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  1. Article ; Online: Umbrella Sampling Simulations of Cardiac Thin Filament Reveal Thermodynamic Consequences of Troponin I Inhibitory Peptide Mutations.

    Cool, Austin M / Lindert, Steffen

    Journal of chemical information and modeling

    2023  Volume 63, Issue 11, Page(s) 3534–3543

    Abstract: The cardiac thin filament comprises F-actin, tropomyosin, and troponin (cTn). cTn is composed of three subunits: troponin C (cTnC), troponin I (cTnI), and troponin T (cTnT). To computationally study the effect of the thin filament on cTn activation ... ...

    Abstract The cardiac thin filament comprises F-actin, tropomyosin, and troponin (cTn). cTn is composed of three subunits: troponin C (cTnC), troponin I (cTnI), and troponin T (cTnT). To computationally study the effect of the thin filament on cTn activation events, we employed targeted molecular dynamics followed by umbrella sampling using a model of the thin filament to measure the thermodynamics of cTn transition events. Our simulations revealed that the thin filament causes an increase in the free energy required to open the cTnC hydrophobic patch and causes a more favorable interaction between this region and the cTnI switch peptide. Mutations to the cTn complex can lead to cardiomyopathy, a collection of diseases that present clinically with symptoms of hypertrophy or dilation of the cardiac muscle, leading to impairment of the heart's ability to function normally and ultimately myocardial infarction or heart failure. Upon introduction of cardiomyopathic mutations to R145 of cTnI, we observed a general decrease in the free energy of opening the cTnC hydrophobic patch, which is on par with previous experimental results. These mutations also exhibited a decrease in electrostatic interactions between cTnI-R145 and actin-E334. After introduction of a small molecule to the wild-type cTnI-actin interface to intentionally disrupt intersubunit contacts, we successfully observed similar thermodynamic consequences and disruptions to the same protein-protein contacts as observed with the cardiomyopathic mutations. Computational studies utilizing the cTn complex in isolation would have been unable to observe these effects, highlighting the importance of using a more physiologically relevant thin-filament model to investigate the global consequences of cardiomyopathic mutations to the cTn complex.
    MeSH term(s) Troponin I/genetics ; Troponin I/chemistry ; Actins/genetics ; Mutation ; Thermodynamics ; Peptides/genetics ; Calcium
    Chemical Substances Troponin I ; Actins ; Peptides ; Calcium (SY7Q814VUP)
    Language English
    Publishing date 2023-06-01
    Publishing country United States
    Document type Journal Article ; 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.3c00388
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Umbrella Sampling Simulations Measure Switch Peptide Binding and Hydrophobic Patch Opening Free Energies in Cardiac Troponin.

    Cool, Austin M / Lindert, Steffen

    Journal of chemical information and modeling

    2022  Volume 62, Issue 22, Page(s) 5666–5674

    Abstract: The cardiac troponin (cTn) complex is an important regulatory protein in heart contraction. Upon binding of ... ...

    Abstract The cardiac troponin (cTn) complex is an important regulatory protein in heart contraction. Upon binding of Ca
    MeSH term(s) Calcium/metabolism ; Hydrophobic and Hydrophilic Interactions ; Troponin C/chemistry ; Troponin I/metabolism
    Chemical Substances Calcium (SY7Q814VUP) ; Troponin C ; Troponin I
    Language English
    Publishing date 2022-10-25
    Publishing country United States
    Document type Journal Article ; 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.2c00508
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Discovery of Nanomolar Inhibitors for Human Dihydroorotate Dehydrogenase Using Structure-Based Drug Discovery Methods.

    Higgins, William T / Vibhute, Sandip / Bennett, Chad / Lindert, Steffen

    Journal of chemical information and modeling

    2024  Volume 64, Issue 2, Page(s) 435–448

    Abstract: We used a structure-based drug discovery approach to identify novel inhibitors of human dihydroorotate dehydrogenase (DHODH), which is a therapeutic target for treating cancer and autoimmune and inflammatory diseases. In the case of acute myeloid ... ...

