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Cornelissen F, Markert G, Deutsch G, Antonara M, Faaij N, Bartelink I, Noske D, Vandertop WP, Bender A, Westerman BA. Explaining Blood-Brain Barrier Permeability of Small Molecules by Integrated Analysis of Different Transport Mechanisms. J Med Chem 2023; 66:7253-7267. [PMID: 37217193 PMCID: PMC10259449 DOI: 10.1021/acs.jmedchem.2c01824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Indexed: 05/24/2023]
Abstract
The blood-brain barrier (BBB) represents a major obstacle to delivering drugs to the central nervous system (CNS), resulting in the lack of effective treatment for many CNS diseases including brain cancer. To accelerate CNS drug development, computational prediction models could save the time and effort needed for experimental evaluation. Here, we studied BBB permeability focusing on active transport (influx and efflux) as well as passive diffusion using previously published and self-curated data sets. We created prediction models based on physicochemical properties, molecular substructures, or their combination to understand which mechanisms contribute to BBB permeability. Our results show that features that predicted passive diffusion over membranes overlap with features that explain endothelial permeation of approved CNS-active drugs. We also identified physical properties and molecular substructures that positively or negatively predicted BBB transport. These findings provide guidance toward identifying BBB-permeable compounds by optimally matching physicochemical and molecular properties to BBB transport mechanisms.
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Affiliation(s)
- Fleur
M.G. Cornelissen
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
| | - Greta Markert
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K.
| | - Ghislaine Deutsch
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K.
| | - Maria Antonara
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K.
| | - Noa Faaij
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
| | - Imke Bartelink
- Department
of Pharmacy, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
| | - David Noske
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
| | - W. Peter Vandertop
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
| | - Andreas Bender
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K.
| | - Bart A. Westerman
- Department
of Neurosurgery, Amsterdam UMC, location VUMC, Cancer Center, Amsterdam 1105, AZ, the Netherlands
- Window
Consortium (www.window-consortium.org)
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Molecular Properties of Drugs Handled by Kidney OATs and Liver OATPs Revealed by Chemoinformatics and Machine Learning: Implications for Kidney and Liver Disease. Pharmaceutics 2021; 13:pharmaceutics13101720. [PMID: 34684013 PMCID: PMC8538396 DOI: 10.3390/pharmaceutics13101720] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 12/31/2022] Open
Abstract
In patients with liver or kidney disease, it is especially important to consider the routes of metabolism and elimination of small-molecule pharmaceuticals. Once in the blood, numerous drugs are taken up by the liver for metabolism and/or biliary elimination, or by the kidney for renal elimination. Many common drugs are organic anions. The major liver uptake transporters for organic anion drugs are organic anion transporter polypeptides (OATP1B1 or SLCO1B1; OATP1B3 or SLCO1B3), whereas in the kidney they are organic anion transporters (OAT1 or SLC22A6; OAT3 or SLC22A8). Since these particular OATPs are overwhelmingly found in the liver but not the kidney, and these OATs are overwhelmingly found in the kidney but not liver, it is possible to use chemoinformatics, machine learning (ML) and deep learning to analyze liver OATP-transported drugs versus kidney OAT-transported drugs. Our analysis of >30 quantitative physicochemical properties of OATP- and OAT-interacting drugs revealed eight properties that in combination, indicate a high propensity for interaction with "liver" transporters versus "kidney" ones based on machine learning (e.g., random forest, k-nearest neighbors) and deep-learning classification algorithms. Liver OATPs preferred drugs with greater hydrophobicity, higher complexity, and more ringed structures whereas kidney OATs preferred more polar drugs with more carboxyl groups. The results provide a strong molecular basis for tissue-specific targeting strategies, understanding drug-drug interactions as well as drug-metabolite interactions, and suggest a strategy for how drugs with comparable efficacy might be chosen in chronic liver or kidney disease (CKD) to minimize toxicity.
