Evaluación de las propiedades tribológicas y mecánicas de recubrimientos de CrC depositados por pulverización catódica magnetrón R.F.

Este artículo presenta los resultados obtenidos con el depósito de una serie de recubrimientos de CrC mediante pulverización catódica por magnetrón r.f., la cual presentó contenidos de carbono en el rango de 2558 % acorde a los análisis EDS. Los valores de dureza de estos recubrimientos estuvieron entre 15 y 24 GPa, hallándose los valores de mayor dureza en las muestras con contenido de carbono en el rango de 3953 %. Se encontró una correlación entre el contenido de carbono y los valores de los coeficientes de fricción, los cuales están en el rango de 0,70 a 0,15, obteniendo estos últimos valores para recubrimientos con exceso de carbono. El comportamiento al desgaste bajo pruebas de deslizamiento en seco mostró también una marcada dependencia con el contenido de carbono. Los mejores resultados de desgaste fueron obtenidos para los recubrimientos con el más alto contenido de carbono

Studying O2 pathways in [NiFe]- and [NiFeSe]-hydrogenases

Hydrogenases are efficient biocatalysts for H2 production and oxidation with various potential biotechnological applications.[NiFe]-class hydrogenases are highly active in both production and oxidation processes—albeit primarily biased to the latter—but suffer from being sensitive to O2.[NiFeSe] hydrogenases are a subclass of [NiFe] hydrogenases with, usually, an increased insensitivity to aerobic environments. In this study we aim to understand the structural causes of the low sensitivity of a [NiFeSe]-hydrogenase, when compared with a [NiFe] class enzyme, by studying the diffusion of O2. To unravel the differences between the two enzymes, we used computational methods comprising Molecular Dynamics simulations with explicit O2 and Implicit Ligand Sampling methodologies. With the latter, we were able to map the free energy landscapes for O2 permeation in both enzymes. We derived pathways from these energy landscapes and selected the kinetically more relevant ones with reactive flux analysis using transition path theory. These studies evidence the existence of quite different pathways in both enzymes and predict a lower permeation efficiency for O2 in the case of the [NiFeSe]-hydrogenase when compared with the [NiFe] enzyme. These differences can explain the experimentally observed lower inhibition by O2 on [NiFeSe]-hydrogenases, when compared with [NiFe]-hydrogenases. A comprehensive map of the residues lining the most important O2 pathways in both enzymes is also presented.publishersversionpublishe

Characterization of the multiheme cytochromes involved in the extracellular electron transfer pathway of Thermincola ferriacetica

Bioelectrochemical systems (BES) are emerging as a suite of versatile sustainable technologies to produce electricity and added‐value compounds from renewable and carbon‐neutral sources using electroactive organisms. The incomplete knowledge on the molecular processes that allow electroactive organisms to exchange electrons with electrodes has prevented their real‐world implementation. In this manuscript we investigate the extracellular electron transfer processes performed by the thermophilic Gram‐positive bacteria belonging to the Thermincola genus, which were found to produce higher levels of current and tolerate higher temperatures in BES than mesophilic Gram‐negative bacteria. In our study, three multiheme c‐type cytochromes, Tfer_0070, Tfer_0075, and Tfer_1887, proposed to be involved in the extracellular electron transfer pathway of T. ferri-acetica, were cloned and over‐expressed in E. coli. Tfer_0070 (ImdcA) and Tfer_1887 (PdcA) were purified and biochemically characterized. The electrochemical characterization of these proteins supports a pathway of extracellular electron transfer via these two proteins. By contrast, Tfer_0075 (CwcA) could not be stabilized in solution, in agreement with its proposed insertion in the pepti-doglycan wall. However, based on the homology with the outer‐membrane cytochrome OmcS, a structural model for CwcA was developed, providing a molecular perspective into the mechanisms of electron transfer across the peptidoglycan layer in Thermincola.publishersversionpublishe

Artificial intelligence-based design of antibody-like engineered protein scaffolds

