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Article ; Online: G Protein Activation Occurs via a Largely Universal Mechanism.

Vithani, Neha / Todd, Tyson D / Singh, Sukrit / Trent, Tony / Blumer, Kendall J / Bowman, Gregory R

The journal of physical chemistry. B

2024 Volume 128, Issue 15, Page(s) 3554–3562

Abstract: Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our ... ...

Abstract	Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over pathway-II, which we experimentally corroborate by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.
MeSH term(s)	Allosteric Regulation ; Proteins/chemistry ; Computer Simulation ; GTP-Binding Protein alpha Subunits/genetics
Chemical Substances	Proteins ; GTP-Binding Protein alpha Subunits
Language	English
Publishing date	2024-04-05
Publishing country	United States
Document type	Journal Article
ISSN	1520-5207
ISSN (online)	1520-5207
DOI	10.1021/acs.jpcb.3c07028
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Correction to Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex.

Zhang, Ivy / Rufa, Dominic A / Pulido, Iván / Henry, Michael M / Rosen, Laura E / Hauser, Kevin / Singh, Sukrit / Chodera, John D

Journal of chemical theory and computation

2024 Volume 20, Issue 2, Page(s) 990–991

Language	English
Publishing date	2024-01-02
Publishing country	United States
Document type	Published Erratum
ISSN	1549-9626
ISSN (online)	1549-9626
DOI	10.1021/acs.jctc.3c01298
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Article: Death by a Thousand Cuts â€" Combining Kinase Inhibitors for Selective Target Inhibition and Rational Polypharmacology.

Outhwaite, Ian R / Singh, Sukrit / Berger, Benedict-Tilman / Knapp, Stefan / Chodera, John D / Seeliger, Markus A

bioRxiv : the preprint server for biology

2023

Abstract: Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. The high sequence and structural conservation of the catalytic kinase domain complicates the development of ... ...

Abstract	Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. The high sequence and structural conservation of the catalytic kinase domain complicates the development of specific kinase inhibitors. As a consequence, most kinase inhibitors also inhibit off-target kinases which complicates the interpretation of phenotypic responses. Additionally, inhibition of off-targets may cause toxicity in patients. Therefore, highly selective kinase inhibition is a major goal in both biomedical research and clinical practice. Currently, efforts to improve selective kinase inhibition are dominated by the development of new kinase inhibitors. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target activities. We have developed a multicompound-multitarget scoring (MMS) method framework that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables rational polypharmacology by allowing optimization of inhibitor combinations against multiple selected on-targets and off-targets. Using MMS with previously published chemogenomic kinase inhibitor datasets we determine inhibitor combinations that achieve potent activity against a target kinase and that are more selective than the most selective single inhibitor against that target. We validate the calculated effect and selectivity of a combination of inhibitors using the
Language	English
Publishing date	2023-01-16
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.13.523972
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Article ; Online: Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting.

Outhwaite, Ian R / Singh, Sukrit / Berger, Benedict-Tilman / Knapp, Stefan / Chodera, John D / Seeliger, Markus A

eLife

2023 Volume 12

Abstract: Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicate the ... ...

Abstract	Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicate the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.
MeSH term(s)	Humans ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/chemistry ; Antineoplastic Agents/therapeutic use ; Phosphotransferases ; Catalytic Domain ; Neoplasms/drug therapy
Chemical Substances	Protein Kinase Inhibitors ; Antineoplastic Agents ; Phosphotransferases (EC 2.7.-)
Language	English
Publishing date	2023-12-04
Publishing country	England
Document type	Journal Article
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.86189
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Article ; Online: Identifying and Overcoming the Sampling Challenges in Relative Binding Free Energy Calculations of a Model Protein:Protein Complex.

Zhang, Ivy / Rufa, Dominic A / Pulido, Iván / Henry, Michael M / Rosen, Laura E / Hauser, Kevin / Singh, Sukrit / Chodera, John D

Journal of chemical theory and computation

2023 Volume 19, Issue 15, Page(s) 4863–4882

Abstract: Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on ... ...

Abstract	Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a graphics processing unit (GPU)-accelerated open-source relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches─alchemical replica exchange and alchemical replica exchange with solute tempering─for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and is available at https://github.com/choderalab/perses.
MeSH term(s)	Thermodynamics ; Molecular Dynamics Simulation ; Entropy ; Protein Binding ; Amino Acids
Chemical Substances	Amino Acids
Language	English
Publishing date	2023-07-14
Publishing country	United States
Document type	Journal Article
ISSN	1549-9626
ISSN (online)	1549-9626
DOI	10.1021/acs.jctc.3c00333
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Article: Identifying and overcoming the sampling challenges in relative binding free energy calculations of a model protein:protein complex.

