Palma, SICJ, Esteves C, Pádua AC, Alves CM, Santos GMC, Costa HMA, Dionisio M, Gamboa H, Gruber J, Roque ACA.
2019.
Enhanced gas sensing with soft functional materials, May 2019. ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings. , Fukuoka, Japan: Institute of Electrical and Electronics Engineers Inc.
AbstractThe materials described in this work result from the selfassembly of liquid crystals and ionic liquids into droplets,
stabilized within a biopolymeric matrix. These systems are
extremely versatile gels, in terms of composition, and offer
potential for fine tuning of both structure and function, as
each individual component can be varied. Here, the
characterization and application of these gels as sensing thin
films in gas sensor devices is presented. The unique
supramolecular structure of the gels is explored for molecular
recognition of volatile organic compounds (VOCs) by
employing gels with distinct formulations to yield
combinatorial optical and electrical responses used in the
distinction and identification of VOCs.
Roque, ACA, Fred A, Gamboa H.
2019.
Foreword, January 2019. BIODEVICES 2019 - 12th International Conference on Biomedical Electronics and Devices, Proceedings; Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019. , Prague: SciTePress
Fernandes, C, Pina AS, Barbosa AJM, Padrão I, Duarte F, Andreia C, Teixeira S, Alves V, Gomes P, Fernandes TG, Dias AMGC, Roque ACA.
2019.
Affinity‐triggered assemblies based on a designed peptide‐peptide affinity pair. Biotechnology Journal. -(-):-.
AbstractAffinity‐triggered assemblies rely on affinity interactions as the driving force to assemble physically‐crosslinked networks. WW domains are small hydrophobic proteins binding to proline‐rich peptides that are typically produced in the insoluble form. Previous works attempted the biological production of the full WW domain in tandem to generate multivalent components for affinity‐triggered hydrogels. In this work, an alternative approach was followed by engineering a 13‐mer minimal version of the WW domain that retains the ability to bind to target proline‐rich peptides. Both ligand and target peptides were produced chemically and conjugated to multivalent polyethylene glycol, yielding two components. Upon mixing, they together form soft biocompatible affinity‐triggered assemblies, stable in stem cell culture media, and displaying mechanical properties in the same order of magnitude as for those hydrogels formed with the full WW protein in tandem.
dos Santos, R, Figueiredo C, Viecinski AC, Pina AS, Barbosa AJM, Roque ACA.
2019.
Designed affinity ligands to capture human serum albumin. Journal of Chromatography A. 1583:88-97.
AbstractHuman serum albumin (HSA) in an important therapeutic agent and disease biomarker, with an increasing market demand. By proteins and drugs that bind to HSA as inspiration, a combinatorial library of 64 triazine-based ligands was rationally designed and screened for HSA binding at physiological conditions. Two triazine-based lead ligands (A3A2 and A6A5), presenting more than 50% HSA bound and high enrichment factors, were selected for further studies. Binding and elution conditions for HSA purification from human plasma were optimized for both ligands. The A6A5 adsorbent yielded a purified HSA sample with 98% purity at 100% recovery yield under mild binding and elution conditions.
Esteves C, Santos GMC, Alves C, Palma S, Porteira AR, Filho J, HA C, Alves VD, Faustino BMM, Ferreira I, Gamboa H, Roque ACA.
2019.
Effect of film thickness in gelatin hybrid gels for artificial olfaction. Materials Today Bio. 1:-.
AbstractArtificial olfaction is a fast-growing field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition in which volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. This results in electrical signals transduced to the brain where pattern recognition is performed. An efficient approach in artificial olfaction combines gas-sensitive materials with dedicated signal processing and classification tools. In this work, films of gelatin hybrid gels with a single composition that change their optical properties upon binding to VOCs were studied as gas-sensing materials in a custom-built electronic nose. The effect of films thickness was studied by acquiring signals from gelatin hybrid gel films with thicknesses between 15 and 90 μm when exposed to 11 distinct VOCs. Several features were extracted from the signals obtained and then used to implement a dedicated automatic classifier based on support vector machines for data processing. As an optical signature could be associated to each VOC, the developed algorithms classified 11 distinct VOCs with high accuracy and precision (higher than 98%), in particular when using optical signals from a single film composition with 30 μm thickness. This shows an unprecedented example of soft matter in artificial olfaction, in which a single gelatin hybrid gel, and not an array of sensing materials, can provide enough information to accurately classify VOCs with small structural and functional differences.
Barbosa, AJM, Roque ACA.
2019.
Free Marine natural products databases for biotechnology and bioengineering. Biotechnology Journal. -(-):-.
AbstractMarine organisms and microorganisms are a source of natural compounds with unique chemical features. These chemical properties are useful for the discovery of new functions and applications of Marine Natural Products (MNP). To extensively exploit the potential implementations of MNPs, they are gathered in chemical databases consenting their study and screening for applications of biotechnological interest. However, classification of MNPs is currently poor in generic chemical databases. The present availability of free‐access focused MNPs databases is scarce and the molecular diversity of these databases is still very low when compared to paid‐access ones. In this review paper, the current scenario of free‐access MNP databases is presented as well as the hindrances involved in their development, mainly compound dereplication. Examples and opportunities on using freely accessible MNP databases in several important areas of biotechnology are also assessed. The scope of this paper is as well to notify the latent potential of these information sources for the discovery and development of new MNPs in biotechnology, and push future efforts to develop a public domain MNP database freely available for the scientific community.
Carvalho, H, Branco R, Leite F, Matzapetakis M, Roque ACA, Iranzo O.
2019.
Hydrolytic zinc metallopeptides using a computational multi-state design approach. Catalysis Science Technology. 9(23):6723-6736.
