Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2

Abstract

Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein–ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein–ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-017-0055-0) contains supplementary material, which is available to authorized users.

How Good is Jarzynski’s Equality for Computer-Aided Drug Design?

“…To start research in this direction, we have chosen the LIE method because it is computationally not expensive but still reliable in many cases. 11 − 13 , 15 , 18 , 40 − 42 Thus, the binding affinity of small molecules to six different proteins was studied using LIE. We found that in all cases, the correlation between the experimental and the simulation results is lower than that of JE, with the exception of MCL-1, where LIE ( R = 0.85) is slightly better than JE ( R = 0.83) ( Table 4 ).…”

“…7 − 9 The contribution from the electrostatic and van der Waals (vdW) interaction energy is obtained through the thermodynamic cycle. 10 In the past few decades, several groups have successfully applied the LIE method to predict new inhibitors of human dihydrofolate reductases 10 and to obtain the binding affinity of inhibitors of neuraminidase, 11 BACE-1, 12 cytochrome P450, 13 , 14 farnesoid X receptor, 15 and others. 16 Several improved versions of LIE were proposed.…”

Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens

“…Usually one is applied to the electrostatic interactions and one to the Lennard–Jones interactions. The extrapolation and use of interaction energies have led to the name Linear Interaction Energy, or LIE method [ 118 , 119 , 120 ]. For a thorough review of its theoretical basis, see [ 121 ].…”

“…Another nuclear receptor, the farnesoid X receptor (FXR), was used as a test case for free energy calculations in 2018 [ 116 , 117 , 120 ]. FXR is involved in regulating bile acid, lipid, and glucose homeostasis [ 131 ], and it has been linked to hepatocarcinogenesis [ 132 ].…”

“…In one of the studies [ 117 ], ligands were first docked to the receptor, then compared using FEP. LIE gave similar errors for the same protein and 47 ligands [ 120 ], at a lower computational cost, but required optimization of the two adjustable LIE parameters using a subset of the ligands.…”