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Nandi S, Bhaduri S, Das D, Ghosh P, Mandal M, Mitra P. Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence. Mol Pharm 2024; 21:1563-1590. [PMID: 38466810 DOI: 10.1021/acs.molpharmaceut.3c01161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.
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Affiliation(s)
- Suvendu Nandi
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Soumyadeep Bhaduri
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Debraj Das
- Centre for Computational and Data Sciences, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Priya Ghosh
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Mahitosh Mandal
- School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Pralay Mitra
- Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
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2
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Jokinen EM, Niemeläinen M, Kurkinen ST, Lehtonen JV, Lätti S, Postila PA, Pentikäinen OT, Niinivehmas SP. Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators. Molecules 2023; 28:molecules28083420. [PMID: 37110655 PMCID: PMC10145393 DOI: 10.3390/molecules28083420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 04/29/2023] Open
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%.
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Affiliation(s)
- Elmeri M Jokinen
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Miika Niemeläinen
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
| | - Sami T Kurkinen
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Jukka V Lehtonen
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, FI-20500 Turku, Finland
- InFLAMES Research Flagship Center, Åbo Akademi University, FI-20500 Turku, Finland
| | - Sakari Lätti
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Pekka A Postila
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Olli T Pentikäinen
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Sanna P Niinivehmas
- MedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
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Kurkinen ST, Lehtonen JV, Pentikäinen OT, Postila PA. Optimization of Cavity-Based Negative Images to Boost Docking Enrichment in Virtual Screening. J Chem Inf Model 2022; 62:1100-1112. [PMID: 35133138 PMCID: PMC8889583 DOI: 10.1021/acs.jcim.1c01145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
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.
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Affiliation(s)
- Sami T Kurkinen
- Institute of Biomedicine, Integrative Physiology and Pharmacy, University of Turku, FI-20014 Turku, Finland.,Aurlide Ltd., FI-21420 Lieto, Finland.,InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Jukka V Lehtonen
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, FI-20500 Turku, Finland.,InFLAMES Research Flagship Center, Åbo Akademi University, FI-20500 Turku, Finland
| | - Olli T Pentikäinen
- Institute of Biomedicine, Integrative Physiology and Pharmacy, University of Turku, FI-20014 Turku, Finland.,Aurlide Ltd., FI-21420 Lieto, Finland.,InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
| | - Pekka A Postila
- Institute of Biomedicine, Integrative Physiology and Pharmacy, University of Turku, FI-20014 Turku, Finland.,Aurlide Ltd., FI-21420 Lieto, Finland.,InFLAMES Research Flagship Center, University of Turku, FI-20014 Turku, Finland
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Pentikäinen OT, Postila PA. Negative Image-Based Rescoring: Using Cavity Information to Improve Docking Screening. Methods Mol Biol 2021; 2266:141-154. [PMID: 33759125 DOI: 10.1007/978-1-0716-1209-5_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Molecular docking produces often lackluster results in real-life virtual screening assays that aim to discover novel drug candidates or hit compounds. The problem lies in the inability of the default docking scoring to properly estimate the Gibbs free energy of binding, which impairs the recognition of the best binding poses and the separation of active ligands from inactive compounds. Negative image-based rescoring (R-NiB) provides both effective and efficient way for re-ranking the outputted flexible docking poses to improve the virtual screening yield. Importantly, R-NiB has been shown to work with multiple genuine drug targets and six popular docking algorithms using demanding benchmark test sets. The effectiveness of the R-NiB methodology relies on the shape/electrostatics similarity between the target protein's ligand-binding cavity and the docked ligand poses. In this chapter, the R-NiB method is described with practical usability in mind.
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Affiliation(s)
- Olli T Pentikäinen
- Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
- Aurlide Ltd., Turku, Finland
| | - Pekka A Postila
- Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, Turku, Finland.
- Aurlide Ltd., Turku, Finland.
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Negative Image-Based Screening: Rigid Docking Using Cavity Information. Methods Mol Biol 2021; 2266:125-140. [PMID: 33759124 DOI: 10.1007/978-1-0716-1209-5_7] [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: 01/31/2023]
Abstract
Rational drug discovery relies heavily on molecular docking-based virtual screening, which samples flexibly the ligand binding poses against the target protein's structure. The upside of flexible docking is that the geometries of the generated docking poses are adjusted to match the residue alignment inside the target protein's ligand-binding pocket. The downside is that the flexible docking requires plenty of computing resources and, regardless, acquiring a decent level of enrichment typically demands further rescoring or post-processing. Negative image-based screening is a rigid docking technique that is ultrafast and computationally light but also effective as proven by vast benchmarking and screening experiments. In the NIB screening, the target protein cavity's shape/electrostatics is aligned and compared against ab initio-generated ligand 3D conformers. In this chapter, the NIB methodology is explained at the practical level and both its weaknesses and strengths are discussed candidly.
