1
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Mukhaleva E, Ma N, van der Velden WJC, Gogoshin G, Branciamore S, Bhattacharya S, Rodin AS, Vaidehi N. Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling. J Biol Chem 2024; 300:107362. [PMID: 38735478 PMCID: PMC11176750 DOI: 10.1016/j.jbc.2024.107362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 05/03/2024] [Accepted: 05/04/2024] [Indexed: 05/14/2024] Open
Abstract
Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces, it is challenging to determine which amino acid pair interactions are cooperative. In this work, we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with Gα subunits. Our results reveal six GPCR:Gα contacts that are common to the different Gα subtypes and show strong cooperativity in the formation of interface. Both the C terminus helix5 and the core of the G protein are codependent entities and play an important role in GPCR coupling. We show that a promiscuous GPCR coupling to different Gα subtypes, makes all the GPCR:Gα contacts that are specific to each Gα subtype (Gαs, Gαi, and Gαq). This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.
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Affiliation(s)
- Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Wijnand J C van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Grigoriy Gogoshin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Andrei S Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
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2
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Kumar A, Vashisth H. Quantitative Assessment of Energetic Contributions of Residues in a SARS-CoV-2 Viral Enzyme/Nanobody Interface. J Chem Inf Model 2024; 64:2068-2076. [PMID: 38460144 DOI: 10.1021/acs.jcim.3c01933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2024]
Abstract
The highly conserved protease enzyme from SARS-CoV-2 (MPro) is crucial for viral replication and is an attractive target for the design of novel inhibitory compounds. MPro is known to be conformationally flexible and has been stabilized in an extended conformation in a complex with a novel nanobody (NB2B4), which inhibits the dimerization of the enzyme via binding to an allosteric site. However, the energetic contributions of the nanobody residues stabilizing the MPro/nanobody interface remain unresolved. We probed these residues using all-atom MD simulations in combination with alchemical free energy calculations by studying the physical residue-residue interactions and discovered the role of hydrophobic and electrostatic interactions in stabilizing the complex. Specifically, we found via mutational analysis that three interfacial nanobody residues (Y59, R106, and L109) contributed significantly, two residues (L107 and P110) contributed moderately, and two residues (H112 and T113) contributed minimally to the overall binding affinity of the nanobody. We also discovered that the nanobody affinity could be enhanced via a charge-reversal mutation (D62R) that alters the local interfacial electrostatic environment of this residue in the complex. These findings are potentially useful in designing novel synthetic nanobodies as allosteric inhibitors of MPro.
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Affiliation(s)
- Amit Kumar
- Department of Physics and Astronomy, Wayne State University, Detroit, Michigan 48201, United States
| | - Harish Vashisth
- Department of Chemical Engineering and Bioengineering, University of New Hampshire, Durham, New Hampshire 03824, United States
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3
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Muhammed Aziz D, Hassan SA, Amin AAM, Abdullah MN, Qurbani K, Aziz SB. A synergistic investigation of azo-thiazole derivatives incorporating thiazole moieties: a comprehensive exploration of their synthesis, characterization, computational insights, solvatochromism, and multimodal biological activity assessment. RSC Adv 2023; 13:34534-34555. [PMID: 38024963 PMCID: PMC10668576 DOI: 10.1039/d3ra06469g] [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] [Received: 09/22/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
In the present study, a novel series of azo-thiazole derivatives (3a-c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including 1H NMR, 13C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 μg mL-1) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 μg mL-1). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day-1) than Hamazine (28 recovery days, 4.14 mg day-1) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a-c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a-c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.
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Affiliation(s)
- Dara Muhammed Aziz
- Department of Chemistry, College of Sciences, University of Raparin, Kurdistan Regional Government Main Street Ranyah 46012 Iraq
| | - Sangar Ali Hassan
- Department of Chemistry, College of Sciences, University of Raparin, Kurdistan Regional Government Main Street Ranyah 46012 Iraq
| | - Alla Ahmad M Amin
- Department of Chemistry, College of Sciences, University of Raparin, Kurdistan Regional Government Main Street Ranyah 46012 Iraq
| | - Media Noori Abdullah
- Department of Chemistry, College of Science, Salahaddin University Erbil 44002 Iraq
| | - Karzan Qurbani
- Department of Biology, College of Sciences, University of Raparin, Kurdistan Regional Government Main Street Ranyah 46012 Iraq
| | - Shujahadeen B Aziz
- Advanced Polymeric Materials Research Lab, Department of Physics, College of Science, University of Sulaimani, Kurdistan Regional Government Qlyasan Street Sulaimani 46001 Iraq
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4
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Mukhaleva E, Ma N, van der Velden WJC, Gogoshin G, Branciamore S, Bhattacharya S, Rodin AS, Vaidehi N. Bayesian network models identify co-operative GPCR:G protein interactions that contribute to G protein coupling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561618. [PMID: 37873104 PMCID: PMC10592737 DOI: 10.1101/2023.10.09.561618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior of interface interactions and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces it is challenging to determine which amino acid pair interactions are cooperative. In this work we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with G proteins. Our results reveal a strong co-dependency in the formation of interface GPCR:G protein contacts. This observation indicates that cooperativity of GPCR:G protein interactions is necessary for the coupling and selectivity of G proteins and is thus critical for receptor function. We have identified subnetworks containing polar and hydrophobic interactions that are common among multiple GPCRs coupling to different G protein subtypes (Gs, Gi and Gq). These common subnetworks along with G protein-specific subnetworks together confer selectivity to the G protein coupling. This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.
