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J. Phys. Chem. B 2008, 112, 1290-1292
Identifying Receptor-Ligand Interactions through an ab Initio Approach Pablo F. Salazar† and Jorge M. Seminario*,†,‡ Department of Chemical Engineering and Department of Electrical and Computer Engineering, Texas A&M UniVersity, College Station, Texas 77843 ReceiVed: August 27, 2007; In Final Form: NoVember 14, 2007
We have demonstrated a qualitative relation between the electric characteristics and binding affinity of a complex receptor-ligand; a large binding affinity correlates with a large charge transfer. This allows us to analyze binding interactions of any complex using small computational resources with acceptable reliability of the results.
It is well-known the importance of ligand-protein interactions in many fundamental biological processes such as enzymatic reactions and molecular recognition.1,2 Even though the speed and accuracy of three-dimensional structure determination (such as nuclear magnetic resonance and X-ray crystallography) of proteins and their complexes increase every year, the ability to predict binding affinity from structures remains severely limited. The calculation of the free energy is a convenient approach to estimate the binding affinity in these systems. Computationally, this requires a sampling through a high-dimensional energy landscape.1 Moreover, we need a highly detailed energy function to describe all the primary interactions (mainly nonbonded) as well as extremely worked algorithms for conformational searching that can reliably find the energetically favorable conformations of a heterogeneous system. Computational simulations of biological systems are based on parametric methods; these methods use a set of molecules of well-known behaviors to generate parameters of more general applicabilitysamong them, force fields methods,3,4 empirical scoring functions,5-7 and statistical potentials.8,9 Besides having a good choice of parametric functions, it is also important to have a good knowledge of the nonbonded interacting forces in receptor-ligand complexes, such as electrostatic, van der Waals, hydrogen bond, aromatic, and hydrophobic interactions.2 One of the weaknesses of parametric methods is the low reliability for unknown systems. Consequently, we have to rely on ab initio quantum-chemistry techniques, whereby the electronic structure is considered explicitly and is solved without any empirical parameters. Among all quantum chemistry techniques, density functional theory (DFT) provides the best relation between accuracy and computational cost. Rather than calculating the free energy, we present an alternative procedure to analyze the binding affinity, which tells us how strongly two molecules interact. Our procedure is based on the electron transfer between a receptor and a ligand. To prove the concept, we create a pseudo-protein-ligand junction under an electric field and calculate its current-voltage characteristics, i.e., the rate of electrons through the active site, and we corelate their behaviors with well-known interactions. For this validation, we build the junction based on molecules of known electrocatalytic interactions, such as hydrogen oxida* Corresponding author. E-mail:
[email protected]. † Department of Chemical Engineering. ‡ Department of Electrical and Computer Engineering.
tion and oxygen reduction on platinum surfaces. Thus, we are introducing a methodology that may be useful to any field in nanotechnology. It is being conceived from the work in computational biology, but it is not limited to that field. We extend the junction with a peptide made of glycine, in such a way that emulates the behavior of a biological system. Thus, the junction resembles a detector made of two electrodes (platinum terminated peptides) to sense molecules such as hydrogen and oxygen for this trial. Pictures of these hybrid systems are shown in Figure 1. Even though this is system is not similar to the common ones seen in biological science, both share the same characteristics needed to describe the binding affinity, i.e., the electron transfer in the active site. We use a combined ab initio approach of the Green’s function adapted from the Landauer theory10-12 and density functional theory (DFT). This procedure (GENIP) has been largely validated and described in several studies.13-16 We optimize the structures of the ligand and Pt-glycine systems with the B3PW91/LANL2DZ/6-311G level of theory.17,18 This level of theory has been thoroughly tested in several applications.19-22 The conformations are verified to be local minima calculating their Hessian matrices. The junctions are solved with an external field along the peptides using the Gaussian-03 program.23 The glycine bulk DOS is also calculated using the Gaussian-03 program; then GENIP program takes the Hamiltonian and overlap matrices to calculate the electrical characteristics of the junctions. Most of the biological processes begin with a transfer of electrons. Once the flow of electrons begins, it goes along a series of acceptors through redox reactions until a determined function is accomplished. Nature assures that this transfer of electrons is specific and efficient. Thus, it is suggested that nature discriminates between ligands according to the transfer rate of electrons that could initiate a biological processes. As predicted by classical theory for nonadiabatic electron transfer, the electron-transfer rate is proportional to the electronic coupling strength between the ligands and receptors and, in the normal region, to the standard free energy as well, reaching a maximum and then decreasing with the driving force free energy when the energy required to reorganize the ligands and the receptors is lower than this driving force. Then this theory combines perfectly the three key variables in protein-ligands interactions that yield an accurate approximation of binding affinity.
