Biology subjects

Moreira, R. A.

Publications and source records attributed to Moreira, R. A..

7 recordsLinked to original sources

bioRxiv2025

JAGUAR CONSERVATION UNITS AS EFFECTIVE TOOL IN A PAYMENT FOR ECOSYSTEM SERVICES SCHEME FOR APEX PREDATOR

This paper proposes a redefinition of Jaguar Conservation Units, emphasizing the role of private rural properties in jaguar populations in Brazil while mitigating conflicts with the species and allowing a more effective implementation of payment for the species environmental services. Jaguars prey domestic livestock, leading to retaliatory killings by ranchers. In this context, the study aims to analyze the environmental and economic parameters associated with the ecosystem services provided by jaguars. The ultimate goal is to develop a regional Payment for Environmental Services (PES) scheme to support jaguar conservation by promoting forest code compliance, maintaining habitat connectivity, and compensating cattle predation, using data from Mato Grosso do Sul (MS), Brazil. Our findings demonstrate the advantages of implementing such program and reveal that the cost of maintaining jaguar populations through a PES, with funds from several independent sources, would be feasible and important for one of the largest jaguar populations in Brazil. HIGHLIGHTSO_LIAnalysis of environmental and economic parameters linked to jaguar ecosystem services. C_LIO_LIDevelopment of a regional Payment for Environmental Services (PES) scheme in Mato Grosso do Sul. C_LIO_LIEvidence of the feasibility and importance of PES to maintain one of the largest jaguar populations in Brazil. C_LI

ecology↗

bioRxiv2025

Spatial Ecology of Jaguars in a Coastal Amazon Island Ecosystem

Understanding the spatial ecology of large carnivores is essential for effective conservation, particularly in insular or fragmented systems where movement is constrained. Jaguars are particularly important to study, as they are opportunistic predators whose diet and behaviour shifts flexibly with local prey availability. We investigated the movement patterns, home range dynamics, and social interactions of jaguars (Panthera onca) on Maraca-Jipioca Island, a pair of small, seasonally flooded islands, in a low-disturbance reserve in the Brazilian Amazon. Using GPS collars, we tracked seven individuals and found that males had significantly larger home ranges (mean: 77.8 km{superscript 2}) than females (mean: 19.5 km{superscript 2}). Despite the islands limited area, home-range overlap was low, and direct encounters were rare. This mirrored the territorial behaviour seen in more expansive mainland populations, but contradicted patterns seen in other populations that specialised on aquatic prey. Jaguars on Maraca-Jipioca moved an average of 7.3 km/day, with no significant differences across sex, age, nor body size. However, movement speed and probability of activity varied significantly across habitats: individuals moved faster in grasslands, wetlands, and water, and more slowly in forests and mangroves. Animals also spent more time resting while in forests and mangroves as compared to grasslands, water, and wetlands. In contrast to the predominantly nocturnal habits reported in continental populations, jaguar activity on Maraca-Jipioca peaked during daylight hours, especially among females. Jaguars showed a marked preference for coastal areas but did not appear to adjust habitat use in response to tidal variation in sea level. Collectively, these findings suggest that the spatial ecology of Maraca-Jipioca jaguars is comprised of typical and novel behaviours, shaped by both the species evolutionary history, and the islands unique ecological context. These findings highlight the species behavioural flexibility and offer rare insights into how a large carnivore persists in an insular Amazonian landscape.

ecology↗

bioRxiv2024

GoMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The G[o]Martini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced G[o]Martini model, which combines a virtual-site implementation of G[o] models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with G[o] models.

biophysics↗

bioRxiv2023

Discovering Secondary Protein Structures via Local Euler Curvature

Protein structure analysis and classification, which is fundamental for predicting protein function, still poses formidable challenges in the fields of molecular biology, mathematics, physics and computer science. In the present work we exploit recent advances in computational topology to define a new intrinsic unsupervised topological fingerprint for proteins. These fingerprints, computed via Local Euler Curvature (LECs), identify secondary protein structures, such as Helices and Sheets, by capturing their distinctive topological signatures. Using an extensive protein residue database, the proposed computational framework not only distinguishes between structural classes via unsupervised clustering but also achieves remarkable accuracy in classifying proteins structures through supervised machine learning classifier. We also show that the internal structure of LEC space embeds the information about the secondary structure of proteins. Beyond its immediate implications for the advancement of critical application areas such as drug design and biotechnology, our approach opens a fascinating avenue towards characterizing the multiscale structures of diverse biopolymers based solely on their geometric and topological attributes.

