Abstract
BackgroundMore and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules. The rapidly increasing amount of publicly available data in biology and chemistry enables researchers to revisit interaction problems by systematic integration and analysis of heterogeneous data. Currently, some tools have been developed to represent these components. However, they have some limitations and only focus on the analysis of either small molecules or proteins or DNAs/RNAs. To the best of our knowledge, there is still a lack of freely-available, easy-to-use and integrated platforms for generating molecular descriptors of DNAs/RNAs, proteins, small molecules and their interactions.ResultsHerein, we developed a comprehensive molecular representation platform, called BioTriangle, to emphasize the integration of cheminformatics and bioinformatics into a molecular informatics platform for computational biology study. It contains a feature-rich toolkit used for the characterization of various biological molecules and complex interaction samples including chemicals, proteins, DNAs/RNAs and even their interactions. By using BioTriangle, users are able to start a full pipelining from getting molecular data, molecular representation to constructing machine learning models conveniently.ConclusionBioTriangle provides a user-friendly interface to calculate various features of biological molecules and complex interaction samples conveniently. The computing tasks can be submitted and performed simply in a browser without any sophisticated installation and configuration process. BioTriangle is freely available at http://biotriangle.scbdd.com.Graphical abstractAn overview of BioTriangle. A platform for generating various molecular representations for chemicals, proteins, DNAs/RNAs and their interactionsElectronic supplementary materialThe online version of this article (doi:10.1186/s13321-016-0146-2) contains supplementary material, which is available to authorized users.
Highlights
More and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules
Particular attention has been paid to a variety of molecular interaction networks and their potential roles in disease mechanism and drug development [1, 4,5,6,7], including transcriptional and post-transcriptional regulatory networks [8,9,10], functional RNA networks [11,12,13], protein–protein interaction networks [14, 15], and metabolic networks [16, 17]
Public databases for human-specific molecular interaction data have been undergoing a rapid growth within the past decade, such as BIND [18], DIP [19], STITCH [20], HPRD [21], TTD [22], DrugBank [23], ChEMBL [24], KEGG [25], BindingDB [26], SuperTarget and Matador [27], to name a few
Summary
More and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules. Some tools have been developed to represent these components They have some limitations and only focus on the analysis of either small molecules or proteins or DNAs/RNAs. To the best of our knowledge, there is still a lack of freely-available, easy-to-use and integrated platforms for generating molecular descriptors of DNAs/RNAs, proteins, small molecules and their interactions. To investigate complex molecular interactions, both biological and chemical knowledge on structures and functions of all the involved molecules are required, especially in the scenarios of identifying new drug targets and their potential ligands or discovering potential biomarkers for complex diseases [28,29,30]. It is necessary and useful to build informatics platforms for unified data or knowledge representation that can integrate the existing efforts from both communities
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