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Sunita, Singhvi N, Gupta V, Singh Y, Shukla P. Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis. Mol Biotechnol 2024; 66:814-823. [PMID: 36913083 DOI: 10.1007/s12033-023-00710-5] [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] [Received: 06/09/2022] [Accepted: 02/24/2023] [Indexed: 03/14/2023]
Abstract
Implementation of computational tools in the identification of novel drug targets for Tuberculosis (TB) has been a promising area of research. TB has been a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) localized primarily on the lungs and it has been one of the most successful pathogen in the history of mankind. Extensively arising drug resistivity in TB has made it a global challenge and need for new drugs has become utmost important.The involvement of Nucleoid-Associated Proteins (NAPs) in maintaining the structure of the genomic material and regulating various cellular processes like transcription, DNA replication, repair and recombination makes significant, has opened a new arena to find the drugs targeting Mtb. The current study aims to identify potential inhibitors of NAPs through a computational approach. In the present work we worked on the eight NAPs of Mtb, namely, Lsr2, EspR, HupB, HNS, NapA, mIHF and NapM. The structural modelling and analysis of these NAPs were carried out. Moreover, molecular interaction were checked and binding energy was identified for 2500 FDA-approved drugs that were selected for antagonist analysis to choose novel inhibitors targeting NAPs of Mtb. Drugs including Amikacin, streptomycin, kanamycin, and isoniazid along with eight FDA-approved molecules that were found to be potential novel targets for these mycobacterial NAPs and have an impact on their functions. The potentiality of several anti-tubercular drugs as therapeutic agents identified through computational modelling and simulation unlocks a new gateway for accomplishing the goal to treat TB.
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Affiliation(s)
- Sunita
- Department of Microbiology, Maharshi Dayanand University, Rohtak, 124001, Haryana, India
- Bacterial Pathogenesis Laboratory, Department of Zoology, University of Delhi, Delhi, 110007, India
| | - Nirjara Singhvi
- Department of Zoology, Hansraj College, University of Delhi, Delhi, 110007, India
- School of Allied Sciences, Dev Bhoomi Uttarakhand University, Dehradun, Uttarakhand, 248001, India
| | - Vipin Gupta
- Ministry of Environment, Forest and Climate Change, Government of India, Dehradun, Uttarakhand, 248001, India
| | - Yogendra Singh
- Bacterial Pathogenesis Laboratory, Department of Zoology, University of Delhi, Delhi, 110007, India
| | - Pratyoosh Shukla
- Department of Microbiology, Maharshi Dayanand University, Rohtak, 124001, Haryana, India.
- Enzyme Technology and Protein Bioinformatics Laboratory, School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.
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2
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Li H, Wei X. A Concise Review of Biomolecule Visualization. Curr Issues Mol Biol 2024; 46:1318-1334. [PMID: 38392202 PMCID: PMC10887528 DOI: 10.3390/cimb46020084] [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: 01/06/2024] [Revised: 01/27/2024] [Accepted: 01/31/2024] [Indexed: 02/24/2024] Open
Abstract
The structural characteristics of biomolecules are a major focus in the field of structural biology. Molecular visualization plays a crucial role in displaying structural information in an intuitive manner, aiding in the understanding of molecular properties. This paper provides a comprehensive overview of core concepts, key techniques, and tools in molecular visualization. Additionally, it presents the latest research findings to uncover emerging trends and highlights the challenges and potential directions for the development of the field.
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Affiliation(s)
- Hui Li
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xinru Wei
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China
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3
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Agrawal S, Austin S. An idea to explore: Augmented reality and LEGO® brick modeling in the biochemistry and cell biology classroom-two tactile ways to teach biomolecular structure-Function. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2023; 51:439-445. [PMID: 37022094 DOI: 10.1002/bmb.21734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 03/05/2023] [Accepted: 03/26/2023] [Indexed: 06/19/2023]
Abstract
We present here two accessible ways for enhanced understanding of complex biological structures and their function in undergraduate Biology and Biochemistry classrooms. These methods can be applied for in-class instruction as well as for remote lessons, as they are cheap, easily available and easy to implement. LEGO® bricks and MERGE CUBE based augmented reality can be applied to make three-dimensional representation for any structure available on PDB. We envisage these techniques to be useful for students when visualizing simple stereochemical problems or complex pathway interactions.
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Affiliation(s)
- Swati Agrawal
- Department of Biology, University of Mary Washington, Fredericksburg, Virginia, USA
| | - Shane Austin
- Department of Biological & Chemical Sciences, The University of the West Indies Cave Hill Campus, Bridgetown, Barbados
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4
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Corey RA, Baaden M, Chavent M. A brief history of visualizing membrane systems in molecular dynamics simulations. FRONTIERS IN BIOINFORMATICS 2023; 3:1149744. [PMID: 37213533 PMCID: PMC10196259 DOI: 10.3389/fbinf.2023.1149744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 03/13/2023] [Indexed: 05/23/2023] Open
Abstract
Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.
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Affiliation(s)
- R. A. Corey
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - M. Baaden
- Centre Nationale de la Recherche Scientifique, Laboratoire de Biochimie Théorique, Université Paris Cité, Paris, France
| | - M. Chavent
- Institut de Pharmacologie et Biologie Structurale, CNRS, Université de Toulouse, Toulouse, France
- *Correspondence: M. Chavent,
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5
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Ippoliti FM, Chari JV, Garg NK. Advancing global chemical education through interactive teaching tools. Chem Sci 2022; 13:5790-5796. [PMID: 35685782 PMCID: PMC9132018 DOI: 10.1039/d2sc01881k] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 04/29/2022] [Indexed: 11/21/2022] Open
Abstract
This perspective highlights our recent efforts to develop interactive resources in chemical education for worldwide usage. First, we highlight online tutorials that connect organic chemistry to medicine and popular culture, along with game-like resources for active learning. Next, we describe efforts to aid students in learning to visualize chemical structures in three dimensions. Finally, we present recent approaches toward engaging children and the general population through organic chemistry coloring and activity books. Collectively, these tools have benefited hundreds of thousands of users worldwide. We hope this perspective promotes a spirit of innovation in chemical education and spurs the development of additional free, interactive, and widely accessible chemical education resources. This perspective highlights the development of interactive chemical education resources for worldwide usage. We hope to promote a spirit of innovation in chemical education and spur the development of new chemical education resources.![]()
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Affiliation(s)
- Francesca M Ippoliti
- Department of Chemistry and Biochemistry, University of California Los Angeles California 90095 USA
| | - Jason V Chari
- Department of Chemistry and Biochemistry, University of California Los Angeles California 90095 USA
| | - Neil K Garg
- Department of Chemistry and Biochemistry, University of California Los Angeles California 90095 USA
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6
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Taylor S, Soneji S. Bioinformatics and the Metaverse: Are We Ready? FRONTIERS IN BIOINFORMATICS 2022; 2:863676. [PMID: 36304263 PMCID: PMC9580841 DOI: 10.3389/fbinf.2022.863676] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/20/2022] [Indexed: 02/01/2023] Open
Abstract
COVID-19 forced humanity to think about new ways of working globally without physically being present with other people, and eXtended Reality (XR) systems (defined as Virtual Reality, Augmented Reality and Mixed Reality) offer a potentially elegant solution. Previously seen as mainly for gaming, commercial and research institutions are investigating XR solutions to solve real world problems from training, simulation, mental health, data analysis, and studying disease progression. More recently large corporations such as Microsoft and Meta have announced they are developing the Metaverse as a new paradigm to interact with the digital world. This article will look at how visualization can leverage the Metaverse in bioinformatics research, the pros and cons of this technology, and what the future may hold.
