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  1. Book ; Online: Multiscale Modeling from Macromolecules to Cell: Opportunities and Challenges of Biomolecular Simulations

    Tozzini, Valentina / Palermo, Giulia / Dal Peraro, Matteo / Bonvin, Alexandre M. J. J. / Amaro, Rommie E.

    2020  

    Keywords Science: general issues ; multiscale modeling ; molecular dynamics simulations ; advanced sampling methods ; coarse grained models ; macro-biomolecules ; molecular crowding ; system biology ; bioinformatics
    Size 1 electronic resource (235 pages)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT021230908
    ISBN 9782889661091 ; 2889661091
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Will the Real Cryptic Pocket Please Stand Out?

    Amaro, Rommie E

    Biophysical journal

    2019  Volume 116, Issue 5, Page(s) 753–754

    MeSH term(s) Ligands ; Protein Binding ; Solvents
    Chemical Substances Ligands ; Solvents
    Language English
    Publishing date 2019-01-26
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 218078-9
    ISSN 1542-0086 ; 0006-3495
    ISSN (online) 1542-0086
    ISSN 0006-3495
    DOI 10.1016/j.bpj.2019.01.018
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 235: Show issues Location:
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  3. Article: Toward Understanding "the Ways" of Allosteric Drugs.

    Amaro, Rommie E

    ACS central science

    2017  Volume 3, Issue 9, Page(s) 925–926

    Language English
    Publishing date 2017-09-13
    Publishing country United States
    Document type News
    ISSN 2374-7943
    ISSN 2374-7943
    DOI 10.1021/acscentsci.7b00396
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: DeepWEST: Deep Learning of Kinetic Models with the Weighted Ensemble Simulation Toolkit for Enhanced Sampling.

    Ojha, Anupam Anand / Thakur, Saumya / Ahn, Surl-Hee / Amaro, Rommie E

    Journal of chemical theory and computation

    2023  Volume 19, Issue 4, Page(s) 1342–1359

    Abstract: Recent advances in computational power and algorithms have enabled molecular dynamics (MD) simulations to reach greater time scales. However, for observing conformational transitions associated with biomolecular processes, MD simulations still have ... ...

    Abstract Recent advances in computational power and algorithms have enabled molecular dynamics (MD) simulations to reach greater time scales. However, for observing conformational transitions associated with biomolecular processes, MD simulations still have limitations. Several enhanced sampling techniques seek to address this challenge, including the weighted ensemble (WE) method, which samples transitions between metastable states using many weighted trajectories to estimate kinetic rate constants. However, initial sampling of the potential energy surface has a significant impact on the performance of WE, i.e., convergence and efficiency. We therefore introduce deep-learned kinetic modeling approaches that extract statistically relevant information from short MD trajectories to provide a well-sampled initial state distribution for WE simulations. This hybrid approach overcomes any statistical bias to the system, as it runs short unbiased MD trajectories and identifies meaningful metastable states of the system. It is shown to provide a more refined free energy landscape closer to the steady state that could efficiently sample kinetic properties such as rate constants.
    Language English
    Publishing date 2023-01-31
    Publishing country United States
    Document type Journal Article
    ISSN 1549-9626
    ISSN (online) 1549-9626
    DOI 10.1021/acs.jctc.2c00282
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: A Reflection on Klaus Schulten.

    Amaro, Rommie E

    Journal of chemical theory and computation

    2017  Volume 13, Issue 1, Page(s) 1–2

    MeSH term(s) Biophysics/history ; Computers/history ; History, 20th Century ; Molecular Dynamics Simulation/history ; Physics/history
    Language English
    Publishing date 2017--10
    Publishing country United States
    Document type Biography ; Editorial ; Historical Article
    ISSN 1549-9626
    ISSN (online) 1549-9626
    DOI 10.1021/acs.jctc.6b01111
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Selectivity and Ranking of Tight-Binding JAK-STAT Inhibitors Using Markovian Milestoning with Voronoi Tessellations.

    Ojha, Anupam Anand / Srivastava, Ambuj / Votapka, Lane William / Amaro, Rommie E

    Journal of chemical information and modeling

    2023  Volume 63, Issue 8, Page(s) 2469–2482

    Abstract: Janus kinases (JAK), a group of proteins in the nonreceptor tyrosine kinase (NRTKs) family, play a crucial role in growth, survival, and angiogenesis. They are activated by cytokines through the Janus kinase-signal transducer and activator of a ... ...

