JOURNAL OF MOLECULAR GRAPHICS & MODELLING

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官方网站：http://www.journals.elsevier.com/journal-of-molecular-graphics-and-modelling/

投稿网址：http://ees.elsevier.com/jmgm/default.asp?acw=c5

PMC链接：http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1093-3263%5BISSN%5D

分子图形和模型杂志致力于发表关于计算机在分子结构、功能、相互作用和设计的理论研究中的应用的论文。该杂志的范围包括分子建模和计算化学的所有方面，包括，例如，分子形状和性质的研究，分子模拟，蛋白质和聚合物工程，药物设计，材料设计，结构-活性和结构-性能关系，数据库挖掘，化合物库设计。作为一份主要的研究期刊，JMGM致力于为我们的读者带来新的知识。因此，提交给该杂志的文件不仅需要报告结果，而且必须得出结论，并探讨提出的工作的含义。我们强烈鼓励作者在编写手稿时牢记这一点。标准模型方法的常规应用，只提供非常有限的新科学见解，将不符合我们的出版标准。报告计算结果的重现性是一个重要问题。在可能的情况下，我们敦促作者使用补充数据来增强他们的论文，例如，在QSAR研究中，机器可读的分子数据集版本，或者在拓扑结构和力场参数文件的新力场参数版本的开发中。现有方法的常规应用不能带来真正的新见解，将不予考虑。

The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.