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A Perspective: Active Role of Lipids in Neurotransmitter Dynamics. Mol Neurobiol 2019; 57:910-925. [PMID: 31595461 PMCID: PMC7031182 DOI: 10.1007/s12035-019-01775-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 09/01/2019] [Indexed: 12/30/2022]
Abstract
Synaptic neurotransmission is generally considered as a function of membrane-embedded receptors and ion channels in response to the neurotransmitter (NT) release and binding. This perspective aims to widen the protein-centric view by including another vital component—the synaptic membrane—in the discussion. A vast set of atomistic molecular dynamics simulations and biophysical experiments indicate that NTs are divided into membrane-binding and membrane-nonbinding categories. The binary choice takes place at the water-membrane interface and follows closely the positioning of the receptors’ binding sites in relation to the membrane. Accordingly, when a lipophilic NT is on route to a membrane-buried binding site, it adheres on the membrane and, then, travels along its plane towards the receptor. In contrast, lipophobic NTs, which are destined to bind into receptors with extracellular binding sites, prefer the water phase. This membrane-based sorting splits the neurotransmission into membrane-independent and membrane-dependent mechanisms and should make the NT binding into the receptors more efficient than random diffusion would allow. The potential implications and notable exceptions to the mechanisms are discussed here. Importantly, maintaining specific membrane lipid compositions (MLCs) at the synapses, especially regarding anionic lipids, affect the level of NT-membrane association. These effects provide a plausible link between the MLC imbalances and neurological diseases such as depression or Parkinson’s disease. Moreover, the membrane plays a vital role in other phases of the NT life cycle, including storage and release from the synaptic vesicles, transport from the synaptic cleft, as well as their synthesis and degradation.
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7
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Kurkinen ST, Lätti S, Pentikäinen OT, Postila PA. Getting Docking into Shape Using Negative Image-Based Rescoring. J Chem Inf Model 2019; 59:3584-3599. [PMID: 31290660 PMCID: PMC6750746 DOI: 10.1021/acs.jcim.9b00383] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the molecular docking algorithms used in structure-based drug discovery. To remedy this problem, elaborate rescoring and postprocessing schemes have been developed with a varying degree of success, specificity, and cost. The negative image-based rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets. The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein's ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is directly used in the similarity comparison to rank the explicit docking poses. Here, the PANTHER/ShaEP-based R-NiB methodology is tested with six popular docking softwares, including GLIDE, PLANTS, GOLD, DOCK, AUTODOCK, and AUTODOCK VINA, using five validated benchmark sets. Overall, the results indicate that R-NiB outperforms the default docking scoring consistently and inexpensively, demonstrating that the methodology is ready for wide-scale virtual screening usage.
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Affiliation(s)
- Sami T Kurkinen
- Institute of Biomedicine, Kiinamyllynkatu 10, Integrative Physiology and Pharmacy , University of Turku , FI-20520 Turku , Finland
| | - Sakari Lätti
- Institute of Biomedicine, Kiinamyllynkatu 10, Integrative Physiology and Pharmacy , University of Turku , FI-20520 Turku , Finland
| | - Olli T Pentikäinen
- Institute of Biomedicine, Kiinamyllynkatu 10, Integrative Physiology and Pharmacy , University of Turku , FI-20520 Turku , Finland.,Aurlide Ltd. , FI-21420 Lieto , Finland
| | - Pekka A Postila
- Department of Biological and Environmental Science , University of Jyvaskyla , P.O. Box 35, FI-40014 Jyvaskyla , Finland
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8
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Jokinen EM, Postila PA, Ahinko M, Niinivehmas S, Pentikäinen OT. Fragment- and negative image-based screening of phosphodiesterase 10A inhibitors. Chem Biol Drug Des 2019; 94:1799-1812. [PMID: 31260165 DOI: 10.1111/cbdd.13584] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 06/12/2019] [Accepted: 06/24/2019] [Indexed: 12/19/2022]
Abstract
A novel virtual screening methodology called fragment- and negative image-based (F-NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A-specific small-molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F-NiB combines features from both fragment-based drug discovery and negative image-based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein-bound ligand(s) are seamlessly combined with the negative image of the target's ligand-binding cavity. This cavity- and fragment-based hybrid model, namely its shape and electrostatics, is used directly in the rigid docking of ab initio generated ligand 3D conformers. In total, 14 compounds were acquired using the F-NiB methodology, 3D quantitative structure-activity relationship modeling, and pharmacophore modeling. Three of the small molecules inhibited PDE10A at ~27 to ~67 μM range in a radiometric assay. In a larger context, the study shows that the F-NiB provides a flexible way to incorporate small-molecule fragments into the drug discovery.
