The authors have declared that no competing interests exist.
Conceived and designed the experiments: JC WZ. Performed the experiments: JC JW. Analyzed the data: JC JW. Contributed reagents/materials/analysis tools: JC WZ. Wrote the paper: JC JW.
Adipocyte fatty-acid binding protein (A-FABP) is an important target of drug designs treating some diseases related to lipid-mediated biology. Molecular dynamics (MD) simulations coupled with solvated interaction energy method (SIE) were carried out to study the binding modes of three inhibitors 8CA, F8A and I4A to A-FABP. The rank of our predicted binding affinities is in accordance with experimental data. The results show that the substitution in the position 5 of
Fatty acid binding proteins are small cytoplasmic proteins that are expressed in a tissue-specific manner
Adipocyte FABP is one of the nine known FABP isoforms, and highly expressed in adipose tissue and macrophages
Pharmacological intervention of A-FABP functions could play an therapeutic role in disorders such as type 2 diabetes and atherosclerosis
Barf et al. clarified the structure-activity relationship of inhibitor/A-FABP complex by using carbazole- and indole-based inhibitors of A-FABP, resulting in the discovery of submicromolar inhibitors
Molecular dynamics (MD) simulations and calculations of binding free energies have been a powerful tool of insight into interactions of inhibitors with proteins
The structural difference is labeled by red circle.
The initial coordinates of 8CA, F8A and I4A/A-FABP complexes were obtained from the protein data bank and their PDB entry are 3FR2, 3FR4 and 3FR5, respectively
For each system, energy minimizations and MD simulations were carried out using the sander module in Amber12 program
Currently, free energy perturbation (FEP), thermodynamic integration (TI), molecular mechanics Poisson-Boltzmann surface area (MM-PSA) and solvated interaction energy methods etc. are usually used to calculate binding free energies. Although FEP and TI methods should give more accurate results, they are extremely time-consuming and require sufficient statistical samplings
Computational alanine scanning method can be used to estimate the interactions of the side chain of residues in proteins with inhibitors. In this work, to examine the effect of electrostatic interactions of the residues Arg126 with inhibitors on bindings, alamine mutation was performed on Arg126. The alanine mutant structure was obtained by altering the coordinates of the wild-type residues, which involves cutting atoms and truncating the mutated residue at Cγ by replacing with a hydrogen atom
In folded proteins, the motions of many residues tend to be correlated. To investigate the effect of inhibitor binding on correlated motions of residues in A-FABP, the cross-correlation matrix
Stability of the complex structure can be reflected by its root mean square deviation (RMSD) of the Cα atoms from the initial structure. The RMSD values of four simulated systems along the entire MD trajectory are shown in
To examine the effect of inhibitor bindings on correlated motions of residues in A-FABP, cross-correlation matrices of the fluctuation were calculated and plotted in
The extent of correlated motions and anticorrelated motions are color-coded for unbound A-FABP(A), 8CA(B), F8A(C) and I4A(D).
The cross-correlation matrices (
To further understand the effect of inhibitor bindings on internal dynamics, the root mean square fluctuation (RMSF) of the Cα atoms was computed and displayed in
The SIE method was applied to calculate binding free energies of the three inhibitors to A-FABP and the results were listed in
Energy |
8CA-wild | 8CA-mutant | F8A-wild | F8A-mutant | I4A-wild | I4A-mutant |
ΔEvdw | −33.35±0.19 | −32.59±0.16 | −33.29±0.12 | −32.74±0.21 | −41.61±0.22 | −40.33±0.18 |
ΔEc | −57.40±0.24 | −20.84±0.21 | −52.04±0.24 | −21.34±0.43 | −59.51±0.23 | −28.08±0.28 |
γ·ΔMSA | −7.55±0.22 | −7.29±0.15 | −7.89±0.02 | −7.74±0.05 | −8.79±0.02 | −8.05±0.04 |
ΔGR | 43.81±0.03 | 24.93±0.02 | 40.84±0.22 | 22.45±0.22 | 45.88±0.17 | 27.44±0.18 |
ΔGbind | −8.63±0.04 | −6.59±0.02 | −8.42±0.02 | −6.97±0.04 | −9.58±0.03 | −7.90±0.03 |
ΔGexp | −8.52 | −8.46 | −8.69 | |||
ΔΔGbind | 2.04 | 1.45 | 2.18 |
All energies are in kcal·mol−1,
ΔEnergy = Energycomplex–EnergyA-FABP–Energyinhibitor,
ΔGexp were derived from the experimental values in Ref (Barf et al. 2009) using the equation ΔG≈–RTlnIC50,
ΔΔGbind = ΔGmutant–ΔGcomplex.
The reaction energy related to the desolvation of polar groups always unfavors inhibitor bindings, which is also found in other works
In the case of the 8CA/A-FABP complex, the intermolecular Coulomb interaction between 8CA and A-FABP is −57.40 kcal·mol−1, which provides an important contribution to the binding. This interaction should include contributions from hydrogen bonds and other polar interactions between 8CA and A-FABP. To clarify this issue, we analyze the hydrogen bonds between 8CA and A-FABP based on the lowest energy structure from MD simulation. The results show that the carboxyl oxygen O1 of 8CA can form three hydrogen bonds with the residues R126 and Y128, while another oxygen atom O2 of the carboxyl also builds a hydrogen bond with Y128 (
Fig. A represents frequency distribution of the H atom…acceptor distance, Fig. B depicts the position of inhibitor 8CA relative to key residues, Fig. C shows the hydrophobic contacts as a function of the simulation time.