    Abstract We used a structure-based drug discovery approach to identify novel inhibitors of human dihydroorotate dehydrogenase (DHODH), which is a therapeutic target for treating cancer and autoimmune and inflammatory diseases. In the case of acute myeloid leukemia, no previously discovered DHODH inhibitors have yet succeeded in this clinical application. Thus, there remains a strong need for new inhibitors that could be used as alternatives to the current standard-of-care. Our goal was to identify novel inhibitors of DHODH. We implemented prefiltering steps to omit PAINS and Lipinski violators at the earliest stages of this project. This enriched compounds in the data set that had a higher potential of favorable oral druggability. Guided by Glide SP docking scores, we found 20 structurally unique compounds from the ChemBridge EXPRESS-pick library that inhibited DHODH with IC
    MeSH term(s) Humans ; Dihydroorotate Dehydrogenase ; Oxidoreductases Acting on CH-CH Group Donors/chemistry ; Oxidoreductases Acting on CH-CH Group Donors/metabolism ; Drug Discovery ; Enzyme Inhibitors/metabolism ; Neoplasms
    Chemical Substances Dihydroorotate Dehydrogenase ; Oxidoreductases Acting on CH-CH Group Donors (EC 1.3.-) ; Enzyme Inhibitors
    Language English
    Publishing date 2024-01-04
    Publishing country United States
    Document type Journal Article
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.3c01358
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Actives-Based Receptor Selection Strongly Increases the Success Rate in Structure-Based Drug Design and Leads to Identification of 22 Potent Cancer Inhibitors.

    Hantz, Eric R / Lindert, Steffen

    Journal of chemical information and modeling

    2022  Volume 62, Issue 22, Page(s) 5675–5687

    Abstract: Computer-aided drug design, an important component of the early stages of the drug discovery pipeline, routinely identifies large numbers of false positive hits that are subsequently confirmed to be experimentally inactive compounds. We have developed a ... ...

    Abstract Computer-aided drug design, an important component of the early stages of the drug discovery pipeline, routinely identifies large numbers of false positive hits that are subsequently confirmed to be experimentally inactive compounds. We have developed a methodology to improve true positive prediction rates in structure-based drug design and have successfully applied the protocol to twenty target systems and identified the top three performing conformers for each of the targets. Receptor performance was evaluated based on the area under the curve of the receiver operating characteristic curve for two independent sets of known actives. For a subset of five diverse cancer-related disease targets, we validated our approach through experimental testing of the top 50 compounds from a blind screening of a small molecule library containing hundreds of thousands of compounds. Our methods of receptor and compound selection resulted in the identification of 22 novel inhibitors in the low μM-nM range, with the most potent being an EGFR inhibitor with an IC
    MeSH term(s) Humans ; Drug Evaluation, Preclinical/methods ; Drug Design ; Drug Discovery/methods ; Molecular Dynamics Simulation ; Neoplasms/drug therapy ; Molecular Docking Simulation
    Language English
    Publishing date 2022-11-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.2c00848
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Computational Exploration and Characterization of Potential Calcium Sensitizing Mutations in Cardiac Troponin C.

    Hantz, Eric R / Lindert, Steffen

    Journal of chemical information and modeling

    2022  Volume 62, Issue 23, Page(s) 6201–6208

    Abstract: Calcium-dependent heart muscle contraction is regulated by the cardiac troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium binding subunit (cNTnC). cNTnC contains one calcium binding site (site II), and altered calcium ...

    Abstract Calcium-dependent heart muscle contraction is regulated by the cardiac troponin protein complex (cTn) and specifically by the N-terminal domain of its calcium binding subunit (cNTnC). cNTnC contains one calcium binding site (site II), and altered calcium binding in this site has been studied for decades. It has been previously shown that cNTnC mutants, which increase calcium sensitization may have therapeutic benefits, such as restoring cardiac muscle contractility and functionality post-myocardial infarction events. Here, we computationally characterized eight mutations for their potential effects on calcium binding affinity in site II of cNTnC. We utilized two distinct methods to estimate calcium binding: adaptive steered molecular dynamics (ASMD) and thermodynamic integration (TI). We observed a sensitizing trend for all mutations based on the employed ASMD methodology. The TI results showed excellent agreement with experimentally known calcium binding affinities in wild-type cNTnC. Based on the TI results, five mutants were predicted to increase calcium sensitivity in site II. This study presents an interesting comparison of the two computational methods, which have both been shown to be valuable tools in characterizing the impacts of calcium sensitivity in mutant cNTnC systems.
    MeSH term(s) Troponin C/chemistry ; Calcium/metabolism ; Troponin I/metabolism ; Protein Binding ; Binding Sites
    Chemical Substances Troponin C ; Calcium (SY7Q814VUP) ; Troponin I
    Language English
    Publishing date 2022-11-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.2c01132
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Computational Methods Elucidate Consequences of Mutations and Post-translational Modifications on Troponin I Effective Concentration to Troponin C.

    Cool, Austin M / Lindert, Steffen

    The journal of physical chemistry. B

    2021  Volume 125, Issue 27, Page(s) 7388–7396

    Abstract: ... ...

