Calculation of free energy changes due to mutations from alchemical free energy simulations

Abstract

How a mutation a®ects the binding free energy of a ligand is a fundamental problem in molecular biology/biochemistry with many applications in pharmacology and biotechnology, e.g. design of drugs and enzymes. Free energy change due to a mutation can be determined most accurately by performing alchemical free energy calculations in molecular dynamics (MD) simulations. Here we discuss the necessary conditions for success of free energy calculations using toxin peptides that bind to ion channels as examples. We show that preservation of the binding mode is an essential requirement but this condition is not always satis¯ed, especially when the mutation involves a charged residue. Otherwise problems with accuracy of results encountered in mutation of charged residues can be overcome by performing the mutation on the ligand in the binding site and bulk simultaneously and in the same system. The proposed method will be useful in improving the a±nity and selectivity pro¯les of drug leads and enzymes via computational design and protein engineering.

Potency-Enhancing Mutations of Gating Modifier Toxins for the Voltage-Gated Sodium Channel NaV1.7 Can Be Predicted Using Accurate Free-Energy Calculations

“…A stable binding mode for the GMT is necessary for accurate FEP predictions as shown in previous studies [ 25 , 28 ]. We examined the pose stability of ten ProTx-II mutants for three different kinds of FEP simulations: no membrane present, membrane present, and Cɑ position restraints present.…”

“…FEP performed well for charge-change mutations with an RMSE of 0.96 ± 0.15 kcal/mol and an R 2 of 0.81. This category of mutations has historically been challenging for FEP [ 28 ], suggesting that recent improvements for predicting charge-changes [ 25 ] were effective. Taken together, these data suggest that FEP can be used to accurately predict how a mutation to a GMT that targets VSDII of Nav1.7 will affect its potency for the channel, setting the stage for its prospective application in biologics drug discovery programs.…”

“…Nevertheless, we begin by performing a retrospective study on forty-seven GMT mutants ( Figure 3 ), re-predicting their experimentally measured changes in potency for Na V 1.7 using both FEP and MM-GB/SA [ 10 , 11 , 14 ]. The dataset includes a large number of charge-change mutations, which historically have been challenging for FEP due to the fact that the peptide toxin binding mode can become unstable during these perturbations [ 25 , 28 ] ( Figure 3 ). Next, to test our hypothesis regarding the importance of modeling the ternary complex for FEP calculations, we examine the pose stability of GMTs during FEP simulations with and without the membrane.…”

Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes

“…Nevertheless, the ΔΔG b for the F23A mutant was calculated to be ~9.8 kJ/mol, in good agreement with the experimental value of ~7.8 kJ/mol. Similarly, another simulation study showed that the mutation R29A in the peptide ShK, a potent inhibitor of Kv1.1, changes the peptide’s binding mode, which prevented the use of FEP to calculate ΔΔG b [ 98 ]. In fact, mutations of charged residues pose a particular challenge for FEP calculations.…”

“…In fact, mutations of charged residues pose a particular challenge for FEP calculations. To address this issue, Rashid et al [ 98 ] reported a multi-step approach in which the Lennard-Jones interactions are decoupled from the Coulomb interactions and the mutation is simultaneously performed on the residue in the bound and unbound state. The approach was used to calculate the ΔΔG b for the R18A mutation in the peptide-channel complex HsTx1-K V 1.1 and the data showed good agreement with experiments.…”