AM1-SM2 and PM3-SM3 parameterized SCF solvation models for free energies in aqueous solution

Cramer, Christopher J.; Truhlar, Donald G.

doi:10.1007/bf00126219

Cited by 330 publications

(316 citation statements)

References 86 publications

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“…To more ac-curately predict the solvation free energy, it is necessary to calculate the screening energy (the electrostatic part) using a more physically rigorous approach. The most popular models for screening energy calculations are the Generalized Born model (GB), [16][17][18][19][20][21] the Poisson-Boltzmann (PB) model, 14,15 and the conductor-like models (COSMO). [22][23][24] Although these models have a somewhat different theoretical basis, after appropriate parametrization, the electrostatic solvation effect can be well represented by each of these models and be applied in molecular docking, binding free energy calculations and protein folding studies.…”

Section: Introductionmentioning

confidence: 99%

Solvation Model Based on Weighted Solvent Accessible Surface Area

et al. 2001

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We have developed a fast procedure to predict solvation free energies for both organic and biological molecules. This solvation model is based on weighted solvent accessible surface area (WSAS). Least-squares fittings have been applied to optimize the weights of SAS for different atom types in order to reproduce the experimental solvation free energies. Good agreement with experimental results has been obtained. For the 184-molecule set (model I), for which there are experimental solvation free energies in 1-octanol, we have achieved an average error of 0.36 kcal/mol, better than that of the SM5.42R universal solvation model 1 by Li et al. For the 245-molecule set (model II) that has experimental aqueous solvation free energies, our WSAS model achieves an average error of 0.48 kcal/mol, marginally larger than that of Li's model (0.46 kcal/mol). We have used a 401-molecule set, the largest training set (model IV) that we know of solvation model development, to derive the SAS weights in order to reproduce the experimental solvation free energies in water. For this model, we have achieved an average unsigned error of 0.54 kcal/mol and an RMS error of 0.79 kcal/mol.The advantage of this model lies in its simplicity and independence of charge models. We have successfully applied this model to predict the relative binding free energies for the five binding modes of HIV-1RT/ efavirenz. The most favorable binding mode, which has an RMSD of 1.1 Å (for 54 C R around the binding site) compared to the crystal structure, has a binding free energy at least 10 kcal/mol more negative than the other binding modes. Moreover, the solvation free energies with WSAS have a high correlation (the correlation coefficient is 0.92) to the solvation free energies calculated by the Poisson-Boltzmann/surface area (PBSA) model. As an efficient and fast approach, WASA is also attractive for protein modeling and protein folding studies. We have applied this model to predict the solvation free energies of the 36-mer villin headpiece subdomain in its native structure, a compact folding intermediate, and a random coil. The rank order of the solvation free energies and the free energies for the three kinds of conformational clusters are in reasonable agreement with those found by MM-PBSA, a widely used solvation free energy model.

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Section: Introductionmentioning

confidence: 99%

Solvation Model Based on Weighted Solvent Accessible Surface Area

et al. 2001

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“…An alternative, which is rapid enough to be generally useful, relates solvation free energy to solvent-accessible surface areas or hydration shell volumes through atomic solvation parameters (Chothia & Janin, 1975;Eisenberg & Mclachlan, 1986;Ooi et al, 1987;Colonna-Cesari & Sander, 1990;Cramer & Truhlar, 1992;Wesson & Eisenberg, 1992;Stouten et al, 1993). In this case, the empirical procedure takes account of not just surface area (entropy), but of the types of atomic groups (enthalpy) on the surface.…”

