Decision letter: Amidst multiple binding orientations on fork DNA, Saccharolobus MCM helicase proceeds N-first for unwinding

DNA replication requires that the duplex genomic DNA strands be separated; a function that is implemented by ring-shaped hexameric helicases in all Domains. Helicases are composed of two domains, an N- terminal DNA binding domain (NTD) and a C- terminal motor domain (CTD). Replication is controlled by loading of helicases at origins of replication, activation to preferentially encircle one strand, and then translocation to begin separation of the two strands. Using a combination of site-specific DNA footprinting, single-turnover unwinding assays, and unique fluorescence translocation monitoring, we have been able to quantify the binding distribution and the translocation orientation of Saccharolobus (formally Sulfolobus) solfataricus MCM on DNA. Our results show that both the DNA substrate and the C-terminal winged-helix (WH) domain influence the orientation but that translocation on DNA proceeds N-first.

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Multiple steroid-binding orientations: alteration of regiospecificity of dehydroepiandrosterone 2- and 7-hydroxylase activities of cytochrome P-450 2a-5 by mutation of residue 209

Biochemical Journal ◽

10.1042/bj3060029 ◽

1995 ◽

Vol 306 (1) ◽

pp. 29-33 ◽

Cited By ~ 11

Author(s):

M Iwasaki ◽

D G Davis ◽

T A Darden ◽

L G Pedersen ◽

M Negishi

Keyword(s):

Dynamic Equilibrium ◽

The Other ◽

Axial Position ◽

Hydroxylase Activity ◽

Steroid Molecule ◽

Multiple Binding ◽

Critical Residues ◽

Steroid Binding ◽

Binding Orientations ◽

Cytochrome P 450

The mutation of Ala-117 to Val conferred dehydroepiandrosterone (DHEA) hydroxylase activity on cytochrome P-450 2a-4, with the production of both 2 alpha- and 7 alpha-hydroxyDHEA at similar rates. P-450 2a-5 which has Val at position 117, acquired high DHEA hydroxylase activity by mutation of Phe-209. Mutant F209L of P-450 2a-5 exhibited strong regiospecificity at the 2-position of the DHEA molecule with the production of 2 alpha-hydroxy DHEA as the major metabolite. On the other hand, mutant F209V of P-450 2a-5 showed the 7-position to be the major hydroxylation site, 7 beta-hydroxyDHEA and 7 alpha-OHDHEA being produced. Therefore the regiospecificity of DHEA hydroxylase activity of P-450 2a-5 is altered between the 2- and 7-position depending on the amino acid at position 209. Modelling of the DHEA molecule in the pocket of bacterial P-450cam showed that the steroid can be accommodated in at least two orientations for which the 2- or 7- position is near the sixth axial position of the haem. Moreover, these two orientations, which are of similar energy, can be interconverted by a 180 degrees rotation of the steroid molecule around its long axis. These results support the hypothesis that the steroid molecule in the pocket is in dynamic equilibrium with multiple binding orientations and that the equilibrium is apparently determined by a few critical residues including those at positions 117 and 209.

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Binding Orientations and Lipid Interactions of Human Amylin at Zwitterionic and Anionic Lipid Bilayers

Journal of Diabetes Research ◽

10.1155/2016/1749196 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13 ◽

Cited By ~ 5

Author(s):

Zhenyu Qian ◽

Yan Jia ◽

Guanghong Wei

Keyword(s):

