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Barnowsky T, Curtarolo S, Krasheninnikov AV, Heine T, Friedrich R. Magnetic State Control of Non-van der Waals 2D Materials by Hydrogenation. Nano Lett 2024; 24:3874-3881. [PMID: 38446590 PMCID: PMC10996018 DOI: 10.1021/acs.nanolett.3c04777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 02/15/2024] [Accepted: 02/15/2024] [Indexed: 03/08/2024]
Abstract
Controlling the magnetic state of two-dimensional (2D) materials is crucial for spintronics. By employing data-mining and autonomous density functional theory calculations, we demonstrate the switching of magnetic properties of 2D non-van der Waals materials upon hydrogen passivation. The magnetic configurations are tuned to states with flipped and enhanced moments. For 2D CdTiO3─a diamagnetic compound in the pristine case─we observe an onset of ferromagnetism upon hydrogenation. Further investigation of the magnetization density of the pristine and passivated systems provides a detailed analysis of modified local spin symmetries and the emergence of ferromagnetism. Our results indicate that selective surface passivation is a powerful tool for tailoring magnetic properties of nanomaterials, such as non-vdW 2D compounds.
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Affiliation(s)
- Tom Barnowsky
- Theoretical
Chemistry, Technische Universität
Dresden, Dresden 01062, Germany
- Institute
of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany
| | - Stefano Curtarolo
- Center
for Extreme Materials, Duke University, Durham, North Carolina 27708, United States
- Materials
Science, Electrical Engineering, and Physics, Duke University, Durham, North Carolina 27708, United States
| | - Arkady V. Krasheninnikov
- Institute
of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany
| | - Thomas Heine
- Theoretical
Chemistry, Technische Universität
Dresden, Dresden 01062, Germany
- Center
for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden-Rossendorf, Görlitz 02826, Germany
| | - Rico Friedrich
- Theoretical
Chemistry, Technische Universität
Dresden, Dresden 01062, Germany
- Institute
of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden 01328, Germany
- Center
for Extreme Materials, Duke University, Durham, North Carolina 27708, United States
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Abdullah SS, Rostamzadeh N, Muanda FT, McArthur E, Weir MA, Sontrop JM, Kim RB, Kamran S, Garg AX. High-Throughput Computing to Automate Population-Based Studies to Detect the 30-Day Risk of Adverse Outcomes After New Outpatient Medication Use in Older Adults with Chronic Kidney Disease: A Clinical Research Protocol. Can J Kidney Health Dis 2024; 11:20543581231221891. [PMID: 38186562 PMCID: PMC10771740 DOI: 10.1177/20543581231221891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/20/2023] [Indexed: 01/09/2024] Open
Abstract
Background Safety issues are detected in about one third of prescription drugs in the years following regulatory agency approval. Older adults, especially those with chronic kidney disease, are at particular risk of adverse reactions to prescription drugs. This protocol describes a new approach that may identify credible drug-safety signals more efficiently using administrative health care data. Objective To use high-throughput computing and automation to conduct 700+ drug-safety cohort studies in older adults in Ontario, Canada. Each study will compare 74 acute (30-day) outcomes in patients who start a new prescription drug (new users) to a group of nonusers with similar baseline health characteristics. Risks will be assessed within strata of baseline kidney function. Design and setting The studies will be population-based, new-user cohort studies conducted using linked administrative health care databases in Ontario, Canada (January 1, 2008, to March 1, 2020). The source population for these studies will be residents of Ontario aged 66 years or older who filled at least one outpatient prescription through the Ontario Drug Benefit (ODB) program during the study period (all residents have universal health care, and those aged 65+ have universal prescription drug coverage through the ODB). Patients We identified 3.2 million older adults in the source population during the study period and built 700+ initial medication cohorts, each containing mutually exclusive groups of new users