The ForceFit program package has been developed for fitting classical force field parameters based upon a force matching algorithm to quantum mechanical gradients of configurations that span the potential energy surface of the system. The program, which runs under UNIX and is written in C++, is an easy-to-use, nonproprietary platform that enables gradient fitting of a wide variety of functional force field forms to quantum mechanical information obtained from Gaussian and NWChem. All aspects of the fitting process are run from a graphical user interface, from the parsing of quantum mechanical data, assembling of a potential energy surface database, setting the force field, and variables to be optimized, choosing a molecular mechanics code for comparison to the reference data, and finally, the initiation of a least squares minimization algorithm. Furthermore, the code is based on a modular templated code design that enables the facile addition of new functionality to the program.
ForceFit is offered under a LGPL license, wherein the user may not redistribute the code, but modifications may be made and if sent back to Prof. Clark, will be incorporated into the next version of the code.
Any results obtained with ForceFit should refer to the following publication:
Waldher, B.; Kuta, J.; Chen, S.; Henson, N.; Clark, A. E. ForceFit: A Code to Fit Classical Force Fields to Quantum Mechanical Potential Energy Surfaces, J. Comp. Chem. 2010, 31, 2307-2316.
moleculaRnetworks is a bundled series of scripts, written in the software package R, for processing molecular simulations data. These scripts are intended for the frame-by-frame geometric and solvent network analysis of aqueous solutes only. The algorithms contained therein are based on graph theory and contain a novel method for identifying the geometric shape adopted by the solvent in the immediate vicinity of the solute, as well as an exploratory approach for describing H-bonding, based on the PageRank algorithm implemented by the Google search engine. The moleculaRnetworks codes include a preprocessor which distills simulation trajectories into physicochemical data arrays, and an interactive analysis script that enables statistical, trend, correlation analyses and other data mining.
Any results obtained with moleculaRnetworks should refer to the following publication:
Mooney, B. L.; Corrales, L. R.; Clark, A. E. “moleculaRnetworks: an Integrated Graph Theoretic and Data Mining Tool to Explore Solvent Organization in Molecular Simulation,” J. Comp. Chem., 2012, DOI: 10.1002/jcc.22917, early view.
This paper also has a detailed description of a typical user session and can act as a user manual.
ChemNetworks is a completely generalized code that complements and dramatically expands upon our previously reported moleculaRnetworks series of R-scripts. As such, it can be used to understand a very large range of chemical systems that include complex solutions, liquid interfaces, self-assemblies, or pure liquids undergoing phase changes. This software converts .xyz coordinates to a graph/network based upon user-defined rules for intermolecular interactions “edges” between molecular “vertices”. Subsequent analyses include degree census, network neighborhood, geodesics, lifetimes of geodesics of each length, and direct structural searches of specific network patterns. These properties can help to understand the network patterns and organization that may influence physical properties and chemical reactivity
Any results obtained with ChemNetworks should refer to the following publication:
Ozkanlar, A.; Clark, A. E. “ChemNetworks: A Complex Network Analysis Tool for Chemical Systems” J. Comp. Chem. 2014, 35, 495-505.