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3
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Nigam AK, Li JG, Lall K, Shi D, Bush KT, Bhatnagar V, Abagyan R, Nigam SK. Unique metabolite preferences of the drug transporters OAT1 and OAT3 analyzed by machine learning. J Biol Chem 2020; 295:1829-1842. [PMID: 31896576 DOI: 10.1074/jbc.ra119.010729] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 12/30/2019] [Indexed: 01/04/2023] Open
Abstract
The multispecific organic anion transporters, OAT1 (SLC22A6) and OAT3 (SLC22A8), the main kidney elimination pathways for many common drugs, are often considered to have largely-redundant roles. However, whereas examination of metabolomics data from Oat-knockout mice (Oat1 and Oat3KO) revealed considerable overlap, over a hundred metabolites were increased in the plasma of one or the other of these knockout mice. Many of these relatively unique metabolites are components of distinct biochemical and signaling pathways, including those involving amino acids, lipids, bile acids, and uremic toxins. Cheminformatics, together with a "logical" statistical and machine learning-based approach, identified a number of molecular features distinguishing these unique endogenous substrates. Compared with OAT1, OAT3 tends to interact with more complex substrates possessing more rings and chiral centers. An independent "brute force" approach, analyzing all possible combinations of molecular features, supported the logical approach. Together, the results suggest the potential molecular basis by which OAT1 and OAT3 modulate distinct metabolic and signaling pathways in vivo As suggested by the Remote Sensing and Signaling Theory, the analysis provides a potential mechanism by which "multispecific" kidney proximal tubule transporters exert distinct physiological effects. Furthermore, a strong metabolite-based machine-learning classifier was able to successfully predict unique OAT1 versus OAT3 drugs; this suggests the feasibility of drug design based on knockout metabolomics of drug transporters. The approach can be applied to other SLC and ATP-binding cassette drug transporters to define their nonredundant physiological roles and for analyzing the potential impact of drug-metabolite interactions.
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Affiliation(s)
- Anisha K Nigam
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093-0693
| | - Julia G Li
- Department of Biology, University of California San Diego, La Jolla, California 92093-0693
| | - Kaustubh Lall
- Department of Computer Engineering, University of California San Diego, La Jolla, California 92093-0693
| | - Da Shi
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093-0693
| | - Kevin T Bush
- Department of Pediatrics, University of California San Diego, La Jolla, California 92093-0693
| | - Vibha Bhatnagar
- Department of Family and Preventative Medicine, University of California San Diego, La Jolla, California 92093-0693
| | - Ruben Abagyan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093-0693.
| | - Sanjay K Nigam
- Department of Pediatrics, University of California San Diego, La Jolla, California 92093-0693; Department of Medicine, University of California San Diego, La Jolla, California 92093-0693.
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4
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Wu H, Xu H, Marivingt-Mounir C, Bonnemain JL, Chollet JF. Vectorizing agrochemicals: enhancing bioavailability via carrier-mediated transport. PEST MANAGEMENT SCIENCE 2019; 75:1507-1516. [PMID: 30537141 DOI: 10.1002/ps.5298] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 11/14/2018] [Accepted: 11/30/2018] [Indexed: 05/02/2023]
Abstract
Systemicity of agrochemicals is an advantageous property for controlling phloem sucking insects, as well as pathogens and pests not accessible to contact products. After the penetration of the cuticle, the plasma membrane constitutes the main barrier to the entry of an agrochemical into the sap flow. The current strategy for developing systemic agrochemicals is to optimize the physicochemical properties of the molecules so that they can cross the plasma membrane by simple diffusion or ion trapping mechanisms. The main problem with current systemic compounds is that they move everywhere within the plant, and this non-controlled mobility results in the contamination of the plant parts consumed by vertebrates and pollinators. To achieve the site-targeted distribution of agrochemicals, a carrier-mediated propesticide strategy is proposed in this review. After conjugating a non-systemic agrochemical with a nutrient (α-amino acids or sugars), the resulting conjugate may be actively transported across the plasma membrane by nutrient-specific carriers. By applying this strategy, non-systemic active ingredients are expected to be delivered into the target organs of young plants, thus avoiding or minimizing subsequent undesirable redistribution. The development of this innovative strategy presents many challenges, but opens up a wide range of exciting possibilities. © 2018 Society of Chemical Industry.
