Network Topological Indices from Chem-Bioinformatics to Legal Sciences and back

Aliuska      Duardo-Sanchez; Grace      Patlewicz; Humberto      Gonzalez-Diaz

Abstract

Bionformatics models describe that structure-property relationships of systems may play an important role to reduce costs in terms of time, human resources, material resources, as well as allow certain laboratory animals replacement in biomedical sciences. Many of these models are in essence Quantitative Structure-Activity or Property Relationships (QSARs/QSPRs). In other words, QSPRs are models that connect the structure of a system with external properties of these systems that are not self-evident after direct inspection of the structure. In particular, QSARs are models that connect the chemical structure of drugs, target (protein, gen, RNA, microorganism, tissue, disease … ), or both (drug and target at the same time) with drug biological activity over this target. Many of these QSAR techniques are based on the use of structural parameters, which are numerical series that codify useful structural information and enable correlations between strcture and biological properties. In parallel, graph theory and Complex Network analysis tools are expanding to new potential fields of application of Information Sciences at different levels from molecules to populations, social or technological networks such as genome, protein-protein networks, sexual disease transmission networks, power electric power network or internet. In all these cases, we can calculate parameters called Topological Indices (TIs) that numerically described the connectedness patterns (structure) between the nodes or actors in a network. Consequently, TIs are very useful as inputs for QSPR models at all structural levels. In fact, even legal systems may be approached using computing and information techniques like networks. So we can construct a complex network of legal systems connecting laws (nodes) that regulate common biological topics for instance. On the other hand, a systematic judicial framework is needed to provide appropriate and relevant guidance for addressing various computing techniques as applied to scientific research. Bioinformatics and computational biology are two areas within the field of biosciences that require more attention from the legal operators. Taking all the previous aspects into consideration, this article reviews both: the use of legal sciences to regulate and protect QSAR models of molecular sytems and the application of QSPR-like models to study legal systems per se. Consequently, as stated in a title, in this review we are going to travel from Cheminformatics, Bioinformatics, and Networks to Legal Sciences and later go back. In the first direction, we review the various legal procedures that are available to protect QSAR software, the acceptance and legal treatment of scientific results and techniques derived from such software, as well as some of the specific tax issues from the computer programs field. In the second direction, we review the representation of legal systems using complex networks, the description of legal social networks with TIs, the development of QSPR models to predict legal and social phenomena. In this sense, the issues reviewed here are: 1- Networks, Topological Indices and QSPR models: Theoretical Background. 2- Notes on reviews of legal issues related to QSAR models. 3- Complex Network Representations in Legal Sciences. 4- Topological Indices of Legal networks. 5. QSPR models to predict causality in crime law networks.

Keywords: Bioinformatics legal issues, social networks, spain financial law network, crime causality network, graph theory, complex networks, QSPR models, topological Indices, QSAR software copyright, OECD, REACH new laws of registration, evaluation, authorization of chemicals