AbstractHydrolytic zinc enzymes are common targets for protein design. The versatility of the zinc chemistry can be combined with the usage of small protein scaffolds for biocatalytic applications. Despite this, the computational design of metal-containing proteins remains challenging due to the need to properly model protein–metal interactions. We addressed these issues by developing a computational multi-state design approach of artificial zinc hydrolases based on small protein scaffolds. The zinc-finger peptide Sp1f2 was redesigned to accommodate a catalytic zinc centre and the villin headpiece C-terminal subdomain HP35 was de novo designed for metal-binding and catalytic activity. Both metallopeptides exhibited metal-induced folding (KZnP,app ≈ 2 × 105 M−1) and hydrolytic activity (k2 ≈ 0.1 M−1 s−1) towards an ester substrate. By focusing on the inherent flexibility of small proteins and their interactions with the metal ion by molecular dynamics simulations and spectroscopic studies, we identified current limitations on computational design of metalloenzymes and propose how these can be overcome by integrating information of protein–metal interactions in long time scale simulations.
Maugeri, G, Lychko I, Sobral R, Roque ACA.
2019.
Identification and Antibiotic-Susceptibility Profiling of Infectious Bacterial Agents: A Review of Current and FutureTrends. Biotechnology Journal. 14(1700750)
AbstractAntimicrobial resistance is one of the most worrying threats to humankind with extremely high healthcare costs associated. The current technologies used in clinical microbiology to identify the bacterial agent and profile antimicrobial susceptibility are time‐consuming and frequently expensive. As a result, physicians prescribe empirical antimicrobial therapies. This scenario is often the cause of therapeutic failures, causing higher mortality rates and healthcare costs, as well as the emergence and spread of antibiotic resistant bacteria. As such, new technologies for rapid identification of the pathogen and antimicrobial susceptibility testing are needed. This review summarizes the current technologies, and the promising emerging and future alternatives for the identification and profiling of antimicrobial resistance bacterial agents, which are expected to revolutionize the field of clinical diagnostics.
Padua, A, Gruber J, Gamboa H, Roque ACA.
2019.
Impact of Sensing Film’s Production Method on Classification Accuracy by Electronic Nose. Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES. , Prague, Czech Republic
AbstractThe development of gas sensing materials is relevant in the field of non-invasive biodevices. In this work, we used an electronic nose (E-nose) developed by our research group, which possess versatile and unique sensing materials. These are gels that can be spread over the substrate by Film Coating or Spin Coating. This study aims to evaluate the influence of the sensing film spreading method selected on the classification capabilities of the E-nose. The methodology followed consisted of performing an experiment where the E-nose was exposed to 13 different pure volatile organic compounds. The sensor array had two sensing films produced by Film Coating, and other two produced by Spin Coating. After data collection, a set of features was extracted from the original signal curves, and the best were selected by Recursive Feature Elimination. Then, the classification performance of Multinomial Logistic regression, Decision Tree, and Naíve Bayes was evaluated. The results showed that both s preading methods for sensing film’s production are adequate since the estimated error of classification was inferior to 4 % for all the classification tools applied.
Santos, G, Alves C, Pádua AC, Palma S, Gamboa H, Roque ACA.
2019.
An Optimized E-nose for Efficient Volatile Sensing and Discrimination. Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIODEVICES. , Prague, Czech Republic
AbstractElectronic noses (E-noses), are usually composed by an array of sensors with different selectivities towards classes of VOCs (Volatile Organic Compounds). These devices have been applied to a variety of fields, including environmental protection, public safety, food and beverage industries, cosmetics, and clinical diagnostics. This work demonstrates that it is possible to classify eleven VOCs from different chemical classes using a single gas sensing biomaterial that changes its optical properties in the presence of VOCs. To accomplish this, an in-house built E-nose, tailor-made for the novel class of gas sensing biomaterials, was improved and combined with powerful machine learning techniques. The device comprises a delivery system, a detection system and a data acquisition and control system. It was designed to be stable, miniaturized and easy-to-handle. The data collected was pre-processed and features and curve fitting parameters were extracted from the original response. A recursive feature selection method was applied to select the best features, and then a Support Vector Machine classifier was implemented to distinguish the eleven distinct VOCs. The results show that the followed methodology allowed the classification of all the VOCs tested with 94.6% (± 0.9%) accuracy.
Batalha, IL, Lychko I, Branco RJF, Iranzo O, Roque ACA.
2019.
β-Hairpins as peptidomimetics of human phosphoprotein-binding domains. Organic & Biomolecular Chemistry. 17:3996-4004.
AbstractPhosphoprotein-binding domains interact with cognate phosphorylated targets ruling several biological processes. The impairment of such interactions is often associated with disease development, namely cancer. The breast cancer susceptibility gene 1 (BRCA1) C-terminal (BRCT) domain is involved in the control of complex signaling networks of the DNA damage response. The capture and identification of BRCT-binding proteins and peptides may be used for the development of new diagnostic tools for diseases with abnormal phosphorylation profiles. Here we show that designed cyclic β-hairpin structures can be used as peptidomimetics of the BRCT domain, with high selectivity in binding to a target phosphorylated peptide. The amino acid residues and spatial constraints involved in the interaction between a phosphorylated peptide (GK14-P) and the BRCT domain were identified and crafted onto a 14-mer β-hairpin template in silico. Several cyclic peptides models were designed and their binding towards the target peptide and other phosphorylated peptides evaluated through virtual screening. Selected cyclic peptides were then synthesized, purified and characterized. The high affinity and selectivity of the lead cyclic peptide towards the target phosphopeptide was confirmed, and the possibility to capture it using affinity chromatography demonstrated. This work paves the way for the development of cyclic β-hairpin peptidomimetics as a novel class of affinity reagents for the highly selective identification and capture of target molecules.