Biology subjects

Lima, J. P. M. S.

Publications and source records attributed to Lima, J. P. M. S..

6 recordsLinked to original sources

bioRxiv2026

SlytheRINs: using graph parameters and residue interaction networks to analyze protein dynamics and structural ensembles

Establishing the relationship between protein structure and functional behavior remains a significant challenge. The recognition that proteins are inherently dynamic, with functions often dependent on conformational changes, is increasingly accepted. Among computational approaches for elucidating protein properties, Residue Interaction Network (RIN) analysis has emerged as a powerful tool. However, conventional RIN analysis is constrained by its reliance on single, static protein structures, which fail to capture the flexibility inherent in dynamic protein folding transitions. To address these limitations, SlytheRINs is introduced as an interactive tool designed for comparative analysis of protein conformations via RINs. SlytheRINs enables dynamic ensemble analysis by decomposing interaction network data across multiple conformations of a single protein and providing detailed residue-interaction mapping across conformational changes via graph parameters in comparative plots. Applying these principles, the conformational variations of the wild-type and a pathogenic variant (G188R) of the human Glucose-6-Phosphatase (G6PC1) catalytic subunit were compared to identify fluctuations in both chemical interactions and graph features associated with conformational changes induced by the residue modification. The analyses identified key shifts in dynamic residue interactions in the protein variant that compromise substrate binding and the catalytic site, thereby elucidating the impact on G6PC1s dynamic behavior and the resulting activity loss. AvailabilityThe source code for SlytheRINs is available on GitHub (https://github.com/evomol-lab/SlytheRINs), while the web tool and documentation are available at https://slytherins.streamlit.app.

bioinformatics↗

bioRxiv2026

RevelioPlots: An Interactive Web Application for Fast AI-Based Protein Models Quality Assessment

High-accuracy protein structure prediction by deep learning requires rigorous model quality assessment, a process currently hampered by fragmented, non-interactive tools designed for older experimental data formats. We present RevelioPlots, an open-source, interactive web application (Python/Streamlit) that simplifies and streamlines the assessment of AI-predicted protein structure quality. Its key feature is the combination of statistical pLDDT score analysis (mean, median, box plots) with an interactive, confidence-colored Ramachandran plot. This integration establishes a direct visual link between a models predicted local reliability (pLDDT) and its stereochemical feasibility (backbone geometry). RevelioPlots handles both individual and batch-uploaded models, intelligently falling back to B-factors as a proxy for pLDDT values. Using example model proteins, we demonstrated the tools effectiveness, revealing differences in reliability and a clear visual correlation between regions of low pLDDT scores and residues in sterically disallowed regions. By unifying these critical metrics, RevelioPlots empowers non-experienced researchers to quickly and intuitively assess, compare, and interpret structural model quality, enabling a more confident and integrated use of predicted data. AvailabilityRevelioPlots is available at revelioplots.streamlit.app, with the source code publicly accessible on GitHub at https://github.com/evomol-lab/RevelioPlots.

bioinformatics↗

bioRxiv2025

Beyond the Shared Inflammatory Axis: Differentiating Molecular Signatures in Psoriatic Arthritis and Ankylosing Spondylitis through Integrated Omics

Spondyloarthropathies (SpA), which include ankylosing spondylitis (AS) and psoriatic arthritis (PsA), are inflammatory rheumatic diseases with overlapping clinical and immunological characteristics but distinct molecular mechanisms. This study aimed to compare transcriptomic signatures of AS and PsA by investigating differentially expressed genes and associated regulatory pathways. Four public RNA-Seq datasets from GEO (GSE186063, GSE117769, GSE205748, and GSE221786) were used. Using an integrative strategy involving scientific text mining, functional enrichment, and biological curation, 433 genes with potential relevance to both conditions were selected. Based on this set, differential gene expression (DEG) analyses were performed, protein-protein interaction (PPI) networks and gene regulatory networks (GRN) were constructed, and hubs and master regulators (MRs) were identified. The integration of these approaches allowed the identification of shared inflammatory pathways, especially related to the IL-23/IL-17 axis, as well as disease-specific signatures. Functional analysis revealed enrichment in Th17 cell differentiation processes, lipopolysaccharide response, and activation of classical inflammatory pathways. This study provides a comprehensive comparative view of the transcriptomic signatures of PsA and AS that point to potential biomarkers and distinct therapeutic targets.

