Discovery of a structural class of antibiotics with explainable deep learning.

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1-9. Deep learning approaches have aided in exploring chemical spaces1,10-15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

Correction to "Structure Based Design of Non-Natural Peptidic Macrocyclic Mcl-1 Inhibitors".

[This corrects the article DOI: 10.1021/acsmedchemlett.6b00464.].

Isoform-Selective ATAD2 Chemical Probe with Novel Chemical Structure and Unusual Mode of Action.

ATAD2 (ANCCA) is an epigenetic regulator and transcriptional cofactor, whose overexpression has been linked to the progress of various cancer types. Here, we report a DNA-encoded library screen leading to the discovery of BAY-850, a potent and isoform selective inhibitor that specifically induces ATAD2 bromodomain dimerization and prevents interactions with acetylated histones in vitro, as well as with chromatin in cells. These features qualify BAY-850 as a chemical probe to explore ATAD2 biology.

Discovery of Clinical Candidate 1-{[(2S,3S,4S)-3-Ethyl-4-fluoro-5-oxopyrrolidin-2-yl]methoxy}-7-methoxyisoquinoline-6-carboxamide (PF-06650833), a Potent, Selective Inhibitor of Interleukin-1 Receptor Associated Kinase 4 (IRAK4), by Fragment-Based Drug Design.

Through fragment-based drug design focused on engaging the active site of IRAK4 and leveraging three-dimensional topology in a ligand-efficient manner, a micromolar hit identified from a screen of a Pfizer fragment library was optimized to afford IRAK4 inhibitors with nanomolar potency in cellular assays. The medicinal chemistry effort featured the judicious placement of lipophilicity, informed by co-crystal structures with IRAK4 and optimization of ADME properties to deliver clinical candidate PF-06650833 (compound 40). This compound displays a 5-unit increase in lipophilic efficiency from the fragment hit, excellent kinase selectivity, and pharmacokinetic properties suitable for oral administration.

Structure Based Design of Non-Natural Peptidic Macrocyclic Mcl-1 Inhibitors.

Mcl-1 is a pro-apoptotic BH3 protein family member similar to Bcl-2 and Bcl-xL. Overexpression of Mcl-1 is often seen in various tumors and allows cancer cells to evade apoptosis. Here we report the discovery and optimization of a series of non-natural peptide Mcl-1 inhibitors. Screening of DNA-encoded libraries resulted in hit compound 1, a 1.5 µM Mcl-1 inhibitor. A subsequent crystal structure demonstrated that compound 1 bound to Mcl-1 in a ß-turn conformation, such that the two ends of the peptide were close together. This proximity allowed for the linking of the two ends of the peptide to form a macrocycle. Macrocyclization resulted in an approximately 10-fold improvement in binding potency. Further exploration of a key hydrophobic interaction with Mcl-1 protein and also with the moiety that engages Arg256 led to additional potency improvements. The use of protein-ligand crystal structures and binding kinetics contributed to the design and understanding of the potency gains. Optimized compound 26 is a <3 nM Mcl-1 inhibitor, while inhibiting Bcl-2 at only 5 µM and Bcl-xL at >99 µM, and induces cleaved caspase-3 in MV4-11 cells with an IC50 of 3 µM after 6 h.

Discovery of a Potent BTK Inhibitor with a Novel Binding Mode by Using Parallel Selections with a DNA-Encoded Chemical Library.

We have identified and characterized novel potent inhibitors of Bruton's tyrosine kinase (BTK) from a single DNA-encoded library of over 110 million compounds by using multiple parallel selection conditions, including variation in target concentration and addition of known binders to provide competition information. Distinct binding profiles were observed by comparing enrichments of library building block combinations under these conditions; one enriched only at high concentrations of BTK and was competitive with ATP, and another enriched at both high and low concentrations of BTK and was not competitive with ATP. A compound representing the latter profile showed low nanomolar potency in biochemical and cellular BTK assays. Results from kinetic mechanism of action studies were consistent with the selection profiles. Analysis of the co-crystal structure of the most potent compound demonstrated a novel binding mode that revealed a new pocket in BTK. Our results demonstrate that profile-based selection strategies using DNA-encoded libraries form the basis of a new methodology to rapidly identify small molecule inhibitors with novel binding modes to clinically relevant targets.

