Solvent Binding Analysis and Computational Alanine Scanning of the Bovine Chymosin–Bovine κ-Casein Complex Using Molecular Integral Equation Theory

Allosteric-Activation Mechanism of Bovine Chymosin Revealed by Bias-Exchange Metadynamics and Molecular Dynamics Simulations

The aspartic protease, bovine chymosin, catalyzes the proteolysis of κ-casein proteins in milk. The bovine chymosin-κ-casein complex is of industrial interest as the enzyme is used extensively in the manufacturing of processed dairy products. The apo form of the enzyme adopts a self-inhibited conformation in which the side chain of Tyr77 occludes the binding site. On the basis of kinetic, mutagenesis, and crystallographic data, it has been widely reported that a HPHPH sequence in the P8-P4 residues of the natural substrate κ-casein acts as the allosteric activator, but the mechanism by which this occurs has not previously been elucidated due to the challenges associated with studying this process by experimental methods. Here we have employed two computational techniques, molecular dynamics and bias-exchange metadynamics simulations, to study the mechanism of allosteric activation and to compute the free energy surface for the process. The simulations reveal that allosteric activation is initiated by interactions between the HPHPH sequence of κ-casein and a small α-helical region of chymosin (residues 112-116). A small conformational change in the α-helix causes the side chain of Phe114 to vacate a pocket that may then be occupied by the side chain of Tyr77. The free energy surface for the self-inhibited to open transition is significantly altered by the presence of the HPHPH sequence of κ-casein.

Water based on a molecular model behaves like a hard-sphere solvent for a nonpolar solute when the reference interaction site model and related theories are employed

For neutral hard-sphere solutes, we compare the reduced density profile of water around a solute g(r), solvation free energy μ, energy U, and entropy S under the isochoric condition predicted by the two theories: dielectrically consistent reference interaction site model (DRISM) and angle-dependent integral equation (ADIE) theories. A molecular model for water pertinent to each theory is adopted. The hypernetted-chain (HNC) closure is employed in the ADIE theory, and the HNC and Kovalenko-Hirata (K-H) closures are tested in the DRISM theory. We also calculate g(r), U, S, and μ of the same solute in a hard-sphere solvent whose molecular diameter and number density are set at those of water, in which case the radial-symmetric integral equation (RSIE) theory is employed. The dependences of μ, U, and S on the excluded volume and solvent-accessible surface area are analyzed using the morphometric approach (MA). The results from the ADIE theory are in by far better agreement with those from computer simulations available for g(r), U, and μ. For the DRISM theory, g(r) in the vicinity of the solute is quite high and becomes progressively higher as the solute diameter d U increases. By contrast, for the ADIE theory, it is much lower and becomes further lower as d U increases. Due to unphysically positive U and significantly larger |S|, μ from the DRISM theory becomes too high. It is interesting that μ, U, and S from the K-H closure are worse than those from the HNC closure. Overall, the results from the DRISM theory with a molecular model for water are quite similar to those from the RSIE theory with the hard-sphere solvent. Based on the results of the MA analysis, we comparatively discuss the different theoretical methods for cases where they are applied to studies on the solvation of a protein.

Fast and General Method To Predict the Physicochemical Properties of Druglike Molecules Using the Integral Equation Theory of Molecular Liquids

We report a method to predict physicochemical properties of druglike molecules using a classical statistical mechanics based solvent model combined with machine learning. The RISM-MOL-INF method introduced here provides an accurate technique to characterize solvation and desolvation processes based on solute-solvent correlation functions computed by the 1D reference interaction site model of the integral equation theory of molecular liquids. These functions can be obtained in a matter of minutes for most small organic and druglike molecules using existing software (RISM-MOL) (Sergiievskyi, V. P.; Hackbusch, W.; Fedorov, M. V. J. Comput. Chem. 2011, 32, 1982-1992). Predictions of caco-2 cell permeability and hydration free energy obtained using the RISM-MOL-INF method are shown to be more accurate than the state-of-the-art tools for benchmark data sets. Due to the importance of solvation and desolvation effects in biological systems, it is anticipated that the RISM-MOL-INF approach will find many applications in biophysical and biomedical property prediction.