Throughout humanity history, viral outbreaks caused devastating epidemics, like the recent COVID-19, caused by the SARS-CoV-2 virus originating in China. As of December 13, 2023, over 772 million confirmed COVID-19 cases, with more than 6.9 million deaths, have been reported globally to the World Health Organization. Over time, SARS-CoV-2 has evolved into different strains with varied characteristics, including immune system evasion and increased infectivity. This highlights the unpredictable nature of future pandemics, needing the development of new methodologies to combat a wide range of viruses. Therapeutic monoclonal antibodies, with their adaptability, show potential in targeting a broad range of viruses. However, their intricate and costly development processes hinder widespread use. Engineered protein scaffolds, such as monobodies13, which are smaller and simpler than monoclonal antibodies, offer a promising alternative. Their expression in bacteria makes their production and development processes simple and cost-effective, presenting exciting prospects for innovative treatments in cancer, infectious diseases, and autoimmune disorders. Although these engineered protein scaffolds have the potential to revolutionize medicine, we need efficient strategies to enable the design of molecules with tailor-made properties. The combination of machine learning methods like ProtGPT24, RFdiffusion5 and MSA Transformer6 and molecular dynamics (MD) simulations can be a powerful strategy to address this problem. This work aims to create a computational framework integrating machine learning techniques and MD simulations to streamline the development of engineered protein scaffolds that combine a high affinity for the target with optimal developability properties (including efficient production in bacteria and high physical and chemical stability). As proof of concept, we are focusing on designing protein scaffolds, including monobodies and helical miniproteins, to neutralize SARS-CoV-2. This approach holds promise for the development of biopharmaceuticals that can be adapted to a broad range of pathogenic agents, contributing to the ongoing battle against infectious diseases.info:eu-repo/semantics/publishedVersio

The importance of lipid conjugation on anti-fusion peptides against Nipah virus

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Nipah virus (NiV) is a recently emerging zoonotic virus that belongs to the Paramyxoviridae family and the Henipavirus genus. It causes a range of conditions, from asymptomatic infection to acute respiratory illness and fatal encephalitis. The high mortality rate of 40 to 90% ranks these viruses among the deadliest viruses known to infect humans. Currently, there is no antiviral drug available for Nipah virus disease and treatment is only supportive. Thus, there is an urgent demand for efficient antiviral therapies. NiV F protein, which catalyzes fusion between the viral and host membranes, is a potential target for antiviral drugs, as it is a key protein in the initial stages of infection. Fusion inhibitor peptides derived from the HRC-domain of the F protein are known to bind to their complementary domain in the protein's transient intermediate state, preventing the formation of a six-helix bundle (6HB) thought to be responsible for driving the fusion of the viral and cell membranes. Here, we evaluated the biophysical and structural properties of four different C-terminal lipid-tagged peptides. Different compositions of the lipid tags were tested to search for properties that might promote efficacy and broad-spectrum activity. Fluorescence spectroscopy was used to study the interaction of the peptides with biomembrane model systems and human blood cells. In order to understand the structural properties of the peptides, circular dichroism measurements and molecular dynamics simulations were performed. Our results indicate a peptide preference for cholesterol-enriched membranes and a lipid conjugation-driven stabilization of the peptide α-helical secondary structure. This work may contribute for the development of highly effective viral fusion against NiV inhibitors.This work was financially supported by Fundação para a Ciência e a Tecnologia—Ministério da Ciência, Tecnologia e Ensino Superior (FCT-MCTES, Portugal), through projects PTDC/BBB-BQB/3494/2014, PTDC/QUI-BIQ/114774/2009, PTDC/CCI-BIO/28200/2017 and Pest-OE/EQB/LA0004/2011, and by National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), project R01AI114736, lead by Anne Moscona (Columbia University Medical Center, NY, USA). This work was also financially supported by Project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER funds through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through FCT-MCTES. MCM, PMS and DL were supported by FCT-MCTES fellowships SFRH/BPD/118731/2016, SFRH/BD/118413/2016 and SFRH/BPD/92537/2013, respectively.info:eu-repo/semantics/publishedVersio

