessible Enamine REAL database. Screening of predicted compounds identified a WDR91 selective compound 1, with a KD of 6 ± 2 µM by surface plasmon resonance. The co-crystal structure confirmed the binding of 1 to the WDR91 side pocket, in proximity to cysteine 487, which led to the discovery of covalent analogues 18 and 19. The covalent adduct formation for 18 and 19 was confirmed by intact mass liquid chromatography-mass spectrometry. The discovery of 1, 18, and 19, accompanying structure-activity relationship, and the co-crystal structures provide valuable insights for designing potent and selective chemical tools against WDR91 to evaluate its therapeutic potential.

Deep Learning Approach for the Discovery of Tumor-Targeting Small Organic Ligands from DNA-Encoded Chemical Libraries.

DNA-Encoded Chemical Libraries (DELs) have emerged as efficient and cost-effective ligand discovery tools, which enable the generation of protein-ligand interaction data of unprecedented size. In this article, we present an approach that combines DEL screening and instance-level deep learning modeling to identify tumor-targeting ligands against carbonic anhydrase IX (CAIX), a clinically validated marker of hypoxia and clear cell renal cell carcinoma. We present a new ligand identification and hit-to-lead strategy driven by machine learning models trained on DELs, which expand the scope of DEL-derived chemical motifs. CAIX-screening datasets obtained from three different DELs were used to train machine learning models for generating novel hits, dissimilar to elements present in the original DELs. Out of the 152 novel potential hits that were identified with our approach and screened in an in vitro enzymatic inhibition assay, 70% displayed submicromolar activities (IC50 < 1 µM). To generate lead compounds that are functionalized with anticancer payloads, analogues of top hits were prioritized for synthesis based on the predicted CAIX affinity and synthetic feasibility. Three lead candidates showed accumulation on the surface of CAIX-expressing tumor cells in cellular binding assays. The best compound displayed an in vitro KD of 5.7 nM and selectively targeted tumors in mice bearing human renal cell carcinoma lesions. Our results demonstrate the synergy between DEL and machine learning for the identification of novel hits and for the successful translation of lead candidates for in vivo targeting applications.

Back pocket flexibility provides group II p21-activated kinase (PAK) selectivity for type I 1/2 kinase inhibitors.

Structure-based methods were used to design a potent and highly selective group II p21-activated kinase (PAK) inhibitor with a novel binding mode, compound 17. Hydrophobic interactions within a lipophilic pocket past the methionine gatekeeper of group II PAKs approached by these type I 1/2 binders were found to be important for improving potency. A structure-based hypothesis and strategy for achieving selectivity over group I PAKs, and the broad kinome, based on unique flexibility of this lipophilic pocket, is presented. A concentration-dependent decrease in tumor cell migration and invasion in two triple-negative breast cancer cell lines was observed with compound 17.

The crystal structure of the catalytic domain of the NF-κB inducing kinase reveals a narrow but flexible active site.

The NF-κB inducing kinase (NIK) regulates the non-canonical NF-κB pathway downstream of important clinical targets including BAFF, RANKL, and LTß. Despite numerous genetic studies associating dysregulation of this pathway with autoimmune diseases and hematological cancers, detailed molecular characterization of this central signaling node has been lacking. We undertook a systematic cloning and expression effort to generate soluble, well-behaved proteins encompassing the kinase domains of human and murine NIK. Structures of the apo NIK kinase domain from both species reveal an active-like conformation in the absence of phosphorylation. ATP consumption and peptide phosphorylation assays confirm that phosphorylation of NIK does not increase enzymatic activity. Structures of murine NIK bound to inhibitors possessing two different chemotypes reveal conformational flexibility in the gatekeeper residue controlling access to a hydrophobic pocket. Finally, a single amino acid difference affects the ability of some inhibitors to bind murine and human NIK with the same affinity.

A second look at mini-protein stability: analysis of FSD-1 using circular dichroism, differential scanning calorimetry, and simulations.

Mini-proteins that contain <50 amino acids often serve as model systems for studying protein folding because their small size makes long timescale simulations possible. However, not all mini-proteins are created equal. The stability and structure of FSD-1, a 28-residue mini-protein that adopted the betabetaalpha zinc-finger motif independent of zinc binding, was investigated using circular dichroism, differential scanning calorimetry, and replica-exchange molecular dynamics. The broad melting transition of FSD-1, similar to that of a helix-to-coil transition, was observed by using circular dichroism, differential scanning calorimetry, and replica-exchange molecular dynamics. The N-terminal beta-hairpin was found to be flexible. The FSD-1 apparent melting temperature of 41 degrees C may be a reflection of the melting of its alpha-helical segment instead of the entire protein. Thus, despite its attractiveness due to small size and purposefully designed helix, sheet, and turn structures, the status of FSD-1 as a model system for studying protein folding should be reconsidered.

Conformational manifold of alpha-aminoisobutyric acid (Aib) containing alanine-based tripeptides in aqueous solution explored by vibrational spectroscopy, electronic circular dichroism spectroscopy, and molecular dynamics simulations.

Replacement of the alpha-proton of an alanine residue to generate alpha-aminoisobutyric acid (Aib) in alanine-based oligopeptides favors the formation of a 3(10) helix when the length of the oligopeptide is about four to six residues. This research was aimed at experimentally identifying the structural impact of an individual Aib residue in an alanine context of short peptides in water and Aib's influence on the conformation of nearest-neighbor residues. The amide I band profile of the IR, isotropic and anisotropic Raman, and vibrational circular dichroism (VCD) spectra of Ac-Ala-Ala-Aib-OMe, Ac-Ala-Aib-Ala-OMe, and Ac-Aib-Ala-Ala-OMe were measured and analyzed in terms of different structural models by utilizing an algorithm that exploits the excitonic coupling between amide I' modes. The conformational search was guided by the respective 1H NMR and electronic circular dichroism spectra of the respective peptides, which were also recorded. From these analyses, all peptides adopted multiple conformations. Aib predominantly sampled the right-handed and left-handed 3(10)-helix region and to a minor extent the bridge region between the polyproline (PPII) and the helical regions of the Ramachandran plot. Generally, alanine showed the anticipated PPII propensity, but its conformational equilibrium was shifted towards helical conformations in Ac-Aib-Ala-Ala-OMe, indicating that Aib can induce helical conformations of neighboring residues positioned towards the C-terminal direction of the peptide. An energy landscape exploration by molecular dynamics simulations corroborated the results of the spectroscopic studies. They also revealed the dynamics and pathways of potential conformational transitions of the corresponding Aib residues.