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Affiliation(s)
- Hanxiang Wu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources and Key Laboratory of Natural Pesticide and Chemical Biology, Ministry of Education, South China Agricultural University, Guangzhou, China
| | - Hanhong Xu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources and Key Laboratory of Natural Pesticide and Chemical Biology, Ministry of Education, South China Agricultural University, Guangzhou, China
| | - Cécile Marivingt-Mounir
- Institut de Chimie des Milieux et des Matériaux de Poitiers (IC2MP), Unité Mixte de Recherche CNRS 7285, Université de Poitiers, Poitiers Cedex 9, France
| | - Jean-Louis Bonnemain
- Laboratoire Écologie et Biologie des Interactions, Unité Mixte de Recherche CNRS 7267, Université de Poitiers, Poitiers Cedex 9, France
| | - Jean-François Chollet
- Institut de Chimie des Milieux et des Matériaux de Poitiers (IC2MP), Unité Mixte de Recherche CNRS 7285, Université de Poitiers, Poitiers Cedex 9, France
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Domínguez-Avila JA, Wall-Medrano A, Velderrain-Rodríguez GR, Chen CYO, Salazar-López NJ, Robles-Sánchez M, González-Aguilar GA. Gastrointestinal interactions, absorption, splanchnic metabolism and pharmacokinetics of orally ingested phenolic compounds. Food Funct 2018; 8:15-38. [PMID: 28074953 DOI: 10.1039/c6fo01475e] [Citation(s) in RCA: 111] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The positive health effects of phenolic compounds (PCs) have been extensively reported in the literature. An understanding of their bioaccessibility and bioavailability is essential for the elucidation of their health benefits. Before reaching circulation and exerting bioactions in target tissues, numerous interactions take place before and during digestion with either the plant or host's macromolecules that directly impact the organism and modulate their own bioaccessibility and bioavailability. The present work is focused on the gastrointestinal (GI) interactions that are relevant to the absorption and metabolism of PCs and how these interactions impact their pharmacokinetic profiles. Non-digestible cell wall components (fiber) interact intimately with PCs and delay their absorption in the small intestine, instead carrying them to the large intestine. PCs not bound to fiber interact with digestible nutrients in the bolus where they interfere with the digestion and absorption of proteins, carbohydrates, lipids, cholesterol, bile salts and micronutrients through the inhibition of digestive enzymes and enterocyte transporters and the disruption of micelle formation. PCs internalized by enterocytes may reach circulation (through transcellular or paracellular transport), be effluxed back into the lumen (P-glycoprotein, P-gp) or be metabolized by phase I and phase II enzymes. Some PCs can inhibit P-gp or phase I/II enzymes, which can potentially lead to drug-nutrient interactions. The absorption and pharmacokinetic parameters are modified by all of the interactions within the digestive tract and by the presence of other PCs. Undesirable interactions have promoted the development of nanotechnological approaches to promote the bioaccessibility, bioavailability, and bioefficacy of PCs.
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Affiliation(s)
- J Abraham Domínguez-Avila
- Coordinación de Tecnología de Alimentos de Origen Vegetal, Centro de Investigación en Alimentación y Desarrollo, A.C. Carretera a la Victoria Km 0.6. C.P. 83304, Hermosillo, Sonora, Mexico.
| | - Abraham Wall-Medrano
- Departamento de Ciencias Químico-Biológicas, Instituto de Ciencias Biomédicas, Universidad Autónoma de Ciudad Juárez, Anillo Envolvente del Pronaf y Estocolmo s/n, CP 32310, Cd. Juárez, Chihuahua, Mexico.