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Affiliation(s)
| | - Pekka A Postila
- Department of Biological and Environmental Science, University of Jyvaskyla, Jyvaskyla, Finland
| | - Mira Ahinko
- Department of Biological and Environmental Science, University of Jyvaskyla, Jyvaskyla, Finland
| | | | - Olli T Pentikäinen
- Institute of Biomedicine, University of Turku, Turku, Finland.,Department of Biological and Environmental Science, University of Jyvaskyla, Jyvaskyla, Finland.,Aurlide Ltd., Lieto, Finland
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9
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A Practical Perspective: The Effect of Ligand Conformers on the Negative Image-Based Screening. Int J Mol Sci 2019; 20:ijms20112779. [PMID: 31174295 PMCID: PMC6600450 DOI: 10.3390/ijms20112779] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 06/03/2019] [Accepted: 06/04/2019] [Indexed: 12/05/2022] Open
Abstract
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.
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Ahinko M, Niinivehmas S, Jokinen E, Pentikäinen OT. Suitability ofMMGBSAfor the selection of correct ligand binding modes from docking results. Chem Biol Drug Des 2018; 93:522-538. [DOI: 10.1111/cbdd.13446] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 11/01/2018] [Accepted: 11/11/2018] [Indexed: 01/21/2023]
Affiliation(s)
- Mira Ahinko
- Department of Biological and Environmental Science & Nanoscience CenterUniversity of Jyvaskyla, MedChem.fi Jyvaskyla Finland
| | - Sanna Niinivehmas
- Department of Biological and Environmental Science & Nanoscience CenterUniversity of Jyvaskyla, MedChem.fi Jyvaskyla Finland
- Institute of Biomedicine, Integrative Physiology and PharmacologyUniversity of Turku, MedChem.fi Turku Finland
| | - Elmeri Jokinen
- Institute of Biomedicine, Integrative Physiology and PharmacologyUniversity of Turku, MedChem.fi Turku Finland
| | - Olli T. Pentikäinen
- Department of Biological and Environmental Science & Nanoscience CenterUniversity of Jyvaskyla, MedChem.fi Jyvaskyla Finland
- Institute of Biomedicine, Integrative Physiology and PharmacologyUniversity of Turku, MedChem.fi Turku Finland
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Rauhamäki S, Postila PA, Lätti S, Niinivehmas S, Multamäki E, Liedl KR, Pentikäinen OT. Discovery of Retinoic Acid-Related Orphan Receptor γt Inverse Agonists via Docking and Negative Image-Based Screening. ACS OMEGA 2018; 3:6259-6266. [PMID: 30023945 PMCID: PMC6044741 DOI: 10.1021/acsomega.8b00603] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 05/31/2018] [Indexed: 05/14/2023]
Abstract
Retinoic acid-related orphan receptor γt (RORγt) has a vital role in the differentiation of T-helper 17 (TH17) cells. Potent and specific RORγt inverse agonists are sought for treating TH17-related diseases such as psoriasis, rheumatoid arthritis, and type 1 diabetes. Here, the aim was to discover novel RORγt ligands using both standard molecular docking and negative image-based screening. Interestingly, both of these in silico techniques put forward mostly the same compounds for experimental testing. In total, 11 of the 34 molecules purchased for testing were verified as RORγt inverse agonists, thus making the effective hit rate 32%. The pIC50 values for the compounds varied from 4.9 (11 μM) to 6.2 (590 nM). Importantly, the fact that the verified hits represent four different cores highlights the structural diversity of the RORγt inverse agonism and the ability of the applied screening methodologies to facilitate much-desired scaffold hopping for drug design.
