Efficient virtual high-content screening using a distance-aware transformer model.

Molecular similarity search is an often-used method in drug discovery, especially in virtual screening studies. While simple one- or two-dimensional similarity metrics can be applied to search databases containing billions of molecules in a reasonable amount of time, this is not the case for complex three-dimensional methods. In this work, we trained a transformer model to autoencode tokenized SMILES strings using a custom loss function developed to conserve similarities in latent space. This allows the direct sampling of molecules in the generated latent space based on their Euclidian distance. Reducing the similarity between molecules to their Euclidian distance in latent space allows the model to perform independent of the similarity metric it was trained on. While we test the method here using 2D similarity as proof-of-concept study, the algorithm will enable also high-content screening with time-consuming 3D similarity metrics. We show that the presence of a specific loss function for similarity conservation greatly improved the model's ability to predict highly similar molecules. When applying the model to a database containing 1.5 billion molecules, our model managed to reduce the relevant search space by 5 orders of magnitude. We also show that our model was able to generalize adequately when trained on a relatively small dataset of representative structures. The herein presented method thereby provides new means of substantially reducing the relevant search space in virtual screening approaches, thus highly increasing their throughput. Additionally, the distance awareness of the model causes the efficiency of this method to be independent of the underlying similarity metric.

Ligand pathways in estrogen-related receptors.

The three subtypes of estrogen-related receptors ERRα, ERRß, and ERRγ are nuclear receptors mediating metabolic processes in various tissues such as the skeletal muscle, fat tissue, bone, and liver. Although the knowledge on their physiological ligands is limited, they have been implicated as drug targets for important indications including diabetes, cardiovascular diseases, and osteoporosis. As in other nuclear receptors, their ligand binding pocket is buried within the core of the receptor and connected to its surrounding by ligand pathways. Here, we investigated these pathways with conventional molecular dynamics as well as metadynamics simulations to reveal their distribution and their capability to facilitate ligand translocation. Dependent on the ERR subtype and the conformational state of the receptor, we could detect different pathways to be favored. Overall, the results suggested pathways IIIa and IIIb to be favored in the agonistic conformation, while antagonists preferred pathways I, II, and V. Along the pathways, the ligands passed different gating mechanisms of the receptor, including groups of protein residues as well as whole secondary structure elements, to leave the binding site. Even though these pathways are suggested to influence ligand specificity of the receptors and their elucidation might advance rational drug design, they have not yet been studied in ERRs.Communicated by Ramaswamy H. Sarma.

Activation of retinoic acid-related orphan receptor γ(t) by parabens and benzophenone UV-filters.

Retinoic acid-related orphan receptor γt (RORγt) regulates immune responses and its impaired function contributes to inflammatory and autoimmune diseases and may promote skin cancer. Synthetic inverse RORγt agonists block the production of Th17-associated cytokines including interleukin (IL)-17A and IL-22 and are under investigation for treatment of such pathologies. Unintentional RORγt activation in skin, following exposure to environmental chemicals, may promote inflammatory skin disease. Parabens and UV-filters, frequently used as additives in cosmetics and body care products, are intensively inspected for endocrine disrupting properties. This study assessed whether such compounds can interfere with RORγ activity using a previously established tetracycline-inducible reporter gene assay in CHO cells. These transactivation experiments revealed hexylparaben, benzylparaben and benzophenone-10 as RORγ agonists (EC50 values: 144 ± 97 nM, 3.39 ± 1.74 µM and 1.67 ± 1.04 µM, respectively), and they could restore RORγ activity after suppression by an inverse agonist. Furthermore, they enhanced RORγt-dependent transcription of the pro-inflammatory IL-17A and/or IL-22 genes in the murine T-cell model EL4. Virtual screening of a cosmetics database for structurally similar chemicals and in vitro testing of the most promising hits revealed benzylbenzoate, benzylsalicylate and 4-methylphenylbenzoate as RORγ agonists (low micromolar EC50 values). Moreover, an analysis of mixtures of the newly identified RORγ agonists suggested additive effects. This study presents novel RORγ(t) agonistic structural scaffolds. By activating RORγ(t) the identified parabens and UV-filters may potentially aggravate pathophysiological conditions, especially skin diseases where highest exposure of such chemicals can be expected. Follow-up studies should assess whether such compounds, either alone or as mixtures, can reach relevant concentrations in tissues and target cells to activate RORγ(t) in vivo.

Evaluation of Xa inhibitors as potential inhibitors of the SARS-CoV-2 Mpro protease.

Based on previous large-scale in silico screening several factor Xa inhibitors were proposed to potentially inhibit SARS-CoV-2 Mpro. In addition to their known anticoagulants activity this potential inhibition could have an additional therapeutic effect on patients with COVID-19 disease. In this study we examined the binding of the Apixaban, Betrixaban and Rivaroxaban to the SARS-CoV-2 Mpro with the use of the MicroScale Thermophoresis technique. Our results indicate that the experimentally measured binding affinity is weak and the therapeutic effect due to the SARS-CoV-2 Mpro inhibition is rather negligible.