| | - Gustavo R Velderrain-Rodríguez
- Coordinación de Tecnología de Alimentos de Origen Vegetal, Centro de Investigación en Alimentación y Desarrollo, A.C. Carretera a la Victoria Km 0.6. C.P. 83304, Hermosillo, Sonora, Mexico.
| | - C-Y Oliver Chen
- Antioxidants Research Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, 711 Washington Street, Boston, Massachusetts 02111, USA.
| | - Norma Julieta Salazar-López
- Departamento de Investigación y Posgrado en Alimentos, Universidad de Sonora, Blvd. Luis Encinas y Rosales S/N Col. Centro, C.P. 83000, Hermosillo, Sonora, Mexico.
| | - Maribel Robles-Sánchez
- Departamento de Investigación y Posgrado en Alimentos, Universidad de Sonora, Blvd. Luis Encinas y Rosales S/N Col. Centro, C.P. 83000, Hermosillo, Sonora, Mexico.
| | - Gustavo A González-Aguilar
- Coordinación de Tecnología de Alimentos de Origen Vegetal, Centro de Investigación en Alimentación y Desarrollo, A.C. Carretera a la Victoria Km 0.6. C.P. 83304, Hermosillo, Sonora, Mexico.
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Ozdemir-Kaynak E, Qutub AA, Yesil-Celiktas O. Advances in Glioblastoma Multiforme Treatment: New Models for Nanoparticle Therapy. Front Physiol 2018; 9:170. [PMID: 29615917 PMCID: PMC5868458 DOI: 10.3389/fphys.2018.00170] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 02/20/2018] [Indexed: 11/30/2022] Open
Abstract
The most lethal form of brain cancer, glioblastoma multiforme, is characterized by rapid growth and invasion facilitated by cell migration and degradation of the extracellular matrix. Despite technological advances in surgery and radio-chemotherapy, glioblastoma remains largely resistant to treatment. New approaches to study glioblastoma and to design optimized therapies are greatly needed. One such approach harnesses computational modeling to support the design and delivery of glioblastoma treatment. In this paper, we critically summarize current glioblastoma therapy, with a focus on emerging nanomedicine and therapies that capitalize on cell-specific signaling in glioblastoma. We follow this summary by discussing computational modeling approaches focused on optimizing these emerging nanotherapeutics for brain cancer. We conclude by illustrating how mathematical analysis can be used to compare the delivery of a high potential anticancer molecule, delphinidin, in both free and nanoparticle loaded forms across the blood-brain barrier for glioblastoma.
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Affiliation(s)
- Elif Ozdemir-Kaynak
- Department of Bioengineering, Faculty of Engineering, Ege University, Bornova-Izmir, Turkey
| | - Amina A Qutub
- Department of Bioengineering, Rice University, Houston, TX, United States
| | - Ozlem Yesil-Celiktas
- Department of Bioengineering, Faculty of Engineering, Ege University, Bornova-Izmir, Turkey.,Biomaterials Innovation Research Center, Division of Biomedical Engineering, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.,Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
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The benefits of in silico modeling to identify possible small-molecule drugs and their off-target interactions. Future Med Chem 2018; 10:423-432. [PMID: 29380627 DOI: 10.4155/fmc-2017-0151] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative platforms. The evolution of computational approaches is driven by the essential criteria that a drug molecule has to fulfill, from the affinity to targets to minimal side effects while having adequate absorption, distribution, metabolism, and excretion (ADME) properties. A combination of ligand- and structure-based drug development approaches is already used to obtain consensus predictions of small molecule activities and their off-target interactions. Further integration of these methods into easy-to-use workflows informed by systems biology could realize the full potential of available data in the drug discovery and reduce the attrition of drug candidates.
