Extending the Nonbonded Cationic Dummy Model to Account for Ion-Induced Dipole Interactions

Abstract

Modeling metalloproteins often requires classical molecular dynamics (MD) simulations in order to capture their relevant motions, which in turn necessitates reliable descriptions of the metal centers involved. One of the most successful approaches to date is provided by the “cationic dummy model”, where the positive charge of the metal ion is transferred toward dummy particles that are bonded to the central metal ion in a predefined coordination geometry. While this approach allows for ligand exchange, and captures the correct electrostatics as demonstrated for different divalent metal ions, current dummy models neglect ion-induced dipole interactions. In the present work, we resolve this weakness by taking advantage of the recently introduced 12–6–4 type Lennard-Jones potential to include ion-induced dipole interactions. We revise our previous dummy model for Mg2+ and demonstrate that the resulting model can simultaneously reproduce the experimental solvation free energy and metal–ligand distances without the need for artificial restraints or bonds. As ion-induced dipole interactions become particularly important for highly charged metal ions, we develop dummy models for the biologically relevant ions Al3+, Fe3+, and Cr3+. Finally, the effectiveness of our new models is demonstrated in MD simulations of several diverse (and highly challenging to simulate) metalloproteins.

Structural and functional insights into the bona fide catalytic state of Streptococcus pyogenes Cas9 HNH nuclease domain

“…Compared to our MD simulations, we identified very limited differences from the QM/MD simulations in terms of the active site configuration. Encouragingly, this observation is consistent with our most recent benchmark work (Zuo and Liu, 2018a) demonstrating the good performance of the used nonbonded Mg 2+ ion model (Liao et al, 2017) in maintaining challenging enzyme metal centers.…”

“…Most recently, we systematically evaluated the performance of all four types of non-bonded Mg 2+ ion models in terms of maintaining a challenging metal center configuration in a nuclease system (Nowotny et al, 2005). Our benchmark calculations demonstrated that the multisite models based a 12-6-4 Lennard-Jones potential (Li and Merz, 2014; Liao et al, 2017), which take charge-induced dipole effects into account, are the only ones that are capable of reproducing the experimental coordination patterns (Zuo and Liu, 2018a). Accordingly, the 12-6-4 type multisite model (Jorgensen et al, 1983) (here the midC4 set) was considered for the Cas9 complex simulation, along with the TIP4PEw model for water, the Joung-Cheatham parameter sets for monovalent ions (Joung and Cheatham, 2008), and the amber force fields ff14SBonlysc , ff99bsc0_chiOL3 , ff99bsc0_OL15 for protein, RNA and DNA, respectively.…”

A positive, growth-based PAM screen identifies noncanonical motifs recognized by the S. pyogenes Cas9

“…All simulations were performed by the CUDA-accelerated version of AMBER16 pmemd engine (pmemd.cuda), using the amber force fields ff14SBonlysc, ff99bsc0_chiOL3, and ff99bsc0_OL15 for describing the protein, RNA, and DNA solutes, respectively ( 41 ). The Joung-Cheatham parameter sets ( 42 ) were chosen for modeling the monovalent metal ions and the recent multisite ion model with a modified Lennard-Jones potential ( 43 ) for the Mg 2+ ions in combination with the TIP4PEw water model. The nonbonded interactions were truncated at 10 Å, and the long-range electrostatics were calculated through the particle mesh Ewald summation method ( 44 ), with a grid spacing of 1 Å.…”

Challenges and advances in the computational modeling of biological phosphate hydrolysis

“…81 Finally, we used Merz' 12-6-4 Lennard-Jones potential, which takes into account ion-induced dipole interactions, 82 to develop new multisite modes for highly charged metal ions. 83 These models have allowed us to explore the activities and selectivities of a range of organophosphate hydrolases, including methyl parathion hydrolase (MPH), 84 and phosphonate monoester hydrolases, 63 as described in the following section.…”