Zhang, Ivy / Rufa, Dominic A / Pulido, Iván / Henry, Michael M / Rosen, Laura E / Hauser, Kevin / Singh, Sukrit / Chodera, John D

bioRxiv : the preprint server for biology

2023

Abstract	Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a GPU-accelerated open-source relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches-alchemical replica exchange and alchemical replica exchange with solute tempering-for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally-determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and available at https://github.com/choderalab/perses .
Language	English
Publishing date	2023-06-21
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.03.07.530278
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Article ; Online: Quantifying Allosteric Communication via Both Concerted Structural Changes and Conformational Disorder with CARDS.

Singh, Sukrit / Bowman, Gregory R

Journal of chemical theory and computation

2017 Volume 13, Issue 4, Page(s) 1509–1517

Abstract: Allosteric (i.e., long-range) communication within proteins is crucial for many biological processes, such as the activation of signaling cascades in response to specific stimuli. However, the physical basis for this communication remains unclear. ... ...

Abstract	Allosteric (i.e., long-range) communication within proteins is crucial for many biological processes, such as the activation of signaling cascades in response to specific stimuli. However, the physical basis for this communication remains unclear. Existing computational methods for identifying allostery focus on the role of concerted structural changes, but recent experimental work demonstrates that disorder is also an important factor. Here, we introduce the Correlation of All Rotameric and Dynamical States (CARDS) framework for quantifying correlations between both the structure and disorder of different regions of a protein. To quantify disorder, we draw inspiration from methods for quantifying "dynamic heterogeneity" from chemical physics to classify segments of a dihedral's time evolution as being in either ordered or disordered regimes. To demonstrate the utility of this approach, we apply CARDS to the Catabolite Activator Protein (CAP), a transcriptional activator that is regulated by Cyclic Adenosine MonoPhosphate (cAMP) binding. We find that CARDS captures allosteric communication between the two cAMP-Binding Domains (CBDs). Importantly, CARDS reveals that this coupling is dominated by disorder-mediated correlations, consistent with NMR experiments that establish allosteric coupling between the CBDs occurs without a concerted structural change. CARDS also recapitulates an enhanced role for disorder in the communication between the DNA-Binding Domains (DBDs) and CBDs in the S62F variant of CAP. Finally, we demonstrate that using CARDS to find communication hotspots identifies regions of CAP that are in allosteric communication without foreknowledge of their identities. Therefore, we expect CARDS to be of great utility for both understanding and predicting allostery.
MeSH term(s)	Allosteric Regulation ; Cyclic AMP/chemistry ; DNA/chemistry ; Molecular Dynamics Simulation ; Molecular Structure ; Proteins/chemistry
Chemical Substances	Proteins ; DNA (9007-49-2) ; Cyclic AMP (E0399OZS9N)
Language	English
Publishing date	2017-03-22
Publishing country	United States
Document type	Journal Article
ISSN	1549-9626
ISSN (online)	1549-9626
DOI	10.1021/acs.jctc.6b01181
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Article ; Online: Simulation of spontaneous G protein activation reveals a new intermediate driving GDP unbinding.

Sun, Xianqiang / Singh, Sukrit / Blumer, Kendall J / Bowman, Gregory R

eLife

2018 Volume 7

Abstract: Activation of heterotrimeric G proteins is a key step in many signaling cascades. However, a complete mechanism for this process, which requires allosteric communication between binding sites that are ~30 Å apart, remains elusive. We construct an ... ...