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Colas C, Masuda M, Sugio K, Miyauchi S, Hu Y, Smith DE, Schlessinger A. Chemical Modulation of the Human Oligopeptide Transporter 1, hPepT1. Mol Pharm 2017; 14:4685-4693. [PMID: 29111754 DOI: 10.1021/acs.molpharmaceut.7b00775] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In humans, peptides derived from dietary proteins and peptide-like drugs are transported via the proton-dependent oligopeptide transporter hPepT1 (SLC15A1). hPepT1 is located across the apical membranes of the small intestine and kidney, where it serves as a high-capacity low-affinity transporter of a broad range of di- and tripeptides. hPepT1 is also overexpressed in the colon of inflammatory bowel disease (IBD) patients, where it mediates the transport of harmful peptides of bacterial origin. Therefore, hPepT1 is a drug target for prodrug substrates interacting with intracellular proteins or inhibitors blocking the transport of toxic bacterial products. In this study, we construct multiple structural models of hPepT1 representing different conformational states that occur during transport and inhibition. We then identify and characterize five ligands of hPepT1 using computational methods, such as virtual screening and QM-polarized ligand docking (QPLD), and experimental testing with uptake kinetic measurements and electrophysiological assays. Our results improve our understanding of the substrate and inhibitor specificity of hPepT1. Furthermore, the newly discovered ligands exhibit unique chemotypes, providing a framework for developing tool compounds with optimal intestinal absorption as well as future IBD therapeutics against this emerging drug target.
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Affiliation(s)
- Claire Colas
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai , New York, New York 10029, United States
| | - Masayuki Masuda
- Faculty of Pharmaceutical Sciences, Toho University , Funabashi, Chiba 274-8510, Japan
| | - Kazuaki Sugio
- Faculty of Pharmaceutical Sciences, Toho University , Funabashi, Chiba 274-8510, Japan
| | - Seiji Miyauchi
- Faculty of Pharmaceutical Sciences, Toho University , Funabashi, Chiba 274-8510, Japan
| | - Yongjun Hu
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan , Ann Arbor, Michigan 48109, United States
| | - David E Smith
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan , Ann Arbor, Michigan 48109, United States
| | - Avner Schlessinger
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai , New York, New York 10029, United States
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Latek D. Rosetta Broker for membrane protein structure prediction: concentrative nucleoside transporter 3 and corticotropin-releasing factor receptor 1 test cases. BMC STRUCTURAL BIOLOGY 2017; 17:8. [PMID: 28774292 PMCID: PMC5543540 DOI: 10.1186/s12900-017-0078-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2017] [Accepted: 07/26/2017] [Indexed: 02/12/2023]
Abstract
Background Membrane proteins are difficult targets for structure prediction due to the limited structural data deposited in Protein Data Bank. Most computational methods for membrane protein structure prediction are based on the comparative modeling. There are only few de novo methods targeting that distinct protein family. In this work an example of such de novo method was used to structurally and functionally characterize two representatives of distinct membrane proteins families of solute carrier transporters and G protein-coupled receptors. The well-known Rosetta program and one of its protocols named Broker was used in two test cases. The first case was de novo structure prediction of three N-terminal transmembrane helices of the human concentrative nucleoside transporter 3 (hCNT3) homotrimer belonging to the solute carrier 28 family of transporters (SLC28). The second case concerned the large scale refinement of transmembrane helices of a homology model of the corticotropin-releasing factor receptor 1 (CRFR1) belonging to the G protein-coupled receptors family. Results The inward-facing model of the hCNT3 homotrimer was used to propose the functional impact of its single nucleotide polymorphisms. Additionally, the 100 ns molecular dynamics simulation of the unliganded hCNT3 model confirmed its validity and revealed mobility of the selected binding site and homotrimer interface residues. The large scale refinement of transmembrane helices of the CRFR1 homology model resulted in the significant improvement of its accuracy with respect to the crystal structure of CRFR1, especially in the binding site area. Consequently, the antagonist CP-376395 could be docked with Autodock VINA to the CRFR1 model without any steric clashes. Conclusions The presented work demonstrated that Rosetta Broker can be a versatile tool for solving various issues referring to protein biology. Two distinct examples of de novo membrane protein structure prediction presented here provided important insights into three major areas of protein biology. Namely, the dynamics of the inward-facing hCNT3 homotrimer system, the structural changes of the CRFR1 receptor upon the antagonist binding and finally, the role of single nucleotide polymorphisms in both, hCNT3 and CRFR1 proteins, were investigated. Electronic supplementary material The online version of this article (doi:10.1186/s12900-017-0078-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Dorota Latek
- Faculty of Chemistry, University of Warsaw, Pasteur St. 1, 02-093, Warsaw, Poland.