Computational design of antiviral biologics targeting Zika virus envelope protein

In the past two decades, the world has struggled with recurrent viral outbreaks, with viruses from diverse families demonstrating pandemic and epidemic potential. One of those viruses is the Zika virus. Despite disease cases having declined globally after 2017, Zika virus transmission persists at low levels in regions like the Americas and a total of 89 countries and territories have reported evidence of Zika virus infection. Despite active research, treatments for Zika virus infection are lacking, and vaccine development remains ongoing. The field of protein design has arisen as a transformative discipline in molecular engineering, allowing precise tailoring of protein properties such as their stability and ability to bind to specific partners. Antiviral biologics, such as small proteins that can bind to and inhibit viral targets, appear as a promising therapeutic option. In the Zika virus, the envelope protein (E) has a pivotal role in viral entry, making it an ideal target for antivirals. The E protein comprises three structural ectodomains (DI, DII, DIII) and a transmembrane region. DIII is an immunoglobulin-like domain that contains receptorbinding sites. In this work we are developing tailor-made antiviral biologics that specifically target and bind to the E protein DIII, preventing viral entry into host cells. The methodology involves identifying epitope regions on the target surface regions, selecting binding motifs from a large Atlas containing a description of a large pool of protein binding motifs, and docking the binding motifs to the epitope. Binding affinity will be optimized using proteinMPNN, a deep learning-based protein sequence design method. Protein structure prediction tools, like AlphaFold2, will be used to filter the most promising designs. Additionally, molecular dynamics simulations will be employed for stability evaluation as an in silico control. Our collaborators will then experimentally evaluate the selected candidates for their binding affinity. This comprehensive approach seeks to redefine strategies in combating the Zika virus, holding the potential to enhance preparedness against emerging viral threats with pandemic potential.info:eu-repo/semantics/publishedVersio

The NBDs that wouldn't die: A cautionary tale of the use of isolated nucleotide binding domains of ABC transporters

COMATOSE (CTS), the plant homologue of Adrenoleukodystrophy protein, is a full length ABC transporter localised in peroxisomes. In a recent article, we reported that the two nucleotide binding domains of CTS are not functionally equivalent in vivo. Mutations in conserved residues in the Walker A (K487A) and B (D606N) motifs of NBD1 resulted in a null phenotype, whereas identical mutations in the equivalent residues in NBD2 (K1136A and D1276N) had no detectable effect.1 In order to study the effect of these mutations on the ATPase activity of the nucleotide binding domains, we cloned and expressed the isolated NBDs as maltose binding protein (MBP) fusion proteins. We show that ATPase activity is associated with the isolated MBP-NBDs. However, mutations of amino acids located in conserved motifs did not result in striking reduction in activity despite well characterized roles in ATP binding and hydrolysis. We urge caution in the interpretation of results obtained from the study of isolated NBD fusions and their extrapolation to the mechanism of ATP hydrolysis in ABC transporter proteins

Addressing the challenge of oligomerization in computational protein design

Computational protein design is a field of research with potential to greatly impact areas such as drug development or enzyme technology, by combining knowledge-based and physics-based methods to design tailor-made proteins. This concept was introduced by David Baker with the development of Rosetta Commons. This is an extensive framework containing tools that enable protein design using physics-based scoring functions. Recently, the field of computational protein design has had major breakthroughs with the introduction of artificial intelligence (AI)-driven tools, namely RFDiffusion1 and ProteinMPNN2, which, when combined with AI-based 3D structure prediction tools (AlphaFold23), provide more efficient protein design pipelines. This project aims to combine AI-driven methods with physics-based methods to re-design a protein binder and increase its affinity for a given target, considering potential oligomeric states of the design candidates. For this purpose, the receptor binding domain (RBD) of the Sars-CoV-2 spike protein was utilized as proof of concept, by starting with a known binder, that was predicted to dimerize, and improving its binding affinity to the RBD. The protocol starts with a molecular dynamics (MD)-based analysis of the original protein binder in solution (in monomer and dimer forms), as well as of the Target:Bindermonomer and Target:Binderdimer complexes. This guides the subsequent design steps, where ProteinMPNN2 is used to improve the binders affinity for the target, considering both the monomer and dimer states of the binder in parallel re-design runs. The best candidates obtained in each re-design run will then be produced in bacterial systems, and their binding affinity and stability evaluated through binding assays and biophysical characterization, respectively. Hopefully, this project will contribute to the validation of computational AI-driven protein design as an approach that holds promise for biopharmaceutical applications and show the importance of combining MD simulations with protein design methodologies to obtain robust protein structures.info:eu-repo/semantics/publishedVersio

