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Hönig SMN, Flachsenberg F, Ehrt C, Neumann A, Schmidt R, Lemmen C, Rarey M. SpaceGrow: efficient shape-based virtual screening of billion-sized combinatorial fragment spaces. J Comput Aided Mol Des 2024; 38:13. [PMID: 38493240 PMCID: PMC10944417 DOI: 10.1007/s10822-024-00551-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 02/13/2024] [Indexed: 03/18/2024]
Abstract
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.
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Affiliation(s)
- Sophia M N Hönig
- BioSolveIT, An der Ziegelei 79, 53757, Sankt Augustin, Germany
- Universität Hamburg, ZBH - Center for Bioinformatics, Albert-Einstein-Ring 8-10, 22761, Hamburg, Germany
| | | | - Christiane Ehrt
- Universität Hamburg, ZBH - Center for Bioinformatics, Albert-Einstein-Ring 8-10, 22761, Hamburg, Germany
| | | | - Robert Schmidt
- BioSolveIT, An der Ziegelei 79, 53757, Sankt Augustin, Germany
| | | | - Matthias Rarey
- Universität Hamburg, ZBH - Center for Bioinformatics, Albert-Einstein-Ring 8-10, 22761, Hamburg, Germany.
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Kavouris JA, McCall LI, Giardini MA, De Muylder G, Thomas D, Garcia-Pérez A, Cantizani J, Cotillo I, Fiandor JM, McKerrow JH, De Oliveira CI, Siqueira-Neto JL, González S, Brown LE, Schaus SE. Discovery of pyrazolopyrrolidinones as potent, broad-spectrum inhibitors of Leishmania infection. FRONTIERS IN TROPICAL DISEASES 2023; 3:1011124. [PMID: 36818551 PMCID: PMC9937549 DOI: 10.3389/fitd.2022.1011124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
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.
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Affiliation(s)
- John A. Kavouris
- Department of Chemistry and Center for Molecular Discovery (BU-CMD), Boston University, Boston, Massachusetts, United States of America
| | - Laura-Isobel McCall
- Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America
| | - Miriam A. Giardini
- Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America
| | - Geraldine De Muylder
- Department of Pathology, Sandler Center for Drug Discovery, University of California San Francisco, San Francisco, California, United States of America
| | - Diane Thomas
- Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America
| | - Adolfo Garcia-Pérez
- Global Health Medicines R&D, GlaxoSmithKline, Severo Ochoa 2, 28760 Tres Cantos, Madrid, Spain
| | - Juan Cantizani
- Global Health Medicines R&D, GlaxoSmithKline, Severo Ochoa 2, 28760 Tres Cantos, Madrid, Spain
| | - Ignacio Cotillo
- Global Health Medicines R&D, GlaxoSmithKline, Severo Ochoa 2, 28760 Tres Cantos, Madrid, Spain
| | - Jose M. Fiandor
- Global Health Medicines R&D, GlaxoSmithKline, Severo Ochoa 2, 28760 Tres Cantos, Madrid, Spain
| | - James H. McKerrow
- Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.,Department of Pathology, Sandler Center for Drug Discovery, University of California San Francisco, San Francisco, California, United States of America
| | - Camila I. De Oliveira
- HUPES, Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais (INCT-DT) -Salvador, Brazil; Instituto de Investigação em Imunologia (iii-INCT), São Paulo, Brazil
| | - Jair L. Siqueira-Neto
- Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.,Department of Pathology, Sandler Center for Drug Discovery, University of California San Francisco, San Francisco, California, United States of America
| | - Silvia González
- Global Health Medicines R&D, GlaxoSmithKline, Severo Ochoa 2, 28760 Tres Cantos, Madrid, Spain
| | - Lauren E. Brown
- Department of Chemistry and Center for Molecular Discovery (BU-CMD), Boston University, Boston, Massachusetts, United States of America
| | - Scott E. Schaus
- Department of Chemistry and Center for Molecular Discovery (BU-CMD), Boston University, Boston, Massachusetts, United States of America.,Correspondence: Scott E. Schaus,
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Meyenburg C, Dolfus U, Briem H, Rarey M. Galileo: Three-dimensional searching in large combinatorial fragment spaces on the example of pharmacophores. J Comput Aided Mol Des 2023; 37:1-16. [PMID: 36418668 PMCID: PMC10032335 DOI: 10.1007/s10822-022-00485-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 10/17/2022] [Indexed: 11/25/2022]
Abstract
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.
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Affiliation(s)
- Christian Meyenburg
- Universität Hamburg, ZBH - Center for Bioinformatics, Universität Hamburg, Bundesstraße 43, 20146, Hamburg, Germany
| | - Uschi Dolfus
- Universität Hamburg, ZBH - Center for Bioinformatics, Universität Hamburg, Bundesstraße 43, 20146, Hamburg, Germany
| | - Hans Briem
- Research & Development, Pharmaceuticals, Computational Molecular Design Berlin, Bayer AG, Building S110, 711, 13342, Berlin, Germany
| | - Matthias Rarey
- Universität Hamburg, ZBH - Center for Bioinformatics, Universität Hamburg, Bundesstraße 43, 20146, Hamburg, Germany.
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Penner P, Martiny V, Gohier A, Gastreich M, Ducrot P, Brown D, Rarey M. Shape-Based Descriptors for Efficient Structure-Based Fragment Growing. J Chem Inf Model 2020; 60:6269-6281. [PMID: 33196169 DOI: 10.1021/acs.jcim.0c00920] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
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.
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Affiliation(s)
- Patrick Penner
- ZBH-Center for Bioinformatics, Universität Hamburg, Bundesstr. 43, 20146 Hamburg, Germany
| | - Virginie Martiny
- Institut Recherches de Servier, 125 Chemin de Ronde, 78290 Croissy, France
| | - Arnaud Gohier
- Institut Recherches de Servier, 125 Chemin de Ronde, 78290 Croissy, France
| | - Marcus Gastreich
- BioSolveIT GmbH, An der Ziegelei 79, 53757 Sankt Augustin, Germany
| | - Pierre Ducrot
- Institut Recherches de Servier, 125 Chemin de Ronde, 78290 Croissy, France
| | - David Brown
- Institut Recherches de Servier, 125 Chemin de Ronde, 78290 Croissy, France
| | - Matthias Rarey
- ZBH-Center for Bioinformatics, Universität Hamburg, Bundesstr. 43, 20146 Hamburg, Germany
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