In silico mutational analyses reveal different ligand-binding abilities of double pockets of medaka fish taste receptor type 1 essential for efficient taste recognition

2021 ◽  
Vol 23 (36) ◽  
pp. 20398-20405
Author(s):  
Hayato Aida ◽  
Rikuri Morita ◽  
Yasuteru Shigeta ◽  
Ryuhei Harada
Keyword(s):  
Ligand Binding ◽  
In Silico ◽  
Taste Receptor ◽  
Receptor Type ◽  
Binding Modes ◽  
Medaka Fish ◽  
Multiple Binding

The heterodimer (T1r2a LBD and T1r3 LBD) of medaka fish taste receptor type 1 provides multiple binding modes, which may be helpful in discriminating various taste substances or detecting concentrations of nutrients efficiently.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Sites ◽  
Degrees Of Freedom ◽  
Dynamics Simulation ◽  
Hiv Integrase ◽  
Binding Modes ◽  
System A ◽  
Multiple Binding ◽  
Internal Degrees Of Freedom

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Dimerization of Corticotropin-Releasing Factor Receptor Type 1 Is Not Coupled to Ligand Binding

2005 ◽  
Vol 25 (4-6) ◽  
pp. 251-276 ◽  
Author(s):  
OLIVER KRAETKE ◽  
BURKHARD WIESNER ◽  
JENNY EICHHORST ◽  
JENS FURKERT ◽  
MICHAEL BIENERT ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Corticotropin Releasing Factor ◽  
Receptor Type

scholarly journals Longitudinal Expression of Testicular TAS1R3 from Prepuberty to Sexual Maturity in Congjiang Xiang Pigs

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 437
Author(s):  
Ting Gong ◽  
Weiyong Wang ◽  
Houqiang Xu ◽  
Yi Yang ◽  
Xiang Chen ◽  
...  
Keyword(s):  
Sexual Maturity ◽  
Cell Function ◽  
Expression Patterns ◽  
Taste Receptor ◽  
Receptor Type ◽  
Mrna Levels ◽  
Early Puberty ◽  
Specific Expression

Testicular expression of taste receptor type 1 subunit 3 (T1R3), a sweet/umami taste receptor, has been implicated in spermatogenesis and steroidogenesis in mice. We explored the role of testicular T1R3 in porcine postnatal development using the Congjiang Xiang pig, a rare Chinese miniature pig breed. Based on testicular weights, morphology, and testosterone levels, four key developmental stages were identified in the pig at postnatal days 15–180 (prepuberty: 30 day; early puberty: 60 day; late puberty: 90 day; sexual maturity: 120 day). During development, testicular T1R3 exhibited stage-dependent and cell-specific expression patterns. In particular, T1R3 levels increased significantly from prepuberty to puberty (p < 0.05), and expression remained high until sexual maturity (p < 0.05), similar to results for phospholipase Cβ2 (PLCβ2). The strong expressions of T1R3/PLCβ2 were observed at the cytoplasm of elongating/elongated spermatids and Leydig cells. In the eight-stage cycle of the seminiferous epithelium in pigs, T1R3/PLCβ2 levels were higher in the spermatogenic epithelium at stages II–VI than at the other stages, and the strong expressions were detected in elongating/elongated spermatids and residual bodies. The message RNA (mRNA) levels of taste receptor type 1 subunit 1 (T1R1) in the testis showed a similar trend to levels of T1R3. These data indicate a possible role of T1R3 in the regulation of spermatid differentiation and Leydig cell function.

scholarly journals In silico prediction of the functional and structural consequences of the non-synonymous single nucleotide polymorphism A122V in bovine CXC chemokine receptor type 1

2020 ◽  
Vol 80 (1) ◽  
pp. 39-46
Author(s):  
A. F. Guzzi ◽  
F. S. L. Oliveira ◽  
M. M. S. Amaro ◽  
P. F. Tavares-Filho ◽  
J. E. Gabriel
Keyword(s):  
Amino Acid ◽  
Chemokine Receptor ◽  
In Silico ◽  
Alpha Helix ◽  
Amino Acid Sequences ◽  
Receptor Type ◽  
Amino Acid Residues ◽  
Causal Polymorphism ◽  
Cxc Chemokine

Abstract The current study aimed to assess whether the A122V causal polymorphism promotes alterations in the functional and structural proprieties of the CXC chemokine receptor type 1 protein (CXCR1) of cattle Bos taurus by in silico analyses. Two amino acid sequences of bovine CXCR1 was selected from database UniProtKB/Swiss-Prot: a) non-polymorphic sequence (A7KWG0) with alanine (A) at position 122, and b) polymorphic sequence harboring the A122V polymorphism, substituting alanine by valine (V) at same position. CXCR1 sequences were submitted as input to different Bioinformatics’ tools to examine the effects of this polymorphism on functional and structural stabilities, to predict eventual alterations in the 3-D structural modeling, and to estimate the quality and accuracy of the predictive models. The A122V polymorphism exerted tolerable and non-deleterious effects on the polymorphic CXCR1, and the predictive structural model for polymorphic CXCR1 revealed an alpha helix spatial structure typical of a receptor transmembrane polypeptide. Although higher variations in the distances between pairs of amino acid residues at target-positions are detected in the polymorphic CXCR1 protein, more than 97% of the amino acid residues in both models were located in favored and allowed conformational regions in Ramachandran plots. Evidences has supported that the A122V polymorphism in the CXCR1 protein is associated with increased clinical mastitis incidence in dairy cows. Thus, the findings described herein prove that the replacement of the alanine by valine amino acids provokes local conformational changes in the A122V-harboring CXCR1 protein, which could directly affect its post-translational folding mechanisms and biological functionality.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Sites ◽  
Degrees Of Freedom ◽  
Dynamics Simulation ◽  
Hiv Integrase ◽  
Binding Modes ◽  
System A ◽  
Multiple Binding ◽  
Internal Degrees Of Freedom

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Mode ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Enhanced Sampling ◽  
Recent Success ◽  
Multiple Binding ◽  
Proper Sampling

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>

Sign in / Sign up

Export Citation Format

Share Document