bioinformatics↗

bioRxiv2023

A novel approach to identify cross-identity peptides between Epstein-Barr virus and central nervous system proteins in Guillain-Barre syndrome and multiple sclerosis

BackgroundGuillain-Barre Syndrome (GBS) and multiple sclerosis are autoimmune diseases associated with an immune system attack response against peripheral and central nervous system autoantigens, respectively. Given the potential of Epstein-Barr virus (EBV) as a risk factor for both multiple sclerosis and GBS, the present study aimed to identify crucial residues among potential EBV CD4+ T lymphocyte epitopes and nervous system proteins. MethodsPublic databases (Allele Frequency Net Database, Immune Epitope Database, Genevestigator and Protein Atlas) were used to select proteins abundant in the nervous system, EBV immunogenic proteins, and HLA haplotypes. Computational tools were employed for predicting HLA-binding peptides and immunogenicity. For this, we developed immuno-cross, a Python tool (https://github.com/evoMOL-Lab/immuno-cross) to compare residue identity among nonamers. ResultsWe found ten proteins from the nervous system and 28 from EBV, which were used for predicting the binding peptides of 21 common HLAs in the world population. A total of 1411 haplotypes were distributed among 51 pairs of HLAs. Simulations were performed to determine whether nonamers from the EBV and nervous system proteins targeted TCR-contact residues. Then, three selection criteria were used, based on the relevance of each contact in the TCR-peptide-MHC interaction. The primary contact has to be located at position P5, and the positions P2, P3, and P8 were weighed as secondary, and P4, P6, and P7 were considered tertiary. Nonamers of EBV proteins and myelin proteins were combined in pairs and compared based on predefined selection criteria. The Periaxin protein had the highest number of nonamers pairs among PNS proteins, with 35 pairs. Four nonamers pairs from APLP1, two from CNP, and two from MBP bind to alleles of the haplotype DR-15. ConclusionsThe new approach proposed herein revealed that peptides derived from nervous system and EBV proteins share identical residues at critical contact points, which supports molecular mimicry. These findings suggest cross-reactivity between them and that the nonamer pairs identified with this approach have the potential to be an autoantigen. Experimental studies are needed to validate these findings.

bioinformatics↗

bioRxiv2020

CoRINs: A tool to compare residue interaction networks from homologous proteins and conformers

MotivationA useful approach to evaluate protein structure and quickly visualize crucial physicochemical interactions related to protein function is to construct Residue Interactions Networks (RINs). By using this application of graphs theory, the amino acid residues constitute the nodes, and the edges represent their interactions with other structural elements. Although several tools that construct RINs are available, many of them do not compare RINs from distinct protein structures. This comparison can give valuable insights into the understanding of conformational changes and the effects of amino acid substitutions in protein structure and function. With that in mind, we present CoRINs (Comparator of Residue Interaction Networks), a software tool that extensively compares RINs. The program has an accessible and user-friendly web interface, which summarizes the differences in several network parameters using interactive plots and tables. As a usage example of CoRINs, we compared RINs from conformers of two cancer-associated proteins. AvailabilityThe program is available at https://github.com/LasisUFRN/CoRINs.

bioinformatics↗

bioRxiv2020

A low-cost smart system for electrophoresis-based nucleic acids detection at the visible spectrum

Nucleic acid detection by electrophoresis is still a quick and accessible technique for many diagnosis methods, primarily at research laboratories or at the point of care units. Standard protocols detect DNA/RNA molecules through specific bound chemical dyes using a UV-transilluminator or UV-photo documentation system. However, the acquisition costs and availability of these devices, mainly the ones with photography and internet connection capabilities, can be prohibitive, especially in developing countries public health units. Also, ultraviolet radiation is a common additional risk factor to professionals that use electrophoresis-based nucleic acid detection. With that in mind, this work describes the development of a low-cost DNA/RNA detection smart system capable of obtaining qualitative and semi-quantitative data from gel analysis. The proposed device explores the visible light absorption range of commonly used DNA/RNA dyes using readily available parts, and simple manufacturing processes, such as light-emitting diodes (LEDs) and 3D impression. By applying IoT techniques, our system covers a wide range of color spectrum in order to detect bands from various commercially used dyes, using Bluetooth communication and a smartphone for hardware control, image capturing, and sharing. The project also enables process scalability and has low manufacturing and maintenance costs. The use of LEDs at the visible spectrum can achieve very reproducible images, providing a high potential for rapid and point-of-care diagnostics as well as applications in several fields such as healthcare, agriculture, and aquaculture.

molecular biology↗