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Affiliation(s)
- Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Wijnand J. C. van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Grigoriy Gogoshin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Andrei S. Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
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5
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Ray Chaudhuri N, Ghosh Dastidar S. Allosteric Boost by TAB1 on the TAK1 Kinase Favorably Sculpts the Thermodynamic Landscape of Activation. J Chem Inf Model 2023; 63:224-239. [PMID: 36374995 DOI: 10.1021/acs.jcim.2c00778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The intricate mechanisms of allosteric regulation in kinases are of general interest to the scientific community for potential therapeutic implications. However, the diversity among kinases and their regulatory routes requires a case-by-case study to widen the repertoire of known mechanisms. The present study achieves this by understanding TAK1 kinase activation by TAB1 as a model phenomenon for the first time. Despite the known capacity of TAK1 to switch between its inactive ("DFG-out") and active-like ("DFG-in") conformations, the questionable role of TAB1 in offering an energetic favor to this has been addressed here using sequential combination of enhanced sampling methods like targeted molecular dynamics (TMD) and Gaussian accelerated molecular dynamics (GaMD). It reveals how a minimal domain of TAB1 sufficiently acts like a "catalytic gear" by favorably sculpting TAK1's thermodynamic landscape (potential of mean force in 2D) that accelerates "in"-"out" conformational switching of the conserved DFG motif. Standard molecular dynamics simulations (∼5 μs) reveal that TAB1 fascinatingly exploits the "lever-like" αF helix of TAK1 kinase domain to remotely propel the DFG motif via subtle helical "unfolding-folding" modifications within the kinase activation loop. The presence of two charged residues on terminal poles of αF helix imparts it, with this unique "lever-like" utility, and this turns out to be one important signature of co-evolution between TAK1 and TAB1. The entire mechanism of TAB1's impact transduction, which is found to be analogous to the moves in the popular "Chinese checker" game, gives a clear proof of the "dynamics-driven allostery" concept in kinases. The findings further benchmark TAK1's known autophosphorylation capacity. A novel insight into kinase allostery is thus provided, which potentiates investigation of similar capacities in other kinases.
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Affiliation(s)
- Nibedita Ray Chaudhuri
- Division of Bioinformatics, Bose Institute, P-1/12 CIT Scheme VII M, Kolkata700054, India
| | - Shubhra Ghosh Dastidar
- Division of Bioinformatics, Bose Institute, P-1/12 CIT Scheme VII M, Kolkata700054, India
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6
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Remote communication between unstructured and structured regions of Bcl-2 tunes its ligand binding capacity: Mechanistic insights. Comput Biol Chem 2022; 100:107736. [DOI: 10.1016/j.compbiolchem.2022.107736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 07/05/2022] [Accepted: 07/16/2022] [Indexed: 11/23/2022]
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7
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Bai F, Puk KM, Liu J, Zhou H, Tao P, Zhou W, Wang S. Sparse group selection and analysis of function-related residue for protein-state recognition. J Comput Chem 2022; 43:1342-1354. [PMID: 35656889 PMCID: PMC9248267 DOI: 10.1002/jcc.26937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 03/23/2022] [Accepted: 05/08/2022] [Indexed: 11/08/2022]
Abstract
Machine learning methods have helped to advance wide range of scientific and technological field in recent years, including computational chemistry. As the chemical systems could become complex with high dimension, feature selection could be critical but challenging to develop reliable machine learning based prediction models, especially for proteins as bio-macromolecules. In this study, we applied sparse group lasso (SGL) method as a general feature selection method to develop classification model for an allosteric protein in different functional states. This results into a much improved model with comparable accuracy (Acc) and only 28 selected features comparing to 289 selected features from a previous study. The Acc achieves 91.50% with 1936 selected feature, which is far higher than that of baseline methods. In addition, grouping protein amino acids into secondary structures provides additional interpretability of the selected features. The selected features are verified as associated with key allosteric residues through comparison with both experimental and computational works about the model protein, and demonstrate the effectiveness and necessity of applying rigorous feature selection and evaluation methods on complex chemical systems.
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Affiliation(s)
- Fangyun Bai
- Department of Management Science and Engineering, Tongji University. Fangyun Bai and Kin Ming Puk contributed equally to this work
| | | | - Jin Liu
- Department of Pharmaceutical Sciences, University of North Texas System College of Pharmacy, University of North Texas Health Science Center
| | - Hongyu Zhou
- Department of Chemistry, Center for Scientific Computation, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University
| | - Peng Tao
- Department of Chemistry, Center for Scientific Computation, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University
| | - Wenyong Zhou
- Department of Management Science and Engineering, Tongji University
| | - Shouyi Wang
- Corresponding author: Shouyi Wang, Department of Industrial, Manufacturing and Systems Engineering, University of Texas at Arlington.