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10
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Molecular properties associated with transporter-mediated drug disposition. Adv Drug Deliv Rev 2017; 116:92-99. [PMID: 28554577 DOI: 10.1016/j.addr.2017.05.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 03/20/2017] [Accepted: 05/25/2017] [Indexed: 12/18/2022]
Abstract
Membrane transporters play a key role in the absorption, distribution, clearance, elimination, and transport of drugs. Understanding the drug properties and structure activity relationships (SAR) for affinity to membrane transporters is critical to optimize clearance and pharmacokinetics during drug design. To facilitate the early identification of clearance mechanism, a framework named the extended clearance classification system (ECCS) was recently introduced. Using in vitro and physicochemical properties that are readily available in early drug discovery, ECCS has been successfully applied to identify major clearance mechanism and to implicate the role of membrane transporters in determining pharmacokinetics. While the crystal structures for most of the drug transporters are currently not available, ligand-based modeling approaches that use information obtained from the structure and molecular properties of the ligands have been applied to associate the drug-related properties and transporter-mediated disposition. The approach allows prospective prediction of transporter both substrate and/or inhibitor affinity and build quantitative structure-activity relationship (QSAR) to enable early optimization of pharmacokinetics, tissue distribution and drug-drug interaction risk. Drug design applications can be further improved through uncovering transporter protein crystal structure and generation of quality data to refine and develop viable predictive models.
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11
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Shaikh N, Sharma M, Garg P. Selective Fusion of Heterogeneous Classifiers for Predicting Substrates of Membrane Transporters. J Chem Inf Model 2017; 57:594-607. [PMID: 28228010 DOI: 10.1021/acs.jcim.6b00508] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Membrane transporters play a crucial role in determining fate of administered drugs in a biological system. Early identification of plausible transporters for a drug molecule can provide insights into its therapeutic, pharmacokinetic, and toxicological profiles. In the present study, predictive models for classifying small molecules into substrates and nonsubstrates of various pharmaceutically important membrane transporters were developed using quantitative structure-activity relationship (QSAR) and proteochemometric (PCM) approaches. For this purpose, 4575 substrate interactions for these transporters were collected from the Metabolism and Transport Database (Metrabase) and the literature. The transporters selected for this study include (i) six efflux transporters, viz., breast cancer resistance protein (BCRP/ABCG2), P-glycoprotein (P-gp/MDR1), and multidrug resistance proteins (MRP1, MRP2, MRP3, and MRP4), and (ii) seven influx transporters, viz., organic cation transporter (OCT1/SO22A1), peptide transporter (PEPT1/SO15A1), apical sodium-bile acid transporter (ASBT/NTCP2), and organic anion transporting peptides (OATP1A2/SO1A2, OATP1B/SO1B1, OATP1B3/SO1B3, and OATP2B1/SO2B1). Various types of descriptors and machine learning methods (classifiers) were evaluated for the development of robust predictive models. Additionally, ensemble models were developed by bagging of homogeneous classifiers and selective fusion of heterogeneous classifiers. It was observed that the latter approach improves the accuracy of substrate/nonsubstrate prediction for transporters (average correct classification rate of more than 0.80 for external validation). Moreover, structural fragments important in determining the substrate specificity across the various transporters were identified. To demonstrate these fragments on the query molecule, contour maps were generated. The prediction efficacy of the developed models was illustrated by a good correlation between the reported logBB value of a molecule and its predicted substrate propensity for blood-brain barrier transporters. Conclusively, this comprehensive modeling analysis can be efficiently employed for the prediction of membrane transporters of a drug, thereby providing insights into its pharmacological profile.
