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.

Targeting diseases with unmet medical needs remains a major challenge, particularly when modulating protein–protein interactions. While small molecules have traditionally been employed for such targets, their limitations have driven the development of biological modalities, including monoclonal antibodies. Macrocycles occupy an intermediate space, combining the selectivity and affinity of biologics with the favorable pharmacokinetic and manufacturability profiles of small molecules. Here, we describe a rational strategy to identify medium-sized peptide-based macrocycles as ligands for TNFα. Using a minimal set of building blocks, we identified macrocycles capable of binding TNFα, demonstrating the feasibility of this approach for an otherwise undrugged cytokine target. Expansion of this strategy through larger building-block libraries, diverse cyclization chemistries, and automated high-throughput synthesis is expected to substantially enhance discovery throughput. This work illustrates the potential of rationally designing macrocycles as targeted therapeutics.

Targeting diseases with unmet medical needs remains a major challenge, particularly when modulating protein–protein interactions. While small molecules have traditionally been employed for such targets, their limitations have driven the development of biological modalities, including monoclonal antibodies. Macrocycles occupy an intermediate space, combining the selectivity and affinity of biologics with the favorable pharmacokinetic and manufacturability profiles of small molecules. Here, we describe a rational strategy to identify medium-sized peptide-based macrocycles as ligands for TNFα. Using a minimal set of building blocks, we identified macrocycles capable of binding TNFα, demonstrating the feasibility of this approach for an otherwise undrugged cytokine target. Expansion of this strategy through larger building-block libraries, diverse cyclization chemistries, and automated high-throughput synthesis is expected to substantially enhance discovery throughput. This work illustrates the potential of rationally designing macrocycles as targeted therapeutics.