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8
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Pham B, Cheng Z, Lopez D, Lindsay RJ, Foutch D, Majors RT, Shen T. Statistical Analysis of Protein-Ligand Interaction Patterns in Nuclear Receptor RORγ. Front Mol Biosci 2022; 9:904445. [PMID: 35782874 PMCID: PMC9240913 DOI: 10.3389/fmolb.2022.904445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 05/16/2022] [Indexed: 11/21/2022] Open
Abstract
The receptor RORγ belongs to the nuclear receptor superfamily that senses small signaling molecules and regulates at the gene transcription level. Since RORγ has a high basal activity and plays an important role in immune responses, inhibitors targeting this receptor have been a focus for many studies. The receptor-ligand interaction is complex, and often subtle differences in ligand structure can determine its role as an inverse agonist or an agonist. We examined more than 130 existing RORγ crystal structures that have the same receptor complexed with different ligands. We reported the features of receptor-ligand interaction patterns and the differences between agonist and inverse agonist binding. Specific changes in the contact interaction map are identified to distinguish active and inactive conformations. Further statistical analysis of the contact interaction patterns using principal component analysis reveals a dominant mode which separates allosteric binding vs. canonical binding and a second mode which may indicate active vs. inactive structures. We also studied the nature of constitutive activity by performing a 100-ns computer simulation of apo RORγ. Using constitutively active nuclear receptor CAR as a comparison, we identified a group of conserved contacts that have similar contact strength between the two receptors. These conserved contact interactions, especially a couple key contacts in H11–H12 interaction, can be considered essential to the constitutive activity of RORγ. These protein-ligand and internal protein contact interactions can be useful in the development of new drugs that direct receptor activity.
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Affiliation(s)
- Bill Pham
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
| | - Ziju Cheng
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
| | - Daniel Lopez
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
| | - Richard J. Lindsay
- UT-ORNL Graduate School of Genome Science and Technology, Knoxville, TN, United States
| | - David Foutch
- UT-ORNL Graduate School of Genome Science and Technology, Knoxville, TN, United States
| | - Rily T. Majors
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
| | - Tongye Shen
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
- *Correspondence: Tongye Shen,
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9
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Yao XQ, Hamelberg D. From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins. J Phys Chem B 2022; 126:2612-2620. [PMID: 35319195 DOI: 10.1021/acs.jpcb.2c00199] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Initiation of biological processes involving protein-ligand binding, transient protein-protein interactions, or amino acid modifications alters the conformational dynamics of proteins. Accompanying these biological processes are ensuing coupled atomic level conformational changes within the proteins. These conformational changes collectively connect multiple amino acid residues at distal allosteric, binding, and/or active sites. Local changes due to, for example, binding of a regulatory ligand at an allosteric site initiate the allosteric regulation. The allosteric signal propagates throughout the protein structure, causing changes at distal sites, activating, deactivating, or modifying the function of the protein. Hence, dynamical responses within protein structures to stimuli contain critical information on protein function. In this Perspective, we examine the description of allosteric regulation from protein dynamical responses and associated alternative and emerging computational approaches to map allosteric communication pathways between distal sites in proteins at the atomic level.
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Affiliation(s)
- Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
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10
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Hidden electrostatic energy contributions define dynamic allosteric communications within p53 during molecular recognition. Biophys J 2021; 120:4512-4524. [PMID: 34478701 DOI: 10.1016/j.bpj.2021.08.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/03/2021] [Accepted: 08/26/2021] [Indexed: 12/15/2022] Open
Abstract
Molecular recognition is fundamental to transcription regulation. As a transcription factor, the tumor suppressor p53 has to recognize either specific DNA sequences or repressor protein partners. However, the molecular mechanism underlying the p53 conformational switch from the DNA-bound to repressor-bound states is not fully characterized. The highly charged nature of these interacting molecules prompted us to explore the nonbonded energy contributions behind molecular recognition of either a DNA or the repressor protein iASPP by p53 DNA binding domain (p53DBD), using molecular dynamics simulation followed by rigorous analyses of energy terms. Our results illuminate the allosteric pathway by which iASPP binding to p53 diminishes binding affinity between p53 and DNA. Even though the p53DBD uses a common framework of residues for recognizing both DNA and iASPP, a comparison of the electrostatics in the two p53DBD complexes revealed significant differences in residue-wise contributions to the electrostatic energy. We found that an electrostatic allosteric communication path exists in the presence of both substrates. It consists of evolutionarily conserved residues, from residue K120 of the binding loop L1 to a distal residue R213 of p53DBD. K120 is near the DNA in the p53DBD-DNA complex, whereas iASPP binding moves it away from its DNA binding position in the p53DBD-iASPP complex. The "energy hubs" (the residues show a higher degree of connectivity with other residues in the electrostatic networks) determined from the electrostatic network analysis established that this conformational change in K120 completely rewires the electrostatic network from K120 to R213, thereby impeding DNA binding. Furthermore, we found shifting populations of hydrogen bonds and salt bridges reduce pairwise electrostatic energies within p53DBD in its DNA-bound state.