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Affiliation(s)
- Naeem Shaikh
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER) , S. A. S. Nagar, Mohali, Punjab-160062, India
| | - Mahesh Sharma
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER) , S. A. S. Nagar, Mohali, Punjab-160062, India
| | - Prabha Garg
- Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER) , S. A. S. Nagar, Mohali, Punjab-160062, India
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12
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Liu HC, Goldenberg A, Chen Y, Lun C, Wu W, Bush KT, Balac N, Rodriguez P, Abagyan R, Nigam SK. Molecular Properties of Drugs Interacting with SLC22 Transporters OAT1, OAT3, OCT1, and OCT2: A Machine-Learning Approach. J Pharmacol Exp Ther 2016; 359:215-29. [PMID: 27488918 DOI: 10.1124/jpet.116.232660] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 07/20/2016] [Indexed: 11/22/2022] Open
Abstract
Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of machine-learning methods and wet laboratory testing of novel predictions. In addition to molecular charge, organic anion transporters (OATs) were found to prefer interacting with planar structures, whereas organic cation transporters (OCTs) interact with more three-dimensional structures (i.e., greater SP3 character). Moreover, compared with OAT1 ligands, OAT3 ligands possess more acyclic tetravalent bonds and have a more zwitterionic/cationic character. In contrast, OCT1 and OCT2 ligands were not clearly distinquishable form one another by the methods employed. Multiple pharmacophore models were generated on the basis of the drugs and, consistent with the machine-learning analyses, one unique pharmacophore created from ligands of OAT3 possessed cationic properties similar to OCT ligands; this was confirmed by quantitative atomic property field analysis. Virtual screening with this pharmacophore, followed by transport assays, identified several cationic drugs that selectively interact with OAT3 but not OAT1. Although the present analysis may be somewhat limited by the need to rely largely on inhibition data for modeling, wet laboratory/in vitro transport studies, as well as analysis of drug/metabolite handling in Oat and Oct knockout animals, support the general validity of the approach-which can also be applied to other SLC and ATP binding cassette drug transporters. This may make it possible to predict the molecular properties of a drug or metabolite necessary for interaction with the transporter(s), thereby enabling better prediction of drug-drug interactions and drug-metabolite interactions. Furthermore, understanding the overlapping specificities of OATs and OCTs in the context of dynamic transporter tissue expression patterns should help predict net flux in a particular tissue of anionic, cationic, and zwitterionic molecules in normal and pathophysiological states.
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Affiliation(s)
- Henry C Liu
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Anne Goldenberg
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Yuchen Chen
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Christina Lun
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Wei Wu
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Kevin T Bush
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Natasha Balac
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Paul Rodriguez
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Ruben Abagyan
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
| | - Sanjay K Nigam
- Departments of Bioengineering (H.C.L.), Pediatrics (A.G., Y.C., C.L., K.T.B., S.K.N.), Medicine (W.W., S.K.N.), Cellular and Molecular Medicine (S.K.N.), and Pharmacology (R.A.), and the San Diego Supercomputer Center (N.B., P.R.), University of California San Diego, La Jolla, California
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Pamanji R, Yashwanth B, Venkateswara Rao J. Profenofos induced biochemical alterations and in silico modelling of hatching enzyme, ZHE1 in zebrafish (Danio rerio) embryos. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2016; 45:123-131. [PMID: 27295611 DOI: 10.1016/j.etap.2016.05.027] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 05/24/2016] [Accepted: 05/29/2016] [Indexed: 06/06/2023]
Abstract
The current study was aimed to investigate the oxidative stress response in zebrafish embryos exposed to sub-lethal (LC10) and lethal (LC50) concentrations of profenofos for 96-h and in silico modelling of zebrafish hatching enzyme, ZHE1 to explain the delayed hatching. Embryos exposed to profenofos under semi-static conditions significantly diminished glutathione (GSH), superoxide dismutase (SOD) and glutathione reductase (GR) levels, but increased the activities of catalase (CAT) and glutathione S-transferase (GST) concomitantly with marked elevation in malondialdehyde (MDA) content in whole-body homogenate of the treated groups compared with control. In addition, stress protein Hsp70 expression and DNA damage were significantly increased in a concentration- dependent manner compared with controls. From the computational docking studies of ZHE1 with profenofos revealed that profenofos is binding to three amino acids, histidine 99, histidine 109 and arginine 182 at the active site of the enzyme through hydrogen bonding which may lead to inhibition of hatching.
