Standard Free Energy of Binding from a One-Dimensional Potential of Mean Force

Doudou, Slimane; Burton, Neil A.; Henchman, Richard H.

doi:10.1021/ct8002354

Cited by 202 publications

(309 citation statements)

References 59 publications

(122 reference statements)

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“…1A) (24). The protein was modeled using the AMBER 99SB force field (34) and the ligand with the general amber force field (GAFF) force field (35) as described by Doudou et al (22). The complex was rotated to align the vector defined by the C7 atom of benzamidine and the Cγ atom of ASP 189 to the z axis of the box.…”

Section: Methodsmentioning

confidence: 99%

“…Previous computational studies on trypsin date back to the 1980s with work by Warshel et al (17) on binding free energies computed from potentials of mean force for trypsin and subtilisin. More recent efforts on the trypsinbenzamidine system, in particular, include studies of the conformational variability of the bound complex (18,19) and benzamidinium-derivatives binding affinity calculations via end-point methods (20,21) and via potential of mean force free-energy biased methods such as umbrella sampling (22) and metadynamics (23). In this work, we report 187 events of binding from bulk to bound based on free diffusion simulations, a quantitative analysis of the process of binding, and the identification of the rate-limiting step in the pathway of binding, which consists of a set of transient hydrogen-bond interactions on the surface of trypsin close to the binding pocket.…”

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confidence: 99%

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Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

Buch

Giorgino

Fabritiis

2011

Proc. Natl. Acad. Sci. U.S.A.

633

766

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The understanding of protein-ligand binding is of critical importance for biomedical research, yet the process itself has been very difficult to study because of its intrinsically dynamic character. Here, we have been able to quantitatively reconstruct the complete binding process of the enzyme-inhibitor complex trypsin-benzamidine by performing 495 molecular dynamics simulations of free ligand binding of 100 ns each, 187 of which produced binding events with an rmsd less than 2 Å compared to the crystal structure. The binding paths obtained are able to capture the kinetic pathway of the inhibitor diffusing from solvent (S0) to the bound (S4) state passing through two metastable intermediate states S2 and S3. Rather than directly entering the binding pocket the inhibitor appears to roll on the surface of the protein in its transition between S3 and the final binding pocket, whereas the transition between S2 and the bound pose requires rediffusion to S3. An estimation of the standard free energy of binding gives ΔG°¼ −5.2 AE 0.4 kcal∕mol (cf. the experimental value −6.2 kcal∕mol), and a two-states kinetic model k on ¼ ð1.5 AE 0.2Þ × 10 8 M −1 s −1 and k off ¼ ð9.5 AE 3.3Þ× 10 4 s −1 for unbound to bound transitions. The ability to reconstruct by simple diffusion the binding pathway of an enzyme-inhibitor binding process demonstrates the predictive power of unconventional high-throughput molecular simulations. Moreover, the methodology is directly applicable to other molecular systems and thus of general interest in biomedical and pharmaceutical research.binding affinity | distributed computing | Markov state model | transition-state kinetics | association rates U nderstanding protein-ligand binding processes is undoubtedly of critical importance in structure-based drug design, and much effort is being invested in experimental and computational methods to resolve binding. The focus has generally resided on predicting the lowest energy binding pose of a ligand (1, 2), but resolving the kinetic mechanisms and structure activity relationships of the ligand has increasingly been recognized to provide additional mechanisms for elucidating therapeutically safe and differentiated responses (3, 4). The kinetics of binding depend on the characteristic transition states of a system. Hence, characterizing the binding pathway is crucial to understanding how to control and reengineer the process of binding.Commonly used methods to experimentally determine kinetic data for biomolecular interactions are available (5), but fast timescale resolution of a binding mechanism with atomic resolution remains difficult due to the intrinsic dynamic and volatile nature of the process of binding. From a computational perspective, the difficulty lies in accurately measuring binding affinities and kinetic parameters, but it has become easier to try to predict binding free energies on a limited number of targets and to qualitatively interpret binding mechanisms using molecular dynamics. Although it still requires substantial computational reso...

