Fisheries Inspection in Portuguese Waters from 2015 to 2023.

As a coastal state, Portugal must ensure active surveillance over its maritime area, ensuring its proper control and inspection. One of the most critical inspection activities is the fishery inspection. To protect biodiversity, we must ensure that all the ships comply with the existing safety regulations and respect the current fishing quotas. This georeferenced dataset describes the fisheries inspections done in Portuguese waters between 2015 and 2023. Since we are dealing with occurrences that may have originated some legal process to the ship's owner, we have ensured data anonymization by pre-processing the dataset to maintain its accuracy while guaranteeing no unique identifiers exist. All the pre-processing performed to ensure data consistency and accuracy is described in detail to allow a quick analysis and implementation of new algorithms. The data containing the results of these inspections can be easily analyzed to implement data mining algorithms that can efficiently retrieve more knowledge and, e.g., suggest new areas of actuation or new strategies.

Spiro-Acridine Compound as a Pteridine Reductase 1 Inhibitor: in silico Target Fishing and in†vitro Studies.

Among the many neglected tropical diseases, leishmaniasis ranks second in mortality rate and prevalence. In a previous study, acridine derivatives were synthesized and tested for their antileishmanial activity against L. chagasi. The most active compound identified in that study (1) showed a single digit IC50 value against the parasite (1.10 µg/mL), but its macromolecular target remained unknown. Aiming to overcome this limitation, this work exploited inverse virtual screening to identify compound 1's putative molecular mechanism of action. In vitro assays confirmed that compound 1 binds to Leishmania chagasi pteridine reductase 1 (LcPTR1), with moderate affinity (Kd=33,1 µM), according to differential scanning fluorimetry assay. Molecular dynamics simulations confirm the stability of LcPTR1-compound 1 complex, supporting a competitive mechanism of action. Therefore, the workflow presented in this work successfully identified PTR1 as a macromolecular target for compound 1, allowing the designing of novel potent antileishmanial compounds.

Side-scan sonar imaging data of underwater vehicles for mine detection.

Unmanned vehicles have become increasingly popular in the underwater domain in the last decade, as they provide better operation reliability by minimizing human involvement in most tasks. Perception of the environment is crucial for safety and other tasks, such as guidance and trajectory control, mainly when operating underwater. Mine detection is one of the riskiest operations since it involves systems that can easily damage vehicles and endanger human lives if manned. Automating mine detection from side-scan sonar images enhances safety while reducing false negatives. The collected dataset contains 1170 real sonar images taken between 2010 and 2021 using a Teledyne Marine Gavia Autonomous Underwater Vehicle (AUV), which includes enough information to classify its content objects as NOn-Mine-like BOttom Objects (NOMBO) and MIne-Like COntacts (MILCO). The dataset is annotated and can be quickly deployed for object detection, classification, or image segmentation tasks. Collecting a dataset of this type requires a significant amount of time and cost, which increases its rarity and relevance to research and industrial development.

Insights to Design New Drugs against Human African Trypanosomiasis Targeting Rhodesain using Covalent Docking, Molecular Dynamics Simulations, and MM-PBSA Calculations.

BACKGROUND: Neglected tropical diseases (NTDs) are parasitic and bacterial diseases that affect approximately 149 countries, mainly the poor population without basic sanitation. Among these, African Human Trypanosomiasis (HAT), known as sleeping sickness, shows alarming data, with treatment based on suramin and pentamidine in the initial phase and melarsoprol and eflornithine in the chronic phase. Thus, to discover new drugs, several studies point to rhodesain as a promising drug target due to the function of protein degradation and intracellular transport of proteins between the insect and host cells and is present in all cycle phases of the parasite. METHODOLOGY: Here, based on the previous studies by Nascimento et al. (2021) that show the main rhodesain inhibitors development in the last decade, molecular docking and dynamics were applied in these inhibitors datasets to reveal crucial information that can be into drug design. Thus, conventional and covalent docking was employed and highlighted the presence of Michael acceptors in the ligands in a peptidomimetics scaffold, and interaction with Gly19, Gly23, Gly65, Asp161, and Trp184 is essential to the inhibiting activity. RESULTS: Also, our findings using MD simulations and MM-PBSA calculations confirmed Gly19, Gly23, Gly65, Asp161, and Trp184, showing high binding energy (ΔGbind between -72.782 to -124.477 kJ.mol-1). In addition, Van der Waals interactions have a better contribution (-140,930 to -96,988 kJ.mol-1) than electrostatic forces (-43,270 to -6,854 kJ.mol-1), indicating Van der Waals interactions are the leading forces in forming and maintaining ligand-rhodesain complexes. CONCLUSION: Furthermore, the Dynamic Cross-Correlation Maps (DCCM) show more correlated movements for all complexes than the free rhodesain and strong interactions in the regions of the aforementioned residues. Principal Component Analysis (PCA) demonstrates complex stability corroborating with RMSF and RMSD. This study can provide valuable insights that can guide researchers worldwide to discover a new promising drug against HAT.

