Research Article Received: 29 December 2013,

Revised: 11 March 2014,

Accepted: 15 March 2014,

Published online in Wiley Online Library

(wileyonlinelibrary.com) DOI: 10.1002/jmr.2373

Molecular recognition of Fc-specific ligands binding onto the consensus binding site of IgG: insights from molecular simulation Hong-Fei Tonga, Dong-Qiang Lina*, Qi-Lei Zhangb, Rong-Zhu Wangb and Shan-Jing Yaob Immunoglobulin G (IgG) plays an important role in clinical diagnosis and therapeutics. Meanwhile, the consensus binding site (CBS) on the Fc domain of IgG is responsible for ligand recognition, especially for Fc-specific ligands. In this study, molecular simulation methods were used to investigate molecular interactions between the CBS of the Fc domain and seven natural Fc-specific ligands. The analysis on the binding energy of the Fc–ligand complex indicated that hydrophobic interactions provide the main driving force for the Fc–ligand binding processes. The hot spots on the ligands and Fc were identified with the computational alanine scanning approach. It was found that the residues of tryptophan and tyrosine on the ligands have significant contributions for the Fc–ligand binding, while Met252, Ile253, Asn434, His435, and Tyr436 are the key residues of Fc. Moreover, two binding modes based on tryptophan or tyrosine were summarized and constructed according to the pairwise interaction analysis. Guidelines for the rational design of CBS-specific ligands with high affinity and specificity were proposed. Copyright © 2014 John Wiley & Sons, Ltd. Additional supporting information may be found in the online version of this article at the publisher’s web site. Keywords: IgG; Fc-specific ligand; affinity; molecular simulation; molecular recognition

INTRODUCTION

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* Correspondence to: D-Q. Lin, State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China. E-mail: [email protected] a H.-F. Tong, D.-Q. Lin State Key Laboratory of Chemical Engineering, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China b Q.-L. Zhang, R.-Z. Wang, S.-J. Yao Key Laboratory of Biomass Chemical Engineering of Ministry of Education, Department of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China

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Immunoglobulin G (IgG) has received special attention for its wide application in clinical therapeutics and immunodiagnostics. Monoclonal antibodies (mAbs) as typical therapeutics of IgG have become the most important way for the treatment of rheumatoid arthritis, multiple sclerosis, and several types of cancers (Choy et al., 1998; Stern and Herrmann, 2005; Rose et al., 2009). In the past few years, huge market profits resulted in the rapid development of antibody engineering and related industrial-scale mAb production. The titers of mammalian cell culture can reach up to 5 g/l currently, even to 13 g/l (Li et al., 2010; Shukla and Thömmes, 2010), which shifts the focus of bioprocess development from upstream to the downstream processing (Roque et al., 2004; Gagnon, 2012). For the downstream processing of mAb production, Protein A (ProA) affinity chromatography is usually the most specific and effective technique to capture IgG from complicated feedstocks. However, the high cost of ProA-based resins, low chemical stability, harsh elution conditions, and potential leaching of ProA ligands during the operation seriously limit the application of ProA resins in large-scale production (Hober et al., 2007). Some pseudobiospecific ligands with low cost and high stability have been developed to overcome these drawbacks. For instance, tryptophan, phenylalanine, and histidine were used with a combination of hydrophobic, pi-stacking, and electrostatic interactions to separate IgG from serum and cell culture supernatant with purity and recovery of 90 and 85% (Smith, 2005; Zhao et al., 2009; Naik et al., 2011; Gagnon, 2012). Moreover, synthetic ligands used for hydrophobic charge-induction

chromatography, such as mercaptomethylimidazole and 4pyridylethylmercaptan, have been studied, which showed good binding capacity for IgG (Burton and Harding, 1998; Guerrier et al., 2000; Xia et al., 2008). Peptide ligands such as ProA mimics (e.g., TG19318 and artificial protein A (APA); Fassina et al., 1996; Fassina et al., 1998; Li et al., 1998a), Protein G (ProG) mimics (Qian et al., 2012; El Khoury and Lowe, 2013), and Protein L mimics (Roque et al., 2005), as well as D2AAG, HWRGWV, and cyclic peptide (Yang et al., 2010; Naik et al., 2011; Lund et al., 2012; Menegatti et al., 2013a), have also been promoted with great efforts. Compared with protein ligands (such as ProA and ProG), these ligands are much less expensive with higher stability. However, they usually show less specificity to IgG and thus require process optimization to improve their separation performance (Menegatti et al., 2013b). Therefore, better understanding on molecular specificity and mechanisms of the recognition process is necessary for the design of novel ligands with high affinity and specificity.

