Abstract
A fully atomistic (AT) modeling of biological macromolecules at relevant length‐ and time‐scales is often cumbersome or not even desirable, both in terms of computational effort required and a posteriori analysis. This difficulty can be overcome with the use of multiresolution models, in which different regions of the same system are concurrently described at different levels of detail. In enzymes, computationally expensive AT detail is crucial in the modeling of the active site in order to capture, for example, the chemically subtle process of ligand binding. In contrast, important yet more collective properties of the remainder of the protein can be reproduced with a coarser description. In the present work, we demonstrate the effectiveness of this approach through the calculation of the binding free energy of hen egg white lysozyme with the inhibitor di‐N‐acetylchitotriose. Particular attention is payed to the impact of the mapping, that is, the selection of AT and coarse‐grained residues, on the binding free energy. It is shown that, in spite of small variations of the binding free energy with respect to the active site resolution, the separate contributions coming from different energetic terms (such as electrostatic and van der Waals interactions) manifest a stronger dependence on the mapping, thus pointing to the existence of an optimal level of intermediate resolution.
Highlights
Recall that the binding free energy calculation consists of three steps: restraint removal, ligand ΔG, and ligand-complex ΔG; of these, only the latter depends on protein resolution, that is, only ΔGlig: The protein-ligand complex free energy (ΔGcompl) assumes different values for different numbers of active site residues described at the all-atom level
We have shown how the dual resolution model employed, constituted by an all-atom subregion coupled to an elastic network model (ENM) remainder, can be used to calculate the binding free energy of an enzyme-substrate complex with AT accuracy
We have computed the total value of the binding free energy as well as that of its various energetic components, and quantitatively inspected how these change when different selections are performed for the subgroup of amino acids, ranging from 3 to 10 in total, to be modeled at the fully AT level
Summary
One of the most relevant challenges of computational biochemistry and biophysics is the accurate calculation of binding free energies,[1,2,3] which represents one of the key steps in the identification of pharmacological targets as well as in the development of new drugs.[4,5,6] the large sizes of the proteins under examination (often above the hundreds of residues), as well as the necessity to screen through large datasets of potential candidate drugs they can interact with, make this effort onerous in terms of time and computational resources.A promising way to mitigate these limitations is the use of multiple-resolution models of the protein, that is, representations in which different parts of the molecule are concurrently described at different levels of accuracy.[7,8,9,10,11,12] The chemically relevant part of the protein, for example, the active site, is modeled at a higher level of detail, typically atomistic (AT). One of the most relevant challenges of computational biochemistry and biophysics is the accurate calculation of binding free energies,[1,2,3] which represents one of the key steps in the identification of pharmacological targets as well as in the development of new drugs.[4,5,6] the large sizes of the proteins under examination (often above the hundreds of residues), as well as the necessity to screen through large datasets of potential candidate drugs they can interact with, make this effort onerous in terms of time and computational resources. On the contrary, a simplified representation is used, where several atoms are lumped together in effective interaction sites. The working hypothesis underlying these methods is that only a relatively small part of the molecule requires an explicitly AT treatment; the remainder, is mainly
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