    Abstract Janus kinases (JAK), a group of proteins in the nonreceptor tyrosine kinase (NRTKs) family, play a crucial role in growth, survival, and angiogenesis. They are activated by cytokines through the Janus kinase-signal transducer and activator of a transcription (JAK-STAT) signaling pathway. JAK-STAT signaling pathways have significant roles in the regulation of cell division, apoptosis, and immunity. Identification of the V617F mutation in the Janus homology 2 (JH2) domain of JAK2 leading to myeloproliferative disorders has stimulated great interest in the drug discovery community to develop JAK2-specific inhibitors. However, such inhibitors should be selective toward JAK2 over other JAKs and display an extended residence time. Recently, novel JAK2/STAT5 axis inhibitors (N-(1H-pyrazol-3-yl)pyrimidin-2-amino derivatives) have displayed extended residence times (hours or longer) on target and adequate selectivity excluding JAK3. To facilitate a deeper understanding of the kinase-inhibitor interactions and advance the development of such inhibitors, we utilize a multiscale Markovian milestoning with Voronoi tessellations (MMVT) approach within the Simulation-Enabled Estimation of Kinetic Rates v.2 (SEEKR2) program to rank order these inhibitors based on their kinetic properties and further explain the selectivity of JAK2 inhibitors over JAK3. Our approach investigates the kinetic and thermodynamic properties of JAK-inhibitor complexes in a user-friendly, fast, efficient, and accurate manner compared to other brute force and hybrid-enhanced sampling approaches.
    MeSH term(s) Antineoplastic Agents ; Cytokines ; Janus Kinase 2 ; Janus Kinase Inhibitors ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/chemistry ; Signal Transduction ; STAT Transcription Factors/antagonists & inhibitors
    Chemical Substances Antineoplastic Agents ; Cytokines ; Janus Kinase 2 (EC 2.7.10.2) ; Janus Kinase Inhibitors ; Protein Kinase Inhibitors ; STAT Transcription Factors
    Language English
    Publishing date 2023-04-06
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.2c01589
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 1230: Show issues Location:
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  7. Article ; Online: Drug Design Data Resource, Grand Challenge 4, second of two issues.

    Gilson, Michael K / Amaro, Rommie E

    Journal of computer-aided molecular design

    2020  Volume 34, Issue 2, Page(s) 97

    MeSH term(s) Drug Design ; Drug Discovery ; Humans ; Ligands ; Protein Binding
    Chemical Substances Ligands
    Language English
    Publishing date 2020-01-28
    Publishing country Netherlands
    Document type Editorial ; Introductory Journal Article
    ZDB-ID 808166-9
    ISSN 1573-4951 ; 0920-654X
    ISSN (online) 1573-4951
    ISSN 0920-654X
    DOI 10.1007/s10822-020-00296-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2625: Show issues Location:
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  8. Article ; Online: COVID19 - Computational Chemists Meet the Moment.

    Mulholland, Adrian J / Amaro, Rommie E

    Journal of chemical information and modeling

    2020  Volume 60, Issue 12, Page(s) 5724–5726

    MeSH term(s) COVID-19 ; Humans ; SARS-CoV-2
    Language English
    Publishing date 2020-12-23
    Publishing country United States
    Document type Editorial
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.0c01395
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Biomolecular Simulations in the Time of COVID19, and After.

    Amaro, Rommie E / Mulholland, Adrian J

    Computing in science & engineering

    2020  Volume 22, Issue 6, Page(s) 30–36

    Abstract: COVID19 has changed life for people worldwide. Despite lockdowns globally, computational research has pressed on, working remotely and collaborating virtually on research questions in COVID19 and the virus it is caused by, SARS-CoV-2. Molecular ... ...

    Abstract COVID19 has changed life for people worldwide. Despite lockdowns globally, computational research has pressed on, working remotely and collaborating virtually on research questions in COVID19 and the virus it is caused by, SARS-CoV-2. Molecular simulations can help to characterize the function of viral and host proteins and have the potential to contribute to the search for vaccines and treatments. Changes in the
    Keywords covid19
    Language English
    Publishing date 2020-09-15
    Publishing country United States
    Document type Journal Article
    ISSN 1521-9615
    ISSN 1521-9615
    DOI 10.1109/MCSE.2020.3024155
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: A Community Letter Regarding Sharing Biomolecular Simulation Data for COVID-19.

    Amaro, Rommie E / Mulholland, Adrian J

    Journal of chemical information and modeling

    2020  Volume 60, Issue 6, Page(s) 2653–2656

    MeSH term(s) Algorithms ; Artificial Intelligence ; Betacoronavirus/isolation & purification ; COVID-19 ; Computational Biology ; Coronavirus Infections/diagnosis ; Coronavirus Infections/therapy ; Humans ; Information Dissemination ; Models, Biological ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/therapy ; SARS-CoV-2 ; Software
    Keywords covid19
    Language English
    Publishing date 2020-05-01
    Publishing country United States
    Document type Letter
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.0c00319
    Database MEDical Literature Analysis and Retrieval System OnLINE

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