    Abstract Ca
    MeSH term(s) Calcium/metabolism ; Mutation ; Myocardium/metabolism ; Protein Processing, Post-Translational ; Troponin C/genetics ; Troponin C/metabolism ; Troponin I/genetics ; Troponin I/metabolism
    Chemical Substances Troponin C ; Troponin I ; Calcium (SY7Q814VUP)
    Language English
    Publishing date 2021-07-02
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 1520-5207
    ISSN (online) 1520-5207
    DOI 10.1021/acs.jpcb.1c03844
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Adaptative Steered Molecular Dynamics Study of Mutagenesis Effects on Calcium Affinity in the Regulatory Domain of Cardiac Troponin C.

    Hantz, Eric R / Lindert, Steffen

    Journal of chemical information and modeling

    2021  Volume 61, Issue 6, Page(s) 3052–3057

    Abstract: Calcium-dependent cardiac muscle contraction is regulated by the protein complex troponin (cTn) and specifically by the regulatory N-terminal domain (N-cTnC) which contains one active ... ...

    Abstract Calcium-dependent cardiac muscle contraction is regulated by the protein complex troponin (cTn) and specifically by the regulatory N-terminal domain (N-cTnC) which contains one active Ca
    MeSH term(s) Calcium/metabolism ; Molecular Dynamics Simulation ; Mutagenesis ; Myocardium/metabolism ; Troponin C/genetics ; Troponin C/metabolism
    Chemical Substances Troponin C ; Calcium (SY7Q814VUP)
    Language English
    Publishing date 2021-06-03
    Publishing country United States
    Document type Journal Article ; 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.1c00419
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Accurate protein structure prediction with hydroxyl radical protein footprinting data.

    Biehn, Sarah E / Lindert, Steffen

    Nature communications

    2021  Volume 12, Issue 1, Page(s) 341

    Abstract: Hydroxyl radical protein footprinting (HRPF) in combination with mass spectrometry reveals the relative solvent exposure of labeled residues within a protein, thereby providing insight into protein tertiary structure. HRPF labels nineteen residues with ... ...

    Abstract Hydroxyl radical protein footprinting (HRPF) in combination with mass spectrometry reveals the relative solvent exposure of labeled residues within a protein, thereby providing insight into protein tertiary structure. HRPF labels nineteen residues with varying degrees of reliability and reactivity. Here, we are presenting a dynamics-driven HRPF-guided algorithm for protein structure prediction. In a benchmark test of our algorithm, usage of the dynamics data in a score term resulted in notable improvement of the root-mean-square deviations of the lowest-scoring ab initio models and improved the funnel-like metric P
    MeSH term(s) Animals ; Humans ; Hydroxyl Radical/chemistry ; Models, Molecular ; Myoglobin/chemistry ; Protein Footprinting/methods ; Proteins/chemistry
    Chemical Substances Myoglobin ; Proteins ; Hydroxyl Radical (3352-57-6)
    Language English
    Publishing date 2021-01-12
    Publishing country England
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-020-20549-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Protein Structure Prediction with Mass Spectrometry Data.

    Biehn, Sarah E / Lindert, Steffen

    Annual review of physical chemistry

    2021  Volume 73, Page(s) 1–19

    Abstract: Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such ... ...

    Abstract Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data.
    MeSH term(s) Hydroxyl Radical ; Mass Spectrometry/methods ; Protein Conformation ; Protein Footprinting ; Proteins/chemistry
    Chemical Substances Proteins ; Hydroxyl Radical (3352-57-6)
    Language English
    Publishing date 2021-11-01
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 1470474-2
    ISSN 1545-1593 ; 0066-426X
    ISSN (online) 1545-1593
    ISSN 0066-426X
    DOI 10.1146/annurev-physchem-082720-123928
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Applications of machine learning in computer-aided drug discovery.

    Turzo, Sm Bargeen Alam / Hantz, Eric R / Lindert, Steffen

    QRB discovery

    2022  Volume 3, Page(s) e14

    Abstract: Machine learning (ML) has revolutionised the field of structure-based drug design (SBDD) in recent years. During the training stage, ML techniques typically analyse large amounts of experimentally determined data to create predictive models in order to ... ...

    Abstract Machine learning (ML) has revolutionised the field of structure-based drug design (SBDD) in recent years. During the training stage, ML techniques typically analyse large amounts of experimentally determined data to create predictive models in order to inform the drug discovery process. Deep learning (DL) is a subfield of ML, that relies on multiple layers of a neural network to extract significantly more complex patterns from experimental data, and has recently become a popular choice in SBDD. This review provides a thorough summary of the recent DL trends in SBDD with a particular focus on de novo drug design, binding site prediction, and binding affinity prediction of small molecules.
    Language English
    Publishing date 2022-09-01
    Publishing country England
    Document type Journal Article ; Review
    ISSN 2633-2892
    ISSN (online) 2633-2892
    DOI 10.1017/qrd.2022.12
    Database MEDical Literature Analysis and Retrieval System OnLINE

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