Biology subjects

Lins, R. D.

Publications and source records attributed to Lins, R. D..

2 recordsLinked to original sources

bioRxiv2025

Ambecovirus, a novel Betacoronavirus subgenus circulating in neotropical bats sheds new light on bat-borne coronaviruses evolution

Understanding the viral diversity harboured by wildlife is essential for effective prediction and prevention of future zoonotic outbreaks. Bats, in particular, are recognized as natural reservoirs for several zoonotic viral pathogens of high impact on public health, including coronaviruses responsible for SARS, the rabies virus, Marburg, Ebola, Nipah and Hendra viruses. However, the large extent of bat viruses remains unexplored, especially in highly biodiverse regions of the Neotropics such as Brazil. We used a meta-transcriptomic to characterize new virus genomes found in blood, oral and anal samples collected from cave- and non-cave bats from Northeast Brazil. From a total of 19 coronavirus-positive bats, we have assembled two complete genomes of a new Betacoronavirus subgenus, named Ambecovirus (American betacoronavirus). The subgenus herein described is phylogenetically placed between the Sarbeco-/Hibeco-/Nebecovirus and the Merbeco-/Embecovirus clades, being basal to the former. While the conserved S2 region of the spike protein retained hallmark domains, including HR1 and HR2, the S1/S2 cleavage site and the furin cleavage site, the S1 region consistently displayed only the N-terminal domain. The receptor-binding domain could not be identified due to high dissimilarity relative to known congeneres. The detection of Ambercovirus in sympatric Pteronotus gymnonotus and Carollia perspicillata bats suggests interspecies transmission. Longitudinal sampling confirmed persistent Ambecovirus infection in P. gymnonotus over multiple years and virus dispersion at a minimum distance of 270 km between caves. The present study confirms that viral diversity in neotropical hosts remains largely unknown not just in Brazil but, likely, in the other countries of the region, supporting the need for a systematic approach to virome exploration and analysis followed by in vitro experimentation to assess zoonotic potential.

evolutionary biology↗

bioRxiv2024

Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning

The design of proteins capable to effectively bind to specific protein targets is crucial for developing therapies, diagnostics, and vaccine candidates for viral infections. Here, we introduce a complementarity-determining regions (CDRs)-grafting approach for designing nanobodies (Nbs) that target specific epitopes, with the aid of computer simulation and machine learning. As a proof-of-concept, we designed, evaluated, and characterized a high-affinity Nb against the spike protein of SARS-CoV-2, the causative agent of the COVID-19 pandemic. The designed Nb, referred to as Nb Ab.2, was synthesized and displayed high-affinity for both the purified receptor-binding domain protein and to the virus-like particle, demonstrating affinities of 9 nM and 60 nM, respectively, as measured with microscale thermophoresis. Circular dichroism showed the designed proteins structural integrity and its proper folding, whereas molecular dynamics simulations provided insights into the internal dynamics of Nb Ab.2. This study shows that our computational pipeline can be used to efficiently design high affinity Nbs with diagnostic and prophylactic potential, which can be tailored to tackle different viral targets. Author summaryIn this study, we present a pipeline for designing a high-affinity nanobody (Nb) targeting the SARS-CoV-2 spike protein using enhanced sampling molecular dynamics simulations and CDR-grafting. To address the challenges of CDR grafting in Nbs, including the need for structural similarity between the CDR motif of interest and the scaffold region, we utilized the Nb scaffold cAbBCII10, known for its versatility in accommodating various CDRs. We generated a library based on the cAbBCII10 framework with diverse, unrelated CDRs and applied machine learning to identify the most promising candidates. Our approach enabled successful engineering of a Nb that binds to the SARS-CoV-2 spike protein with high affinity, demonstrating the effectiveness of our design pipeline for potential therapeutic applications.

biophysics↗