Global minimization via classical tunneling assisted by collective force field formation

<div><div><div><p>A new reactive force field based on the ReaxFF formalism is effectively parametrized against an extended training set of quantum chemistry data (containing more than 120 different structures) to describe accurately silver- and silver-thiolate systems. The results obtained with this novel representation demonstrate that the novel ReaxFF paradigm is a powerful methodology to reproduce more appropriately average geometric and energetic properties of metal clusters and slabs when compared to the earlier ReaxFF parametrizations dealing with silver and gold. ReaxFF cannot describe adequately specific geometrical features such as the observed shorter distances between the under-coordinated atoms at the cluster edges. Geometric and energetic properties of thiolates adsorbed on a silver Ag20 pyramid are correctly represented by the new ReaxFF and compared with results for gold. The simulation of self-assembled monolayers of thiolates on a silver (111) surface does not indicate the formation of staples in contrast to the results for gold-thiolate systems.</p></div></div></div>

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Driving Torsion Scans with Wavefront Propagation

10.26434/chemrxiv.12044673.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Yudong Qiu ◽

Daniel Smith ◽

Chaya Stern ◽

mudong feng ◽

Lee-Ping Wang

Keyword(s):

Potential Energy ◽

Force Field ◽

Degrees Of Freedom ◽

Computational Cost ◽

Initial Guess ◽

Field Development ◽

Force Field Development ◽

Wavefront Propagation ◽

Open Source Software Package

<div>The parameterization of torsional / dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields.</div><div>Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms.</div><div>To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values.</div><div>However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses.</div><div>In this paper we propose a systematic and versatile workflow called \textit{TorsionDrive} to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development.</div><div>The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described.</div><div>The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.</div>

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Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

10.26434/chemrxiv.6030563 ◽

2018 ◽

Author(s):

Allan J. R. Ferrari ◽

Fabio C. Gozzo ◽

Leandro Martinez

Keyword(s):

Mass Spectrometry ◽

Amino Acid ◽

Force Field ◽

Protein Structures ◽

Protein Structure Determination ◽

Structural Modeling ◽

Cross Linking ◽

Amino Acid Residues ◽

Distance Constraints ◽

Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

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