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Affiliation(s)
- Rajesh Pamanji
- Biology Division, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
| | - Bomma Yashwanth
- Biology Division, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
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14
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Bergström CAS, Charman WN, Porter CJH. Computational prediction of formulation strategies for beyond-rule-of-5 compounds. Adv Drug Deliv Rev 2016; 101:6-21. [PMID: 26928657 DOI: 10.1016/j.addr.2016.02.005] [Citation(s) in RCA: 106] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 02/11/2016] [Accepted: 02/17/2016] [Indexed: 12/12/2022]
Abstract
The physicochemical properties of some contemporary drug candidates are moving towards higher molecular weight, and coincidentally also higher lipophilicity in the quest for biological selectivity and specificity. These physicochemical properties move the compounds towards beyond rule-of-5 (B-r-o-5) chemical space and often result in lower water solubility. For such B-r-o-5 compounds non-traditional delivery strategies (i.e. those other than conventional tablet and capsule formulations) typically are required to achieve adequate exposure after oral administration. In this review, we present the current status of computational tools for prediction of intestinal drug absorption, models for prediction of the most suitable formulation strategies for B-r-o-5 compounds and models to obtain an enhanced understanding of the interplay between drug, formulation and physiological environment. In silico models are able to identify the likely molecular basis for low solubility in physiologically relevant fluids such as gastric and intestinal fluids. With this baseline information, a formulation scientist can, at an early stage, evaluate different orally administered, enabling formulation strategies. Recent computational models have emerged that predict glass-forming ability and crystallisation tendency and therefore the potential utility of amorphous solid dispersion formulations. Further, computational models of loading capacity in lipids, and therefore the potential for formulation as a lipid-based formulation, are now available. Whilst such tools are useful for rapid identification of suitable formulation strategies, they do not reveal drug localisation and molecular interaction patterns between drug and excipients. For the latter, Molecular Dynamics simulations provide an insight into the interplay between drug, formulation and intestinal fluid. These different computational approaches are reviewed. Additionally, we analyse the molecular requirements of different targets, since these can provide an early signal that enabling formulation strategies will be required. Based on the analysis we conclude that computational biopharmaceutical profiling can be used to identify where non-conventional gateways, such as prediction of 'formulate-ability' during lead optimisation and early development stages, are important and may ultimately increase the number of orally tractable contemporary targets.
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Affiliation(s)
- Christel A S Bergström
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, Victoria 3052, Australia; Department of Pharmacy, Uppsala University, Uppsala Biomedical Center, P.O. Box 580, SE-751 23 Uppsala, Sweden.
| | - William N Charman
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, Victoria 3052, Australia
| | - Christopher J H Porter
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, Victoria 3052, Australia; ARC Centre of Excellence in Convergent Nano-Bio Science and Technology, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, Victoria 3052, Australia
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15
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Mendes P, Oliver SG, Kell DB. Response to ‘The Need for Speed’, by Matsson et al . Trends Pharmacol Sci 2016; 37:245-246. [DOI: 10.1016/j.tips.2016.02.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 02/02/2016] [Indexed: 12/22/2022]
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