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\subsection*{Advantages and Disadvantages of Open Source}  The value of open source software in cheminformatics and molecular modelling is somewhat controversial. Unsurprisingly, those affiliated with commercial scientific software argue that traditional commercial development, with its associated support and development, provides a superior value \cite{Krylov_2015}, while open source advocates feel the benefits outweigh the burdens \cite{Gezelter_2015,Jacob_2016}. Opponents Our goal is not revisit these arguments. Instead, we assert that open source scientific software is a \textit{de facto} part of the scientific community and so in this review we enumerate those open source packages that fall within the domain of cheminformatics and molecular modelling.  There are a few aspects of the open source software debate that we find particularly relevant. First, opponents  are right to point out that free software is not free - users of open source software generally take on a much greater burden in supporting the software than with commercial software. This is one reason why it is important, when possible, to seek open source software that is under active development and supported by a broad community. In Therefore, in  this review we attempt to quantify the current level of development and support of each package as an indirect measure of quality and usability. Reference recent commentary   Advantages   Free  Not a black box   Can improve, extend, Second, the primary advantage of open source software is the ability to redistribute code without restriction. This inherently enables reproducibility  and incorporate  Reproducibility (reference royal society report)  Easy distribution (sourceforge, github)  Did lets scientists ``on the shoulders of giants'' instead of reinventing the wheel. Consequently, in this review  we mention free?  Disadvantages  Difficult limit ourselves  tocommercialize (not  a disadvantage from scientific standpoint, but has implications for users)  Support is often limited or nonexistent   Development depends survey of true open source software and exclude source-available software that may place restrictions  on active communities the publication  of user-developers   Many packages are primarily developed/supported by a single person (concern about sustainability)  Modeling is a niche area not highly populated by programmers  Methodology for identifying software: click2drug.org, sourceforge, ?? reproducible research results.  \section{Methods}  Shoudl also investigate http://cheminformatics.org/  Evaluation criteria: license, development activity rating, usage, number of developers (active)  Categories:  cheminformatics (putting toolkits in here), QSAR, visualization, docking, protein structure, protein dynamics, virtual screening, ??/      How much evaluation are we going to do? First look for existing articles. 
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docking - vina compared itself to autodock..      \cite{Koes_2011}