Abstract	Activation of heterotrimeric G proteins is a key step in many signaling cascades. However, a complete mechanism for this process, which requires allosteric communication between binding sites that are ~30 Å apart, remains elusive. We construct an atomically detailed model of G protein activation by combining three powerful computational methods: metadynamics, Markov state models (MSMs), and CARDS analysis of correlated motions. We uncover a mechanism that is consistent with a wide variety of structural and biochemical data. Surprisingly, the rate-limiting step for GDP release correlates with tilting rather than translation of the GPCR-binding helix 5. β-Strands 1 - 3 and helix 1 emerge as hubs in the allosteric network that links conformational changes in the GPCR-binding site to disordering of the distal nucleotide-binding site and consequent GDP release. Our approach and insights provide foundations for understanding disease-implicated G protein mutants, illuminating slow events in allosteric networks, and examining unbinding processes with slow off-rates.
MeSH term(s)	Allosteric Regulation ; Binding Sites ; GTP-Binding Protein alpha Subunits, Gq-G11/chemistry ; GTP-Binding Protein alpha Subunits, Gq-G11/metabolism ; GTP-Binding Proteins/chemistry ; GTP-Binding Proteins/metabolism ; Guanosine Diphosphate/chemistry ; Guanosine Diphosphate/metabolism ; Markov Chains ; Molecular Dynamics Simulation ; Probability ; Protein Structure, Secondary ; Receptors, G-Protein-Coupled/chemistry ; Receptors, G-Protein-Coupled/metabolism ; Thermodynamics
Chemical Substances	Receptors, G-Protein-Coupled ; Guanosine Diphosphate (146-91-8) ; GTP-Binding Proteins (EC 3.6.1.-) ; GTP-Binding Protein alpha Subunits, Gq-G11 (EC 3.6.5.1)
Language	English
Publishing date	2018-10-05
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.38465
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Article ; Online: SARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential.

Vithani, Neha / Ward, Michael D / Zimmerman, Maxwell I / Novak, Borna / Borowsky, Jonathan H / Singh, Sukrit / Bowman, Gregory R

Biophysical journal

2021 Volume 120, Issue 14, Page(s) 2880–2889

Abstract: Coronaviruses have caused multiple epidemics in the past two decades, in addition to the current COVID-19 pandemic that is severely damaging global health and the economy. Coronaviruses employ between 20 and 30 proteins to carry out their viral ... ...

Abstract	Coronaviruses have caused multiple epidemics in the past two decades, in addition to the current COVID-19 pandemic that is severely damaging global health and the economy. Coronaviruses employ between 20 and 30 proteins to carry out their viral replication cycle, including infection, immune evasion, and replication. Among these, nonstructural protein 16 (Nsp16), a 2'-O-methyltransferase, plays an essential role in immune evasion. Nsp16 achieves this by mimicking its human homolog, CMTr1, which methylates mRNA to enhance translation efficiency and distinguish self from other. Unlike human CMTr1, Nsp16 requires a binding partner, Nsp10, to activate its enzymatic activity. The requirement of this binding partner presents two questions that we investigate in this manuscript. First, how does Nsp10 activate Nsp16? Although experimentally derived structures of the active Nsp16/Nsp10 complex exist, structures of inactive, monomeric Nsp16 have yet to be solved. Therefore, it is unclear how Nsp10 activates Nsp16. Using over 1 ms of molecular dynamics simulations of both Nsp16 and its complex with Nsp10, we investigate how the presence of Nsp10 shifts Nsp16's conformational ensemble to activate it. Second, guided by this activation mechanism and Markov state models, we investigate whether Nsp16 adopts inactive structures with cryptic pockets that, if targeted with a small molecule, could inhibit Nsp16 by stabilizing its inactive state. After identifying such a pocket in SARS-CoV2 Nsp16, we show that this cryptic pocket also opens in SARS-CoV1 and MERS but not in human CMTr1. Therefore, it may be possible to develop pan-coronavirus antivirals that target this cryptic pocket.
Language	English
Publishing date	2021-03-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	218078-9
ISSN	1542-0086 ; 0006-3495
ISSN (online)	1542-0086
ISSN	0006-3495
DOI	10.1016/j.bpj.2021.03.024
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Article ; Online: A cryptic pocket in Ebola VP35 allosterically controls RNA binding.

Cruz, Matthew A / Frederick, Thomas E / Mallimadugula, Upasana L / Singh, Sukrit / Vithani, Neha / Zimmerman, Maxwell I / Porter, Justin R / Moeder, Katelyn E / Amarasinghe, Gaya K / Bowman, Gregory R

Nature communications

2022 Volume 13, Issue 1, Page(s) 2269

Abstract: Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying ... ...

Abstract	Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola virus viral protein 35 (VP35). VP35 plays multiple essential roles in Ebola's replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these results, we expect this pipeline will be applicable to other proteins.
MeSH term(s)	DNA Viruses/genetics ; Ebolavirus/genetics ; Hemorrhagic Fever, Ebola ; Humans ; RNA, Double-Stranded/genetics ; Viral Proteins/genetics ; Viral Regulatory and Accessory Proteins/genetics
Chemical Substances	RNA, Double-Stranded ; Viral Proteins ; Viral Regulatory and Accessory Proteins
Language	English
Publishing date	2022-04-27
Publishing country	England
Document type	Journal Article ; 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	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-29927-9
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