scholarly journals Benefits and constrains of covalency: the role of loop length in protein stability and ligand binding

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sara Linse ◽  
Eva Thulin ◽  
Hanna Nilsson ◽  
Johannes Stigler
Keyword(s):  
Ligand Binding ◽  
Protein Stability ◽  
Extreme Case ◽  
Bound State ◽  
Marginal Effect ◽  
Length Variation ◽  
Loop Length ◽  
Linker Length ◽  
Single Domain Protein ◽  
Calbindin D

AbstractProtein folding is governed by non-covalent interactions under the benefits and constraints of the covalent linkage of the backbone chain. In the current work we investigate the influence of loop length variation on the free energies of folding and ligand binding in a small globular single-domain protein containing two EF-hand subdomains—calbindin D9k. We introduce a linker extension between the subdomains and vary its length between 1 to 16 glycine residues. We find a close to linear relationship between the linker length and the free energy of folding of the Ca2+-free protein. In contrast, the linker length has only a marginal effect on the Ca2+ affinity and cooperativity. The variant with a single-glycine extension displays slightly increased Ca2+ affinity, suggesting that the slightly extended linker allows optimized packing of the Ca2+-bound state. For the extreme case of disconnected subdomains, Ca2+ binding becomes coupled to folding and assembly. Still, a high affinity between the EF-hands causes the non-covalent pair to retain a relatively high apparent Ca2+ affinity. Our results imply that loop length variation could be an evolutionary option for modulating properties such as protein stability and turnover without compromising the energetics of the specific function of the protein.

scholarly journals The influence of Coulomb interaction screening on the excitons in disordered two-dimensional insulators

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
E. V. Kirichenko ◽  
V. A. Stephanovich
Keyword(s):  
Coulomb Interaction ◽  
Energy Levels ◽  
Transition Metal Dichalcogenides ◽  
Extreme Case ◽  
Bound State ◽  
Joint Effect ◽  
Two Dimensional ◽  
Inorganic Substances ◽  
Metal Dichalcogenides ◽  
Interaction Screening

AbstractWe study the joint effect of disorder and Coulomb interaction screening on the exciton spectra in two-dimensional (2D) structures. These can be van der Waals structures or heterostructures of organic (polymeric) semiconductors as well as inorganic substances like transition metal dichalcogenides. We consider 2D screened hydrogenic problem with Rytova–Keldysh interaction by means of so-called fractional Scrödinger equation. Our main finding is that above synergy between screening and disorder either destroys the exciton (strong screening) or promote the creation of a bound state, leading to its collapse in the extreme case. Our second finding is energy levels crossing, i.e. the degeneracy (with respect to index $$\mu $$ μ ) of the exciton eigenenergies at certain discrete value of screening radius. Latter effects may also be related to the quantum manifestations of chaotic exciton behavior in above 2D semiconductor structures. Hence, they should be considered in device applications, where the interplay between dielectric screening and disorder is important.

scholarly journals Protein stability induced by ligand binding correlates with changes in protein flexibility

2003 ◽  
Vol 12 (7) ◽  
pp. 1496-1506 ◽  
Author(s):  
María Soledad Celej ◽  
Guillermo G. Montich ◽  
Gerardo D. Fidelio
Keyword(s):  
Ligand Binding ◽  
Protein Stability ◽  
Protein Flexibility

scholarly journals Intersubunit linker length as a modifier of protein stability: Crystal structures and thermostability of mutant TRAP

2008 ◽  
Vol 17 (3) ◽  
pp. 518-526 ◽  
Author(s):  
Masahiro Watanabe ◽  
Yumiko Mishima ◽  
Ichiro Yamashita ◽  
Sam-Yong Park ◽  
Jeremy R.H. Tame ◽  
...  
Keyword(s):  
Protein Stability ◽  
Crystal Structures ◽  
Linker Length

scholarly journals Simulating Protein-Ligand Binding with Neural Network Potentials

2019 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Christopher Rowley
Keyword(s):  
Neural Network ◽  
Ligand Binding ◽  
Computational Cost ◽  
Bound State ◽  
Drug Binding ◽  
Cancer Drug ◽  
Molecular Conformations ◽  
Drug Molecules ◽  
The Stability ◽  
Dynamics Simulations