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11
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Lim JPL, Braza MKE, Nellas RB. The effect of ligand affinity to the contact dynamics of the ligand binding domain of thyroid hormone receptor - retinoid X receptor. J Mol Graph Model 2021; 104:107829. [PMID: 33450664 DOI: 10.1016/j.jmgm.2020.107829] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/19/2020] [Accepted: 12/21/2020] [Indexed: 11/19/2022]
Abstract
Ligand-based allostery has been gaining attention for its importance in protein regulation and implication in drug design. One of the interesting cases of protein allostery is the thyroid hormone receptor - retinoid x receptor (TR:RXR), which regulates the gene expression of important physiological processes, such as development and metabolism. It is regulated by the TR native ligand triiodothyronine (T3), which displays anticooperative behavior to the RXR ligand 9-cis retinoic acid (9C). In contrast to this anticooperative behavior, 9C has been shown to increase the activity of TR:RXR. Here we probed the influence of the affinity and the interactions of the TR ligand to the allostery of the TR:RXR through contact dynamics and residue networks. The TR ligand analogs were designed to have higher (G2) and lower (N1) binding energies than T3 when docked to the TR:RXR(9C) complex. The aqueous TR(N1/T3/G2):RXR(9C) complexes were subjected to 30 ns all-atom simulations using theNAMD. The program CAMERRA was used to capture the subtle perturbations of TR:RXR by mapping the residue contact dynamics. Various parts of the TR ligands; including the hydrophilic head, the iodine substituents, and the ligand tail; have been probed for their significance in ligand affinity. The results on the T3 and G2 complexes suggest that ligand affinity can be utilized as a predictor for anticooperative systems on which ligand is more likely to dissociate or remain bound. All 3 complexes also display distinct contact networks for cross-dimer signalling and ligand communication. Understanding ligand-based allostery could potentially unveil secrets of ligand-regulated protein dynamics, a foundation for the design of better and more efficient allosteric drugs.
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Affiliation(s)
- James Peter L Lim
- Institute of Chemistry, College of Science, University of the Philippines Diliman, Quezon City, Philippines
| | - Mac Kevin E Braza
- Institute of Chemistry, College of Science, University of the Philippines Diliman, Quezon City, Philippines
| | - Ricky B Nellas
- Institute of Chemistry, College of Science, University of the Philippines Diliman, Quezon City, Philippines.
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12
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Liu Q, Zhou J, Gao J, Ma W, Wang S, Xing L. Rational design of EGFR dimerization-disrupting peptides: A new strategy to combat drug resistance in targeted lung cancer therapy. Biochimie 2020; 176:128-137. [DOI: 10.1016/j.biochi.2020.07.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/13/2020] [Accepted: 07/18/2020] [Indexed: 12/24/2022]
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13
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Zhang W, Liu J, Shan H, Yin F, Zhong B, Zhang C, Yu X. Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II. J Drug Target 2020; 28:802-810. [PMID: 32354236 DOI: 10.1080/1061186x.2020.1757100] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Wei Zhang
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jiazhi Liu
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Haojie Shan
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Fuli Yin
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Biao Zhong
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Chi Zhang
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Xiaowei Yu
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
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14
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Surpeta B, Sequeiros-Borja CE, Brezovsky J. Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering. Int J Mol Sci 2020; 21:E2713. [PMID: 32295283 PMCID: PMC7215530 DOI: 10.3390/ijms21082713] [Citation(s) in RCA: 9] [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: 03/18/2020] [Revised: 04/10/2020] [Accepted: 04/12/2020] [Indexed: 12/13/2022] Open
Abstract
Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.
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Affiliation(s)
- Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
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15
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Bordelon T, Bobay B, Murphy A, Reese H, Shanahan C, Odeh F, Broussard A, Kormos C, Menegatti S. Translating antibody-binding peptides into peptoid ligands with improved affinity and stability. J Chromatogr A 2019; 1602:284-299. [DOI: 10.1016/j.chroma.2019.05.047] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 05/03/2019] [Accepted: 05/24/2019] [Indexed: 12/18/2022]
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16
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Lindsay RJ, Pham B, Shen T, McCord RP. Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework. Nucleic Acids Res 2019; 46:8143-8152. [PMID: 29992238 PMCID: PMC6144818 DOI: 10.1093/nar/gky604] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 06/25/2018] [Indexed: 11/13/2022] Open
Abstract
Conformational ensembles of biopolymers, whether proteins or chromosomes, can be described using contact matrices. Principal component analysis (PCA) on the contact data has been used to interrogate both protein and chromosome structures and/or dynamics. However, as these fields have developed separately, variants of PCA have emerged. Previously, a variant we hereby term Implicit-PCA (I-PCA) has been applied to chromosome contact matrices and revealed the spatial segregation of active and inactive chromatin. Separately, Explicit-PCA (E-PCA) has previously been applied to proteins and characterized their correlated structure fluctuations. Here, we swapped analysis methods (I-PCA and E-PCA), applying each to a different biopolymer type (chromosome or protein) than the one for which they were initially developed. We find that applying E-PCA to chromosome distance matrices derived from microscopy data can reveal the dominant motion (concerted fluctuation) of these chromosomes. Further, by applying E-PCA to Hi-C data across the human blood cell lineage, we isolated the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we applied I-PCA to simulation snapshots of proteins, the major component reported the consensus features of the structure, making this a promising approach for future analysis of semi-structured proteins.
