Free energies predictions

THE CHALLENGES OF MAKING USEFUL PROTEIN-LIGAND FREE ENERGY PREDICTIONS FOR DRUG DISCOVERY... 

If our conformational and free energy predictions were correct, we expect min(C) = - i rinXc . Otherwise, the most we could expect is ... 

Figure 9. Coexistence curves for a parent distribution with pf = 0.2. Shown are the values of p, of the coexisting phases horizontal lines guide the eye where new phases appear. Curves are labeled by n, the number of moment densities retained in the moment free energy. Predictions for n = 10 are indistinguishable from an exact calculation (in bold).

Figure 8.3 Convergence with number of binomial moments of hydration free energy predicted using several default models for a spherical solute with distance of closest approach 3.0 A for water oxygen atoms. Identifications are diamonds (dash-dot lines), hard-sphere default HS), crosses (short dash line), Lennard-Jones LJ) default squares (long dash line), Poisson default triangles (dotted line), cluster Poisson default and circles (solid line), flat default. For this circumstance, yth-order binomial moments are non-zero through j = 9, and the horizontal line is the prediction with all nine moments included. Among the predictions at j = 2, the best default model is the Lennard-Jones case. But with the hard-sphere model excepted, the differences are slight. See Hummer et al. (1996), Gomez et al. (1999) and Pratt etal. (1999) for details of the calculations.

Figure 5.1.5. Excess Gibbs free-energy predictions for the acetone and water binary system at 298 K. The circles are calculated from experimental data (see text), the solid line with crosses reflects the UNIFAC predictions, and the smooth solid line denotes the results of the WS model. The large, medium, and short dashed lines are from the HVOS, HVO, and MHVl models, respectively the dotted line is from the MHVl model and the dot-dash line represents the results of the LCVM model.

Bortolato, A. and Moro, S. (2007) In silico binding free energy predictability by using the linear interaction energy (LIE) method bromobenzrmidazole CK2 inhibitors as a case study. Journal of Chemical Information and Modeling, 47, 572-582. 

Michel, J., Verdonk, M.L., Essex, J.W. Protein-Kgand binding free energy predictions by implicit solvent simulation A tool for lead optimization , J. Med. Chem. 2006,49, 7427-39. 

An updated recursive algorithm that minimizes free energy predicts 82.5% of phylogenetically determined base pairs from sequence in four small subunit rRNAs, four group I introns, three group II introns, and 41 tRNAs. The rRNAs and group II introns were folded in phylogenetically determined domains of no more than 500 nucleotides. 

Zheng Xianmin, "The Free Energy Prediction and the Principie of Le Chateiier," j. Chem. Educ., Voi. 66, 1989, 401 02. 

The continuum methods are advantageous because solvent effects are treated in a physically reasonable way, the methods require modest computational resources, and their simplicity allows one to easily extend standard methods for treating gas phase systems to the solvent realm. One disadvantage is that continuum model free energy predictions are sensitive to the atomic radii used to define the solute-solvent dielectric interface. However, these radii can effectively be determined by parameterization using small systems [24]. 

Spontaneity, Entropy and Free Energy Predicting dangerous spontaneous reactions. Respecting chemicals hidden energy content. 

Yildirim, I., Stern, H. A., Sponer, J., Spackova, N., 8c Turner, D. H. (2009). Effects of restrained sampling space and nonplanar amino groups on free-energy predictions for RNA with imino and sheared tandem GA base Pairs. Flanked by GC, CG, iGiC or iCIG base pairs. Journal of Chemical Theory and Computation, 5, 2088. 

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