H.-F. TONG ET AL. Molecular simulation with advanced computational tools provides a new way to study protein–ligand interactions and reveal biorecognition processes, which can help us understand some complicated functions of ligand groups during binding processes(Zamolo et al., 2010; Zhang and Sun, 2010; Huang et al., 2011a; Lin et al., 2012a; Lin et al., 2012b). 3D structural information of IgG can be analyzed with molecular simulation, and binding sites with some complementary ligands can be identified, which will benefit the design of novel IgG-specific ligands. Because ProA and ProG are widely used as the affinity ligands for antibody purification with high specificity, the binding sites of ProA and ProG on IgG could be possible target spots for ligand design. Research found that the Fc region of IgG bears a highly conserved sequence and structure, which provides a perfect site named as consensus binding site (CBS) on the hinge region of the Fc fragment for the binding of a series of natural ligands (DeLano et al., 2000), including proteins, peptides, and RNA (Nezlin and Ghetie, 2004; Nomura et al., 2010). These Fc-specific ligands have a high affinity with Fc and high geometry complementary at the binding interface. Therefore, understanding the mechanism of molecular recognition between CBS and these specific ligands would certainly help the rational design of Fc-specific ligands for IgG purification. In the present work, molecular dynamics (MD) simulation was used to study the interaction mode of Fc-ligand complexes. The Fc-specific ligands are ProA (Deisenhofer, 1981), ProG (Sauer-Eriksson et al., 1995), peptide Fc-III (DeLano et al., 2000), neonatal Fc receptor (FcRn) (Burmeister et al., 1994), rheumatoid factor (RF) (Corper et al., 1997), human tripartite motif TRIM21 (TRIM21) (James et al., 2007), and HSV-1 Fc-receptors (gE-gI) (Sprague et al., 2006), named LA, LB, LC, LD, LE, LF, and LG, respectively. Specifically, the results were focused on the binding and molecular recognition at the CBS region. The molecular structures of IgG and the seven Fc–ligand complexes are shown in Figure 1. The binding free energy of the complexes was evaluated using the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) method, and the binding modes were analyzed with an alanine scanning method based on the MMgeneralized Born surface area (MM/GBSA). The hot spots on Fc and ligands were identified according to the energy contribution and pairwise interaction analysis. Finally, two consensus binding

models were proposed to reveal the general mechanism of molecular recognition between the Fc domain and Fc-specific ligands.

MATERIALS AND METHODS Molecular systems Seven Fc–ligand complexes were used in this study, and the coordinates of the complexes were obtained from the Protein Data Bank (PDB), which are listed in Table 1. A single Fc chain of IgG without a carbohydrate was extracted to construct the Fc–ligand complexes for MD simulation. As IgG1 is the most attractive and widespread subclass of IgG in diagnostic and therapeutic applications, and the Fc sequence identity between IgG1 and IgG4 is as high as 95.6%, the Fc domain of LE (PDB: 1ADQ, IgG4 subclass) was replaced with an Fc domain from LA (PDB:1FC2, IgG1 subclass). AMBER ff10 force field was used to describe the force field parameters of Fc–ligand complexes (Hornak et al., 2006), and these complexes were solvated with TIP3P water (Jorgensen et al., 1983) in a cubic box with periodic boundary conditions, leaving a minimum distance of 8 Å between the complex and the edge of the box. Sodium and chlorine ions were added to neutralize the net charges in the simulation box. Simulation approaches All MD simulations were performed at neutral pH using AMBER 11 software (Case et al., 2005), and detailed simulation processes were performed as follows: Minimization: The complex was restrained with a harmonic potential k(Δx)2, where Δx is the displacement and k the force constant (k = 500 kcal mol1 Å2). Minimization (2000 cycles) was used to remove any possible unfavorable contact between solvents and solutes, and 1500 steps minimization was then performed without restraints. Heating: Simulated annealing of 20 ps at constant volume was applied to raise the temperature of the system from 0 to 300 K. A weak

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Figure 1. Molecular structures of IgG and Fc–ligand complexes. IgG: heavy chains are shown in blue and green, light chains are shown in red, and Fc domain is shown in dark blue and dark green. Complexes: LA (ProA), LB (ProG), LC (peptide Fc-III), LD (FcRn), LE (RF), LF (TRIM21), LG (gE-gI), and Fc domain are shown in green, and ligands are shown in red.