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

Buch

Giorgino

Fabritiis

2011

Proc. Natl. Acad. Sci. U.S.A.

633

766

View full text Add to dashboard Cite

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“…To determine the standard free energy of binding ⌬G 0 , the free energy ⌬G V for changing from the standard-state volume V 0 ϭ 1661 Å 3 , which corresponds to a 1 M concentration, to the sampled unbound volume and the free energy ⌬G R to remove the restraints have to be included (38,39). The ⌬G 0 of binding can then be calculated as shown in Equation 3,…”

Section: Methodsmentioning

confidence: 99%

A Single Mutation in a Tunnel to the Active Site Changes the Mechanism and Kinetics of Product Release in Haloalkane Dehalogenase LinB

Biedermannová

Prokop

Góra

et al. 2012

Journal of Biological Chemistry

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Background: Tunnel properties affect ligand passage in enzymes with buried active sites. Results: A tunnel mutation from leucine to tryptophan changes the mechanism of bromide ion release from haloalkane dehalogenase LinB. Conclusion:Interactions of the bromide ion with the tryptophan increase free energy barrier for its passage, causing the reaction mechanism change. Significance: The results provide guidelines for enzyme engineering.

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“…The standard free energy of binding, ⌬G o , is related to Kd via K d ϭ V 0 exp(Ϫ⌬G o /RT), where V 0 ϭ 1.661 nm 3 is the standard volume corresponding to a standard concentration of 1 M. ⌬G o was computed from the 1D PMF, W(z), using the method of Doudou et al (34) under the assumption that confinement of the three sampled ions in the bulk region is provided by the simulation cell (for details, see SI Methods).…”

Section: Methodsmentioning

confidence: 99%

Simulations of anion transport through OprP reveal the molecular basis for high affinity and selectivity for phosphate

Pongprayoon

Beckstein

Wee

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

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The outer membrane protein OprP from Pseudomonas aeruginosa forms a phosphate selective pore. To understand the mechanism of phosphate permeation and selectivity, we used three simulation techniques [equilibrium molecular dynamics simulations, steered molecular dynamics, and calculation of a potential of mean force (PMF)]. The PMF for phosphate reveals a deep free energy well midway along the OprP channel. Two adjacent phosphate-binding sites (W1 and W2), each with a well depth of Ϸ8 kT, are identified close to the L3 loop in the most constricted region of the pore. A dissociation constant for phosphate of 6 M is computed from the PMF, within the range of reported experimental values. The transfer of phosphate between sites W1 and W2 is correlated with changes in conformation of the sidechain of K121, which serves as a ''charged brush'' to facilitate phosphate passage between the two subsites. OprP also binds chloride, but less strongly than phosphate, as calculated from a Cl ؊ PMF. The difference in affinity and hence selectivity is due to the ''Lys-cluster'' motif, the positive charges of which interact strongly with a partially dehydrated phosphate ion but are shielded from a Cl ؊ by the hydration shell of the smaller ion. Our simulations suggest that OprP does not conform to the conventional picture of a channel with relatively flat energy landscape for permeant ions, but rather resembles a membrane-inserted binding protein with a high specificity that allows access to a centrally located binding site from both the extracellular and the periplasmic spaces.free energy profile ͉ potential of mean force ͉ anion selectivity ͉ hydration ͉ molecular dynamics simulation

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Standard Free Energy of Binding from a One-Dimensional Potential of Mean Force

Cited by 202 publications

References 59 publications

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

A Single Mutation in a Tunnel to the Active Site Changes the Mechanism and Kinetics of Product Release in Haloalkane Dehalogenase LinB

Simulations of anion transport through OprP reveal the molecular basis for high affinity and selectivity for phosphate

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