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Affiliation(s)
- Stephen Taylor
- Analysis, Visualization and Informatics Group, MRC Weatherall Institute of Computational Biology, MRC Weatherall Institute of Molecular Medicine, Oxford, United Kingdom
- *Correspondence: Stephen Taylor,
| | - Shamit Soneji
- Division of Molecular Hematology, Department of Laboratory Medicine, Faculty of Medicine, BMC, Lund University, Lund, Sweden
- Lund Stem Cell Center, Faculty of Medicine, BMC, Lund University, Lund, Sweden
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Fombona-Pascual A, Fombona J, Vicente R. Augmented Reality, a Review of a Way to Represent and Manipulate 3D Chemical Structures. J Chem Inf Model 2022; 62:1863-1872. [PMID: 35373563 PMCID: PMC9044447 DOI: 10.1021/acs.jcim.1c01255] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
Augmented reality
(AR) is a mixed technology that superimposes
three-dimensional (3D) digital data onto an image of reality. This
technology enables users to represent and manipulate 3D chemical structures.
In spite of its potential, the use of these tools in chemistry is
still scarce. The aim of this work is to identify the real situation
of AR developments and its potential for 3D visualization of molecules.
A descriptive analysis of a selection of 143 research publications
(extracted from Web of Science between 2018 and 2020) highlights some
significant AR examples that had been implemented in chemistry, in
both education and research environments. Although the traditional
2D screen visualization is still preferred when teaching chemistry,
the application of AR in early education has shown potential to facilitate
the understanding and visualization of chemical structures. The increasing
connectivity of the AR technology to web platforms and scientific
networks should translate into new opportunities for teaching and
learning strategies.
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Affiliation(s)
- Alba Fombona-Pascual
- Organic and Inorganic Chemistry Department, University of Oviedo, Av. Julian Clavería, Oviedo 33006, Spain
| | - Javier Fombona
- Education Sciences Department, University of Oviedo, C. Aniceto Sela, Oviedo 33005, Spain
| | - Rubén Vicente
- Organic and Inorganic Chemistry Department, University of Oviedo, Av. Julian Clavería, Oviedo 33006, Spain
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8
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Online tools to easily build virtual molecular models for display in augmented and virtual reality on the web. J Mol Graph Model 2022; 114:108164. [PMID: 35325844 DOI: 10.1016/j.jmgm.2022.108164] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 11/20/2022]
Abstract
Several groups developed in the last years augmented and virtual reality (AR/VR) software to visualize 3D molecules, most rather static, limited in content, and requiring software installs, some even requiring expensive hardware. We launched in 2020 moleculARweb (https://molecularweb.epfl.ch), a website that offers interactive content for chemistry and structural biology education through commodity web-based AR that works on consumer devices like smartphones, tablets and laptops. Among thousands of users, teachers increasingly request more biological macromolecules to be available, a demand that we cannot address individually. Therefore, to allow users to build their own material, we built a web interface where they can create online AR experiences in few steps starting from Protein Data Bank, AlphaFold or custom uploaded structures, or from virtual objects/scenes exported from the Visual Molecular Dynamics program, without any programming knowledge. The web tool also returns WebXR sessions for viewing and manipulating the models in WebXR-compatible devices including smartphones, tablets, and also immersive VR headsets with WebXR-capable browsers, where models can be manipulated even with bare hands when supported by the device. The tool is accessible for free at https://molecularweb.epfl.ch/pages/pdb2ar.html.
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Guérinot C, Marcon V, Godard C, Blanc T, Verdier H, Planchon G, Raimondi F, Boddaert N, Alonso M, Sailor K, Lledo PM, Hajj B, El Beheiry M, Masson JB. New Approach to Accelerated Image Annotation by Leveraging Virtual Reality and Cloud Computing. FRONTIERS IN BIOINFORMATICS 2022; 1:777101. [PMID: 36303792 PMCID: PMC9580868 DOI: 10.3389/fbinf.2021.777101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/15/2021] [Indexed: 01/02/2023] Open
Abstract
Three-dimensional imaging is at the core of medical imaging and is becoming a standard in biological research. As a result, there is an increasing need to visualize, analyze and interact with data in a natural three-dimensional context. By combining stereoscopy and motion tracking, commercial virtual reality (VR) headsets provide a solution to this critical visualization challenge by allowing users to view volumetric image stacks in a highly intuitive fashion. While optimizing the visualization and interaction process in VR remains an active topic, one of the most pressing issue is how to utilize VR for annotation and analysis of data. Annotating data is often a required step for training machine learning algorithms. For example, enhancing the ability to annotate complex three-dimensional data in biological research as newly acquired data may come in limited quantities. Similarly, medical data annotation is often time-consuming and requires expert knowledge to identify structures of interest correctly. Moreover, simultaneous data analysis and visualization in VR is computationally demanding. Here, we introduce a new procedure to visualize, interact, annotate and analyze data by combining VR with cloud computing. VR is leveraged to provide natural interactions with volumetric representations of experimental imaging data. In parallel, cloud computing performs costly computations to accelerate the data annotation with minimal input required from the user. We demonstrate multiple proof-of-concept applications of our approach on volumetric fluorescent microscopy images of mouse neurons and tumor or organ annotations in medical images.
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Affiliation(s)
- Corentin Guérinot
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
- Perception and Memory Unit, CNRS UMR3571, Institut Pasteur, Paris, France
- Sorbonne Université, Collège Doctoral, Paris, France
| | - Valentin Marcon
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
| | - Charlotte Godard
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
- École Doctorale Physique en Île-de-France, PSL University, Paris, France
| | - Thomas Blanc
- Sorbonne Université, Collège Doctoral, Paris, France
- Laboratoire Physico-Chimie, Institut Curie, PSL Research University, CNRS UMR168, Paris, France
| | - Hippolyte Verdier
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
- Histopathology and Bio-Imaging Group, Sanofi R&D, Vitry-Sur-Seine, France
- Université de Paris, UFR de Physique, Paris, France
| | - Guillaume Planchon
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
| | - Francesca Raimondi
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
- Unité Médicochirurgicale de Cardiologie Congénitale et Pédiatrique, Centre de Référence des Malformations Cardiaques Congénitales Complexes M3C, Hôpital Universitaire Necker-Enfants Malades, Université de Paris, Paris, France
- Pediatric Radiology Unit, Hôpital Universitaire Necker-Enfants Malades, Université de Paris, Paris, France
- UMR-1163 Institut Imagine, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
| | - Nathalie Boddaert
- Pediatric Radiology Unit, Hôpital Universitaire Necker-Enfants Malades, Université de Paris, Paris, France
- UMR-1163 Institut Imagine, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
| | - Mariana Alonso
- Perception and Memory Unit, CNRS UMR3571, Institut Pasteur, Paris, France
| | - Kurt Sailor
- Perception and Memory Unit, CNRS UMR3571, Institut Pasteur, Paris, France
| | - Pierre-Marie Lledo
- Perception and Memory Unit, CNRS UMR3571, Institut Pasteur, Paris, France
| | - Bassam Hajj
- Sorbonne Université, Collège Doctoral, Paris, France
- École Doctorale Physique en Île-de-France, PSL University, Paris, France
| | - Mohamed El Beheiry
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
| | - Jean-Baptiste Masson
- Decision and Bayesian Computation, USR 3756 (C3BI/DBC) & Neuroscience Department CNRS UMR 3751, Université de Paris, Institut Pasteur, Paris, France
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10
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A new visual design language for biological structures in a cell. Structure 2022; 30:485-497.e3. [DOI: 10.1016/j.str.2022.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/28/2021] [Accepted: 01/04/2022] [Indexed: 01/16/2023]
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11
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Levkovich O, Yarden A. Conceptualizing learning about proteins with a molecular viewer in high school based on the integration of two theoretical frameworks. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2021; 49:917-925. [PMID: 34486801 DOI: 10.1002/bmb.21576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 08/23/2021] [Indexed: 06/13/2023]
Abstract
The use of a molecular viewer to visualize proteins has become more prevalent in high schools in recent years. We relied on the foundations of two theoretical frameworks to analyze questions in two learning tasks designed for 10th- to 12th-grade biotechnology majors that make use of Jmol. The two theoretical frameworks were: (i) classification of scientific knowledge into content, procedural, and epistemic knowledge; and (ii) evaluation of the cognitive skills central to visual literacy in biochemistry. During the analysis, two sub-elements of procedural knowledge emerged from the data: (i) the visualization of molecular models, and (ii) the use of Jmol software features. Based on the theoretical frameworks and data analysis, we suggest a conceptualization of learning about proteins using a molecular viewer, where the scientific knowledge elements are integrated with the eight cognitive skills central to visual literacy in biochemistry. In addition, a model presenting a hierarchy for the knowledge elements and sub-elements is suggested. In this model, content knowledge is a basic requirement; without it, the other knowledge elements cannot be used. Moreover, the use of epistemic knowledge or Jmol software features is not possible without visualization of the molecular models, which requires content knowledge. This conceptualization is expected to facilitate the development of learning tasks, decrease the complexity of knowledge acquisition for students; it may also assist the teacher during the teaching process.