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Copyright © 2014 John Wiley & Sons, Ltd.

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MOLECULAR RECOGNITION OF FC-SPECIFIC LIGANDS BINDING ONTO IGG Table 1. Fc–ligand complexes on the conserved CH2–CH3 domain junction Name

PDB ID

Resolution (Å)

LA LB LC LD LE LF LG

1FC2 1FCC 1DN2 1FRT 1ADQ 2IWG 2GJ7

2.80 3.20 2.70 4.50 3.15 2.35 5.00

Fc IgG1 IgG1 IgG1 IgG1 IgG4 IgG1 IgG1

(Homo sapiens) (H. sapiens) (H. sapiens) (H. sapiens) (H. sapiens) (H. sapiens) (H. sapiens)

restraint was imposed on the complex (k = 10 kcal mol1 Å2) to avoid wild structural fluctuations. Equilibration: Run for 100 ps with a time step of 1 fs at constant pressure to allow the relaxation of water density. The k of harmonic restraint was diminished to 0.01. Production: Run for a standard period of 15 ns at constant pressure and temperature (300 K). In order to avoid the relative bending of the CH2 and CH3 domains during the simulation and keep certain freedom of the residues, a weak harmonic restraint with the force constant of 10 was imposed on the terminal residues of the Fc chain. In all simulation steps, the temperature was controlled with a Langevin dynamics algorithm and a collision frequency = 2 ps1. The pressure in the equilibration phase was controlled by means of a weak coupling Berendsen scheme. The SHAKE algorithm was used for all covalent bonds involving hydrogen using a 2-fs time step (Ryckaert et al., 1977). The nonbonded cutoff was set as 10 Å, and long-range electrostatic interactions were evaluated using the particle mesh Ewald method (Crowley et al., 1997). Snapshots were collected every 4 ps. The structures were extracted every 500 fs for successive analysis. The binding free energy between Fc and the ligands was determined using the MM/PBSA and MM/GBSA approach (Wang et al., 2001). Binding energy analysis The binding free energy between Fc and the ligands was determined using the MM/PBSA protocol. The protein–ligand binding free energy is estimated as the sum of gas phase energy (ΔGgas), solvation energy (ΔΔGsol), and the entropic energy (TΔSgas), ΔGbinding ¼ ΔGgas þ ΔΔGsol  TΔSgas

(1)

where Ggas is the molecular energy in the gas phase, which contains an intermolecular electrostatic term (Gele),van der Waals (vdW) term (Gvdw), and internal energy term(Gint er): ΔGgas ¼ ΔGinter þ ΔGele þ ΔGvdw

(2)

and Gsol can be divided into polar and nonpolar parts, Gsol ¼ GNP þ GPB

(3)

Here, PBSA can be used to evaluate the electrostatic solvation energy (GPB), whereas the nonpolar contribution (GNB) as a linear function of the solvent-accessible surface area (SASA) with a probe radius of 1.4 Å is given by

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(4)

Reference

Protein A Protein G Peptide Fc-III FcRn RF TRIM21 gE-gI

Deisenhofer, 1981 Sauer-Eriksson et al., 1995 DeLano et al., 2000 Burmeister et al., 1994 Corper et al., 1997 James et al., 2007 Sprague et al., 2006

where the surface tension and the offset b were set to the standard values of 0.00542 kcal mol1 Å2 and 0.92 kcal mol1 in this work, respectively. Despite the expensive computational overhead and low prediction accuracy, the last 20 snapshots for each complex were extracted to evaluate the entropy contribution TΔSgas using the Nmode module of AMBER 11. As the main goal of this work is to identify the role of residues, the absolute binding free energy is not necessary, and the binding free energy (ΔGbinding) reported here is the relative binding free energy with the entropy contribution. The energetic terms in Eqn (1) were averaged over the simulation trajectory. Alanine scanning method The alanine scanning method with the MM/GBSA protocol was used to determine the contribution of a specific residue in the binding process between Fc and the ligands. For the computational alanine scanning, the residues of the ligands at a distance within 10 Å to Fc or the residues of Fc at a distance within 10 Å to the ligands were mutated into alanine one by one. The difference of the binding energy between a mutated Fc–ligand complex and the original one can be calculated as follows: ΔΔGbinding ¼ ΔGmutant  ΔGwild type