and nonusers. Nonusers were randomly assigned cohort entry dates that followed the same distribution of prescription start dates as new users. Eligibility criteria included a baseline estimated glomerular filtration rate (eGFR) measurement within 12 months before the cohort entry date (median time was 71 days before cohort entry in the new user group), no prior receipt of maintenance dialysis or a kidney transplant, and no prior prescriptions for drugs in the same subclass as the study drug. New users and nonusers will be balanced on ~400 baseline health characteristics using inverse probability of treatment weighting on propensity scores within 3 strata of baseline eGFR: ≥60, 45 to <60, <45 mL/min per 1.73 m2. Outcomes We will compare new user and nonuser groups on 74 clinically relevant outcomes (17 composites and 57 individual outcomes) in the 30 days after cohort entry. We used a prespecified approach to identify these 74 outcomes. Statistical analysis plan In each cohort, we will obtain eGFR-stratum-specific weighted risk ratios and risk differences using modified Poisson regression and binomial regression, respectively. Additive and multiplicative interaction by eGFR category will be examined. Drug-outcome associations that meet prespecified criteria (identified signals) will be further examined in additional analyses (including survival, negative-control exposure, and E-value analyses) and visualizations. Results The initial medication cohorts had a median of 6120 new users per cohort (interquartile range: 1469-38 839) and a median of 1 088 301 nonusers (interquartile range: 751 697-1 267 009). Medications with the largest number of new users were amoxicillin trihydrate (n = 1 000 032), cephalexin (n = 571 566), prescription acetaminophen (n = 571 563), and ciprofloxacin (n = 504,374); 19% to 29% of new users in these cohorts had an eGFR <60 mL/min per 1.73 m2. Limitations Despite our use of robust techniques to balance baseline indicators and to control for confounding by indication, residual confounding will remain a possibility. Only acute (30-day) outcomes will be examined. Our data sources do not include nonprescription (over-the-counter) drugs or drugs prescribed in hospitals and do not include outpatient prescription drug use in children or adults <65 years. Conclusion This accelerated approach to conducting postmarket drug-safety studies has the potential to more efficiently detect drug-safety signals in a vulnerable population. The results of this protocol may ultimately help improve medication safety.
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Affiliation(s)
| | - Neda Rostamzadeh
- Insight Lab, Western University and ICES Western, London, ON, Canada
| | - Flory T. Muanda
- London Health Sciences Centre, Western University and ICES Western, London, ON, Canada
| | - Eric McArthur
- London Health Sciences Centre and ICES Western, London, ON, Canada
| | - Matthew A. Weir
- London Health Sciences Centre, Western University and ICES Western, London, ON, Canada
| | | | | | - Sedig Kamran
- Insight Lab, Western University, London, ON, Canada
| | - Amit X. Garg
- London Health Sciences Centre, Western University and ICES Western, London, ON, Canada
- Victoria Hospital, London Health Sciences Centre, London, ON, Canada
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Abstract
Two-dimensional (2D) materials are frequently associated with the sheets forming bulk layered compounds bonded by van der Waals (vdW) forces. The anisotropy and weak interaction between the sheets have also been the main criteria in the computational search for new 2D systems, predicting ∼2000 exfoliable compounds. However, some representatives of a new type of non-vdW 2D systems, without layered 3D analogues, were recently manufactured. For this novel materials class, data-driven design principles are still missing. Here, we outline a set of 8 binary and 20 ternary candidates by filtering the AFLOW-ICSD database according to structural prototypes. The oxidation state of the surface cations regulates the exfoliation energy with low oxidation numbers leading to weak bonding─a useful descriptor to obtain novel 2D materials also providing clear guidelines for experiments. A vast range of appealing electronic, optical, and magnetic properties make the candidates attractive for various applications and particularly spintronics.