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Affiliation(s)
- Ohad Levkovich
- Department of Science Teaching, Weizmann Institute of Science, Rehovot, Israel
| | - Anat Yarden
- Department of Science Teaching, Weizmann Institute of Science, Rehovot, Israel
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12
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Cook J, Brown M, Sellwood M, Campbell C, Kouppas P, Poronnik P. XR game development as a tool for authentic, experiential, and collaborative learning. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2021; 49:846-847. [PMID: 34410022 DOI: 10.1002/bmb.21572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 07/20/2021] [Accepted: 07/29/2021] [Indexed: 06/13/2023]
Abstract
This brief review provides insights into the recent advances made by the Unity game engine into education and the ways that learning resources can be used to teach novice bioscience students to use the VR/AR affordances of the platform. We present our own practises for implementation of a novel gamification task for final-year bioscience students and reflect on the changes we have had to make in order to overcome challenges presented by the COVID-19 pandemic.
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Affiliation(s)
- Jim Cook
- ICT TechLab, The University of Sydney, Darlington, New South Wales, Australia
| | - Martin Brown
- Westmead Living Lab, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Matthew Sellwood
- Media Lab, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
| | - Craig Campbell
- Media Lab, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
| | | | - Philip Poronnik
- Media Lab, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
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13
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Shannon RJ, Deeks HM, Burfoot E, Clark E, Jones AJ, Mulholland AJ, Glowacki DR. Exploring human-guided strategies for reaction network exploration: Interactive molecular dynamics in virtual reality as a tool for citizen scientists. J Chem Phys 2021; 155:154106. [PMID: 34686059 DOI: 10.1063/5.0062517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The emerging fields of citizen science and gamification reformulate scientific problems as games or puzzles to be solved. Through engaging the wider non-scientific community, significant breakthroughs may be made by analyzing citizen-gathered data. In parallel, recent advances in virtual reality (VR) technology are increasingly being used within a scientific context and the burgeoning field of interactive molecular dynamics in VR (iMD-VR) allows users to interact with dynamical chemistry simulations in real time. Here, we demonstrate the utility of iMD-VR as a medium for gamification of chemistry research tasks. An iMD-VR "game" was designed to encourage users to explore the reactivity of a particular chemical system, and a cohort of 18 participants was recruited to playtest this game as part of a user study. The reaction game encouraged users to experiment with making chemical reactions between a propyne molecule and an OH radical, and "molecular snapshots" from each game session were then compiled and used to map out reaction pathways. The reaction network generated by users was compared to existing literature networks demonstrating that users in VR capture almost all the important reaction pathways. Further comparisons between humans and an algorithmic method for guiding molecular dynamics show that through using citizen science to explore these kinds of chemical problems, new approaches and strategies start to emerge.
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Affiliation(s)
- Robin J Shannon
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Helen M Deeks
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Eleanor Burfoot
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Edward Clark
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | - Alex J Jones
- School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
| | | | - David R Glowacki
- ArtSci Foundation International, 5th floor Mariner House, Bristol, BS1 4QD, United Kingdom
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14
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Smith C, Friel CJ. Development and use of augmented reality models to teach medicinal chemistry. CURRENTS IN PHARMACY TEACHING & LEARNING 2021; 13:1010-1017. [PMID: 34294241 DOI: 10.1016/j.cptl.2021.06.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 01/07/2021] [Accepted: 06/08/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND PURPOSE Students in the doctor of pharmacy curriculum have varied backgrounds in their chemical training and also their ability to make mental conversions from two-dimensional chemical representations, on lecture slides or textbook images, to three-dimensional cognitive understanding. In order to bridge the gap, augmented reality (AR) models were developed to provide an alternative learning medium for the students. AR was selected to take advantage of the ubiquitous presence of smartphones, without incurring the expense of Virtual Reality hardware. EDUCATIONAL ACTIVITY AND SETTING AR models were developed and introduced in the classroom in three phases. Student survey responses were used to improve the utility of the models in between phases. Active learning exercises were developed that required both individual and group interactions to complete. FINDINGS An optimized AR model creation workflow was developed that allowed each AR model to be created and posted in about 30 min. Depending on the phase of the study, 69% to 88% of the students found the AR models easy to use and 58% to 83% wanted to see more AR models used in future lectures. A majority (76%) of the students viewed the AR models on their smartphones. SUMMARY Augmented reality modules were created for use in medicinal chemistry courses in the pharmacy curriculum. Models were introduced in phases and included iterative improvements based on student feedback. The AR exercises provided active learning opportunities and were well received. The majority of students would like additional AR modules used in the course.
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Affiliation(s)
- Chase Smith
- Department of Pharmaceutical Sciences, School of Pharmacy-Worcester/Manchester, MCPHS University, 19 Foster Street, Worcester, MA 01608, United States.
| | - Carolyn J Friel
- Department of Pharmaceutical Sciences, School of Pharmacy-Worcester/Manchester, MCPHS University, 19 Foster Street, Worcester, MA 01608, United States.
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15
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Shiragannavar SJ, Madagi SB. Identification of vaccine candidate proteins in Ureaplasma urealyticum causing infertility. Indian J Sex Transm Dis AIDS 2021; 42:95-100. [PMID: 34909611 PMCID: PMC8628103 DOI: 10.4103/ijstd.ijstd_7_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 02/07/2019] [Accepted: 12/18/2020] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Ureaplasma urealyticum has gained resistance to number of antibiotics and has been of the greatest concerns nowadays. The treatment options remain extremely low due to the increased levels of intrinsic resistance gained by the pathogen. AIM The present study focuses on designing a peptide-based vaccine as there is no vaccine available for the pathogen. MATERIALS AND METHODS All the protein sequences of pathogen were collected and examined using various in silico methods to identify the most immunogenic proteins. The study identifies the proteins which are antigenic in nature which induce the immune response, which lends to quick response of immune system on reinfection. The study describes peptide-based vaccine against U. urealyticum using molecular docking and molecular dynamics simulation approach. RESULTS The study identifies novel putative vaccine candidate proteins that are antigenic, membrane bound and non-allergenic. CONCLUSION The results of the study imply that the vaccine candidate proteins identified may bring about vigorous enduring defensive immunity against U. urealyticum.