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Affiliation(s)
- Sanna Rauhamäki
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
| | - Pekka A. Postila
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
| | - Sakari Lätti
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
- Institute
of Biomedicine, Integrative Physiology and Pharmacology, Kiinamyllynkatu 10 C6, University of Turku, FI-20520 Turku, Finland
| | - Sanna Niinivehmas
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
- Institute
of Biomedicine, Integrative Physiology and Pharmacology, Kiinamyllynkatu 10 C6, University of Turku, FI-20520 Turku, Finland
| | - Elina Multamäki
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
| | - Klaus R. Liedl
- Institute
of General, Inorganic and Theoretical Chemistry, Centre for Chemistry
and Biomedicine, University of Innsbruck, Innrain 82, A-6020 Innsbruck, Austria
| | - Olli T. Pentikäinen
- Department
of Biological and Environmental Science & Nanoscience Center, University of Jyväskylä, P.O. Box 35, Jyväskylä FI-40014 University of Jyvaskyla, Finland
- Institute
of Biomedicine, Integrative Physiology and Pharmacology, Kiinamyllynkatu 10 C6, University of Turku, FI-20520 Turku, Finland
- Institute
of General, Inorganic and Theoretical Chemistry, Centre for Chemistry
and Biomedicine, University of Innsbruck, Innrain 82, A-6020 Innsbruck, Austria
- E-mail: (O.T.P.)
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12
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Niinivehmas S, Postila PA, Rauhamäki S, Manivannan E, Kortet S, Ahinko M, Huuskonen P, Nyberg N, Koskimies P, Lätti S, Multamäki E, Juvonen RO, Raunio H, Pasanen M, Huuskonen J, Pentikäinen OT. Blocking oestradiol synthesis pathways with potent and selective coumarin derivatives. J Enzyme Inhib Med Chem 2018; 33:743-754. [PMID: 29620427 PMCID: PMC6010071 DOI: 10.1080/14756366.2018.1452919] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
A comprehensive set of 3-phenylcoumarin analogues with polar substituents was synthesised for blocking oestradiol synthesis by 17-β-hydroxysteroid dehydrogenase 1 (HSD1) in the latter part of the sulphatase pathway. Five analogues produced ≥62% HSD1 inhibition at 5 µM and, furthermore, three of them produced ≥68% inhibition at 1 µM. A docking-based structure-activity relationship analysis was done to determine the molecular basis of the inhibition and the cross-reactivity of the analogues was tested against oestrogen receptor, aromatase, cytochrome P450 1A2, and monoamine oxidases. Most of the analogues are only modestly active with 17-β-hydroxysteroid dehydrogenase 2 – a requirement for lowering effective oestradiol levels in vivo. Moreover, the analysis led to the synthesis and discovery of 3-imidazolecoumarin as a potent aromatase inhibitor. In short, coumarin core can be tailored with specific ring and polar moiety substitutions to block either the sulphatase pathway or the aromatase pathway for treating breast cancer and endometriosis.
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Affiliation(s)
- Sanna Niinivehmas
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Pekka A Postila
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Sanna Rauhamäki
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Elangovan Manivannan
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland.,b School of Pharmacy , Devi Ahilya University , Indore , India
| | - Sami Kortet
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland.,c Department of Chemistry and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Mira Ahinko
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Pasi Huuskonen
- d School of Pharmacy , University of Eastern Finland , Kuopio , Finland
| | - Niina Nyberg
- d School of Pharmacy , University of Eastern Finland , Kuopio , Finland
| | | | - Sakari Lätti
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Elina Multamäki
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Risto O Juvonen
- d School of Pharmacy , University of Eastern Finland , Kuopio , Finland
| | - Hannu Raunio
- d School of Pharmacy , University of Eastern Finland , Kuopio , Finland
| | - Markku Pasanen
- d School of Pharmacy , University of Eastern Finland , Kuopio , Finland
| | - Juhani Huuskonen
- c Department of Chemistry and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland
| | - Olli T Pentikäinen
- a Department of Biological and Environmental Science and Nanoscience Center , University of Jyvaskyla , Jyvaskyla , Finland.,f Institute of Biomedicine, University of Turku , Turku , Finland
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13
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Kurkinen ST, Niinivehmas S, Ahinko M, Lätti S, Pentikäinen OT, Postila PA. Improving Docking Performance Using Negative Image-Based Rescoring. Front Pharmacol 2018; 9:260. [PMID: 29632488 PMCID: PMC5879118 DOI: 10.3389/fphar.2018.00260] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 03/08/2018] [Indexed: 12/05/2022] Open
Abstract
Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.
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Affiliation(s)
- Sami T Kurkinen
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland
| | - Sanna Niinivehmas
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland
| | - Mira Ahinko
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland
| | - Sakari Lätti
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland
| | - Olli T Pentikäinen
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland.,Institute of Biomedicine, Integrative Physiology and Pharmacy, University of Turku, Turku, Finland
| | - Pekka A Postila
- Department of Biological and Environmental Science and Nanoscience Center, University of Jyvaskyla, Jyväskylä, Finland
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14
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Niinivehmas SP, Manivannan E, Rauhamäki S, Huuskonen J, Pentikäinen OT. Identification of estrogen receptor α ligands with virtual screening techniques. J Mol Graph Model 2016; 64:30-39. [PMID: 26774287 DOI: 10.1016/j.jmgm.2015.12.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Revised: 12/22/2015] [Accepted: 12/29/2015] [Indexed: 11/16/2022]
Abstract
Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5.