(5)

where ΔΔGbinding is the difference of binding energy between the mutated Fc–ligand complex and the original one, Δ Gmutant is the binding free energy for the mutated Fc–ligand complex, and ΔGwild type is the binding free energy for an Fc–ligand without alanine mutation.

RESULTS AND DISCUSSION Binding free energy for different Fc–ligand complexes For seven Fc–ligand complexes, the binding interfaces are located on the CBS region of Fc, which is the hinge domain between CH2 and CH3 of IgG (Figure 1). During the MD simulation, the root-mean-square deviation (RMSD) of the complex and the distance between Fc and the ligands were calculated, and the results are shown in Figures S1 and S2. It can be seen that the RMSD and the distance calculated can reach to a plateau after 5 ns of simulation. Therefore, the trajectories at the range of 5 to 15 ns were used for the energy analysis. The binding free energy of the seven Fc–ligand complexes was calculated via the MM/PBSA approach, and the results are shown in Table 2. The TΔSgas contribution for ProA-IgG was 30.7 kcal mol1, and the absolute binding free energy was estimated at 9.7 kcal mol1, which is in good agreement with the experimental results in the literature (between 9.8 and

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GNP ¼ γ  SASA þ b

Ligand

H.-F. TONG ET AL. Table 2. Energy terms and the binding free energy of Fc–ligand complex Contribution ΔGele ΔGvdW ΔGgas ΔGPB ΔGNP ΔGsol ΔGbinding ΔGpolar ΔGnonploar TΔSgas

LA

LB

LC

LD

LE

LF

LG

231.1 69.4 300.5 267.5 7.5 260.0 9.7 36.4 76.9 30.7

281.1 65.5 346.6 294.6 6.8 287.8 14.9 13.5 72.3 43.9

159.6 66.9 226.5 182.6 6.6 175.9 17.0 22.9 73.5 33.5

211.6 59.8 271.4 252.2 5.4 246.7 0.9 40.6 65.2 25.6

194.5 75.7 270.2 232.9 8.9 223.9 4.9 38.4 84.6 41.4

174.3 105.7 279.9 240.6 11.5 229.1 2.1 66.3 117.2 48.8

159.8 104.2 264.1 220.1 10.8 209.4 6.0 60.3 115 48.7

*The unit for energy is kcal mol1. 10.3 kcal mol1; Li et al., 1998b; Saha et al., 2003). The binding free energy for ProG was estimated at 14.9 kcal mol1 when including TΔSgas contribution (43.9 kcal mol1), and the value determined by the experiment was 11.1 kcal mol1 (Saha et al., 2003). The results indicated a higher affinity of ProG than ProA, which is in agreement with experimental observations. Although the absolute binding energy for other complexes showed some differences to the experimental measurement, the ranking of the relative affinity for these complexes is consistent with experimental observations. It was found that FcRn had the lowest binding ability than others. The high unfavorable polar interactions plus the relatively weak nonpolar binding interactions resulted in a lower binding affinity between FcRn and Fc. This result indicates that MM/PBSA is reliable for the analysis of these Fc–ligand complexes in this study. To identify the interaction terms between Fc and the ligands, ΔGbinding can be divided into nonpolar (hydrophobic) and polar terms. By comparing the energy terms listed in Table 2, it can be found that the hydrophobic energy (ΔGnonpolar) is favorable for binding, while the electrostatic energy (ΔGpolar) plays an opposite role with positive energy values. The unfavorable electrostatic energy is the consequence of insufficient compensation between the favorable intermolecular electrostatic energy (ΔGele) and the larger unfavorable electrostatic solvation effect (ΔGPB). Hence, a strong hydrophobic interaction with a high absolute value of ΔGnonpolar is the main driving force during the Fc–ligand binding process, and details will be further analyzed. Hot spots on the ligands in the Fc–ligand binding