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Affiliation(s)
- Shilpa Jeevappa Shiragannavar
- Department of Studies and Research in Bioinformatics and Biotechnology, Karnataka State Akkamahadevi Women's University, Vijayapura, Karnataka, India
| | - Shivakumar B. Madagi
- Department of Studies and Research in Bioinformatics and Biotechnology, Karnataka State Akkamahadevi Women's University, Vijayapura, Karnataka, India
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16
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Pereshivkina P, Karandasheva N, Mikhaylenko M, Kurushkin M. Immersive Molecular Dynamics in Virtual Reality: Increasing Efficiency of Educational Process with Companion Converter for NarupaXR. J Imaging 2021. [PMCID: PMC8321342 DOI: 10.3390/jimaging7060097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Visualization has always been a crucial part of the educational process. Implementing computer algorithms and virtual reality tools into it is vital for the new generation engineers, scientists and researchers. In the field of chemistry education, various software that allow dynamic molecular building and viewing are currently available. These software are now used to enhance the learning process and ensure better understanding of the chemical processes from the visual perspective. The present short communication provides a summary of these applications based on the NarupaXR program, which is a great educational tool that combines the functionality and simple design necessary for an educational tool. NarupaXR is used with a companion application “Narupa Builder” which requires a different file format, therefore a converter that allows a simple transition between the two extensions has been developed. The converter sufficiently increases the efficiency of the educational process. The automatic converter is freely available on GitLab The current communication provides detailed written instructions that can simplify the installation process of the converter and facilitate the use of both the software and the hardware of the VR set.
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17
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Xu K, Liu N, Xu J, Guo C, Zhao L, Wang HW, Zhang QC. VRmol: an integrative web-based virtual reality system to explore macromolecular structure. Bioinformatics 2021; 37:1029-1031. [PMID: 32745209 DOI: 10.1093/bioinformatics/btaa696] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Revised: 07/21/2020] [Accepted: 07/27/2020] [Indexed: 12/22/2022] Open
Abstract
SUMMARY Structural visualization and analysis are fundamental to explore macromolecular functions. Here, we present a novel integrative web-based virtual reality (VR) system-VRmol, to visualize and study molecular structures in an immersive virtual environment. Importantly, it is integrated with multiple online databases and is able to couple structure studies with associated genomic variations and drug information in a visual interface by cloud-based drug docking. VRmol thus can serve as an integrative platform to aid structure-based translational research and drug design. AVAILABILITY AND IMPLEMENTATION VRmol is freely available (https://VRmol.net), with detailed manual and tutorial (https://VRmol.net/docs). The code of VRmol is available as open source under the MIT license at http://github.com/kuixu/VRmol. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Kui Xu
- MOE Key Laboratory of Bioinformatics, School of Life Sciences, Beijing 100084, China.,Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China.,Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China
| | - Nan Liu
- Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China.,Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China.,Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jingle Xu
- MOE Key Laboratory of Bioinformatics, School of Life Sciences, Beijing 100084, China.,Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China
| | - Chunlong Guo
- Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China
| | - Lingyun Zhao
- Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China.,Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Hong-Wei Wang
- Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China.,Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China.,Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, School of Life Sciences, Beijing 100084, China.,Beijing Advanced Innovation Center for Structural Biology, Beijing Frotier Research Center for Biological Structures, Beijing 100084, China.,Tsinghua-Peking Joint Center for Life Sciences, Beijing 100084, China
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18
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Yallapragada VVB, Xu T, Walker SP, Tabirca S, Tangney M. Pepblock Builder VR - An Open-Source Tool for Gaming-Based Bio-Edutainment in Interactive Protein Design. Front Bioeng Biotechnol 2021; 9:674211. [PMID: 34055764 PMCID: PMC8160467 DOI: 10.3389/fbioe.2021.674211] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 03/24/2021] [Indexed: 11/13/2022] Open
Abstract
Proteins mediate and perform various fundamental functions of life. This versatility of protein function is an attribute of its 3D structure. In recent years, our understanding of protein 3D structure has been complemented with advances in computational and mathematical tools for protein modelling and protein design. 3D molecular visualisation is an essential part in every protein design and protein modelling workflow. Over the years, stand-alone and web-based molecular visualisation tools have been used to emulate three-dimensional view on computers. The advent of virtual reality provided the scope for immersive control of molecular visualisation. While these technologies have significantly improved our insights into protein modelling, designing new proteins with a defined function remains a complicated process. Current tools to design proteins lack user-interactivity and demand high computational skills. In this work, we present the Pepblock Builder VR, a gaming-based molecular visualisation tool for bio-edutainment and understanding protein design. Simulating the concepts of protein design and incorporating gaming principles into molecular visualisation promotes effective game-based learning. Unlike traditional sequence-based protein design and fragment-based stitching, the Pepblock Builder VR provides a building block style environment for complex structure building. This provides users a unique visual structure building experience. Furthermore, the inclusion of virtual reality to the Pepblock Builder VR brings immersive learning and provides users with "being there" experience in protein visualisation. The Pepblock Builder VR works both as a stand-alone and VR-based application, and with a gamified user interface, the Pepblock Builder VR aims to expand the horizons of scientific data generation to the masses.
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Affiliation(s)
- Venkata V. B. Yallapragada
- Cancer Research @ UCC, University College Cork, Cork, Ireland
- SynBioCentre, University College Cork, Cork, Ireland
| | - Tianshu Xu
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
| | - Sidney P. Walker
- Cancer Research @ UCC, University College Cork, Cork, Ireland
- SynBioCentre, University College Cork, Cork, Ireland
| | - Sabin Tabirca
- School of Computer Science and Information Technology, University College Cork, Cork, Ireland
- Department of Computer Science, Transylvania University of Braşov, Braşov, Romania
| | - Mark Tangney
- Cancer Research @ UCC, University College Cork, Cork, Ireland
- SynBioCentre, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
- iEd Hub, University College Cork, Cork, Ireland
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19
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Pirch S, Müller F, Iofinova E, Pazmandi J, Hütter CVR, Chiettini M, Sin C, Boztug K, Podkosova I, Kaufmann H, Menche J. The VRNetzer platform enables interactive network analysis in Virtual Reality. Nat Commun 2021; 12:2432. [PMID: 33893283 PMCID: PMC8065164 DOI: 10.1038/s41467-021-22570-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 03/09/2021] [Indexed: 12/17/2022] Open
Abstract
Networks provide a powerful representation of interacting components within complex systems, making them ideal for visually and analytically exploring big data. However, the size and complexity of many networks render static visualizations on typically-sized paper or screens impractical, resulting in proverbial ‘hairballs’. Here, we introduce a Virtual Reality (VR) platform that overcomes these limitations by facilitating the thorough visual, and interactive, exploration of large networks. Our platform allows maximal customization and extendibility, through the import of custom code for data analysis, integration of external databases, and design of arbitrary user interface elements, among other features. As a proof of concept, we show how our platform can be used to interactively explore genome-scale molecular networks to identify genes associated with rare diseases and understand how they might contribute to disease development. Our platform represents a general purpose, VR-based data exploration platform for large and diverse data types by providing an interface that facilitates the interaction between human intuition and state-of-the-art analysis methods. Data-rich networks can be difficult to interpret beyond a certain size. Here, the authors introduce a platform that uses virtual reality to allow the visual exploration of large networks, while interfacing with data repositories and other analytical methods to improve the interpretation of big data.