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Affiliation(s)
- Richard J Lindsay
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Bill Pham
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Tongye Shen
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Rachel Patton McCord
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
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17
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Pham B, Lindsay RJ, Shen T. Effector-Binding-Directed Dimerization and Dynamic Communication between Allosteric Sites of Ribonucleotide Reductase. Biochemistry 2019; 58:697-705. [PMID: 30571104 DOI: 10.1021/acs.biochem.8b01131] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Proteins forming dimers or larger complexes can be strongly influenced by their effector-binding status. We investigated how the effector-binding event is coupled with interface formation via computer simulations, and we quantified the correlation of two types of contact interactions: between the effector and its binding pocket and between protein monomers. This was achieved by connecting the protein dynamics at the monomeric level with the oligomer interface information. We applied this method to ribonucleotide reductase (RNR), an essential enzyme for de novo DNA synthesis. RNR contains two important allosteric sites, the s-site (specificity site) and the a-site (activity site), which bind different effectors. We studied these different binding states with atomistic simulation and used their coarse-grained contact information to analyze the protein dynamics. The results reveal that the effector-protein dynamics at the s-site and dimer interface formation are positively coupled. We further quantify the resonance level between these two events, which can be applied to other similar systems. At the a-site, different effector-binding states (ATP vs dATP) drastically alter the protein dynamics and affect the activity of the enzyme. On the basis of these results, we propose a new mechanism of how the a-site regulates enzyme activation.
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Affiliation(s)
- Bill Pham
- Department of Biochemistry & Cellular and Molecular Biology , University of Tennessee , Knoxville , Tennessee 37996 , United States
| | - Richard J Lindsay
- UT-ORNL Graduate School of Genome Science and Technology , Knoxville , Tennessee 37996 , United States
| | - Tongye Shen
- Department of Biochemistry & Cellular and Molecular Biology , University of Tennessee , Knoxville , Tennessee 37996 , United States
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18
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Lindsay RJ, Siess J, Lohry DP, McGee TS, Ritchie JS, Johnson QR, Shen T. Characterizing protein conformations by correlation analysis of coarse-grained contact matrices. J Chem Phys 2018; 148:025101. [PMID: 29331124 DOI: 10.1063/1.5004141] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We have developed a method to capture the essential conformational dynamics of folded biopolymers using statistical analysis of coarse-grained segment-segment contacts. Previously, the residue-residue contact analysis of simulation trajectories was successfully applied to the detection of conformational switching motions in biomolecular complexes. However, the application to large protein systems (larger than 1000 amino acid residues) is challenging using the description of residue contacts. Also, the residue-based method cannot be used to compare proteins with different sequences. To expand the scope of the method, we have tested several coarse-graining schemes that group a collection of consecutive residues into a segment. The definition of these segments may be derived from structural and sequence information, while the interaction strength of the coarse-grained segment-segment contacts is a function of the residue-residue contacts. We then perform covariance calculations on these coarse-grained contact matrices. We monitored how well the principal components of the contact matrices is preserved using various rendering functions. The new method was demonstrated to assist the reduction of the degrees of freedom for describing the conformation space, and it potentially allows for the analysis of a system that is approximately tenfold larger compared with the corresponding residue contact-based method. This method can also render a family of similar proteins into the same conformational space, and thus can be used to compare the structures of proteins with different sequences.
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Affiliation(s)
- Richard J Lindsay
- UT-ORNL Graduate School of Genome Science and Technology, Knoxville, Tennessee 37996, USA
| | - Jan Siess
- Department of Mathematics, Rutgers University, Piscataway, New Jersey 08854, USA
| | - David P Lohry
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Trevor S McGee
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Jordan S Ritchie
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Quentin R Johnson
- UT-ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
| | - Tongye Shen
- UT-ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
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19
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Abstract
The nuclear receptor family of transcription factor proteins mediates endocrine function and plays critical roles in the development, physiology and pharmacology. Malfunctioning nuclear receptors are associated with several disease states. The functional activity of nuclear receptors is regulated by small molecular hormonal and synthetic molecules. Multiple sources of evidence have identified and distinguished between the different allosteric pathways initiated by ligands, DNA and cofactors such as co-activators and co-repressors. Also, these biophysical studies are attempting to determine how these pathways that regulate co-activator and DNA recognition can control gene transcription. Thus, there is a growing interest in determining the genome-scale impact of allostery in nuclear receptors. Today, it is accepted that a detailed understanding of the allosteric regulatory pathways within the nuclear receptor molecular complex will enable the development of efficient drug therapies in the long term.
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Affiliation(s)
- Elias J Fernandez
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, USA.