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Hot spots are critical factors for the understanding of binding mechanisms. Therefore, the contribution of the residues on the ligands was determined using the alanine scanning method, and ΔΔGbinding of important residue is reported in Figure 2 and Table S1. Taking LA as the example, Gln129, Phe132, Tyr133, Leu136, Glu143, Ile150, and Lys154 from ProA were found to have relatively great contributions (as shown in Figure 2—LA). The residues are the same as the results reported by Salvalaglio et al. (Salvalaglio et al., 2009) but are different from a free energy decomposition method (Huang et al., 2011b). The disputed residues are Gln129, Leu136, and Ile150 identified using the alanine scanning and His137 identified with the free energy decomposition method. In addition, Lys154 is identified as a favorable residue in binding with alanine scanning, whereas

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it has a negative effect in binding with the free energy decomposition method. One of the important differences between the two methods is that computational alanine scanning provides a contribution of only the side chain, while free energy decomposition includes both the side chain and backbone. The results of computational alanine scanning can be compared directly with the results of an experimental alanine scanning. As reported by Elisabeth (Sauer-Eriksson et al., 1995), Gln129 participates in charged and H-bonding interactions, and Leu136 can form hydrophobic contact and H-bonds with Fc, while His137 was excluded. Therefore, the results with alanine scanning would be more meaningful. The simulation results indicate that the binding of these ligands onto the CBS region of Fc is mainly driven by hydrophobic forces, as there are a high proportion of hydrophobic residues of hot spots (details are shown in Table S1). For example, Phe132, Tyr133, and Leu136 of LA; Trp43 and Tyr45 of LB; Leu6, Val10, and Trp11 of LC; Trp133 and Pro134 of LD; Trp52H, Tyr98H, and Val99H of LE; Trp299, Tyr328, Leu370, Trp383, and Phe450 of LF; Ile246, Ile249, Tyr311, Pro321, and Val342 of LG have significant nonpolar contributions. In addition, electrostatic forces are also important for the binding as the charged residues are usually distributed around the hydrophobic core. Ligand gE-gI has positively charged key residues; peptide Fc-III and FcRn have negatively charged key residues, while the rest contain both types of residues. The electrostatic assistance promotes the formation of the Fc–ligand complex. Previously, Phe132 and Tyr133 have been used to develop ProA mimetic affinity ligands, while Asn35 and Trp43 were selected to mimic ProG (Li et al., 1998b; Qian et al., 2012). Lichtarge et al. (Lichtarge et al., 1996) reported that the residue composition of hot spots at a protein–protein interface is very regular, and the study by Moreira et al. (Moreira et al., 2007) indicated that the fundamental residues are tryptophan (21%), arginine (13.3%), and tyrosine (12.3%). These three residues also appeared frequently at the interface of the Fc–ligand binding processes in this work. Hot spots on Fc in the Fc–ligand complex The CBS located on the CH2–CH3 interface of Fc is highly solvent accessible, relatively hydrophobic, conformation flexible and favorable for H-bond formation (DeLano et al., 2000). The CBS interface distribution for each ligand is shown in Figure S3. The intrinsic properties of CBS make it a suitable site for the binding with different ligands. For better understanding the binding

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MOLECULAR RECOGNITION OF FC-SPECIFIC LIGANDS BINDING ONTO IGG

Figure 2. Energy contribution of key residues on the ligands for the Fc–ligand binding. Ligands are shown as a ribbon with a transparent surface in silver. Key residues are shown as sticks with hydrophobic residues in brown, positively charged residues in blue, negatively charged residues in red, and polar neural residue in yellow.

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The analysis on individual Fc–ligand complexes was provided in the Supporting Information. All key residues on the CBS of Fc for the Fc–ligand binding are shown in Figure 4. These residues cover a large area from top

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mechanism between Fc and ligands, the most important residues on the CBS region of Fc should be identified. The changes in binding energy of the top seven residues are reported in Figure 3, and the energy values are listed in Table S2.

H.-F. TONG ET AL.

Figure 3. Energy contribution of key residues on Fc for the Fc–ligand binding. Fc is shown with a silver surface, hydrophobic residue in brown, positively charged residue in blue, negatively charged residue in red, polar neural residue in orange, and histidine in green. Key residues on the ligands are shown as sticks with cyan, blue, and red bonds.