Study of nitrogen heterocycles as DNA/HSA binder, topoisomerase inhibitors and toxicological safety.

Four new nitrogen-containing heterocyclic derivatives (acridine, quinoline, indole, pyridine) were synthesized and their biological properties were evaluated. The compounds showed affinity for DNA and HSA, with CAIC and CAAC displaying higher binding constants (Kb) of 9.54 × 104 and 1.06 × 106, respectively. The fluorescence quenching assay (Ksv) revealed suppression values ranging from 0.34 to 0.64 × 103 M-1 for ethidium bromide (EB) and 0.1 to 0.34 × 103 M-1 for acridine orange (AO). Molecular docking confirmed the competition of the derivatives with intercalation probes at the same binding site. At 10 µM concentrations, the derivatives inhibited topoisomerase IIα activity. In the antiproliferative assays, the compounds demonstrated activity against MCF-7 and T47-D tumor cells and nonhemolytic profile. Regarding toxicity, no acute effects were observed in the embryos. However, some compounds caused enzymatic and cardiac changes, particularly the CAIC, which increased SOD activity and altered heart rate compared to the control. These findings suggest potential antitumor action of the derivatives and indicate that substituting the acridine core with different cores does not interfere with their interaction and topoisomerase inhibition. Further investigations are required to assess possible toxicological effects, including reactive oxygen species generation.

Georeferenced dataset of maritime piracy in the Gulf of Guinea from 2010 to 2021.

Piracy has been a global concern and a threat to the safety of people performing maritime trade around the globe. Since ancient times maritime piracy has been a common practice that, unfortunately, has not ended in the current days. A georeferenced dataset providing the position, meteorologic conditions, and a description of the occurrence can provide essential information for analyzing this global phenomenon. The dataset focuses on the Gulf of Guinea (GoG) as an area dominated by corruption and weak supervision capacity by the local authorities. The time interval considered in this paper is between 2010 and 2021. Using this simple dataset, it is possible to analyze attributes such as when the piracy occurred or if the illegal activity involved deaths or kidnapping. The accuracy of the data was guaranteed by cross-referencing data sources, so we have 595 pirate attacks accurately described. This dataset can easily be used for data mining, allowing further analysis of the patterns and trends of pirate attacks in the GoG over time.

Overview of the New Bioactive Heterocycles as Targeting Topoisomerase Inhibitors Useful Against Colon Cancer.

Colorectal cancer (CRC) is the third most common worldwide cancer with high mortality. Factors such as more effective screening programs and improvements in treatment modalities have favored a decrease in the incidence and mortality rate of colorectal cancer in the last three decades. Metastatic CRC is incurable in most cases, and therapy using multiple drugs can increase patients' life expectancy by 2 to 3 years. Chemotherapy is the primary treatment, and fluoropyrimidines correspond to the first treatment line. They can be used in monotherapy or therapeutic schemes of oxaliplatin, FOLFOX (intravenous fluorouracil, leucovorin, and oxaliplatin), and CAPOX (oral capecitabine and oxaliplatin) or regimens based on Irinotecan, such FOLFIRI (fluorouracil, leucovorin, and Irinotecan) and CAPIRI (capecitabine and Irinotecan). Like Camptothecin, irinotecan and other analogs have a mechanism of action based on forming a ternary complex with Topoisomerase I and DNA by reversibly binding, providing DNA damage and consequent cell death. This way, topoisomerases are vital enzymes for DNA maintenance and cell viability. Thus, here we will review the main works demonstrating the correlation between the inhibition of different isoforms of topoisomerases and the in vitro cytotoxic activity in colon cancer. The findings revealed that natural compounds, semi-synthetic and synthetic analogs showed potential cytotoxicity against several colon cancer cell lines in vitro and that this activity was often accompanied by the ability to inhibit type I and II topoisomerases, demonstrating that these enzymes can be promising drug targets for the development of new chemotherapeutics against colon cancer.