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Affiliation(s)
- Sanna P Niinivehmas
- Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland
| | - Elangovan Manivannan
- Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland; School of Pharmacy, Devi Ahilya University, Indore 452001, Madhya Pradesh, India
| | - Sanna Rauhamäki
- Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland
| | - Juhani Huuskonen
- Department of Chemistry & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland
| | - Olli T Pentikäinen
- Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014, Finland.
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15
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Virtanen SI, Niinivehmas SP, Pentikäinen OT. Case-specific performance of MM-PBSA, MM-GBSA, and SIE in virtual screening. J Mol Graph Model 2015; 62:303-318. [DOI: 10.1016/j.jmgm.2015.10.012] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Revised: 10/23/2015] [Accepted: 10/26/2015] [Indexed: 01/24/2023]
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16
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Ultrafast protein structure-based virtual screening with Panther. J Comput Aided Mol Des 2015; 29:989-1006. [PMID: 26407559 DOI: 10.1007/s10822-015-9870-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 09/19/2015] [Indexed: 12/31/2022]
Abstract
Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.
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17
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Craig IR, Pfleger C, Gohlke H, Essex JW, Spiegel K. Pocket-space maps to identify novel binding-site conformations in proteins. J Chem Inf Model 2011; 51:2666-79. [PMID: 21910474 DOI: 10.1021/ci200168b] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The identification of novel binding-site conformations can greatly assist the progress of structure-based ligand design projects. Diverse pocket shapes drive medicinal chemistry to explore a broader chemical space and thus present additional opportunities to overcome key drug discovery issues such as potency, selectivity, toxicity, and pharmacokinetics. We report a new automated approach to diverse pocket selection, PocketAnalyzer(PCA), which applies principal component analysis and clustering to the output of a grid-based pocket detection algorithm. Since the approach works directly with pocket shape descriptors, it is free from some of the problems hampering methods that are based on proxy shape descriptors, e.g. a set of atomic positional coordinates. The approach is technically straightforward and allows simultaneous analysis of mutants, isoforms, and protein structures derived from multiple sources with different residue numbering schemes. The PocketAnalyzer(PCA) approach is illustrated by the compilation of diverse sets of pocket shapes for aldose reductase and viral neuraminidase. In both cases this allows identification of novel computationally derived binding-site conformations that are yet to be observed crystallographically. Indeed, known inhibitors capable of exploiting these novel binding-site conformations are subsequently identified, thereby demonstrating the utility of PocketAnalyzer(PCA) for rationalizing and improving the understanding of the molecular basis of protein-ligand interaction and bioactivity. A Python program implementing the PocketAnalyzer(PCA) approach is available for download under an open-source license ( http://sourceforge.net/projects/papca/ or http://cpclab.uni-duesseldorf.de/downloads ).
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Affiliation(s)
- Ian R Craig
- Novartis Institutes for Biomedical Research, Wimblehurst Road, Horsham, West Sussex RH12 5AB, UK.
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18
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Niinivehmas SP, Virtanen SI, Lehtonen JV, Postila PA, Pentikäinen OT. Comparison of virtual high-throughput screening methods for the identification of phosphodiesterase-5 inhibitors. J Chem Inf Model 2011; 51:1353-63. [PMID: 21591817 DOI: 10.1021/ci1004527] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Reliable and effective virtual high-throughput screening (vHTS) methods are desperately needed to minimize the expenses involved in drug discovery projects. Here, we present an improvement to the negative image-based (NIB) screening: the shape, the electrostatics, and the solvation state of the target protein's ligand-binding site are included into the vHTS. Additionally, the initial vHTS results are postprocessed with molecular mechanics/generalized Born surface area (MMGBSA) calculations to estimate the favorability of ligand-protein interactions. The results show that docking produces very good early enrichment for phosphodiesterase-5 (PDE-5); however, in general, the NIB and the ligand-based screening performed better with or without the added electrostatics. Furthermore, the postprocessing of the NIB screening results using MMGBSA calculations improved the early enrichment for the PDE-5 considerably, thus, making hit discovery affordable.
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Affiliation(s)
- Sanna P Niinivehmas
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland
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