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Affiliation(s)
- Sebastian Pirch
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria
| | - Felix Müller
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria
| | - Eugenia Iofinova
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Julia Pazmandi
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria.,Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Vienna, Austria
| | - Christiane V R Hütter
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria
| | - Martin Chiettini
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria
| | - Celine Sin
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria
| | - Kaan Boztug
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Vienna, Austria.,St. Anna Children's Cancer Research Institute (CCRI), Vienna, Austria.,St. Anna Children's Hospital, Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria.,Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Iana Podkosova
- Institute of Visual Computing and Human-Centered Technology, TU Wien, Vienna, Austria
| | - Hannes Kaufmann
- Institute of Visual Computing and Human-Centered Technology, TU Wien, Vienna, Austria
| | - Jörg Menche
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna, Austria. .,Faculty of Mathematics, University of Vienna, Vienna, Austria.
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20
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Visualizing protein structures - tools and trends. Biochem Soc Trans 2021; 48:499-506. [PMID: 32196545 DOI: 10.1042/bst20190621] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Revised: 03/01/2020] [Accepted: 03/04/2020] [Indexed: 02/06/2023]
Abstract
Molecular visualization is fundamental in the current scientific literature, textbooks and dissemination materials. It provides an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Tools for visual exploration of structural data have become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. This mini-review was written as a short and compact overview for scientists who need to visualize protein structures and want to make an informed decision which tool they should use. Here, we first describe a few 'Swiss Army knives' geared towards protein visualization for everyday use with an existing large user base, then focus on more specialized tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.
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21
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Richardson JS, Richardson DC, Goodsell DS. Seeing the PDB. J Biol Chem 2021; 296:100742. [PMID: 33957126 PMCID: PMC8167287 DOI: 10.1016/j.jbc.2021.100742] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 04/26/2021] [Accepted: 04/30/2021] [Indexed: 01/21/2023] Open
Abstract
Ever since the first structures of proteins were determined in the 1960s, structural biologists have required methods to visualize biomolecular structures, both as an essential tool for their research and also to promote 3D comprehension of structural results by a wide audience of researchers, students, and the general public. In this review to celebrate the 50th anniversary of the Protein Data Bank, we present our own experiences in developing and applying methods of visualization and analysis to the ever-expanding archive of protein and nucleic acid structures in the worldwide Protein Data Bank. Across that timespan, Jane and David Richardson have concentrated on the organization inside and between the macromolecules, with ribbons to show the overall backbone "fold" and contact dots to show how the all-atom details fit together locally. David Goodsell has explored surface-based representations to present and explore biological subjects that range from molecules to cells. This review concludes with some ideas about the current challenges being addressed by the field of biomolecular visualization.
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Affiliation(s)
- Jane S Richardson
- Department of Biochemistry, Duke University, Durham, North Carolina, USA.
| | - David C Richardson
- Department of Biochemistry, Duke University, Durham, North Carolina, USA
| | - David S Goodsell
- Department of Integrative and Computational Biology, The Scripps Research Institute, La Jolla, California, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, the State University of New Jersey, Piscataway, New Jersey, USA.
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22
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Todd H, Emsley P. Development and assessment of CootVR, a virtual reality computer program for model building. ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2021; 77:19-27. [PMID: 33404522 PMCID: PMC7787110 DOI: 10.1107/s2059798320013625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/12/2020] [Indexed: 12/03/2022]
Abstract
Virtual reality-specific tools for model building are possible, and can provide an order-of-magnitude speedup over mouse-and-keyboard tools in certain situations. Biological macromolecules have complex three-dimensional shapes that are experimentally examined using X-ray crystallography and electron cryo-microscopy. Interpreting the data that these methods yield involves building 3D atomic models. With almost every data set, some portion of the time put into creating these models must be spent manually modifying the model in order to make it consistent with the data; this is difficult and time-consuming, in part because the data are ‘blurry’ in three dimensions. This paper describes the design and assessment of CootVR (available at http://hamishtodd1.github.io/cvr), a prototype computer program for performing this task in virtual reality, allowing structural biologists to build molecular models into cryo-EM and crystallographic data using their hands. CootVR was timed against Coot for a very specific model-building task, and was found to give an order-of-magnitude speedup for this task. A from-scratch model build using CootVR was also attempted; from this experience it is concluded that currently CootVR does not give a speedup over Coot overall.
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Affiliation(s)
- Hamish Todd
- Huawei Research and Development, Cambridge, United Kingdom
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
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23
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Pettersen EF, Goddard TD, Huang CC, Meng EC, Couch GS, Croll TI, Morris JH, Ferrin TE. UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci 2021; 30:70-82. [PMID: 32881101 PMCID: PMC7737788 DOI: 10.1002/pro.3943] [Citation(s) in RCA: 3666] [Impact Index Per Article: 1222.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/26/2020] [Accepted: 08/28/2020] [Indexed: 12/27/2022]
Abstract
UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.
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Affiliation(s)
- Eric F. Pettersen
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Thomas D. Goddard
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Conrad C. Huang
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Elaine C. Meng
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Gregory S. Couch
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Tristan I. Croll
- Cambridge Institute for Medical Research, Department of HaematologyUniversity of CambridgeCambridgeUK
| | - John H. Morris
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Thomas E. Ferrin
- Department of Pharmaceutical ChemistryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
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24
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Poronnik P, Sellwood MJ. Bioscience education 2030 and beyond: Where will technology take the curriculum? BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2020; 48:563-567. [PMID: 32745335 DOI: 10.1002/bmb.21393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 05/22/2020] [Indexed: 06/11/2023]
Abstract
This brief review explores the ever-increasing role that technological affordances may play in the 21C biochemistry and molecular biology curriculum. We consider the need to develop digital and creative fluencies in our students and the importance of creativity and visualization in learning science. The potential of virtual reality (VR) platforms to complement these goals are discussed with a number of examples. Finally, we look into the future where to see how VR might fit into a future curriculum.
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Affiliation(s)
- Philip Poronnik
- Discipline of Physiology, School of Medical Sciences, The University of Sydney, Camperdown, New South Wales, Australia
| | - Matthew J Sellwood
- Discipline of Physiology, School of Medical Sciences, The University of Sydney, Camperdown, New South Wales, Australia
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25
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Calvelo M, Piñeiro Á, Garcia-Fandino R. An immersive journey to the molecular structure of SARS-CoV-2: Virtual reality in COVID-19. Comput Struct Biotechnol J 2020; 18:2621-2628. [PMID: 32983399 PMCID: PMC7500438 DOI: 10.1016/j.csbj.2020.09.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/11/2020] [Accepted: 09/12/2020] [Indexed: 02/04/2023] Open
Abstract
The era of the explosion of immersive technologies has bumped head-on with the coronavirus disease 2019 (COVID-19) global pandemic caused by the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2). The proper understanding of the three-dimensional structures that compose the virus, as well as of those involved in the infection process and in treatments, is expected to contribute to the advance of fundamental and applied research against this pandemic, including basic molecular biology studies and drug design. Virtual reality (VR) is a powerful technology to visualize the biomolecular structures that are currently being identified for SARS-CoV-2 infection, opening possibilities to significant advances in the understanding of the disease-associate mechanisms and thus to boost new therapies and treatments. The present availability of VR for a large variety of practical applications together with the increasingly easiness, quality and economic access of this technology is transforming the way we interact with digital information. Here, we review the software implementations currently available for VR visualization of SARS-CoV-2 molecular structures, covering a range of virtual environments: CAVEs, desktop software, and cell phone applications, all of them combined with head-mounted devices like cardboards, Oculus Rift or the HTC Vive. We aim to impulse and facilitate the use of these emerging technologies in research against COVID-19 trying to increase the knowledge and thus minimizing risks before placing huge amounts of money for the development of potential treatments.