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Affiliation(s)
- Rico Friedrich
- Institute of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, 01328 Dresden, Germany
- Center for Autonomous Materials Design, Duke University, Durham, North Carolina 27708, United States
| | - Mahdi Ghorbani-Asl
- Institute of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, 01328 Dresden, Germany
| | - Stefano Curtarolo
- Center for Autonomous Materials Design, Duke University, Durham, North Carolina 27708, United States
- Materials Science, Electrical Engineering, and Physics, Duke University, Durham, North Carolina 27708, United States
| | - Arkady V Krasheninnikov
- Institute of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-Rossendorf, 01328 Dresden, Germany
- Department of Applied Physics, Aalto University, Aalto 00076, Finland
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Brito JJ, Mosqueiro T, Rotman J, Xue V, Chapski DJ, la Hoz JD, Matias P, Martin LS, Zelikovsky A, Pellegrini M, Mangul S. Telescope: an interactive tool for managing large-scale analysis from mobile devices. Gigascience 2020; 9:giz163. [PMID: 31972019 PMCID: PMC6977584 DOI: 10.1093/gigascience/giz163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/26/2019] [Accepted: 12/19/2019] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND In today's world of big data, computational analysis has become a key driver of biomedical research. High-performance computational facilities are capable of processing considerable volumes of data, yet often lack an easy-to-use interface to guide the user in supervising and adjusting bioinformatics analysis via a tablet or smartphone. RESULTS To address this gap we proposed Telescope, a novel tool that interfaces with high-performance computational clusters to deliver an intuitive user interface for controlling and monitoring bioinformatics analyses in real-time. By leveraging last generation technology now ubiquitous to most researchers (such as smartphones), Telescope delivers a friendly user experience and manages conectivity and encryption under the hood. CONCLUSIONS Telescope helps to mitigate the digital divide between wet and computational laboratories in contemporary biology. By delivering convenience and ease of use through a user experience not relying on expertise with computational clusters, Telescope can help researchers close the feedback loop between bioinformatics and experimental work with minimal impact on the performance of computational tools. Telescope is freely available at https://github.com/Mangul-Lab-USC/telescope.
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Affiliation(s)
- Jaqueline J Brito
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA
| | - Thiago Mosqueiro
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Jeremy Rotman
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Victor Xue
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Douglas J Chapski
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, 650 Charles E. Young Drive, Los Angeles, CA 90095, USA
| | - Juan De la Hoz
- Center for Neurobehavioral Genetics, University of California Los Angeles, 695 Charles E Young Dr S, Los Angeles, CA 90095, USA
| | - Paulo Matias
- Department of Computer Science, Federal University of São Carlos, km 325 Rod. Washington Luis, São Carlos, SP 13565–905, Brazil
| | - Lana S Martin
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA
| | - Alex Zelikovsky
- Department of Computer Science, Georgia State University, 1 Park Place, Atlanta, GA 30303, USA
- The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow 119991, Russia
| | - Matteo Pellegrini
- Institute for Quantitative and Computational Biosciences, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA 90089-9121, USA
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van Beusekom B, Touw WG, Tatineni M, Somani S, Rajagopal G, Luo J, Gilliland GL, Perrakis A, Joosten RP. Homology-based hydrogen bond information improves crystallographic structures in the PDB. Protein Sci 2018; 27:798-808. [PMID: 29168245 PMCID: PMC5818736 DOI: 10.1002/pro.3353] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 11/16/2017] [Accepted: 11/16/2017] [Indexed: 01/06/2023]
Abstract
The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H-bond) distances as a source of information. However, H-bond restraints can improve structures at low resolution where diffraction data are limited. To improve low-resolution structure refinement, we present methods for deriving H-bond information either globally from well-refined high-resolution structures from the PDB-REDO databank, or specifically from on-the-fly constructed sets of homologous high-resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low-resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB-REDO databank (https://pdb-redo.eu). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.
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Affiliation(s)
- Bart van Beusekom
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Wouter G. Touw
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Mahidhar Tatineni
- San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman DriveLa JollaCalifornia92093‐0505
| | - Sandeep Somani
- Discovery Sciences, Janssen R&D LLCSpring HousePennsylvania
| | | | - Jinquan Luo
- Janssen BioTherapeutics, Janssen R&D LLCSpring HousePennsylvania
| | | | - Anastassis Perrakis
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
| | - Robbie P. Joosten
- Department of BiochemistryNetherlands Cancer Institute, Plesmanlaan 121Amsterdam1066 CXThe Netherlands
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Galiano V, Garcia-Valtanen P, Micol V, Encinar JA. Looking for inhibitors of the dengue virus NS5 RNA-dependent RNA-polymerase using a molecular docking approach. Drug Des Devel Ther 2016; 10:3163-3181. [PMID: 27784988 PMCID: PMC5066851 DOI: 10.2147/dddt.s117369] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The dengue virus (DENV) nonstructural protein 5 (NS5) contains both an N-terminal methyltransferase domain and a C-terminal RNA-dependent RNA polymerase domain. Polymerase activity is responsible for viral RNA synthesis by a de novo initiation mechanism and represents an attractive target for antiviral therapy. The incidence of DENV has grown rapidly and it is now estimated that half of the human population is at risk of becoming infected with this virus. Despite this, there are no effective drugs to treat DENV infections. The present in silico study aimed at finding new inhibitors of the NS5 RNA-dependent RNA polymerase of the four serotypes of DENV. We used a chemical library comprising 372,792 nonnucleotide compounds (around 325,319 natural compounds) to perform molecular docking experiments against a binding site of the RNA template tunnel of the virus polymerase. Compounds with high negative free energy variation (ΔG <−10.5 kcal/mol) were selected as putative inhibitors. Additional filters for favorable druggability and good absorption, distribution, metabolism, excretion, and toxicity were applied. Finally, after the screening process was completed, we identified 39 compounds as lead DENV polymerase inhibitor candidates. Potentially, these compounds could act as efficient DENV polymerase inhibitors in vitro and in vivo.