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confidence: 99%

Prediction of protein complexes using empirical free energy functions

1996

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A long sought goal in the physical chemistry of macromolecular structure, and one directly relevant to understanding the molecular basis of biological recognition, is predicting the geometry of bimolecular complexes from the geometries of their free monomers. Even when the monomers remain relatively unchanged by complex formation, prediction has been difficult because the free energies of alternative conformations of the complex have been difficult to evaluate quickly and accurately. This has forced the use of incomplete target functions, which typically do no better than to provide tens of possible complexes with no way of choosing between them. Here we present a general framework for empirical free energy evaluation and report calculations, based on a relatively complete and easily executable free energy function, that indicate that the structures of complexes can be predicted accurately from the structures of monomers, including close sequence homologues. The calculations also suggest that the binding free energies themselves may be predicted with reasonable accuracy. The method is compared to an alternative formulation that has also been applied recently to the same data set. Both approaches promise to open new opportunities in macromolecular design and specificity modification.Keywords: desolvation free energy; electrostatic interaction energy; rigid body docking; side-chain conformational search Understanding biological function at its most fundamental level, and manipulating it for therapeutic purposes, requires understanding the molecular basis of specificity. The critical determinant of true understanding is the ability to make quantitative predictions. In the case of molecular recognition, this means predicting the geometry of a complex from the free structures of its constituents.Even when conformations remain relatively unperturbed by reaction, thereby restricting the search for potential molecular complexes to a manageable size, achieving the goal of true prediction has proved elusive. Rigid body docking algorithms (Cherfils et al., 1991;Jiang & Kim, 1991;Shoichet & Kuntz, 1991;Bacon & Moult, 1992;Stoddard & Koshland, 1992;Walls & Sternberg, 1992;Helmer-Citterich & Tramontano, 1994;Judson et al., 1995) permit exploration of the orientations of a ligand in a receptor combining site, and effectively select those relatively few that meet prespecified criteria-including surface complementarity, interaction energy, and hydrophobic surface burial.As shown by Shoichet and Kuntz (1991), the methods go far toward reducing hundreds of thousands of possibilities to tens ~

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“…Over the neutral set, SM2 and SM3 had rms errors of 0.9 and 1.3 kcal/mol, respectively, and over the ionic set these errors were 3.9 and 5.6 kcal/mol, respectively. The larger errors exhibited by SM3 are associated in part with the now well known poor quality of PM3 partial charges on N atoms [26].…”

Section: Smx Models For Semiempirical Hamiltoniansmentioning

confidence: 99%

“…The next two SMx models to be reported, SM2 [26,41] and SM3 [26,42], were also aqueous solvation models based on semiempirical Hamiltonians. SM2 was designed for use with AM1 and SM3 for use with the Parameterized Model 3 (PM3) of Stewart [43].…”

Section: Smx Models For Semiempirical Hamiltoniansmentioning

confidence: 99%

“…In the SMx models, the reaction field operator is represented using the generalized Born (GB) equation [6,8,[19][20][21][22][23][24][25][26][27][28]. In the GB approach, the charge distribution of the solute is represented by an atomcentered distribution of monopoles (i.e., partial atomic charges) and at each atom k the reaction field is defined as…”

Section: Introduction and Underlying Physicsmentioning

confidence: 99%

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SMx Continuum Models for Condensed Phases

Cramer

Truhlar

2006

Trends and Perspectives in Modern Computational Science

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Abstract:The SMx continuum models are designed to include condensed-phase effects in classical and quantum mechanical electronic structure calculations and can also be used for calculating geometries and vibrational frequencies in condensed phases. Originally developed for homogeneous liquid solutions, the SMx models have seen substantial application to more complicated condensed phases as well, e.g., the airwater interface, soil, phospholipid membranes, and vapor pressures of crystals as well as liquids. Bulk electrostatics are accounted for via a generalized Born formalism, and other physical contributions to free energies of interaction between a solute and the surrounding condensed phase are modeled by environmentally sensitive atomic surface tensions associated with solute atoms having surface area exposed to the surrounding medium. The underlying framework of the models, including the charge models used for the electrostatics, and some of the models' most recent extensions are summarized in this report. In addition, selected applications to environmental chemistry problems are presented.

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AM1-SM2 and PM3-SM3 parameterized SCF solvation models for free energies in aqueous solution

Cited by 330 publications

References 86 publications

Solvation Model Based on Weighted Solvent Accessible Surface Area

Solvation Model Based on Weighted Solvent Accessible Surface Area

Prediction of protein complexes using empirical free energy functions

SMx Continuum Models for Condensed Phases

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