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Affiliation(s)
- Martín Calvelo
- Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CIQUS), Departamento de Química Orgánica, Universidade de Santiago de Compostela, Spain
| | - Ángel Piñeiro
- Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, Spain
| | - Rebeca Garcia-Fandino
- Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CIQUS), Departamento de Química Orgánica, Universidade de Santiago de Compostela, Spain.,Departamento de Química e Bioquímica, Faculdade de Ciências da Universidade do Porto, Porto, Portugal
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26
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Wang J, Youkharibache P, Zhang D, Lanczycki CJ, Geer RC, Madej T, Phan L, Ward M, Lu S, Marchler GH, Wang Y, Bryant SH, Geer LY, Marchler-Bauer A. iCn3D, a web-based 3D viewer for sharing 1D/2D/3D representations of biomolecular structures. Bioinformatics 2020; 36:131-135. [PMID: 31218344 DOI: 10.1093/bioinformatics/btz502] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 05/03/2019] [Accepted: 06/13/2019] [Indexed: 12/17/2022] Open
Abstract
MOTIVATION Build a web-based 3D molecular structure viewer focusing on interactive structural analysis. RESULTS iCn3D (I-see-in-3D) can simultaneously show 3D structure, 2D molecular contacts and 1D protein and nucleotide sequences through an integrated sequence/annotation browser. Pre-defined and arbitrary molecular features can be selected in any of the 1D/2D/3D windows as sets of residues and these selections are synchronized dynamically in all displays. Biological annotations such as protein domains, single nucleotide variations, etc. can be shown as tracks in the 1D sequence/annotation browser. These customized displays can be shared with colleagues or publishers via a simple URL. iCn3D can display structure-structure alignments obtained from NCBI's VAST+ service. It can also display the alignment of a sequence with a structure as identified by BLAST, and thus relate 3D structure to a large fraction of all known proteins. iCn3D can also display electron density maps or electron microscopy (EM) density maps, and export files for 3D printing. The following example URL exemplifies some of the 1D/2D/3D representations: https://www.ncbi.nlm.nih.gov/Structure/icn3d/full.html?mmdbid=1TUP&showanno=1&show2d=1&showsets=1. AVAILABILITY AND IMPLEMENTATION iCn3D is freely available to the public. Its source code is available at https://github.com/ncbi/icn3d. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jiyao Wang
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Philippe Youkharibache
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA.,National Cancer Institute, National Institutes of Health, Bethesda, MD 20894, USA
| | - Dachuan Zhang
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Christopher J Lanczycki
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Renata C Geer
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Thomas Madej
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA.,National Cancer Institute, National Institutes of Health, Bethesda, MD 20894, USA
| | - Lon Phan
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Minghong Ward
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Shennan Lu
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Gabriele H Marchler
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Yanli Wang
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Stephen H Bryant
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Lewis Y Geer
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
| | - Aron Marchler-Bauer
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD 20894, USA
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27
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Pramudwiatmoko A, Gutmann G, Ueno Y, Kakugo A, Yamamura M, Konagaya A. Tensegrity representation of microtubule objects using unified particle objects and springs. CHEM-BIO INFORMATICS JOURNAL 2020. [DOI: 10.1273/cbij.20.19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- Arif Pramudwiatmoko
- School of Computing, Department of Computer Science, Tokyo Institute of Technology
- Universitas Teknologi Yogyakarta
| | - Gregory Gutmann
- School of Computing, Department of Computer Science, Tokyo Institute of Technology
| | - Yutaka Ueno
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology
| | - Akira Kakugo
- Faculty of Science, Hokkaido University
- Graduate School of Chemical Sciences and Engineering, Hokkaido University
| | - Masayuki Yamamura
- School of Computing, Department of Computer Science, Tokyo Institute of Technology
| | - Akihiko Konagaya
- School of Computing, Department of Computer Science, Tokyo Institute of Technology
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28
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Černý J, Božíková P, Svoboda J, Schneider B. A unified dinucleotide alphabet describing both RNA and DNA structures. Nucleic Acids Res 2020; 48:6367-6381. [PMID: 32406923 PMCID: PMC7293047 DOI: 10.1093/nar/gkaa383] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 04/11/2020] [Accepted: 04/30/2020] [Indexed: 12/13/2022] Open
Abstract
By analyzing almost 120 000 dinucleotides in over 2000 nonredundant nucleic acid crystal structures, we define 96+1 diNucleotide Conformers, NtCs, which describe the geometry of RNA and DNA dinucleotides. NtC classes are grouped into 15 codes of the structural alphabet CANA (Conformational Alphabet of Nucleic Acids) to simplify symbolic annotation of the prominent structural features of NAs and their intuitive graphical display. The search for nontrivial patterns of NtCs resulted in the identification of several types of RNA loops, some of them observed for the first time. Over 30% of the nearly six million dinucleotides in the PDB cannot be assigned to any NtC class but we demonstrate that up to a half of them can be re-refined with the help of proper refinement targets. A statistical analysis of the preferences of NtCs and CANA codes for the 16 dinucleotide sequences showed that neither the NtC class AA00, which forms the scaffold of RNA structures, nor BB00, the DNA most populated class, are sequence neutral but their distributions are significantly biased. The reported automated assignment of the NtC classes and CANA codes available at dnatco.org provides a powerful tool for unbiased analysis of nucleic acid structures by structural and molecular biologists.
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Affiliation(s)
- Jiří Černý
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, CZ-252 50 Vestec, Prague-West, Czech Republic
| | - Paulína Božíková
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, CZ-252 50 Vestec, Prague-West, Czech Republic
| | - Jakub Svoboda
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, CZ-252 50 Vestec, Prague-West, Czech Republic
| | - Bohdan Schneider
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, CZ-252 50 Vestec, Prague-West, Czech Republic
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29
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Goodsell DS, Olson AJ, Forli S. Art and Science of the Cellular Mesoscale. Trends Biochem Sci 2020; 45:472-483. [PMID: 32413324 PMCID: PMC7230070 DOI: 10.1016/j.tibs.2020.02.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 02/12/2020] [Accepted: 02/27/2020] [Indexed: 12/22/2022]
Abstract
Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.