Drug molecules adopt a range of conformations both in solution and in their protein-bound state. The strain and reduced flexibility of bound drugs can partially counter the intermolecular interactions that drive protein–ligand binding. To make accurate computational predictions of drug binding affinities, computational chemists have attempted to develop efficient empirical models of these interactions, although these methods are not always reliable. Machine learning has allowed the development of highly-accurate neural-network potentials (NNPs), which are capable of predicting the stability of molecular conformations with accuracy comparable to state-of-the-art quantum chemical calculations but at a billionth of the computational cost. Here, we demonstrate that these methods can be used to represent the intramolecular forces of protein-bound drugs within molecular dynamics simulations. These simulations are shown to be capable of predicting the protein–ligand binding pose and conformational component of the absolute Gibbs energy of binding for a set of drug molecules. Notably, the conformational energy for anti-cancer drug erlotinib binding to its target was found to considerably overestimated by a molecular mechanical model, while the NNP predicts a more moderate value. Although the ANI-1ccX NNP was not trained to describe ionic molecules, reasonable binding poses are predicted for charged ligands, although this method is not suitable for modeling the ligands in solution.

scholarly journals Simulating Protein-Ligand Binding with Neural Network Potentials

2019 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Christopher Rowley
Keyword(s):  
Neural Network ◽  
Ligand Binding ◽  
Computational Cost ◽  
Bound State ◽  
Drug Binding ◽  
Cancer Drug ◽  
Molecular Conformations ◽  
Drug Molecules ◽  
The Stability ◽  
Dynamics Simulations

Drug molecules adopt a range of conformations both in solution and in their protein-bound state. The strain and reduced flexibility of bound drugs can partially counter the intermolecular interactions that drive protein–ligand binding. To make accurate computational predictions of drug binding affinities, computational chemists have attempted to develop efficient empirical models of these interactions, although these methods are not always reliable. Machine learning has allowed the development of highly-accurate neural-network potentials (NNPs), which are capable of predicting the stability of molecular conformations with accuracy comparable to state-of-the-art quantum chemical calculations but at a billionth of the computational cost. Here, we demonstrate that these methods can be used to represent the intramolecular forces of protein-bound drugs within molecular dynamics simulations. These simulations are shown to be capable of predicting the protein–ligand binding pose and conformational component of the absolute Gibbs energy of binding for a set of drug molecules. Notably, the conformational energy for anti-cancer drug erlotinib binding to its target was found to considerably overestimated by a molecular mechanical model, while the NNP predicts a more moderate value. Although the ANI-1ccX NNP was not trained to describe ionic molecules, reasonable binding poses are predicted for charged ligands, although this method is not suitable for modeling the ligands in solution.

scholarly journals Effect of loop length variation on quadruplex-Watson Crick duplex competition

2008 ◽  
Vol 36 (13) ◽  
pp. 4433-4442 ◽  
Author(s):  
Niti Kumar ◽  
Bankanidhi Sahoo ◽  
K. A. S. Varun ◽  
Sudipta Maiti ◽  
Souvik Maiti
Keyword(s):  
Length Variation ◽  
Loop Length

scholarly journals Conformational Changes of Spo0F along the Phosphotransfer Pathway

2005 ◽  
Vol 187 (24) ◽  
pp. 8221-8227 ◽  
Author(s):  
Kottayil I. Varughese
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Conformational Changes ◽  
Solution Structure ◽  
Three Dimensional ◽  
Bound State ◽  
Dimensional Structure ◽  
Single Domain Protein ◽  
Secondary Messenger ◽  
Domain Protein ◽  
Apo State

ABSTRACT Spo0F is a secondary messenger in the sporulation phosphorelay, and its structure has been characterized crystallographically in the apo-state, in the metal-bound state, and in an interacting state with a phosphotransferase. Additionally, the solution structure of the molecule has been characterized by nuclear magnetic resonance techniques in the unliganded state and in complex with beryllofluoride. Spo0F is a single-domain protein with a well-defined three-dimensional structure, but it is capable of adapting to specific conformations for catching and releasing the phosphoryl moiety. This commentary deals with the conformational fluctuations of the molecule as it moves from an apo-state to a metal-coordinated state, to a phosphorylated state, and then to a phosphoryl-transferring state.

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