Lipid Bilayers ◽

Helical Structure ◽

Terminal Region ◽

Islet Amyloid ◽

Anionic Lipid ◽

Multiple Binding ◽

Preferential Binding ◽

Dynamics Simulations ◽

Binding Orientations ◽

Human Amylin

Increasing evidence suggests that the interaction of human islet amyloid polypeptide (hIAPP) with lipids may facilitate hIAPP aggregation and cause the death of pancreatic isletβ-cells. However, the detailed hIAPP-membrane interactions and the influences of lipid compositions are unclear. In this study, as a first step to understand the mechanism of membrane-mediated hIAPP aggregation, we investigate the binding behaviors of hIAPP monomer at zwitterionic palmitoyloleoyl-phosphatidylcholine (POPC) bilayer by performing atomistic molecular dynamics simulations. The results are compared with those of hIAPP at anionic palmitoyloleoyl-phosphatidylglycerol (POPG) bilayers. We find that the adsorption of hIAPP to POPC bilayer is mainly initiated from the C-terminal region and the peptide adopts a helical structure with multiple binding orientations, while the adsorption to POPG bilayer is mostly initiated from the N-terminal region and hIAPP displays one preferential binding orientation, with its hydrophobic residues exposed to water. hIAPP monomer inserts into POPC lipid bilayers more readily than into POPG bilayers. Peptide-lipid interaction analyses show that the different binding features of hIAPP at POPC and POPG bilayers are attributed to different magnitudes of electrostatic and hydrogen-bonding interactions with lipids. This study provides mechanistic insights into the different interaction behaviors of hIAPP with zwitterionic and anionic lipid bilayers.

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Surface Plasmon Resonance Analysis of Antifungal Azoles Binding to CYP3A4 with Kinetic Resolution of Multiple Binding Orientations†

Biochemistry ◽

10.1021/bi0600042 ◽

2006 ◽

Vol 45 (20) ◽

pp. 6341-6353 ◽

Cited By ~ 47

Author(s):

Josh T. Pearson ◽

John J. Hill ◽

Jennifer Swank ◽

Nina Isoherranen ◽

Kent L. Kunze ◽

...

Keyword(s):

Surface Plasmon Resonance ◽

Surface Plasmon ◽

Plasmon Resonance ◽

Kinetic Resolution ◽

Surface Plasmon Resonance Analysis ◽

Resonance Analysis ◽

Multiple Binding ◽

Binding Orientations

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Reading the phosphorylation code: binding of the 14-3-3 protein to multivalent client phosphoproteins

Biochemical Journal ◽

10.1042/bcj20200084 ◽

2020 ◽

Vol 477 (7) ◽

pp. 1219-1225 ◽

Cited By ~ 4

Author(s):

Nikolai N. Sluchanko

Keyword(s):

Protein Function ◽

Intrinsically Disordered Protein ◽

Structural Basis ◽

Major Protein ◽

Post Translational Modifications ◽

Protein Protein Interaction ◽

Intrinsically Disordered ◽

Biochemical Journal ◽

Multiple Binding ◽

And Control

Many major protein–protein interaction networks are maintained by ‘hub’ proteins with multiple binding partners, where interactions are often facilitated by intrinsically disordered protein regions that undergo post-translational modifications, such as phosphorylation. Phosphorylation can directly affect protein function and control recognition by proteins that ‘read’ the phosphorylation code, re-wiring the interactome. The eukaryotic 14-3-3 proteins recognizing multiple phosphoproteins nicely exemplify these concepts. Although recent studies established the biochemical and structural basis for the interaction of the 14-3-3 dimers with several phosphorylated clients, understanding their assembly with partners phosphorylated at multiple sites represents a challenge. Suboptimal sequence context around the phosphorylated residue may reduce binding affinity, resulting in quantitative differences for distinct phosphorylation sites, making hierarchy and priority in their binding rather uncertain. Recently, Stevers et al. [Biochemical Journal (2017) 474: 1273–1287] undertook a remarkable attempt to untangle the mechanism of 14-3-3 dimer binding to leucine-rich repeat kinase 2 (LRRK2) that contains multiple candidate 14-3-3-binding sites and is mutated in Parkinson's disease. By using the protein-peptide binding approach, the authors systematically analyzed affinities for a set of LRRK2 phosphopeptides, alone or in combination, to a 14-3-3 protein and determined crystal structures for 14-3-3 complexes with selected phosphopeptides. This study addresses a long-standing question in the 14-3-3 biology, unearthing a range of important details that are relevant for understanding binding mechanisms of other polyvalent proteins.

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Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

10.26434/chemrxiv.12670676.v2 ◽

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>

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

10.26434/chemrxiv.5406907.v2 ◽

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>

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

10.26434/chemrxiv.5406907 ◽

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>

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Faculty Opinions recommendation of Dynamic binding orientations direct activity of HIV reverse transcriptase.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1108800.564758 ◽

2008 ◽

Author(s):

Vincent Emery

Keyword(s):

Reverse Transcriptase ◽

Hiv Reverse Transcriptase ◽

Dynamic Binding ◽

Binding Orientations

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