Targeting SmCB1: Perspectives and Insights to Design Antischistosomal Drugs.

Neglected tropical diseases (NTDs) are prevalent in tropical and subtropical countries, and schistosomiasis is among the most relevant diseases worldwide. In addition, one of the two biggest problems in developing drugs against this disease is related to drug resistance, which promotes the demand to develop new drug candidates for this purpose. Thus, one of the drug targets most explored, Schistosoma mansoni Cathepsin B1 (SmCB1 or Sm31), provides new opportunities in drug development due to its essential functions for the parasite's survival. In this way, here, the latest developments in drug design studies targeting SmCB1 were approached, focusing on the most promising analogs of nitrile, vinyl sulphones, and peptidomimetics. Thus, it was shown that despite being a disease known since ancient times, it remains prevalent throughout the world, with high mortality rates. The therapeutic arsenal of antischistosomal drugs consists only of praziquantel, which is widely used for this purpose and has several advantages, such as efficacy and safety. However, it has limitations, such as the impossibility of acting on the immature worm and exploring new targets to overcome these limitations. SmCB1 shows its potential as a cysteine protease with a catalytic triad consisting of Cys100, His270, and Asn290. Thus, design studies of new inhibitors focus on their catalytic mechanism for designing new analogs. In fact, nitrile and sulfonamide analogs show the most significant potential in drug development, showing that these chemical groups can be better exploited in drug discovery against schistosomiasis. We hope this manuscript guides the authors in searching for promising new antischistosomal drugs.

Anti-Inflammatory Activity of N'-(3-(1H-indol-3-yl)benzylidene)-2-cyanoacetohydrazide Derivative via sGC-NO/Cytokine Pathway.

The N-acylhydrazone function has been reported as a pharmacophore group of molecules with diverse pharmacological activities, including anti-inflammatory effects. Therefore, this study was designed to evaluate the anti-inflammatory potential of the compound N'-(3-(1H-indol-3-yl)benzylidene)-2-cyanoacetohydrazide (JR19) in vivo. The study started with the carrageenan-induced peritonitis model, followed by an investigation of leukocyte migration using the subcutaneous air pouch test and an assessment of the antinociceptive profile using formalin-induced pain. A preliminary molecular docking study focusing on the crystallographic structures of NFκB, iNOS, and sGC was performed to determine the likely mechanism of action. The computational study revealed satisfactory interaction energies with the selected targets, and the same peritonitis model was used to validate the involvement of the nitric oxide pathway and cytokine expression in the peritoneal exudate of mice pretreated with L-NAME or methylene blue. In the peritonitis assay, JR19 (10 and 20 mg/kg) reduced leukocyte migration by 59% and 52%, respectively, compared to the vehicle group, with the 10 mg/kg dose used in subsequent assays. In the subcutaneous air pouch assay, the reduction in cell migration was 66%, and the response to intraplantar formalin was reduced by 39%, particularly during the inflammatory phase, suggesting that the compound lacks central analgesic activity. In addition, a reversal of the anti-inflammatory effect was observed in mice pretreated with L-NAME or methylene blue, indicating the involvement of iNOS and sGC in the anti-inflammatory response of JR19. The compound effectively and significantly decreased the levels of IL-6, TNF-α, IL-17, and IFN-γ, and this effect was reversed in animals pretreated with L-NAME, supporting a NO-dependent anti-inflammatory effect. In contrast, pretreatment with methylene blue only reversed the reduction in TNF-α levels. Therefore, these results demonstrate the pharmacological potential of the novel N-acylhydrazone derivative, which acts through the nitric oxide pathway and cytokine signaling, making it a strong candidate as an anti-inflammatory and immunomodulatory agent.

The Power of Molecular Dynamics Simulations and Their Applications to Discover Cysteine Protease Inhibitors.

