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Development and testing of a general amber force field.

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TLDR
A general Amber force field for organic molecules is described, designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most organic and pharmaceutical molecules that are composed of H, C, N, O, S, P, and halogens.
Abstract
We describe here a general Amber force field (GAFF) for organic molecules. GAFF is designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most organic and pharmaceutical molecules that are composed of H, C, N, O, S, P, and halogens. It uses a simple functional form and a limited number of atom types, but incorporates both empirical and heuristic models to estimate force constants and partial atomic charges. The performance of GAFF in test cases is encouraging. In test I, 74 crystallographic structures were compared to GAFF minimized structures, with a root-mean-square displacement of 0.26 A, which is comparable to that of the Tripos 5.2 force field (0.25 A) and better than those of MMFF 94 and CHARMm (0.47 and 0.44 A, respectively). In test II, gas phase minimizations were performed on 22 nucleic acid base pairs, and the minimized structures and intermolecular energies were compared to MP2/6-31G* results. The RMS of displacements and relative energies were 0.25 A and 1.2 kcal/mol, respectively. These data are comparable to results from Parm99/RESP (0.16 A and 1.18 kcal/mol, respectively), which were parameterized to these base pairs. Test III looked at the relative energies of 71 conformational pairs that were used in development of the Parm99 force field. The RMS error in relative energies (compared to experiment) is about 0.5 kcal/mol. GAFF can be applied to wide range of molecules in an automatic fashion, making it suitable for rational drug design and database searching.

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Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations

TL;DR: A machine learning (ML) based approach for predicting partial charges extracted from density functional theory (DFT) electron densities and the training set was chosen with the goal to provide a broad coverage of the known chemical space of druglike molecules.
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Molecular dynamics simulations reveal ligand-controlled positioning of a peripheral protein complex in membranes

TL;DR: Natural supplies of bryostatin, a compound in clinical trials for Alzheimer’s disease, cancer, and HIV, are scarce, and molecular dynamics simulations to understand how brystatin interacts with membrane-bound protein kinase C are performed, offering insights for the design of b Bryostatin analogs.
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Conformational transitions upon ligand binding: holo-structure prediction from apo conformations.

TL;DR: A method to predict the structure ofprotein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure is presented and a protocol is presented that is expected to enable structure modeling of protein/ligands complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available.
References
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Journal ArticleDOI

A well-behaved electrostatic potential based method using charge restraints for deriving atomic charges: the RESP model

TL;DR: In this paper, the authors present an approach to generate electrostatic potential (ESP) derived charges for molecules, which optimally reproduce the intermolecular interaction properties of molecules with a simple two-body additive potential, provided that a suitably accurate level of quantum mechanical calculation is used to derive the ESP around the molecule.
Journal ArticleDOI

Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94

TL;DR: The first published version of the Merck molecular force field (MMFF) is MMFF94 as mentioned in this paper, which is based on the OPLS force field and has been applied to condensed-phase processes.
Journal ArticleDOI

A new force field for molecular mechanical simulation of nucleic acids and proteins

TL;DR: In this paper, a force field for simulation of nucleic acids and proteins is presented, which is based on the ECEPP, UNECEPP, and EPEN energy refinement software.
Journal ArticleDOI

How Well Does a Restrained Electrostatic Potential (RESP) Model Perform in Calculating Conformational Energies of Organic and Biological Molecules

TL;DR: In this paper, the authors present conformational energies for a molecular mechanical model (Parm99) developed for organic and biological molecules using the restrained electrostatic potential (RESP) approach to derive the partial charges.
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