Investigation of α-conotoxin unbinding using umbrella sampling

Yu, Rilei; Tabassum, Nargis; Jiang, Tao

doi:10.1016/j.bmcl.2016.01.013

Cited by 10 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The umbrella sampling is more efficient than MD simulations for conformation sampling, and it has been frequently applied to predict the binding free energies of the conotoxins to their target proteins [ 41 , 42 , 43 , 44 , 45 , 46 ]. In this study, umbrella sampling was used to predict the binding affinities of PIIIA against varied Na V subtypes.…”

Section: Resultsmentioning

confidence: 99%

Determination of the μ-Conotoxin PIIIA Specificity Against Voltage-Gated Sodium Channels from Binding Energy Calculations

et al. 2018

Self Cite

View full text Add to dashboard Cite

Voltage-gated sodium (NaV) channels generate and propagate action potentials in excitable cells, and several NaV subtypes have become important targets for pain management. The μ-conotoxins inhibit subtypes of the NaV with varied specificity but often lack of specificity to interested subtypes. Engineering the selectivity of the μ-conotoxins presents considerable complexity and challenge, as it involves the optimization of their binding affinities to multiple highly conserved NaV subtypes. In this study, a model of NaV1.4 bound with μ-conotoxin PIIIA complex was constructed using homology modeling, docking, molecular dynamic simulations and binding energy calculations. The accuracy of this model was confirmed based on the experimental mutagenesis data. The complex models of PIIIA bound with varied subtypes of NaV1.x (x = 1, 2, 3, 5, 6, 7, 8, or 9) were built using NaV1.4/PIIIA complex as a template, and refined using molecular dynamic simulations. The binding affinities of PIIIA to varied subtypes of NaV1.x (x = 1 to 9) were calculated using the Molecular Mechanics Generalized Born/Surface Area (MMGB/SA) and umbrella sampling, and were compared with the experimental values. The binding affinities calculated using MMGB/SA and umbrella sampling are correlated with the experimental values, with the former and the latter giving correlation coefficient of 0.41 (R2) and 0.68 (R2), respectively. Binding energy decomposition suggests that conserved and nonconserved residues among varied NaV subtypes have a synergistic effect on the selectivity of PIIIA.

show abstract

Section: Resultsmentioning

confidence: 99%

Determination of the μ-Conotoxin PIIIA Specificity Against Voltage-Gated Sodium Channels from Binding Energy Calculations

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…To explore this hypothesis, the binding interaction between the enzyme and metal ion was investigated for the wild type system and its C122A mutant. Thus, the binding energy of Mn(II) was derived from the potential of mean force (PMF) extracted from umbrella sampling simulations . Umbrella sampling is based on the idea that by running several restrained MD simulations in which each window explore a particular region along the reaction coordinate between two interacting species (ξ), the entire conformational space is sampled.…”

Section: Materials and Methods: In Silico Modelingmentioning

confidence: 99%

Homology model of the human tRNA splicing ligase RtcB

et al. 2017

View full text Add to dashboard Cite

RtcB is an essential human tRNA ligase required for ligating the 2',3'-cyclic phosphate and 5'-hydroxyl termini of cleaved tRNA halves during tRNA splicing and XBP1 fragments during endoplasmic reticulum stress. Activation of XBP1 has been implicated in various human tumors including breast cancer. Here we present, for the first time, a homology model of human RtcB (hRtcB) in complex with manganese and covalently bound GMP built from the Pyrococcus horikoshii RtcB (bRtcB) crystal structure, PDB ID 4DWQA. The structure is analyzed in terms of stereochemical quality, folding reliability, secondary structure similarity with bRtcB, druggability of the active site binding pocket and its metal-binding microenvironment. In comparison with bRtcB, loss of a manganese-coordinating water and movement of Asn226 (Asn202 in 4DWQA) to form metal-ligand coordination, demonstrates the uniqueness of the hRtcB model. Rotation of GMP leads to the formation of an additional metal-ligand coordination (Mn-O). Umbrella sampling simulations of Mn binding in wild type and the catalytically inactive C122A mutant reveal a clear reduction of Mn binding ability in the mutant, thus explaining the loss of activity therein. Our results furthermore clearly show that the GTP binding site of the enzyme is a well-defined pocket that can be utilized as target site for in silico drug discovery.

show abstract

“…This is the case for ligand unbinding, where the time scale reaches up to several hours or days, and is thus too computationally expensive for a single unbiased MD simulation starting from the ligand bound conformation; nowadays it is possible to reach the millisecond time scale on specialized machines (Shaw et al 2009). Kinetic descriptions of binding and unbinding have been addressed by several diferent approaches, including, but not limited to, methods introducing an energy bias as a scalar in the potential energy equation of the system (Fukunishi et al 2002;Hamelberg et al 2004;Luitz and Zacharias 2014;Mollica et al 2015Mollica et al , 2016Pierce et al 2012;Sinko et al 2013;Wang et al 2013) and methods requiring a preliminary deinition of a set of collective variables (CVs) to be biased during the simulation (Barducci et al 2011;Bui et al 2003;Gervasio et al 2005;Guo et al 2016;Isralewitz et al 2001;Laio and Parrinello 2002;Laio et al 2005;Li 2005;Patel et al 2014;Torrie and Valleau 1977;Yu et al 2016). CVs can be for example intermolecular or interatomic distances, angles formed by atoms or group of atoms, coordination numbers, degree of solvation and they are used in order to drive the binding/unbinding transition and to map the corresponding energy proile.…”

Section: U N C O R R E C T E D P R O O Fmentioning

confidence: 99%

Impact of protein–ligand solvation and desolvation on transition state thermodynamic properties of adenosine A2A ligand binding kinetics

Deganutti¹,

Zhukov²,

Deflorian³

et al. 2017

In Silico Pharmacol.

View full text Add to dashboard Cite

Ligand-protein binding kinetic rates are growing in importance as parameters to consider in drug discovery and lead optimization. In this study we analysed using surface plasmon resonance (SPR) the transition state (TS) properties of a set of six adenosine A receptor inhibitors, belonging to both the xanthine and the triazolo-triazine scaffolds. SPR highlighted interesting differences among the ligands in the enthalpic and entropic components of the TS energy barriers for the binding and unbinding events. To better understand at a molecular level these differences, we developed suMetaD, a novel molecular dynamics (MD)-based approach combining supervised MD and metadynamics. This method allows simulation of the ligand unbinding and binding events. It also provides the system conformation corresponding to the highest energy barrier the ligand is required to overcome to reach the final state. For the six ligands evaluated in this study their TS thermodynamic properties were linked in particular to the role of water molecules in solvating/desolvating the pocket and the small molecules. suMetaD identified kinetic bottleneck conformations near the bound state position or in the vestibule area. In the first case the barrier is mainly enthalpic, requiring the breaking of strong interactions with the protein. In the vestibule TS location the kinetic bottleneck is instead mainly of entropic nature, linked to the solvent behaviour.

show abstract

Investigation of α-conotoxin unbinding using umbrella sampling

Cited by 10 publications

References 29 publications

Determination of the μ-Conotoxin PIIIA Specificity Against Voltage-Gated Sodium Channels from Binding Energy Calculations

Determination of the μ-Conotoxin PIIIA Specificity Against Voltage-Gated Sodium Channels from Binding Energy Calculations

Homology model of the human tRNA splicing ligase RtcB

Impact of protein–ligand solvation and desolvation on transition state thermodynamic properties of adenosine A2A ligand binding kinetics

Contact Info

Product

Resources

About