Discovery of Potent Inhibitors of 11β-Hydroxysteroid Dehydrogenase Type 1 Using a Novel Growth-Based Protocol of in Silico Screening and Optimization in CONTOUR

SpaceGrow: efficient shape-based virtual screening of billion-sized combinatorial fragment spaces

The growing size of make-on-demand chemical libraries is posing new challenges to cheminformatics. These ultra-large chemical libraries became too large for exhaustive enumeration. Using a combinatorial approach instead, the resource requirement scales approximately with the number of synthons instead of the number of molecules. This gives access to billions or trillions of compounds as so-called chemical spaces with moderate hardware and in a reasonable time frame. While extremely performant ligand-based 2D methods exist in this context, 3D methods still largely rely on exhaustive enumeration and therefore fail to apply. Here, we present SpaceGrow: a novel shape-based 3D approach for ligand-based virtual screening of billions of compounds within hours on a single CPU. Compared to a conventional superposition tool, SpaceGrow shows comparable pose reproduction capacity based on RMSD and superior ranking performance while being orders of magnitude faster. Result assessment of two differently sized subsets of the eXplore space reveals a higher probability of finding superior results in larger spaces highlighting the potential of searching in ultra-large spaces. Furthermore, the application of SpaceGrow in a drug discovery workflow was investigated in four examples involving G protein-coupled receptors (GPCRs) with the aim to identify compounds with similar binding capabilities and molecular novelty.

Discovery of pyrazolopyrrolidinones as potent, broad-spectrum inhibitors of Leishmania infection

Introduction

Leishmaniasis is a parasitic disease that affects more than 1 million people worldwide annually, predominantly in resource-limited settings. The challenge in compound development is to exhibit potent activity against the intracellular stage of the parasite (the stage present in the mammalian host) without harming the infected host cells. We have identified a compound series (pyrazolopyrrolidinones) active against the intracellular parasites of Leishmania donovani and L. major; the causative agents of visceral and cutaneous leishmaniasis in the Old World, respectively.

Methods

In this study, we performed medicinal chemistry on a newly discovered antileishmanial chemotype, with over 100 analogs tested. Studies included assessments of antileishmanial potency, toxicity towards host cells, and in vitro ADME screening of key drug properties.

Results and discussion

Members of the series showed high potency against the deadliest form, visceral leishmaniasis (approximate EC₅₀ ≥ 0.01 μM without harming the host macrophage up to 10.0 μM). In comparison, the most efficient monotherapy treatment for visceral leishmaniasis is amphotericin B, which presents similar activity in the same assay (EC₅₀ = 0.2 μM) while being cytotoxic to the host cell at 5.0 μM. Continued development of this compound series with the Discovery Partnership with Academia (DPAc) program at the GlaxoSmithKline Diseases of the Developing World (GSK DDW) laboratories found that the compounds passed all of GSK's criteria to be defined as a potential lead drug series for leishmaniasis.

Conclusion

Here, we describe preliminary structure-activity relationships for antileishmanial pyrazolopyrrolidinones, and our progress towards the identification of candidates for future in vivo assays in models of visceral and cutaneous leishmaniasis.

Galileo: Three-dimensional searching in large combinatorial fragment spaces on the example of pharmacophores

Fragment spaces are an efficient way to model large chemical spaces using a handful of small fragments and a few connection rules. The development of Enamine's REAL Space has shown that large spaces of readily available compounds may be created this way. These are several orders of magnitude larger than previous libraries. So far, searching and navigating these spaces is mostly limited to topological approaches. A way to overcome this limitation is optimization via metaheuristics which can be combined with arbitrary scoring functions. Here we present Galileo, a novel Genetic Algorithm to sample fragment spaces. We showcase Galileo in combination with a novel pharmacophore mapping approach, called Phariety, enabling 3D searches in fragment spaces. We estimate the effectiveness of the approach with a small fragment space. Furthermore, we apply Galileo to two pharmacophore searches in the REAL Space, detecting hundreds of compounds fulfilling a HSP90 and a FXIa pharmacophore.

Shape-Based Descriptors for Efficient Structure-Based Fragment Growing

Structure-based fragment growing is one of the key techniques in fragment-based drug design. Fragment growing is commonly practiced based on structural and biophysical data. Computational workflows are employed to predict which fragment elaborations could lead to high-affinity binders. Several such workflows exist but many are designed to be long running noninteractive systems. Shape-based descriptors have been proven to be fast and perform well at virtual-screening tasks. They could, therefore, be applied to the fragment-growing problem to enable an interactive fragment-growing workflow. In this work, we describe and analyze the use of specific shape-based directional descriptors for the task of fragment growing. The performance of these descriptors that we call ray volume matrices (RVMs) is evaluated on two data sets containing protein-ligand complexes. While the first set focuses on self-growing, the second measures practical performance in a cross-growing scenario. The runtime of screenings using RVMs as well as their robustness to three dimensional perturbations is also investigated. Overall, it can be shown that RVMs are useful to prefilter fragment candidates. For up to 84% of the 3299 generated self-growing cases and for up to 66% of the 326 generated cross-growing cases, RVMs could create poses with less than 2 Å root-mean-square deviation to the crystal structure with average query speeds of around 30,000 conformations per second. This opens the door for fast explorative screenings of fragment libraries.