Effect of pH on the influenza fusion peptide properties unveiled by constant-pH molecular dynamics simulations combined with experiment

© The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.The influenza virus fusion process, whereby the virus fuses its envelope with the host endosome membrane to release the genetic material, takes place in the acidic late endosome environment. Acidification triggers a large conformational change in the fusion protein, hemagglutinin (HA), which enables the insertion of the N-terminal region of the HA2 subunit, known as the fusion peptide, into the membrane of the host endosome. However, the mechanism by which pH modulates the molecular properties of the fusion peptide remains unclear. To answer this question, we performed the first constant-pH molecular dynamics simulations of the influenza fusion peptide in a membrane, extending for 40 µs of aggregated time. The simulations were combined with spectroscopic data, which showed that the peptide is twofold more active in promoting lipid mixing of model membranes at pH 5 than at pH 7.4. The realistic treatment of protonation introduced by the constant-pH molecular dynamics simulations revealed that low pH stabilizes a vertical membrane-spanning conformation and leads to more frequent contacts between the fusion peptide and the lipid headgroups, which may explain the increase in activity. The study also revealed that the N-terminal region is determinant for the peptide's effect on the membrane.This work was financially supported by FCT—Fundação para a Ciência e a Tecnologia, Portugal, through projects PTDC/QUI-BIQ/114774/2009, PTDC/CCI-BIO/28200/2017 and Pest-OE/EQB/LA0004/2011. This work was also financially supported by Project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through FCT—Fundação para a Ciência e a Tecnologia. DL was supported by FCT post-doc fellowship SFRH/BPD/92537/2013.info:eu-repo/semantics/publishedVersio

Antiviral proteins targeting Influenza A hemagglutinin: design, production and characterization

In recent years we have felt the devastating impact of viral pandemics, highlighting the need for preparation for future pandemics. Antiviral biologics, including small proteins that bind to and block viral targets, are promising therapeutic options that should be explored to increase pandemic preparedness. One of the viruses with high pandemic potential is influenza, the causative agent of flu. Despite being characterized by annual seasonal epidemics, global pandemics caused by this virus have occurred sporadically and unpredictably1. In the Influenza virus, the fusion of the viral and host membrane (a crucial step in infection) is elicited by hemagglutinin A (HA), a homotrimeric glycoprotein, which engages the virus with sialic acid receptors at the host cell surface and is a privileged target for antivirals2. The focus of this work is the design of Virus-Targeting Antibody-like scaffolds (ViTAls), which can bind to HA, thereby blocking Influenza A entry into host cells. The design is based on innovative strategies that combine knowledge-based and physics-based computational methods to generate tens of thousands of ViTAls, which are ranked according to relevant parameters, such as binding free energy and shape complementarity. The folding stability and conformational dynamics of selected designs are studied through molecular dynamics simulations to obtain a deeper knowledge of their properties and discard candidates that are predicted to be unstable. The candidates that pass all the computational filters are then produced in bacteria and tested using a platform based on biolayer interferometry to assess their binding affinity for the target and on differential scanning fluorimetry to evaluate their thermal stability. Those that have a high binding affinity and high thermal stability are produced in higher amounts and characterized using biophysical techniques and will subsequently be validated using in vitro neutralization assays. This work contributes to the development and validation of an innovative strategy that can be applied to tackle a broad range of viruses, including influenza A.info:eu-repo/semantics/publishedVersio