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20
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Johnson QR, Lindsay RJ, Shen T. CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue-residue associations. J Comput Chem 2018; 39:1568-1578. [PMID: 29464733 DOI: 10.1002/jcc.25192] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 01/04/2018] [Accepted: 01/29/2018] [Indexed: 12/20/2022]
Abstract
A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue-residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Quentin R Johnson
- National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee, 37996.,Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830
| | - Richard J Lindsay
- Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830.,UT-ORNL Graduate School of Genome Science and Technology, Knoxville, Tennessee, 37996
| | - Tongye Shen
- Oak Ridge National Laboratory, UT-ORNL Center for Molecular Biophysics, Oak Ridge, Tennessee, 37830.,Department of Biochemistry Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee, 37996
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21
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Sinha S, Maity A, Ghosh Dastidar S. BIM Binding Remotely Regulates BAX Activation: Insights from the Free Energy Landscapes. J Chem Inf Model 2018; 58:370-382. [PMID: 29278499 DOI: 10.1021/acs.jcim.7b00628] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Activation of the pro-apoptotic BAX protein, a BCL-2 family member, is known to trigger apoptosis by forming pores in the mitochondrial outer membrane (MOM). While in the cytosol, release of its transmembrane C-terminal helix (called α9 helix) from a well-characterized binding pocket (BC groove) and subsequent permeabilization of the MOM are understood to be the initiating events of the activation. Concerning what initiates BAX activation, so far one plausible suggestion has been that the transient attachment of BH3-only peptide at a distal site from the BC groove triggers the activation process. Yet how this pivotal step displaces α9 from the BC groove has remained poorly understood. Using a combination of standard molecular dynamics and enhanced sampling methods, the energy landscape of BIM (BH3-only peptide) induced BAX activation has been computed, and the molecular origin of those events is hereby reported in atomistic detail. The simulated transition pathway of α9 release reveals that BIM subdues the energetic cost of the process by reducing the activation energy barrier to some extent but mostly by minimizing the free energy difference between the active (α9-released) and inactive (α9-bound) states. Interestingly, the flexibility of the α9 helix itself plays a decisive role in this mechanism. The impact of BIM encounter at the distal site is found to propagate to the α9 (BC groove bound) mostly through conserved pathways of residue level interactions. Overall, the thermodynamic basis of the "hit-and-run" mechanism for activation of the BCL-2 family is presented reconciling the available biochemical observations.
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Affiliation(s)
- Souvik Sinha
- Bioinformatics Centre, Bose Institute , P-1/12 CIT Scheme VII M, Kolkata 700054, India
| | - Atanu Maity
- Bioinformatics Centre, Bose Institute , P-1/12 CIT Scheme VII M, Kolkata 700054, India
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22
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Abstract
Allosteric effect implies ligand binding at one site leading to structural and/or dynamical changes at a distant site. PDZ domains are classic examples of dynamic allostery without conformational changes, where distal side-chain dynamics is modulated on ligand binding and the origin has been attributed to entropic effects. In this work, we unearth the energetic basis of the observed dynamic allostery in a PDZ3 domain protein using molecular dynamics simulations. We demonstrate that electrostatic interaction provides a highly sensitive yardstick to probe the allosteric modulation in contrast to the traditionally used structure-based parameters. There is a significant population shift in the hydrogen-bonded network and salt bridges involving side chains on ligand binding. The ligand creates a local energetic perturbation that propagates in the form of dominolike changes in interresidue interaction pattern. There are significant changes in the nature of specific interactions (nonpolar/polar) between interresidue contacts and accompanied side-chain reorientations that drive the major redistribution of energy. Interestingly, this internal redistribution and rewiring of side-chain interactions led to large cancellations resulting in small change in the overall enthalpy of the protein, thus making it difficult to detect experimentally. In contrast to the prevailing focus on the entropic or dynamic effects, we show that the internal redistribution and population shift in specific electrostatic interactions drive the allosteric modulation in the PDZ3 domain protein.
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23
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Fernandez EJ, Gahlot V, Rodriguez C, Amburn J. DNA-induced unfolding of the thyroid hormone receptor α A/B domain through allostery. FEBS Open Bio 2017; 7:854-864. [PMID: 28593140 PMCID: PMC5458466 DOI: 10.1002/2211-5463.12229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 04/10/2017] [Accepted: 04/11/2017] [Indexed: 01/22/2023] Open
Affiliation(s)
- Elias J. Fernandez
- Biochemistry & Cellular and Molecular Biology; University of Tennessee; Knoxville TN USA
| | - Vandna Gahlot
- Biochemistry & Cellular and Molecular Biology; University of Tennessee; Knoxville TN USA
| | - Celeste Rodriguez
- Biochemistry & Cellular and Molecular Biology; University of Tennessee; Knoxville TN USA
| | - Jacob Amburn
- Biochemistry & Cellular and Molecular Biology; University of Tennessee; Knoxville TN USA
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24
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Sayyed-Ahmad A, Prakash P, Gorfe AA. Distinct dynamics and interaction patterns in H- and K-Ras oncogenic P-loop mutants. Proteins 2017; 85:1618-1632. [PMID: 28498561 DOI: 10.1002/prot.25317] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2017] [Revised: 04/27/2017] [Accepted: 05/05/2017] [Indexed: 12/31/2022]
Abstract