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(Lys317) to bottom (Glu382). In the center, Met252, Ile253, Met428, and Tyr436 constitute a hydrophobic core, and nonpolar interactions are the main contributions of Met252, Ile253, and Met428 on

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Fc for binding. Close to the hydrophobic core, there are three histidines (His310, His433, and His435), which could have pi-stacked aromatic interactions with aromatic residues of the ligands. In the

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MOLECULAR RECOGNITION OF FC-SPECIFIC LIGANDS BINDING ONTO IGG

Figure 4. Key residues on the CBS of Fc for the binding of seven ligands tested. The color of residues are marked as the same as Figure 3.

middle of these histidines and the hydrophobic core, Asn434 could establish charge–charge interactions and H-bonds to enhance the binding ability. At the border of the binding site on CBS are some polar and charge residues, such as lysine, arginine, and glutamic acid. The distribution of residues on the Fc surface is correlated with the key residues on the ligands as shown in Figure 3. Discussions on the recognition mechanism of the Fc–ligand complex

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P1, which have a pi–pi interaction with His435 on CBS and can form hydrophobic interactions with Met252 and Ile253 on CBS. Although phenylalanine replaces tryptophan at P1 for LA (as shown in Figure S4—LA) and proline and tyrosine take the place of tryptophan at P1 for LG (as shown in Figure S4—LG), these residues are likely to have a pi–pi interaction with His435 and Tyr436. The P2 position could be glutamine, lysine, proline, valine, and isoleucine in this study. Residues at P2 have vdW interactions with Met252, Ile253, ASN434, and Tyr436 and electrostatic forces with ASN434 on CBS. In addition, the residues on P2 may have a weak interaction with His435 on CBS. However, for LB, Lys31 at P2 bent its long carbon chain and has a cation–pi interaction with Trp43 on ligand itself, which leads to negative binding effects. As shown in Figure 6e, the TYR mode normally has a tyrosine residue at P1 and a hydrophobic residue at P2. Tyrosine has a high conservation propensity on the Fc–ligand binding sites, which can offer a hydrophobic surface. It can combine both aromatic pi-interactions and the hydrogen bonding using its 4-hydroxyl group. The tyrosine residue of LE (as shown in Figure S4—LE) has strong electrostatic force with Asn434 and vdW interactions with Met252, Tyr436, His435, and Asn434 on CBS, while tyrosine of LF (as shown in Figure S4—LF) interacts with Fc via electrostatic interactions with Asn434 and vdW interactions with Ile253, Tyr436, and Asn434. At the P2 position, the residues could be valine or phenylalanine that further stabilizes the Fc–ligand binding mainly through the vdW interactions with Met252 and His435 and both vdW and electrostatic interactions with Asn434 on CBS of Fc. After the analysis of Fc and ligand molecules, it can be found that hydrophobic interaction is the main driving force for the seven Fc–ligand complexes. In addition, electrostatic interactions as well as the pi–pi stacking and H-bonds are also important in stabilizing the Fc–ligand complexes. The information obtained can be used to guide the rational design of ligands with high affinity and specificity for Fc binding. Some guidelines on the design of Fc-specific ligands are summarized. (1) The binding specificity of ligands on CBS of Fc is dominated by multiple interactions, and it is important to balance different molecular interactions, including hydrophobic interaction, electrostatic interaction, pi–pi stacking, and H-bonding interaction, whereas hydrophobic interaction is essential and critical.

