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BioProtIS: Streamlining protein-ligand interaction pipeline for analysis in genomic and transcriptomic exploration

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Author(s):
Virgens, Graziela Soria ; Oliveira, Julia ; Cardoso, Maria Izadora Oliveira ; Teodoro, Joao Alfredo ; Amaral, Danilo T.
Total Authors: 5
Document type: Journal article
Source: JOURNAL OF MOLECULAR GRAPHICS & MODELLING; v. 128, p. 8-pg., 2024-02-02.
Abstract

The identification of protein-ligand interactions plays a pivotal role in elucidating biological processes and discovering potential bioproducts. Harnessing the capabilities of computational methods in drug discovery, we introduce an innovative Inverted Virtual Screening (IVS) pipeline. This pipeline Integrated molecular dynamics and docking analyses to ensure that protein structures are not only energetically favorable but also representative of stable conformations. The primary objective of this pipeline is to automate and streamline the analysis of protein-ligand interactions at both genomic and transcriptomic scales. In the contemporary post-genomic era, high-throughput computational screening for bioproducts, biological systems, and therapeutic drugs has become a cornerstone practice. This approach offers the promise of cost-effectiveness, time efficiency, and optimization of laboratory work. Nevertheless, a notable deficiency persists in the availability of efficient pipelines capable of automating the virtual screening process, seamlessly integrating input and output, and leveraging the full potential of open-source tools. To bridge this critical gap, we have developed a versatile pipeline known as BioProtIS. This tool seamlessly integrates a suite of state-of-the-art tools, including Modeller, AlphaFold, Gromacs, FPOCKET, and AutoDock Vina, thus facilitating the streamlined docking of ligands with an expansive repertoire of proteins sourced from genomes and transcriptomes, and substrates. To assess the pipeline's performance, we employed the transcriptomes of Cereus jamacaru (a cactus species) and Aspisoma lineatum (firefly), along with the genome of Homo sapiens. This integration not only improves the accuracy of ligand-protein interactions by minimizing replicability deviations but also optimizes the discovery process by enabling the simultaneous evaluation of multiple substrates. Furthermore, our pipeline accommodates distinct testing scenarios, such as blind docking or site-specific targeting, which are invaluable in applications ranging from drug repositioning to the exploration of new allosteric binding sites and toxicity assessments. BioProtIS has been designed with modularity at its core. This inherent flexibility empowers users to make custom modifications directly within the source code, tailoring the pipeline to their specific research needs. Moreover, it lays the foundation for seamless integration of diverse docking algorithms in future iterations, promising ongoing advancements in the field of computational biology. This pipeline is available for free distribution and can be download at: https://github. com/BBMDO/BioProtIS. (AU)

FAPESP's process: 20/16162-3 - Automated and predictive comparative phylogeography of neotropical species
Grantee:Isabel Aparecida da Silva Bonatelli
Support Opportunities: Regular Research Grants
FAPESP's process: 23/06458-0 - In silico bioprospecting of mandacaru (Cactaceae): discovery of potential genetic products for controlling skin blemishes and oiliness.
Grantee:Júlia de Oliveira
Support Opportunities: Scholarships in Brazil - Scientific Initiation
FAPESP's process: 20/15161-3 - Adaptation during biogeographic transitions from the Cerrado to the Caatinga: evolutionary parallelism and idiosyncrasies in independent clades of genus Cereus (Cactaceae)
Grantee:Fernando de Faria Franco
Support Opportunities: BIOTA-FAPESP Program - Regular Research Grants
FAPESP's process: 22/09910-9 - Survey of bioluminescent organisms from the Ecological Station of Juréia-Itatins: biodiversity, molecular evolution, and environmental bioindicator
Grantee:Danilo Trabuco do Amaral
Support Opportunities: BIOTA-FAPESP Program - Regular Research Grants