biochemistry↗

bioRxiv2021

Optimizing mechanostable anchor points of engineered lipocalin in complex with CTLA-4

We used single-molecule AFM force spectroscopy (AFM-SMFS) to screen residues along the backbone of a non-antibody protein binding scaffold (lipocalin/anticalin), and determine the optimal anchor point that maximizes binding strength of the interaction with its target (CTLA-4). By incorporating non-canonical amino acids into anticalin, and using click chemistry to attach an Fg{beta} peptide at internal sequence positions, we were able to mechanically dissociate anticalin from CTLA-4 by pulling from eight different anchoring residues using an AFM cantilever tip. We found that pulling on the anticalin from residue 60 or 87 resulted in significantly higher rupture forces and a decrease in koff by 2-3 orders of magnitude over a force range of 50-200 pN. Five of the six internal pulling points tested were significantly more stable than N- or C-terminal anchor points, rupturing at up to 250 pN at loading rates of 0.1-10 nN sec-1. Anisotropic network modelling and molecular dynamics simulations using the G[o]-MARTINI approach explained the mechanism underlying the geometric dependency of mechanostability. These results suggest that optimization of attachment residue position for therapeutic and diagnostic cargo can provide large improvements in binding strength, allowing affinity maturation without requiring genetic mutation of binding interface residues.

biophysics↗

bioRxiv2020

Characterization of structural and energetic differences between conformations of the SARS-CoV-2 spike protein

The novel coronavirus disease 2019 (COVID-19) pandemic has disrupted modern societies and their economies. The resurgence in COVID-19 cases as part of the second wave is observed across Europe and the Americas. The scientific response has enabled a complete structural characterization of the Severe Acute Respiratory Syndrome - novel Coronavirus 2 (SARS-CoV-2). Among the most relevant proteins required by the novel coronavirus to facilitate the cell entry mechanism is the spike protein trimer. This protein possesses a receptor-binding domain (RBD) that binds the cellular angiotensin-converting enzyme 2 (ACE2) and then triggers the fusion of viral and host cell membranes. In this regard, a comprehensive characterization of the structural stability of the spike protein is a crucial step to find new therapeutics to interrupt the process of recognition. On the other hand, it has been suggested the participation of more than one RBD as a possible mechanism to enhance cell entry. Here we discuss the protein structural stability based on the computational determination of the dynamic contact map and the energetic difference of the spike protein conformations via the mapping of the hydration free energy by the Poisson-Boltzmann method. We expect our result to foster the discussion of the number of RBD involved during recognition and the repurposing of new drugs to disable the recognition by discovering new hotspots for drug targets apart from the flexible loop in the RBD that binds the ACE2.

biophysics↗

bioRxiv2019

The Euler Characteristic and Topological Phase Transitions in Complex Systems

In this work, we use methods and concepts of applied algebraic topology to comprehensively explore the recent idea of topological phase transitions (TPT) in complex systems. TPTs are characterized by the emergence of nontrivial homology groups as a function of a threshold parameter. Under certain conditions, one can identify TPTs via the zeros of the Euler characteristic or by singularities of the Euler entropy. Recent works provide strong evidence that TPTs can be interpreted as a complex networks intrinsic fingerprint. This work illustrates this possibility by investigating some classic network and empirical protein interaction networks under a topological perspective. We first investigate TPT in protein-protein interaction networks (PPIN) using methods of topological data analysis for two variants of the Duplication-Divergence model, namely, the totally asymmetric model and the heterodimerization model. We compare our theoretical and computational results to experimental data freely available for gene co-expression networks (GCN) of Saccharomyces cerevisiae, also known as bakers yeast, as well as of the nematode Caenorhabditis elegans. Supporting our theoretical expectations, we can detect topological phase transitions in both networks obtained according to different similarity measures. Later, we perform numerical simulations of TPTs in four classical network models: the Erd[o]s-Renyi model, the Watts-Strogatz model, the Random Geometric model, and the Barabasi-Albert. Finally, we discuss some perspectives and insights on the topic. Given the universality and wide use of those models across disciplines, our work indicates that TPT permeates a wide range of theoretical and empirical networks.

biophysics↗