Complex | Hydrogen bonding | HB energy (kcal/mol) |
8CA-A-FABP | O2…R126HE | −0.76±0.11 |
O1…R126HH21 | −2.50±0.19 | |
O1…Y128HH | −1.81±0.20 | |
O2…Y128HH | −0.69±0.12 | |
F8A-A-FABP | O12…R126HE | −1.17±0.14 |
O11…R126HH21 | −1.77±0.16 | |
O11…Y128HH | −0.46±0.10 | |
O12…Y128HH | −2.05±0.18 | |
I4A-A-FABP | O26…R126HE | −1.34±0.13 |
O27…R126HH21 | −1.80±0.13 | |
O27…Y128HH | −0.51±0.10 | |
O26…Y128HH | −2.60±0.15 | |
H18…S55OG | −0.55±(0.12) |
The inhibitor 8CA has a negative charge and can interact favorably with the positively charged residues. The previous work from Barf et al. showed that the inhibitors can produce strong polar interaction with A-FABP
Inhibitors | Residues | Polar interaction (Wild) | Polar interaction (R126A) |
8ca | R78 | −5.93±0.45 | −6.20±0.38 |
R106 | −10.21±0.47 | −14.12±0.24 | |
R126 | −21.96±0.72 | −0.10±0.05 | |
F8A | R78 | −6.08±0.31 | −6.99±0.41 |
R106 | −8.01±0.52 | −13.30±0.47 | |
R126 | −20.01±0.66 | −0.01±0.07 | |
I4A | R78 | −7.56±0.35 | −6.45±0.28 |
R106 | −10.43±0.42 | −14.78±0.31 | |
R126 | −23.26±0.51 | −0.05±0.04 |
According to Table1, besides the intermolecular Coulomb interactions, 8CA also produces favorable van der Waals interaction (−33.35 kcal·mol−1) with A-FABP. In order to recognize the contributions of separate residues to van der Waals interaction, the LIGPLOT program was applied to perform the statistical analysis of hydrophobic contacts between 8CA and A-FABP, and a function of the hydrophobic contacts as simulation time was displayed in
For the F8A/A-FABP complex, the intermolecular Coulomb interactions of F8A with A-FABP is −52.04 kcal·mol−1. This interaction mainly comes from the contributions of hydrogen bonds (
Fig. A represents frequency distribution of the H atom…acceptor distance, Fig. B depicts the position of inhibitor F8A relative to key residues, Fig. C shows the hydrophobic contacts as a function of the simulation time.
In the case of the I4A/A-FABP complex, the intermolecular Coulomb interaction of I4A with A-FABP is −59.51 kcal·mol−1, which is mainly owed to the hydrogen bond interactions of I4A with S55, R126 and Y128 and the charge-charge interactions between I4A and the positively charged residue R78, R106 and R126. The frequency distribution of the H atom-acceptor distance in
Fig. A represents frequency distribution of the H atom…acceptor distance, Fig. B depicts the position of inhibitor I4A relative to key residues, Fig. C shows the hydrophobic contacts as a function of the simulation time.
Based on the above analyses, two interesting discoveries were obtained: (1) All of three inhibitors form stable hydrophobic contacts with the residues F16, M20, P38, S53, F57, A75 and I104, moreover, their carboxyl produce strong polar interaction with R78, R106, R126 and Y128. These residues just locate at the range corresponding to the obvious decrease in the RMSF (except for the residue 85–95) and the significant alternation of correlated motion. Especially, the polar interaction between inhibitors and R16 and Y128 produces a significant effect on the correlated motion of the C terminus (the range R1) relative to the N terminus, and favors the stability of the C terminus of A-FABP. (2) Both the substitutions of the position 2 and 5 in the benzyl of the common scaffold induce the rearrangement of the residues nearby them. However, the results are different, the substitution of the position 2 reduces the binding affinity, while the substitution of the position 5 and the seven-membered ring of the scaffold strengthen the inhibitor bindings, which basically agrees with the experimental results of Barf et al
To confirm the significant role of R126, a computational alanine scanning mutagenesis was performed on R126.
According to
In addition, the mutation R126A induces obvious increase of the intermolecular Coulomb interactions of R106 with inhibitors and the slight reduction of van der Waals interaction between inhibitors and A-FABP. The cause is that R126A decreases the intermolecular Coulomb interactions and the numbers of hydrogen bonds, which in turn results in the loss of intermolecular restrictions and induce the change of the interatomic position. Based on the above analyses, the polar interactions of R126 with the three inhibitors play a key role in the bindings of inhibitors to A-FABP and favors stability of the binding complex.
In the present work, the binding modes of the three inhibitors 8CA, F8A and I4A to A-FABP were studied by using a combination of 60-ns MD simulation in explicit water and SIE method. Our results show that two substitutions generate different effect on the inhibitor bindings, the substitution in the position 5 of