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Affiliation(s)
- Vicente Galiano
- Physics and Computer Architecture Department, Miguel Hernández University (UMH), Elche, Spain
| | - Pablo Garcia-Valtanen
- Experimental Therapeutics Laboratory, Hanson and Sansom Institute for Health Research, School of Pharmacy and Medical Science, University of South Australia, Adelaide, Australia
| | - Vicente Micol
- Molecular and Cell Biology Institute, Miguel Hernández University (UMH), Elche, Spain; CIBER: CB12/03/30038, Physiopathology of the Obesity and Nutrition, CIBERobn, Instituto de Salud Carlos III, Palma de Mallorca, Spain
| | - José Antonio Encinar
- Molecular and Cell Biology Institute, Miguel Hernández University (UMH), Elche, Spain
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Encinar JA, Fernández-Ballester G, Galiano-Ibarra V, Micol V. In silico approach for the discovery of new PPARγ modulators among plant-derived polyphenols. Drug Des Devel Ther 2015; 9:5877-95. [PMID: 26604687 PMCID: PMC4639521 DOI: 10.2147/dddt.s93449] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Peroxisome proliferator-activated receptor gamma (PPARγ) is a well-characterized member of the PPAR family that is predominantly expressed in adipose tissue and plays a significant role in lipid metabolism, adipogenesis, glucose homeostasis, and insulin sensitization. Full agonists of synthetic thiazolidinediones (TZDs) have been therapeutically used in clinical practice to treat type 2 diabetes for many years. Although it can effectively lower blood glucose levels and improve insulin sensitivity, the administration of TZDs has been associated with severe side effects. Based on recent evidence obtained with plant-derived polyphenols, the present in silico study aimed at finding new selective human PPARγ (hPPARγ) modulators that are able to improve glucose homeostasis with reduced side effects compared with TZDs. Docking experiments have been used to select compounds with strong binding affinity (ΔG values ranging from −10.0±0.9 to −11.4±0.9 kcal/mol) by docking against the binding site of several X-ray structures of hPPARγ. These putative modulators present several molecular interactions with the binding site of the protein. Additionally, most of the selected compounds have favorable druggability and good ADMET properties. These results aim to pave the way for further bench-scale analysis for the discovery of new modulators of hPPARγ that do not induce any side effects.
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Affiliation(s)
| | | | | | - Vicente Micol
- Molecular and Cell Biology Institute, Miguel Hernández University, Elche, Spain ; CIBER: CB12/03/30038 Physiopathology of Obesity and Nutrition, CIBERobn, Instituto de Salud Carlos III, Palma de Mallorca, Spain
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Wu XL, Beissinger TM, Bauck S, Woodward B, Rosa GJM, Weigel KA, Gatti NDL, Gianola D. A primer on high-throughput computing for genomic selection. Front Genet 2011; 2:4. [PMID: 22303303 PMCID: PMC3268564 DOI: 10.3389/fgene.2011.00004] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2010] [Accepted: 02/07/2011] [Indexed: 12/30/2022] Open
Abstract
High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized genetic gain). Eventually, HTC may change our view of data analysis as well as decision-making in the post-genomic era of selection programs in animals and plants, or in the study of complex diseases in humans.
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Affiliation(s)
- Xiao-Lin Wu
- Department of Dairy Science, University of Wisconsin Madison, WI, USA
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