Despite years of study, the structural or dynamical basis for the differential reactivity and oncogenicity of Ras isoforms and mutants remains unclear. In this study, we investigated the effects of amino acid variations on the structure and dynamics of wild type and oncogenic mutants G12D, G12V, and G13D of H- and K-Ras proteins. Based on data from µs-scale molecular dynamics simulations, we show that the overall structure of the proteins remains similar but there are important differences in dynamics and interaction networks. We identified differences in residue interaction patterns around the canonical switch and distal loop regions, and persistent sodium ion binding near the GTP particularly in the G13D mutants. Our results also suggest that different Ras variants have distinct local structural features and interactions with the GTP, variations that have the potential to affect GTP release and hydrolysis. Furthermore, we found that H-Ras proteins and particularly the G12V and G13D variants are significantly more flexible than their K-Ras counterparts. Finally, while most of the simulated proteins sampled the effector-interacting state 2 conformational state, G12V and G13D H-Ras adopted an open switch state 1 conformation that is defective in effector interaction. These differences have implications for Ras GTPase activity, effector or exchange factor binding, dimerization and membrane interaction. Proteins 2017; 85:1618-1632. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Abdallah Sayyed-Ahmad
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, Texas, 77030
| | - Priyanka Prakash
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, Texas, 77030
| | - Alemayehu A Gorfe
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, Texas, 77030
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25
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Sridhar J, Liu J, Komati R, Schroeder R, Jiang Q, Tram P, Riley K, Foroozesh M. Ortho-Methylarylamines as Time-Dependent Inhibitors of Cytochrome P450 1A1 Enzyme. Drug Metab Lett 2017; 10:270-277. [PMID: 28000546 PMCID: PMC6697106 DOI: 10.2174/1872312810666161220155226] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Revised: 12/01/2016] [Accepted: 12/01/2016] [Indexed: 11/22/2022]
Abstract
BACKGROUND Members of the cytochrome P450 1A family metabolize many procarcinogens such as polycyclicaromatic hydrocarbons and heterocyclic amines. Inactivation of these enzymes is a prerequisite for cancer prevention and treatment in certain cases. Mechanism-based inhibition (time and co-factor dependent) is an effective method for the inactivation of these enzymes. Our recent study on emodin analogs revealed an anthraquinone with ortho-methylarylamine moiety that exhibited timedependent inhibition of P450 enzymes 1A1 and 1A2. METHODS To determine whether the amino group or the methyl group or both were responsible for the time-dependent inhibition of these enzymes, a set of eleven compounds containing the orthomethylarylamine moiety were identified through a database search, and studied for the inhibition of the P450 enzymes 1A1, 1A2, 2A6 and 2B1. Our earlier studies on carbazole derivatives provided us with highly selective P450 1A2 inhibitors. Glycine scanning studies were performed on the docked proteinligand complexes of compounds 1-20 in order to understand the contribution of different protein residues towards the ligand binding. RESULTS Four compounds were found to cause selective time-dependent inhibition of P450 1A1 with KI values ranging from 0.24 to 8.25 mM. These compounds exhibited only direct inhibition of P450 1A2. Molecular modeling studies of these molecules indicated that the shapes of the molecules, their binding modes, and the methyl substituent in close proximity (4.5-5.7 Å) to the heme-Fe all contributed to their selective time-dependent inhibition activity on P450 1A1. Glycine scanning studies for P450 1A1 indicated that ligand interaction with Phe123 was the strongest binding contributor and similar studies for P450 1A2 indicated that ligand interactions with the phenylalanine residues 226 and 260 were the largest binding contributors. CONCLUSION Four compounds have been identified that exhibit selective time-dependent inhibition of P450 1A1. Modeling studies have indicated that the proximity of the aromatic methyl group to the heme-Fe could be the main contributor for time-dependent inhibition. Future studies will focus on the confirmation of the involvement of the aromatic methyl group in enzyme inactivation.
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Affiliation(s)
- Jayalakshmi Sridhar
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Jiawang Liu
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Rajesh Komati
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Richard Schroeder
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Quan Jiang
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Phan Tram
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Kevin Riley
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
| | - Maryam Foroozesh
- Department of Chemistry, Xavier University of Louisiana, One Drexel Drive, New Orleans, Louisiana 70125, United States
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26
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Barman A, Hamelberg D. Coupled Dynamics and Entropic Contribution to the Allosteric Mechanism of Pin1. J Phys Chem B 2016; 120:8405-15. [DOI: 10.1021/acs.jpcb.6b02123] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Arghya Barman
- Department
of Chemistry and
the Center for Biotechnology and Drug Design, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department
of Chemistry and
the Center for Biotechnology and Drug Design, Georgia State University, Atlanta, Georgia 30302-3965, United States
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27
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Kalescky R, Zhou H, Liu J, Tao P. Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery. PLoS Comput Biol 2016; 12:e1004893. [PMID: 27115535 PMCID: PMC4846164 DOI: 10.1371/journal.pcbi.1004893] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Accepted: 04/01/2016] [Indexed: 12/22/2022] Open
Abstract
Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier's principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery.