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Affiliation(s)
- David S Goodsell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA; Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, the State University of New Jersey, Piscataway, NJ 08854, USA.
| | - Arthur J Olson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Stefano Forli
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
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30
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Cassidy KC, Šefčík J, Raghav Y, Chang A, Durrant JD. ProteinVR: Web-based molecular visualization in virtual reality. PLoS Comput Biol 2020; 16:e1007747. [PMID: 32231351 PMCID: PMC7147804 DOI: 10.1371/journal.pcbi.1007747] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 04/10/2020] [Accepted: 02/25/2020] [Indexed: 01/21/2023] Open
Abstract
Protein structure determines biological function. Accurately conceptualizing 3D protein/ligand structures is thus vital to scientific research and education. Virtual reality (VR) enables protein visualization in stereoscopic 3D, but many VR molecular-visualization programs are expensive and challenging to use; work only on specific VR headsets; rely on complicated model-preparation software; and/or require the user to install separate programs or plugins. Here we introduce ProteinVR, a web-based application that works on various VR setups and operating systems. ProteinVR displays molecular structures within 3D environments that give useful biological context and allow users to situate themselves in 3D space. Our web-based implementation is ideal for hypothesis generation and education in research and large-classroom settings. We release ProteinVR under the open-source BSD-3-Clause license. A copy of the program is available free of charge from http://durrantlab.com/protein-vr/, and a working version can be accessed at http://durrantlab.com/pvr/. Proteins are microscopic machines that help maintain, defend, and regulate cells. Properly understanding the three-dimensional structures of these machines–as well as the small molecules that interact with them–can advance scientific fields ranging from basic molecular biology to drug discovery. Virtual reality (VR) is a powerful tool for studying protein structures. But many current systems for viewing molecules in VR, though effective, have challenging usability limitations. We have created a new web application called ProteinVR that overcomes these challenges. ProteinVR enables VR molecular visualization in users’ browsers, without requiring them to install a separate program or plugin. It runs on a broad range of desktop, laptop, and mobile devices. For users without VR headsets, ProteinVR leverages mobile-device orientation sensors or video-game-style keyboard navigation to provide an immersive experience. We release ProteinVR as open-source software and have posted a working version at http://durrantlab.com/pvr/.
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Affiliation(s)
- Kevin C Cassidy
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jan Šefčík
- Faculty of Information Technology, Czech Technical University in Prague, Prague, Czech Republic
| | - Yogindra Raghav
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Alexander Chang
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jacob D Durrant
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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31
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Abriata LA. Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers. PeerJ Comput Sci 2020; 6:e260. [PMID: 33816912 PMCID: PMC7924717 DOI: 10.7717/peerj-cs.260] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 01/22/2020] [Indexed: 06/12/2023]
Abstract
For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, most tools available today for immersive modeling require specialized hardware and software, and are costly and cumbersome to set up. These limitations prevent wide use of immersive technologies in education and research centers in a standardized form, which in turn prevents large-scale testing of the actual effects of such technologies on learning and thinking processes. Here, I discuss building blocks for creating marker-based AR applications that run as web pages on regular computers, and explore how they can be exploited to develop web content for handling virtual molecular systems in commodity AR with no more than a webcam- and internet-enabled computer. Examples span from displaying molecules, electron microscopy maps and molecular orbitals with minimal amounts of HTML code, to incorporation of molecular mechanics, real-time estimation of experimental observables and other interactive resources using JavaScript. These web apps provide virtual alternatives to physical, plastic-made molecular modeling kits, where the computer augments the experience with information about spatial interactions, reactivity, energetics, etc. The ideas and prototypes introduced here should serve as starting points for building active content that everybody can utilize online at minimal cost, providing novel interactive pedagogic material in such an open way that it could enable mass-testing of the effect of immersive technologies on chemistry education.
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Affiliation(s)
- Luciano A. Abriata
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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32
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BigTop: a three-dimensional virtual reality tool for GWAS visualization. BMC Bioinformatics 2020; 21:39. [PMID: 32005132 PMCID: PMC6995189 DOI: 10.1186/s12859-020-3373-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 01/17/2020] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) are typically visualized using a two-dimensional Manhattan plot, displaying chromosomal location of SNPs along the x-axis and the negative log-10 of their p-value on the y-axis. This traditional plot provides a broad overview of the results, but offers little opportunity for interaction or expansion of specific regions, and is unable to show additional dimensions of the dataset. RESULTS We created BigTop, a visualization framework in virtual reality (VR), designed to render a Manhattan plot in three dimensions, wrapping the graph around the user in a simulated cylindrical room. BigTop uses the z-axis to display minor allele frequency of each SNP, allowing for the identification of allelic variants of genes. BigTop also offers additional interactivity, allowing users to select any individual SNP and receive expanded information, including SNP name, exact values, and gene location, if applicable. BigTop is built in JavaScript using the React and A-Frame frameworks, and can be rendered using commercially available VR headsets or in a two-dimensional web browser such as Google Chrome. Data is read into BigTop in JSON format, and can be provided as either JSON or a tab-separated text file. CONCLUSIONS Using additional dimensions and interactivity options offered through VR, we provide a new, interactive, three-dimensional representation of the traditional Manhattan plot for displaying and exploring GWAS data.
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33
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Baumann U. Structure-Function Relationships of the Repeat Domains of RTX Toxins. Toxins (Basel) 2019; 11:toxins11110657. [PMID: 31718085 PMCID: PMC6891781 DOI: 10.3390/toxins11110657] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 11/07/2019] [Accepted: 11/09/2019] [Indexed: 01/08/2023] Open
Abstract
RTX proteins are a large family of polypeptides of mainly Gram-negative origin that are secreted into the extracellular medium by a type I secretion system featuring a non-cleavable C-terminal secretion signal, which is preceded by a variable number of nine-residue tandem repeats. The three-dimensional structure forms a parallel β-roll, where β-strands of two parallel sheets are connected by calcium-binding linkers in such a way that a right-handed spiral is built. The Ca2+ ions are an integral part of the structure, which cannot form without them. The structural determinants of this unique architecture will be reviewed with its conservations and variations together with the implication for secretion and folding of these proteins. The general purpose of the RTX domains appears to act as an internal chaperone that keeps the polypeptide unfolded in the calcium-deprived cytosol and triggers folding in the calcium-rich extracellular medium. A rather recent addition to the structural biology of the RTX toxin is a variant occurring in a large RTX adhesin, where this non-canonical β-roll binds to ice and diatoms.
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Affiliation(s)
- Ulrich Baumann
- Institute of Biochemistry, University of Cologne, Zülpicherstrasse 47, D-50674 Cologne, Germany
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34
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Doak DG, Denyer GS, Gerrard JA, Mackay JP, Allison JR. Peppy: A virtual reality environment for exploring the principles of polypeptide structure. Protein Sci 2019; 29:157-168. [PMID: 31622516 DOI: 10.1002/pro.3752] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 10/14/2019] [Accepted: 10/15/2019] [Indexed: 11/06/2022]
Abstract
A key learning outcome for undergraduate biochemistry classes is a thorough understanding of the principles of protein structure. Traditional approaches to teaching this material, which include two-dimensional (2D) images on paper, physical molecular modeling kits, and projections of 3D structures into 2D, are unable to fully capture the dynamic 3D nature of proteins. We have built a virtual reality application, Peppy, aimed at facilitating teaching of the principles of protein secondary structure. Rather than attempt to model molecules with the same fidelity to the underlying physical chemistry as existing, research-oriented molecular modelling approaches, we took the more straightforward approach of harnessing the Unity video game physics engine. Indeed, the simplicity and limitations of our model are strengths in a teaching context, provoking questions and thus deeper understanding. Peppy allows exploration of the relative effects of hydrogen bonding (and electrostatic interactions more generally), backbone φ/ψ angles, basic chemical structure, and steric effects on a polypeptide structure in an accessible format that is novel, dynamic, and fun to use. Apart from describing the implementation and use of Peppy, we discuss the outcomes of deploying Peppy in undergraduate biochemistry courses.
