Exploring the parameter space of the coarse‐grained UNRES force field by random search: Selecting a transferable medium‐resolution force field

We explored the energy‐parameter space of our coarse‐grained UNRES force field for large‐scale ab initio simulations of protein folding, to obtain good initial approximations for hierarchical optimization of the force field with new virtual‐bond‐angle bending and side‐chain‐rotamer potentials which we recently introduced to replace the statistical potentials. 100 sets of energy‐term weights were generated randomly, and good sets were selected by carrying out replica‐exchange molecular dynamics simulations of two peptides with a minimal α‐helical and a minimal β‐hairpin fold, respectively: the tryptophan cage (PDB code: 1L2Y) and tryptophan zipper (PDB code: 1LE1). Eight sets of parameters produced native‐like structures of these two peptides. These eight sets were tested on two larger proteins: the engrailed homeodomain (PDB code: 1ENH) and FBP WW domain (PDB code: 1E0L); two sets were found to produce native‐like conformations of these proteins. These two sets were tested further on a larger set of nine proteins with α or α + β structure and found to locate native‐like structures of most of them. These results demonstrate that, in addition to finding reasonable initial starting points for optimization, an extensive search of parameter space is a powerful method to produce a transferable force field. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Update of the ATTRACT force field for the prediction of protein–protein binding affinity

Determining the protein–protein interactions is still a major challenge for molecular biology. Docking protocols has come of age in predicting the structure of macromolecular complexes. However, they still lack accuracy to estimate the binding affinities, the thermodynamic quantity that drives the formation of a complex. Here, an updated version of the protein–protein ATTRACT force field aiming at predicting experimental binding affinities is reported. It has been designed on a dataset of 218 protein–protein complexes. The correlation between the experimental and predicted affinities reaches 0.6, outperforming most of the available protocols. Focusing on a subset of rigid and flexible complexes, the performance raises to 0.76 and 0.69, respectively. © 2017 Wiley Periodicals, Inc.     

Determination of side‐chain‐rotamer and side‐chain and backbone virtual‐bond‐stretching potentials of mean force from AM1 energy surfaces of terminally‐blocked amino‐acid residues,for coarse‐grained simulations of protein structure and folding. I. The method

In this and the accompanying article, we report the development of new physics‐based side‐chain‐rotamer and virtual‐bond‐deformation potentials which now replace the respective statistical potentials used so far in our physics‐based united‐reside UNRES force field for large‐scale simulations of protein structure and dynamics. In this article, we describe the methodology for determining the corresponding potentials of mean force (PMF's) from the energy surfaces of terminally‐blocked amino‐acid residues calculated with the AM1 quantum‐mechanical semiempirical method. The approach is based on minimization of the AM1 energy for fixed values of the angles λ for rotation of the peptide groups about the C^α ··· C^α virtual bonds, and for fixed values of the side‐chain dihedral angles χ, which formed a multidimensional grid. A harmonic‐approximation approach was developed to extrapolate from the energy at a given grid point to other points of the conformational space to compute the respective contributions to the PMF. To test the applicability of the harmonic approximation, the rotamer PMF's of alanine and valine obtained with this approach have been compared with those obtained by using a Metropolis Monte Carlo method. The PMF surfaces computed with the harmonic approximation are more rugged and have more pronounced minima than the MC‐calculated surfaces but the harmonic‐approximation‐and MC‐calculated PMF values are linearly correlated. The potentials derived with the harmonic approximation are, therefore, appropriate for UNRES for which the weights (scaling factors) of the energy terms are determined by force‐field optimization for foldability. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Comparison of energy‐loss functions from REELS spectra with surface and bulk energy loss functions for Ag

Effective energy‐loss functions were derived from the reflection electron energy‐loss spectroscopy (REELS) spectra of Ag by an extended Landau approach. The effective energy‐loss functions obtained are close to the surface energy‐loss function in the low‐energy‐loss region, but tend to be closer to the bulk energy‐loss function in the higher energy‐loss region for higher primary energy. The REELS spectra incorporating the effective energy‐loss function are also reproduced in a Monte‐Carlo simulation model and confirm that the simulation reproduces the experimental REELS spectra with considerable success. Copyright © 2003 John Wiley & Sons, Ltd.     

Extension of the CHARMM general force field to sulfonyl‐containing compounds and its utility in biomolecular simulations

Presented is an extension of the CHARMM General Force Field (CGenFF) to enable the modeling of sulfonyl‐containing compounds. Model compounds containing chemical moieties such as sulfone, sulfonamide, sulfonate, and sulfamate were used as the basis for the parameter optimization. Targeting high‐level quantum mechanical and experimental crystal data, the new parameters were optimized in a hierarchical fashion designed to maintain compatibility with the remainder of the CHARMM additive force field. The optimized parameters satisfactorily reproduced equilibrium geometries, vibrational frequencies, interactions with water, gas phase dipole moments, and dihedral potential energy scans. Validation involved both crystalline and liquid phase calculations showing the newly developed parameters to satisfactorily reproduce experimental unit cell geometries, crystal intramolecular geometries, and pure solvent densities. The force field was subsequently applied to study conformational preference of a sulfonamide based peptide system. Good agreement with experimental IR/NMR data further validated the newly developed CGenFF parameters as a tool to investigate the dynamic behavior of sulfonyl groups in a biological environment. CGenFF now covers sulfonyl group containing moieties allowing for modeling and simulation of sulfonyl‐containing compounds in the context of biomolecular systems including compounds of medicinal interest. © 2012 Wiley Periodicals, Inc.