10.1021/jp0768569 CCC: $40.75 © 2008 American Chemical Society Published on Web 01/09/2008
Receptor-Ligand Interactions
Figure 1. (a) Gly-Pt-OO-Pt-Gly junction. (b) Gly-Pt-HH-PtGly (right) junction. (c) Gly-Pd-OO-Pd-Gly junction. Bulk glycine (blue), Pd (pink), O (red). Pt (purple), H (white).
The results in Figure 2 show a diode behavior with a threshold voltage for conduction of 3.8 V. This threshold depends only on the source electrode, i.e., a bulk of glycine; for higher voltages the current is noticeable, although it is not clear from the panels of Figure 2 due to the linear scale. Figure 2a shows a higher conductance when the hydrogen dimer is bonded close to the platinum interface rather than when the hydrogen dimer is dissociated. We correlate these currents with the binding affinity between the molecules; a higher affinity yields a higher current through the system. In agreement with the experiments,24 the slow rate of oxygen-reduction catalysis due the slow transport of electrons through the platinum surface is explained with low affinity of platinum for hydrogen dissociated. Furthermore, we prove our results under different junctions and conditions; we increase the size of the active site of the pseudo-
J. Phys. Chem. B, Vol. 112, No. 4, 2008 1291
Figure 2. I-V for (a) G-Pt-HH-Pt-G with H2 dissociated (blue) and H2 bonded (pink), (b) G-Pt-OO-Pt-G with O2 dissociated (maroon) and O2 bounded (red), and (c) G-Pd-OO-Pd-G (green) and G-Pt-OO-Pt-G (maroon).
protein system, and we got a lower current (not shown) in the system, validating in this manner the electronic coupling strength factor. Figure 2b shows a larger conductance when the oxygen dimer is dissociated close to the platinum surface rather than when the oxygen is bonded. This is in agreement with the experiments as well and explains the formation of hydroxides in platinum surfaces that consequently take out the platinum from the system, degrading the cathode. We analyze the identification of the binding interactions using Pd as an alternative catalyst (Figure 1c). Pd is cheaper but the affinity of oxygen for Pd is smaller than the one for Pt. We test this affinity making an analysis of the highest occupied molecular orbital (HOMO) for both systems (Figure 3) at the same isovalue (0.02 au). We notice that indeed there
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Figure 3. (a) HOMO for the -Pt-OO-Pt- junction (-7.09 eV) and (b) for the -Pd-OO-Pd- junction (-7.07 eV).
is a slight higher probability of most energetic electrons with the Pt electrodes than with the Pd ones. Then, as expected, we get a lower current for weaker binding interactions as can be seen in Figure 2c when palladium is the terminal. We have demonstrated a qualitative relation between the electric characteristics and binding affinity of a complex receptor-ligand; a high binding affinity correlates with a high charge transfer. This allows us to analyze binding interactions of any complex, reducing tremendously computational resources while maintaining reliability of the results. Acknowledgment. We appreciate the support of the US Defense Threat Reduction Agency (DTRA) through the US Army Research Office (ARO) as well as the US Department of Energy (DOE). References and Notes (1) Nienhaus, G. U. Computer Simulation of Protein-Ligand Interactions. In Protein-Ligand Interactions: Methods and Applications; Nienhaus, G. U., Ed.; Humana Press: Ulm, Germany, 2005. (2) Bo¨hm, H. J.; Schneider, G. Introduction to molecular recognition models. In Protein-Ligand Interactions; Bo¨hm, H. J., Schneider, G., Eds.; Wiley: New York, 2003.
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