Computational Selectivity Assessment of Protease Inhibitors against SARS-CoV-2.

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious global health threat. Since no specific therapeutics are available, researchers around the world screened compounds to inhibit various molecular targets of SARS-CoV-2 including its main protease (Mpro) essential for viral replication. Due to the high urgency of these discovery efforts, off-target binding, which is one of the major reasons for drug-induced toxicity and safety-related drug attrition, was neglected. Here, we used molecular docking, toxicity profiling, and multiple molecular dynamics (MD) protocols to assess the selectivity of 33 reported non-covalent inhibitors of SARS-CoV-2 Mpro against eight proteases and 16 anti-targets. The panel of proteases included SARS-CoV Mpro, cathepsin G, caspase-3, ubiquitin carboxy-terminal hydrolase L1 (UCHL1), thrombin, factor Xa, chymase, and prostasin. Several of the assessed compounds presented considerable off-target binding towards the panel of proteases, as well as the selected anti-targets. Our results further suggest a high risk of off-target binding to chymase and cathepsin G. Thus, in future discovery projects, experimental selectivity assessment should be directed toward these proteases. A systematic selectivity assessment of SARS-CoV-2 Mpro inhibitors, as we report it, was not previously conducted.

Decision Making in Structure-Based Drug Discovery: Visual Inspection of Docking Results.

Molecular docking is a computational method widely used in drug discovery. Due to the inherent inaccuracies of molecular docking, visual inspection of binding modes is a crucial routine in the decision making process of computational medicinal chemists. Despite its apparent importance for medicinal chemistry projects, guidelines for the visual docking pose assessment have been hardly discussed in the literature. Here, we review the medicinal chemistry literature with the aim of identifying consistent principles for visual inspection, highlighting cases of its successful application, and discussing its limitations. In this context, we conducted a survey reaching experts in both academia and the pharmaceutical industry, which also included a challenge to distinguish native from incorrect poses. We were able to collect 93 expert opinions that offer valuable insights into visually supported decision-making processes. This perspective shall motivate discussions among experienced computational medicinal chemists and guide young scientists new to the field to stratify their compounds.

Conformational Landscape of Cytochrome P450 Reductase Interactions.

Oxidative reactions catalyzed by Cytochrome P450 enzymes (CYPs), which constitute the most relevant group of drug-metabolizing enzymes, are enabled by their redox partner Cytochrome P450 reductase (CPR). Both proteins are anchored to the membrane of the endoplasmic reticulum and the CPR undergoes a conformational change in order to interact with the respective CYP and transfer electrons. Here, we conducted over 22 microseconds of molecular dynamics (MD) simulations in combination with protein-protein docking to investigate the conformational changes necessary for the formation of the CPR-CYP complex. While some structural features of the CPR and the CPR-CYP2D6 complex that we highlighted confirmed previous observations, our simulations revealed additional mechanisms for the conformational transition of the CPR. Unbiased simulations exposed a movement of the whole protein relative to the  membrane, potentially to facilitate interactions with its diverse set of redox partners. Further, we present a structural mechanism for the susceptibility of the CPR to different redox states based on the flip of a glycine residue disrupting the local interaction network that maintains inter-domain proximity. Simulations of the CPR-CYP2D6 complex pointed toward an additional interaction surface of the FAD domain and the proximal side of CYP2D6. Altogether, this study provides novel structural insight into the mechanism of CPR-CYP interactions and underlying conformational changes, improving our understanding of this complex machinery Cytochrome P450 reductase; CPR; conformational; dynamicsrelevant for drug metabolism.

Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds.

The rapid outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China followed by its spread around the world poses a serious global concern for public health. To this date, no specific drugs or vaccines are available to treat SARS-CoV-2 despite its close relation to the SARS-CoV virus that caused a similar epidemic in 2003. Thus, there remains an urgent need for the identification and development of specific antiviral therapeutics against SARS-CoV-2. To conquer viral infections, the inhibition of proteases essential for proteolytic processing of viral polyproteins is a conventional therapeutic strategy. In order to find novel inhibitors, we computationally screened a compound library of over 606 million compounds for binding at the recently solved crystal structure of the main protease (Mpro) of SARS-CoV-2. A screening of such a vast chemical space for SARS-CoV-2 Mpro inhibitors has not been reported before. After shape screening, two docking protocols were applied followed by the determination of molecular descriptors relevant for pharmacokinetics to narrow down the number of initial hits. Next, molecular dynamics simulations were conducted to validate the stability of docked binding modes and comprehensively quantify ligand binding energies. After evaluation of potential off-target binding, we report a list of 12 purchasable compounds, with binding affinity to the target protease that is predicted to be more favorable than that of the cocrystallized peptidomimetic compound. In order to quickly advise ongoing therapeutic intervention for patients, we evaluated approved antiviral drugs and other protease inhibitors to provide a list of nine compounds for drug repurposing. Furthermore, we identified the natural compounds (-)-taxifolin and rhamnetin as potential inhibitors of Mpro. Rhamnetin is already commercially available in pharmacies.