Discovery of cofactor-specific, bactericidal Mycobacterium tuberculosis InhA inhibitors using DNA-encoded library technology.

Millions of individuals are infected with and die from tuberculosis (TB) each year, and multidrug-resistant (MDR) strains of TB are increasingly prevalent. As such, there is an urgent need to identify novel drugs to treat TB infections. Current frontline therapies include the drug isoniazid, which inhibits the essential NADH-dependent enoyl-acyl-carrier protein (ACP) reductase, InhA. To inhibit InhA, isoniazid must be activated by the catalase-peroxidase KatG. Isoniazid resistance is linked primarily to mutations in the katG gene. Discovery of InhA inhibitors that do not require KatG activation is crucial to combat MDR TB. Multiple discovery efforts have been made against InhA in recent years. Until recently, despite achieving high potency against the enzyme, these efforts have been thwarted by lack of cellular activity. We describe here the use of DNA-encoded X-Chem (DEX) screening, combined with selection of appropriate physical properties, to identify multiple classes of InhA inhibitors with cell-based activity. The utilization of DEX screening allowed the interrogation of very large compound libraries (1011 unique small molecules) against multiple forms of the InhA enzyme in a multiplexed format. Comparison of the enriched library members across various screening conditions allowed the identification of cofactor-specific inhibitors of InhA that do not require activation by KatG, many of which had bactericidal activity in cell-based assays.

Overview of Recent Progress in Protein-Expression Technologies for Small-Molecule Screening.

Production of novel soluble and membrane-localized protein targets for functional and affinity-based screening has often been limited by the inability of traditional protein-expression systems to generate recombinant proteins that have properties similar to those of their endogenous counterparts. Such targets have often been labeled as challenging. Although biological validation of these challenging targets for specific disease areas may be strong, discovery of small-molecule modulators can be greatly delayed or completely halted due to target-expression issues. In this article, the limitations of traditional protein-expression systems will be discussed along with new systems designed to overcome these challenges. Recent work in this field has focused on two major areas for both soluble and membrane targets: construct-design strategies to improve expression levels and new hosts that can carry out the posttranslational modifications necessary for proper target folding and function. Another area of active research has been on the reconstitution of solubilized membrane targets for both structural analysis and screening. Finally, the potential impact of these new systems on the output of small-molecule screening campaigns will be discussed.

Fragment-based screen against HIV protease.

We have employed a fragment-based screen against wild-type (NL4-3) HIV protease (PR) using the Active Sight fragment library and X-ray crystallography. The experiments reveal two new binding sites for small molecules. PR was co-crystallized with fragments, or crystals were soaked in fragment solutions, using five crystal forms, and 378 data sets were collected to 2.3-1.3 A resolution. Fragment binding induces a distinct conformation and specific crystal form of TL-3 inhibited PR during co-crystallization. One fragment, 2-methylcyclohexanol, binds in the 'exo site' adjacent to the Gly(16)Gly(17)Gln(18)loop where the amide of Gly(17)is a specific hydrogen bond donor, and hydrophobic contacts occur with the side chains of Lys(14)and Leu(63). Another fragment, indole-6-carboxylic acid, binds on the 'outside/top of the flap' via hydrophobic contacts with Trp(42), Pro(44), Met(46), and Lys(55), a hydrogen bond with Val(56), and a salt-bridge with Arg(57). 2-acetyl-benzothiophene also binds at this site. This study is the first fragment-based crystallographic screen against HIV PR, and the first time that fragments were screened against an inhibitor-bound drug target to search for compounds that both bind to novel sites and stabilize the inhibited conformation of the target.