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Updating sting platform and its relational database for complementing of a dictionary containing principal descriptors that characterize the ten most studied internal protein nano environments

Grant number: 18/25327-6
Support type:Regular Research Grants
Duration: December 01, 2019 - November 30, 2021
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Goran Nesic
Grantee:Goran Nesic
Home Institution: Embrapa Informática Agropecuária. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA). Ministério da Agricultura, Pecuária e Abastecimento (Brasil). Campinas , SP, Brazil
Assoc. researchers:Fábio Rogério de Moraes ; Ivan Mazoni ; Luiz César Borro

Abstract

We suggest the modernization of the STING platform with the update of the current source code in order to support new technologies and software platforms, as well as the reconstruction of the world's largest relational database of physical-chemical and structural descriptors of proteins - the STING_RDB. The elaboration and incorporation to the STING platform of new analysis and visualization tools with support to large volumes of data and high processing will contribute to the expansion of the scope of study in Computational Biology and will provide subsidy for scientific research in several domains such as Agriculture, Biology, Pharmacy and Medicine, and even the development of a scalable solution for high-performance calculations and problems related to graphical presentation of data in Structural Computational Biology. Embrapa's GPBC is responsible for the platform and the corresponding STING database, which is one of the oldest examples of Big Data (existing in its primary form since 1998). The modernization of the STING platform is presented here as an activity that will be done in successive stages, progressively reducing the legacy code in favor of the new platform. In the end, the system will be fully converted to use current technologies. The emphasis of this proposal also focuses on future horizons and foresees the applications of the new platform and STING_RDB. The numerous agreements established, especially with the universities of the State of São Paulo (USP, Unicamp, UNESP, Unifesp), would benefit from using the new STING platform and its database. Likewise, the entire line of research adopted at the Embrapa's GPBC would contribute to these collaborations: the study of the nano environments of protein structures would offer a better understanding of the interactions between proteins, proteins and ligands and proteins with DNA. The BlueStar STING platform can already be considered as a scientific legacy not only of the Embrapa system but also, and more broadly, of Brazilian science since it has been providing services to users around the world for two decades. STING was part of educational programs in Universities in England and the USA. In Brazil, we have been able to organize several schools (such as ESPCA) and events (such as X-meeting and ISMB 2006), often with participation of the highest level of academic authorities (bringing Nobel prizes to meet our target audience here in the Brazilian territory) and we also have signed dozens of agreements that connected Embrapa's researchers with laboratories of the main Universities and Scientific Institutions of the State of São Paulo, Brazil, Latin America and the world in general. During these two decades, a range of biological problems was addressed with the use of the platform and the knowledge generated from the STING platform spawning even patent applications. At this moment, it becomes essential to update the STING platform to guarantee the continuation of services to the scientific community. This project is definitely the most appropriate way to do this. Blue Star STING follows the data recovery trend. Processing capacity (servers, CPU cores, memory, etc.) already have a stabilized or even declining value, but the bit value has considerably increased. Consequently, the need for increased storage and processing capacity generates a growth cycle and broadening database of raw and processed data spawns outbursts of aggregated values. The dictionary of descriptors of the most studied nano environments and their complementation with the inclusion of nano environments not yet addressed, but biologically extremely relevant represents a more relevant example that illustrates the fundamental connection between biological data and applications aimed at innovation. This project definitely does not sin in the particular area that establishes the straight line between basic and applied science, and between general knowledge and innovation. (AU)