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Affiliation(s)
- David G Doak
- Games Art and Design, Norwich University of the Arts, Norwich, UK
| | - Gareth S Denyer
- School of Life and Environmental Sciences, University of Sydney, New South Wales, Australia
| | - Juliet A Gerrard
- School of Biological Sciences, University of Auckland, Auckland, New Zealand.,School of Chemical Sciences, University of Auckland, Auckland, New Zealand
| | - Joel P Mackay
- School of Life and Environmental Sciences, University of Sydney, New South Wales, Australia
| | - Jane R Allison
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
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35
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O'Connor MB, Bennie SJ, Deeks HM, Jamieson-Binnie A, Jones AJ, Shannon RJ, Walters R, Mitchell TJ, Mulholland AJ, Glowacki DR. Interactive molecular dynamics in virtual reality from quantum chemistry to drug binding: An open-source multi-person framework. J Chem Phys 2019; 150:220901. [PMID: 31202243 DOI: 10.1063/1.5092590] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
As molecular scientists have made progress in their ability to engineer nanoscale molecular structure, we face new challenges in our ability to engineer molecular dynamics (MD) and flexibility. Dynamics at the molecular scale differs from the familiar mechanics of everyday objects because it involves a complicated, highly correlated, and three-dimensional many-body dynamical choreography which is often nonintuitive even for highly trained researchers. We recently described how interactive molecular dynamics in virtual reality (iMD-VR) can help to meet this challenge, enabling researchers to manipulate real-time MD simulations of flexible structures in 3D. In this article, we outline various efforts to extend immersive technologies to the molecular sciences, and we introduce "Narupa," a flexible, open-source, multiperson iMD-VR software framework which enables groups of researchers to simultaneously cohabit real-time simulation environments to interactively visualize and manipulate the dynamics of molecular structures with atomic-level precision. We outline several application domains where iMD-VR is facilitating research, communication, and creative approaches within the molecular sciences, including training machines to learn potential energy functions, biomolecular conformational sampling, protein-ligand binding, reaction discovery using "on-the-fly" quantum chemistry, and transport dynamics in materials. We touch on iMD-VR's various cognitive and perceptual affordances and outline how these provide research insight for molecular systems. By synergistically combining human spatial reasoning and design insight with computational automation, technologies such as iMD-VR have the potential to improve our ability to understand, engineer, and communicate microscopic dynamical behavior, offering the potential to usher in a new paradigm for engineering molecules and nano-architectures.
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Affiliation(s)
- Michael B O'Connor
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Simon J Bennie
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Helen M Deeks
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Alexander Jamieson-Binnie
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Alex J Jones
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Robin J Shannon
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Rebecca Walters
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Thomas J Mitchell
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
| | - David R Glowacki
- Intangible Realities Laboratory, University of Bristol, Cantock's Close, Bristol BS8 1TS, United Kingdom
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36
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Construction of small molecular CTLA4 analogs with CD80-binding affinity. Biochem Biophys Res Commun 2019; 513:694-700. [PMID: 30987824 DOI: 10.1016/j.bbrc.2019.04.041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 04/04/2019] [Indexed: 12/31/2022]
Abstract
A variety of CTLA4-Fc fusion proteins and anti-CTLA4 monoclonal antibody have been approved. Given the shortcomings of macromolecular antibodies, recombinant proteins derived from the tenth unit of human type III fibronectin (FN3) termed monobody were studied as CTLA4 analogs in this study. A peptide EL161 derived from CD80-binding domain (MYPPPY motifs) in the complementarity determining region (CDR) 3 of CTLA4 was found to inhibit the interaction of CTLA4 with CD80 significantly. Afterward, the peptide EL16 as well as the CDR1 of CTLA4 which is also critical for its binding to CD80 were grafted onto FN3 and obtained a novel CD80 binding monobody protein CFN13.2 CFN13 showed 80% binding affinity compared to CTLA4. In addition, to increase the half-life, CFN13 was fused to human IgG1 Fc to generate CFN13-Fc fusion protein. As expected, CFN13-Fc bound to CD80 in a dosage-dependent manner as CFN13 did, and displayed 41.0% and 31.4% inhibition on the interaction of CTLA4-Fc with CD80 at 200 μg/ml and 100 μg/ml respectively. Moreover, peptide EL16 could inhibit CFN13-Fc binding to CD80 significantly, with the inhibition ratio of 64.3% and 52.8% at 100 and 50 μg/ml respectively, indicating that the peptide EL16 and CFN13-Fc shared the similar binding sites with CD80 and the CDR3 motif of CTLA4 contributed more than CDR1 in binding to CD80. In summary, our study provides insights into small molecular analogs of CTLA4.
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37
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Hagita K, Matsumoto S, Ota K. Study of Commodity VR for Computational Material Sciences. ACS OMEGA 2019; 4:3990-3999. [PMID: 31459608 PMCID: PMC6649102 DOI: 10.1021/acsomega.8b03483] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 01/25/2019] [Indexed: 06/10/2023]
Abstract
Recent advancements in virtual reality (VR) devices and software environments make it possible to easily incorporate this technology for many applications, including computational materials science. For studying three-dimensional (3D) structure models and related chemical information, we focused on using a commodity VR device (VIVE) and an authoring tool (Unity). To visualize 3D chemical structures, disturbances like judder due to dropped frames should be eliminated from the VR experience to improve simulations. We propose a simple evaluation method that is straightforward for the nonexpert or novice VR user. We examine the major visualization representations including ball, ball and stick, and isosurface systems. For systematic benchmark measurements, a pendulum from the VR device was used to generate periodic oscillatory motion during measurements of a time series in frames per second (fps). For VIVE with a refresh rate of 90 Hz, judder occurred when less than 90 fps. We demonstrated the system size limitations for the results of molecular dynamics simulations of phase separation of ABA block copolymers and experimental observations of filler morphologies in rubber.
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Affiliation(s)
- Katsumi Hagita
- Department
of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka 239-8686, Japan
| | - Shigenori Matsumoto
- Research
& Development Group, Hitachi, Ltd., 832-2, Horiguchi, Hitachinaka, Ibaraki 312-0034, Japan
| | - Koji Ota
- Advanced
Technology Research & Development Center, Hitachi Chemical Co. Ltd., 48 Wadai, Tsukuba, Ibaraki 300-4247, Japan
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38
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Goodstadt MN, Marti-Renom MA. Communicating Genome Architecture: Biovisualization of the Genome, from Data Analysis and Hypothesis Generation to Communication and Learning. J Mol Biol 2018; 431:1071-1087. [PMID: 30419242 DOI: 10.1016/j.jmb.2018.11.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 10/29/2018] [Accepted: 11/01/2018] [Indexed: 01/07/2023]
Abstract
Genome discoveries at the core of biology are made by visual description and exploration of the cell, from microscopic sketches and biochemical mapping to computational analysis and spatial modeling. We outline the experimental and visualization techniques that have been developed recently which capture the three-dimensional interactions regulating how genes are expressed. We detail the challenges faced in integration of the data to portray the components and organization and their dynamic landscape. The goal is more than a single data-driven representation as interactive visualization for de novo research is paramount to decipher insights on genome organization in space.
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Affiliation(s)
- Mike N Goodstadt
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, Barcelona 08028, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain.
| | - Marc A Marti-Renom
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, Barcelona 08028, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Pg. Lluis Companys 23, Barcelona 08010, Spain.
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