The General AMBER Force Field (GAFF) has been broadly used by researchers all over the world to perform in silico simulations and modelings on diverse scientific topics, especially in the field of computer-aided drug design whose primary task is to accurately predict the affinity and selectivity of receptor-ligand binding. The atomic partial charges in GAFF and the second generation of GAFF (GAFF2) were originally developed with the quantum mechanics derived restrained electrostatic potential charge, but in practice, users usually adopt an efficient charge method, Austin Model 1-bond charge corrections (AM1-BCC), based on which, without expensive ab initio calculations, the atomic charges could be efficiently and conveniently obtained with the ANTECHAMBER module implemented in the AMBER software package. In this work, we developed a new set of BCC parameters specifically for GAFF2 using 442 neutral organic solutes covering diverse functional groups in aqueous solution. Compared to the original BCC parameter set, the new parameter set significantly reduced the mean unsigned error (MUE) of hydration free energies from 1.03 kcal/mol to 0.37 kcal/mol. More excitingly, this new AM1-BCC model also showed excellent performance in the solvation free energy (SFE) calculation on diverse solutes in various organic solvents across a range of different dielectric constants. In this large-scale test with totally 895 neutral organic solventsolute systems, the new parameter set led to accurate SFE predictions with the MUE and the root-mean-square-error of 0.51 kcal/mol and 0.65 kcal/mol, respectively. This newly developed charge model, ABCG2, paved a promising path for the next generation GAFF development.

The effects of beta-sheet breaker peptides KLVFF and LPFFD on the oligomerization of amyloid peptides were studied by all-atom simulations. It was found that LPFFD interferes the aggregation of Aβ(16-22) peptides to a greater extent than does KLVFF. Using the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method, we found that the former binds more strongly to Aβ(16-22). Therefore, by simulations, we have clarified the relationship between aggregation rates and binding affinity: the stronger the ligand binding, the slower the oligomerization process. The binding affinity of pentapeptides to full-length peptide Aβ(1-40) and its mature fibrils has been considered using the Autodock and MM-PBSA methods. The hydrophobic interaction between ligands and receptors plays a more important role for association than does hydrogen bonding. The influence of beta-sheet breaker peptides on the secondary structures of monomer Aβ(1-40) was studied in detail, and it turns out that, in their presence, the total beta-sheet content can be enhanced. However, the aggregation can be slowed because the beta-content is reduced in fibril-prone regions. Both pentapeptides strongly bind to monomer Aβ(1-40), as well as to mature fibrils, but KLVFF displays a lower binding affinity than LPFFD. Our findings are in accord with earlier experiments that both of these peptides can serve as prominent inhibitors. In addition, we predict that LPFFD inhibits/degrades the fibrillogenesis of full-length amyloid peptides better than KLVFF. This is probably related to a difference in their total hydrophobicities in that the higher the hydrophobicity, the lower the inhibitory capacity. The GROMOS96 43a1 force field with explicit water and the force field proposed by Morris et al. (Morris et al. J. Comput. Chem. 1998, 19, 1639 ) were employed for all-atom molecular dynamics simulations and Autodock experiments, respectively.

The dimer of the amyloid-β peptide Aβ of 42 residues is the smallest toxic species in Alzheimer’s disease, but its equilibrium structures are unknown. Here we determined the equilibrium ensembles generated by the four atomistic OPLS-AA, CHARMM22*, AMBER99sb-ildn, and AMBERsb14 force fields with the TIP3P water model. On the basis of 144 µs replica exchange molecular dynamics simulations (with 750 ns per replica), we find that the four force fields lead to random coil ensembles with calculated cross-collision sections, hydrodynamics properties, and small-angle X-ray scattering profiles independent of the force field. There are, however, marked differences in secondary structure, with the AMBERsb14 and CHARMM22* ensembles overestimating the CD-derived helix content, and the OPLS-AA and AMBER99sb-ildn secondary structure contents in agreement with CD data. Also the intramolecular beta-hairpin content spanning residues 17–21 and 30–36 varies between 1.5% and 13%. Overall, there are significant differences in tertiary and quaternary conformations among all force fields, and the key finding, irrespective of the force field, is that the dimer is stabilized by nonspecific interactions, explaining therefore its possible transient binding to multiple cellular partners and, in part, its toxicity.

We investigated the effects of 17 widely used atomistic molecular mechanics force fields (MMFFs) on the structures and kinetics of amyloid peptide assembly. To this end, we performed large-scale all-atom molecular dynamics simulations in explicit water on the dimer of the sevenresidue fragment of the Alzheimer's amyloid-β peptide, Aβ16−22, for a total time of 0.34 ms. We compared the effects of these MMFFs by analyzing various global reaction coordinates, secondary structure contents, the fibril population, the in-register and out-of-register architectures, and the fibril formation time at 310 K. While the AMBER94, AMBER99, and AMBER12SB force fields do not predict any β-sheets, the seven force fields, AMBER96, GROMOS45a3, GROMOS53a5, GROMOS53a6, GROMOS43a1, GROMOS43a2, and GROMOS54a7, form β-sheets rapidly. In contrast, the following five force fields, AMBER99-ILDN, AMBER14SB, CHARMM22*, CHARMM36, and CHARMM36m, are the best candidates for studying amyloid peptide assembly, as they provide good balances in terms of structures and kinetics. We also investigated the assembly mechanisms of dimeric Aβ16−22 and found that the fibril formation rate is predominantly controlled by the total β-strand content.