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Based on the molecular simulation analyzed, the frequency of key residues on Fc for the seven Fc–ligand complexes is shown in Figure 5 and listed in Table S3. The most important residues are identified as Met252, Ile253, Asn434, His435, and Tyr436. These five residues could be classified further into three groups: (i) hydrophobic residues (including Met252 and Ile253) that form the key hydrophobic core; (ii) His435 and Tyr436 could contribute pi-stacking, H-bonds, and electrostatic interactions; and (iii) the last type (Asn434) is capable of forming hydrogen bonding and electrostatic interactions. The nearest and furthest distance between these residues was 6.1 and 18.8 Å. The pairwise interactions between key residues on the ligands and key residues on Fc were further analyzed, and the results are shown in Table S4. It was found that Gln129 and Phe132 on LA, Lys31 and Trp43 on LB, Val10 and Trp11 on LC, Trp133 and Pro134 on LD, Tyr98 and Val99 on LE, Tyr328 and Phe450 on LF, and Ile246, Ile249, Tyr311, and Pro321 on LG could interact with CBS mainly through three key sites that were formed by the most important residues on Fc (Met252, Ile253, Asn434, His435, and Tyr436). It was found that the binding modes can be classified into two modes, named TRP mode and TYR mode, as shown in Figure 6. LA, LB, LC, LD, and LG belong to the TRP mode, while LE and LF belong to the TYR mode. For the TRP mode, tryptophan plays a unique function for the Fc–ligand binding with multifunctional interactions including hydrophobic interaction, electrostatic interaction, and aromatic pi-interactions. It is also a hydrogen bonding donor and has a large hydrophobic surface. Moreover, tryptophan can protect fragile hydrogen bonds from water (Fernández, 2002). Figure 6d shows that the TRP mode could be characterized as one aromatic residue (which is usually tryptophan) at position 1 (P1) and one auxiliary residue at position 2 (P2). For LB, LC, and LD (as shown in Figure S4-LB, Figure S4-LC, and Figure S4-LD, respectively), it is found that a tryptophan residue is located at

Figure 5. The consensus key residue distributions on CBS of Fc for the Fc– ligand binding. The most important residues are shown with a name and number. These residues are divided into three groups that are enclosed with a white, green, and red line, respectively. Hb, hydrogen bonding; E, electrostatic interaction; H, hydrophobic interaction; pi, pi–pi or pi–cation interaction.

H.-F. TONG ET AL.

Figure 6. Two consensus modes for the Fc–ligand binding. (a) Key residues on CBS shown as sticks, (b) electrostatic surface of key residues on CBS (positive in blue and negative in red), (c) hydrophobic surface of key residues on CBS (hydrophobic in orange, hydrophilic in blue, and neutral in gray), (d) TRP mode, and (e) TYR mode.

(2) Aromatic residues on the ligand are important for the binding on CBS of Fc, which could form hydrophobic interactions, pi–pi stacking, and H-bonding interactions. Tryptophan and tyrosine are two special amino acids that both have aromatic rings and H-bonding sites, which could be considered as the key groups to construct a high affinity ligand binding onto CBS of Fc. (3) The ideal auxiliary group at P2 could be hydrophobic, aromatic, or weak acid residues for the TRP mode, while hydrophobic residues would be favorable for the TYR mode. (4) The distance between the key group and the auxiliary group of ligands may need to be adjusted following the key residues distributed on CH2 and CH3 of Fc. The average distance between the two groups is about 6.8 Å. (5) Residues with a long chain and positive charges should be excluded, as they can have interactions with aromatic groups on the ligands and disturb the binding of the ligand onto CBS of Fc.

complexes and explore the molecular recognition characteristics of the Fc-specific ligands binding onto the CBS region of Fc. The binding free energy of the Fc–ligand complexes was calculated to identify the affinity between ligands and Fc. The energy analysis results indicated that hydrophobic interaction is the main driving force for the Fc–ligand binding. Moreover, the hot residues on ligands and Fc were identified in terms of the free energy contribution of each residue. The molecular simulation results demonstrated that the residues with an aromatic ring are of great importance on the ligands, while the residues Met252, Ile253, Asn434, His435, and Tyr436 on CBS are the hot spots of CBS on Fc. Finally, two binding models were constructed according to the pairwise interaction analysis, which are on the basis of tryptophan and tyrosine, respectively. These modes could be considered as the core structure for the design of biomimetic ligand binding onto CBS of Fc. Suggestions were proposed to help guide the rational design of novel Fc-specific ligands with high affinity and specificity.

Acknowledgements

CONCLUSIONS Molecular simulation with MM/PBSA analysis and computational alanine scanning method was used to investigate seven Fc–ligand

This work was supported by the National Natural Science Foundation of China and the Zhejiang Provincial Natural Science Foundation of China.

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MOLECULAR RECOGNITION OF FC-SPECIFIC LIGANDS BINDING ONTO IGG

J. Mol. Recognit. 2014; 27: 501–509

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Molecular recognition of Fc-specific ligands binding onto the consensus binding site of IgG: insights from molecular simulation.

Immunoglobulin G (IgG) plays an important role in clinical diagnosis and therapeutics. Meanwhile, the consensus binding site (CBS) on the Fc domain of...
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