Assessment of the Fragment Docking Program SEED

Structure-Based Design of CBP/EP300 Degraders: When Cooperativity Overcomes Affinity

We present the development of dCE-2, a structurally novel PROTAC targeting the CREB-binding protein (CBP) and E1A-associated protein (EP300)-two homologous multidomain enzymes crucial for enhancer-mediated transcription. The design of dCE-2 was based on the crystal structure of an in-house bromodomain (BRD) inhibitor featuring a 3-methyl-cinnoline acetyl-lysine mimic acetyl-lysine mimic discovered by high-throughput fragment docking. Our study shows that, despite its modest binding affinity to CBP/EP300-BRD, dCE-2's remarkable protein degradation activity stems from its good cooperativity, which we demonstrate by the characterization of its ternary complex formation both in vitro and in cellulo. Molecular dynamics simulations indicate that in aqueous solvents, this active degrader populates both folded and extended conformations, which are likely to promote cell permeability and ternary complex formation, respectively.

Small-Molecule Inhibitors of the m7G-RNA Writer METTL1

We discovered the first inhibitors of the m7G-RNA writer METTL1 by high-throughput docking and an enzymatic assay based on luminescence. Eleven compounds, which belong to three different chemotypes, show inhibitory activity in the range 40-300 μM. Two adenine derivatives identified by docking have very favorable ligand efficiency of 0.34 and 0.31 kcal/mol per non-hydrogen atom, respectively. Molecular dynamics simulations provide evidence that the inhibitors compete with the binding of the cosubstrate S-adenosyl methionine to METTL1. We also present a soakable crystal form that was used to determine the structure of the complex of METTL1 with sinefungin at a resolution of 1.85 Å.

Redocking the PDB

Molecular docking is a standard technique in structure-based drug design (SBDD). It aims to predict the 3D structure of a small molecule in the binding site of a receptor (often a protein). Despite being a common technique, it often necessitates multiple tools and involves manual steps. Here, we present the JAMDA preprocessing and docking workflow that is easy to use and allows fully automated docking. We evaluate the JAMDA docking workflow on binding sites extracted from the complete PDB and derive key factors determining JAMDA's docking performance. With that, we try to remove most of the bias due to manual intervention and provide a realistic estimate of the redocking performance of our JAMDA preprocessing and docking workflow for any PDB structure. On this large PDBScan22 data set, our JAMDA workflow finds a pose with an RMSD of at most 2 Å to the crystal ligand on the top rank for 30.1% of the structures. When applying objective structure quality filters to the PDBScan22 data set, the success rate increases to 61.8%. Given the prepared structures from the JAMDA preprocessing pipeline, both JAMDA and the widely used AutoDock Vina perform comparably on this filtered data set (the PDBScan22-HQ data set).

Identification of a BAZ2A-Bromodomain Hit Compound by Fragment Growing

BAZ2A is an epigenetic regulator affecting transcription of ribosomal RNA. It is overexpressed in aggressive and recurrent prostate cancer, promoting cellular migration. Its bromodomain is characterized by a shallow and difficult-to-drug pocket. Here, we describe a structure-based fragment-growing campaign for the identification of ligands of the BAZ2A bromodomain. By combining docking, competition binding assays, and protein crystallography, we have extensively explored the interactions of the ligands with the rim of the binding pocket, and in particular ionic interactions with the side chain of Glu1820, which is unique to BAZ2A. We present 23 high-resolution crystal structures of the holo BAZ2A bromodomain and analyze common bromodomain/ligand motifs and favorable intraligand interactions. Binding of some of the compounds is enantiospecific, with affinity in the low micromolar range. The most potent ligand has an equilibrium dissociation constant of 7 μM and a good selectivity over the paralog BAZ2B bromodomain.

Fragment-to-Lead Medicinal Chemistry Publications in 2020

Fragment-based drug discovery (FBDD) continues to evolve and make an impact in the pharmaceutical sciences. We summarize successful fragment-to-lead studies that were published in 2020. Having systematically analyzed annual scientific outputs since 2015, we discuss trends and best practices in terms of fragment libraries, target proteins, screening technologies, hit-optimization strategies, and the properties of hit fragments and the leads resulting from them. As well as the tabulated Fragment-to-Lead (F2L) programs, our 2020 literature review identifies several trends and innovations that promise to further increase the success of FBDD. These include developing structurally novel screening fragments, improving fragment-screening technologies, using new computer-aided design and virtual screening approaches, and combining FBDD with other innovative drug-discovery technologies.

Fragment-based drug design facilitates selective kinase inhibitor discovery

Protein kinases (PKs) are important drug targets, but kinases selectivity poses a challenge to protein kinase inhibitors (PKIs) design. Fragment-based drug discovery (FBDD) has achieved great success in the discovery of highly specific PKIs. It makes full use of kinase-fragment interaction in target kinase subpockets to obtain promising selectivity. However, it's difficult to understand the complicated kinase-fragment interaction space, and systemic discussion of these interactions is still lacking. Herein, we introduce the advantages of the FBDD strategy in PKIs design. Key features of the selectivity of kinase-fragment interactions are summarized and analyzed. Some promising PKIs are introduced as case studies to help understand the fragment-to-lead (F2L) optimization process. Novel strategies and technologies for FBDD in PKIs discovery are also outlooked.

Fragment Binding to the Nsp3 Macrodomain of SARS-CoV-2 Identified Through Crystallographic Screening and Computational Docking

The SARS-CoV-2 macrodomain (Mac1) within the non-structural protein 3 (Nsp3) counteracts host-mediated antiviral ADP-ribosylation signalling. This enzyme is a promising antiviral target because catalytic mutations render viruses non-pathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of diverse fragment libraries resulted in 214 unique macrodomain-binding fragments, out of 2,683 screened. An additional 60 molecules were selected from docking over 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several crystallographic and docking fragment hits were validated for solution binding using three biophysical techniques (DSF, HTRF, ITC). Overall, the 234 fragment structures presented explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.