Streptococcus pneumoniae causes invasive infections such as otitis media, pneumonia and meningitis. It produces the pneumolysin (Ply) toxin, which forms a pore onto the host cell membrane and has multiple functions in the pathogenesis of S. pneumoniae. The Ply C-terminal domain 4 mediates binding to membrane cholesterol and induces the formation of pores composed of up to 40 Ply monomers. Ply has a key role in the establishment of nasal colonization, pneumococcal transmission from host to host and pathogenicity. Altogether, 27 hydrolysable tannins were tested for Ply inhibition in a hemolysis assay and a tannin-protein precipitation assay. Pentagalloylglucose (PGG) and gemin A showed nanomolar inhibitory activity. Ply oligomerization on the erythrocyte surface was inhibited with PGG. PGG also inhibited Ply cytotoxicity to A549 human lung epithelial cells. Molecular modelling of Ply interaction with PGG suggests that it binds to the pocket formed by domains 2, 3 and 4. In this study, we reveal the structural features of hydrolysable tannins that are required for interaction with Ply. Monomeric hydrolysable tannins containing three to four flexible galloyl groups have the highest inhibitory power to Ply cytotoxicity and are followed by oligomers. Of the oligomers, macrocyclic and C-glycosidic structures were weaker in their inhibition than the glucopyranose-based oligomers. Accordingly, PGG-type monomers and oligomers might have therapeutic value in the targeting of S. pneumoniae infections.

Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein’s ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer generation software for acquiring the best NIB screening results using cyclooxygenase-2 (COX-2) as the example system. Secondly, the entire NIB workflow from the protein structure preparation, model build-up, and ligand conformer generation to the similarity comparison is performed for COX-2. Accordingly, hands-on instructions are provided on how to employ the NIB methodology from start to finish, both with the rigid docking and docking rescoring using noncommercial software. The practical aspects of the NIB methodology, especially the effect of ligand conformers, are discussed thoroughly, thus, making the methodology accessible for new users.

Phytochromes are red light-sensing photoreceptor proteins that bind a bilin chromophore. Here, we investigate the role of a conserved histidine (H260) and tyrosine (Y263) in the chromophore-binding domain (CBD) of Deinococcus radiodurans phytochrome (DrBphP). Using crystallography, we show that in the H260A variant, the missing imidazole side chain leads to increased water content in the binding pocket. On the other hand, Y263F mutation reduces the water occupancy around the chromophore. Together, these changes in water coordination alter the protonation and spectroscopic properties of the biliverdin. These results pinpoint the importance of this conserved histidine and tyrosine, and the related water network, for the function and applications of phytochromes. Graphical abstract

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. RORγt is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target’s binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known RORγt activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low μM range RORγt inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of ~29%.

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein –ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Molecular docking is a key in silico method used routinely in modern drug discovery projects. Although docking provides high-quality ligand binding predictions, it regularly fails to separate the active compounds from the inactive ones. In negative image-based rescoring (R-NiB), the shape/electrostatic potential (ESP) of docking poses is compared to the negative image of the protein’s ligand binding cavity. While R-NiB often improves the docking yield considerably, the cavity-based models do not reach their full potential without expert editing. Accordingly, a greedy search-driven methodology, brute force negative image-based optimization (BR-NiB), is presented for optimizing the models via iterative editing and benchmarking. Thorough and unbiased training, testing and stringent validation with a multitude of drug targets, and alternative docking software show that BR-NiB ensures excellent docking efficacy. BR-NiB can be considered as a new type of shape-focused pharmacophore modeling, where the optimized models contain only the most vital cavity information needed for effectively filtering docked actives from the inactive or decoy compounds. Finally, the BR-NiB code for performing the automated optimization is provided free-of-charge under MIT license via GitHub (https://github.com/jvlehtonen/brutenib) for boosting the success rates of docking-based virtual screening campaigns.