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Affiliation(s)
- Robert Kalescky
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America
| | - Hongyu Zhou
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America
| | - Jin Liu
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America
- Department of Pharmaceutical Sciences, University of North Texas System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, Texas, United States of America
- * E-mail: (JL); (PT)
| | - Peng Tao
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America
- * E-mail: (JL); (PT)
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28
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Clark AK, Wilder JH, Grayson AW, Johnson QR, Lindsay RJ, Nellas RB, Fernandez EJ, Shen T. The Promiscuity of Allosteric Regulation of Nuclear Receptors by Retinoid X Receptor. J Phys Chem B 2016; 120:8338-45. [PMID: 27110634 DOI: 10.1021/acs.jpcb.6b02057] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The promiscuous protein retinoid X receptor (RXR) displays essential allosteric regulation of several members in the nuclear hormone receptor superfamily via heterodimerization and (anti)cooperative binding of cognate ligands. Here, the structural basis of the positive allostery of RXR and constitutive androstane receptor (CAR) is revealed. In contrast, a similar computational approach had previously revealed the mechanism for negative allostery in the complex of RXR and thyroid receptor (TR). By comparing the positive and negative allostery of RXR complexed with CAR and TR respectively, we reported the promiscuous allosteric control involving RXR. We characterize the allosteric mechanism by expressing the correlated dynamics of selected residue-residue contacts which was extracted from atomistic molecular dynamics simulation and statistical analysis. While the same set of residues in the binding pocket of RXR may initiate the residue-residue interaction network, RXR uses largely different sets of contacts (only about one-third identical) and allosteric modes to regulate TR and CAR. The promiscuity of RXR control may originate from multiple factors, including (1) the frustrated fit of cognate ligand 9c to the RXR binding pocket and (2) the different ligand-binding features of TR (loose) versus CAR (tight) to their corresponding cognate ligands.
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Affiliation(s)
| | | | | | - Quentin R Johnson
- UT-ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory , Oak Ridge, Tennessee 37830, United States
| | - Richard J Lindsay
- UT-ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory , Oak Ridge, Tennessee 37830, United States
| | - Ricky B Nellas
- Institute of Chemistry, University of the Philippines Diliman , Quezon City, Philippines
| | | | - Tongye Shen
- UT-ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory , Oak Ridge, Tennessee 37830, United States
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29
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Johnson QR, Lindsay RJ, Nellas RB, Shen T. Pressure-induced conformational switch of an interfacial protein. Proteins 2016; 84:820-7. [DOI: 10.1002/prot.25031] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Revised: 02/04/2016] [Accepted: 03/01/2016] [Indexed: 12/14/2022]
Affiliation(s)
- Quentin R. Johnson
- UT-ORNL Graduate School of Genome Science and Technology; University of Tennessee; Knoxville Tennessee 37996
- Oak Ridge National Laboratory; Center for Molecular Biophysics; Oak Ridge Tennessee 37830
| | - Richard J. Lindsay
- Oak Ridge National Laboratory; Center for Molecular Biophysics; Oak Ridge Tennessee 37830
- Department of Biochemistry and Cellular & Molecular Biology; University of Tennessee; Knoxville Tennessee 37996
| | - Ricky B. Nellas
- Institute of Chemistry, University of the Philippines Diliman; Quezon City Philippines
| | - Tongye Shen
- Oak Ridge National Laboratory; Center for Molecular Biophysics; Oak Ridge Tennessee 37830
- Department of Biochemistry and Cellular & Molecular Biology; University of Tennessee; Knoxville Tennessee 37996
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30
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Dynamical network of residue-residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation. Proc Natl Acad Sci U S A 2016; 113:4735-40. [PMID: 27071107 DOI: 10.1073/pnas.1523573113] [Citation(s) in RCA: 118] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue-residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general.
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Guarnera E, Berezovsky IN. Allosteric sites: remote control in regulation of protein activity. Curr Opin Struct Biol 2016; 37:1-8. [DOI: 10.1016/j.sbi.2015.10.004] [Citation(s) in RCA: 88] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Revised: 10/19/2015] [Accepted: 10/22/2015] [Indexed: 01/22/2023]
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Lang EJM, Heyes LC, Jameson GB, Parker EJ. Calculated pKa Variations Expose Dynamic Allosteric Communication Networks. J Am Chem Soc 2016; 138:2036-45. [DOI: 10.1021/jacs.5b13134] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | | | - Geoffrey B. Jameson
- Institute
of Fundamental Sciences, Massey University, PO Box 11-222, Palmerston North 4422, New Zealand
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Affiliation(s)
- Andre A. S. T. Ribeiro
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
| | - Vanessa Ortiz
- Department of Chemical Engineering, Columbia University, New York, New York 10027, United States
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Johnson QR, Lindsay RJ, Petridis L, Shen T. Investigation of Carbohydrate Recognition via Computer Simulation. Molecules 2015; 20:7700-18. [PMID: 25927900 PMCID: PMC6272577 DOI: 10.3390/molecules20057700] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 04/15/2015] [Accepted: 04/15/2015] [Indexed: 12/11/2022] Open
Abstract
Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.
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Affiliation(s)
- Quentin R Johnson
- UT-ORNL Graduate School of Genome Science and Technology, Knoxville, TN 37996, USA.
| | - Richard J Lindsay
- Department of Biochemistry and Cellular & Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA.
| | - Loukas Petridis
- Center for Molecular Biophysics, Oak Ridge National Lab, Oak Ridge, TN 37830, USA.
| | - Tongye Shen
- Department of Biochemistry and Cellular & Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA.
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