On the attribution and additivity of binding energies

Jencks, William P.

doi:10.1073/pnas.78.7.4046

Cited by 900 publications

(811 citation statements)

References 35 publications

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“…However, about half of the rotational/ translational entropy loss will go toward increasing the vibrational entropy upon binding (Finkelstein & Janin, 1989). The remaining 8 kcal/mol net entropy loss is in good agreement with the range of 7-1 1 kcal/mol, estimated for enzymatic reactions in the liquid phase (Page & Jencks, 1971;Jencks, 1981). In addition, the loss of dilutional or cratic entropy adds about 2 kcal/mol (Kauzmann, 1959).…”

Section: Side-chain Entropy Changesupporting

confidence: 80%

Empirical free energy calculation: Comparison to calorimetric data

Weng¹,

DeLisi²,

Vajda³

1997

Protein Science

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An effective free energy potential, developed originally for binding free energy calculation, is compared to calorimetric data on protein unfolding, described by a linear combination of changes in polar and nonpolar surface areas. The potential consists of a molecular mechanics energy term calculated for a reference medium (vapor or nonpolar liquid), and empirical terms representing solvation and entropic effects. It is shown that, under suitable conditions, the free energy function agrees well with the calorimetric expression. An additional result of the comparison is an independent estimate of the side-chain entropy loss, which is shown to agree with a structure-based entropy scale. These findings confirm that simple functions can be used to estimate the free energy change in complex systems, and that a binding free energy evaluation model can describe the thermodynamics of protein unfolding correctly. Furthermore, it is shown that folding and binding leave the sum of solute-solute and solute-solvent van der Waals interactions nearly invariant and, due to this invariance, it may be advantageous to use a nonpolar liquid rather than vacuum as the reference medium.Keywords: binding free energy; free energy calculation; heat capacity; protein unfolding Calculating the free energy change in protein folding and association is a classical problem in biophysical chemistry. In principle, free energy differences can be obtained by molecular dynamics and Monte Carlo simulations that allow for similar molecules to be interconverted, and the relative free energies determined by perturbation or integration techniques (Mezei & Beveridge, 1986; Reynolds et al., 1992). However, simulation methods are far too expensive computationally for free energy calculation in conformational search, docking, and design (Wilson et al., 1991). The simplest remedy is to neglect solvation and entropic contributions in applications, but it is well known that energy-type target functions are frequently unable to distinguish between correct and incorrect proteins folds (Novotny et al., 1988), or correct and incorrect docked conformations (Shoichet & Kuntz, 1991 becoming the standard in computer-aided molecular design (Ajay & Murcko, 1995).We have developed a relatively complete empirical free energy function, and evaluated it against a range of structural and thermodynamic data (Vajda et al., Gulukota et al., 1996;King et al., 1996; Weng et ai., 1996). The free energy change, AG = G2 -G I , between two states is calculated according to the expression:where AE, Act,, and AS, represent the energy change, the desolvation free energy, and the change in conformational entropy, respectively. The last term, AC,,t/lrrr includes all other free energy changes associated with translational, rotational, vibrational, cratic, and protonation/deprotonation effects (Novotny et al., 1989; Vajda et al., 1994).The function has been developed originally for calculating receptor-ligand binding free energies, and we used a number of simplifying assumptions t...

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Section: Side-chain Entropy Changesupporting

confidence: 80%

Empirical free energy calculation: Comparison to calorimetric data

Weng¹,

DeLisi²,

Vajda³

1997

Protein Science

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“…Therefore, the double mutant R83A/R133A was also chosen for study. 23 The aromatic residue, W160, is located at both types of threefold interfaces, but, again, the energetic effect at the ferritin-like threefold interface is predicted to be more significant than at the Dps-like symmetry interface (Supporting Information Figs. S11 and S12).…”

Section: Selection Of Interfacial Residues For Mutagenesismentioning

confidence: 99%

Rational disruption of the oligomerization of the mini‐ferritin E. coli DPS through protein‐protein interface mutation

Zhang

Chee

et al. 2011

Protein Science

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DNA-binding protein from starved cells (DPS), a mini-ferritin capable of self-assembling into a 12-meric nano-cage, was chosen as the basis for an alanine-shaving mutagenesis study to investigate the importance of key amino acid residues, located at symmetry-related protein-protein interfaces, in controlling protein stability and self-assembly. Nine mutants were designed through simple inspection, synthesized, and subjected to transmission electron microscopy, circular dichroism, size exclusion chromatography, and ''virtual alanine scanning'' computational analysis. The data indicate that many of these residues may be hot spot residues. Most remarkably, two residues, R83 and R133, were observed to shift the oligomerization state to~50% dimer. Based on the hypothesis that these two residues constitute a ''hot strip,'' located at the ferritin-like threefold axis, the double mutant was generated which completely shuts down detectable formation of 12-mer in solution, favoring a cooperatively folded dimer. The fact that this effect logically builds upon the single mutants emphasizes that complex self-assembly has the potential to be manipulated rationally. This study should have an impact on the fundamental understanding of the assembly of DPS protein cages specifically and protein quaternary structure in general. In addition, as there is much interest in applying these and similar systems to the templation of nano-materials and drug delivery, the ability to control this ferritin's oligomerization state and stability could prove especially valuable.

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“…This species is characterized by the loss of three degrees each of translational and rotational entropy accompanying "2 + 1" association reactions. These entropy losses are in part offset by introduced vibrations specific to the complex (Jencks, 1981). The components of such a complex as envisioned would largely retain the solvation shells of the individual proteins, and few of the short-range interactions of the docked complex would be established (Van Oss, 1995).…”

Section: Transition State Structures For Protein Dockingmentioning

confidence: 99%