A large family of enzymes with the function of hydrolyzing peptide bonds, called peptidases or cysteine proteases (CPs), are divided into three categories according to the peptide chain involved. CPs catalyze the hydrolysis of amide, ester, thiol ester, and thioester peptide bonds. They can be divided into several groups, such as papain-like (CA), viral chymotrypsin-like CPs (CB), papain-like endopeptidases of RNA viruses (CC), legumain-type caspases (CD), and showing active residues of His, Glu/Asp, Gln, Cys (CE). The catalytic mechanism of CPs is the essential cysteine residue present in the active site. These mechanisms are often studied through computational methods that provide new information about the catalytic mechanism and identify inhibitors. The role of computational methods during drug design and development stages is increasing. Methods in Computer-Aided Drug Design (CADD) accelerate the discovery process, increase the chances of selecting more promising molecules for experimental studies, and can identify critical mechanisms involved in the pathophysiology and molecular pathways of action. Molecular dynamics (MD) simulations are essential in any drug discovery program due to their high capacity for simulating a physiological environment capable of unveiling significant inhibition mechanisms of new compounds against target proteins, especially CPs. Here, a brief approach will be shown on MD simulations and how the studies were applied to identify inhibitors or critical information against cysteine protease from several microorganisms, such as Trypanosoma cruzi (cruzain), Trypanosoma brucei (rhodesain), Plasmodium spp. (falcipain), and SARS-CoV-2 (Mpro). We hope the readers will gain new insights and use our study as a guide for potential compound identifications using MD simulations.

Exploring N-myristoyltransferase as a promising drug target against parasitic neglected tropical diseases.

Neglected tropical diseases (NTDs) constitute a group of approximately 20 infectious diseases that mainly affect the impoverished population without basic sanitation in tropical countries. These diseases are responsible for many deaths worldwide, costing billions of dollars in public health investment to treat and control these infections. Among them are the diseases caused by protozoa of the Trypanosomatid family, which constitute Trypanosoma cruzi (Chagas disease), Trypanosoma brucei (sleeping sickness), and Leishmaniasis. In addition, there is a classification of other diseases, called the big three, AIDS, tuberculosis, and malaria, which are endemic in countries with tropical conditions. Despite the high mortality rates, there is still a gap in the treatment. The drugs have a high incidence of side effects and protozoan resistance, justifying the investment in developing new alternatives. In fact, the Target-Based Drug Design (TBDD) approach is responsible for identifying several promising compounds, and among the targets explored through this approach, N-myristoyltransferase (NMT) stands out. It is an enzyme related to the co-translational myristoylation of N-terminal glycine in various peptides. The myristoylation process is a co-translation that occurs after removing the initiator methionine. This process regulates the assembly of protein complexes and stability, which justifies its potential as a drug target. In order to propose NMT as a potential target for parasitic diseases, this review will address the entire structure and function of this enzyme and the primary studies demonstrating its promising potential against Leishmaniasis, T. cruzi, T. brucei, and malaria. We hope our information can help researchers worldwide search for potential drugs against these diseases that have been threatening the health of the world's population.

ACW-02 an Acridine Triazolidine Derivative Presents Antileishmanial Activity Mediated by DNA Interaction and Immunomodulation.

The present study proposed the synthesis of a novel acridine derivative not yet described in the literature, chemical characterization by NMR, MS, and IR, followed by investigations of its antileishmanial potential. In vitro assays were performed to assess its antileishmanial activity against L. amazonensis strains and cytotoxicity against macrophages through MTT assay and annexin V-FITC/PI, and the ability to perform an immunomodulatory action using CBA. To investigate possible molecular targets, its interaction with DNA in vitro and in silico targets were evaluated. As results, the compound showed good antileishmanial activity, with IC50 of 6.57 (amastigotes) and 94.97 (promastigotes) µg mL-1, associated with non-cytotoxicity to macrophages (CC50 > 256.00 µg mL-1). When assessed by flow cytometry, 99.8% of macrophages remained viable. The compound induced an antileishmanial effect in infected macrophages and altered TNF-α, IL-10 and IL-6 expression, suggesting a slight immunomodulatory activity. DNA assay showed an interaction with the minor grooves due to the hyperchromic effect of 47.53% and Kb 1.17 × 106 M-1, and was sustained by docking studies. Molecular dynamics simulations and MM-PBSA calculations propose cysteine protease B as a possible target. Therefore, this study demonstrates that the new compound is a promising molecule and contributes as a model for future works.

Scaffold repositioning of spiro-acridine derivatives as fungi chitinase inhibitor by target fishing and in vitro studies.

The concept of "one target, one drug, one disease" is not always true, as compounds with previously described therapeutic applications can be useful to treat other maladies. For example, acridine derivatives have several potential therapeutic applications. In this way, identifying new potential targets for available drugs is crucial for the rational management of diseases. Computational methodologies are interesting tools in this field, as they use rational and direct methods. Thus, this study focused on identifying other rational targets for acridine derivatives by employing inverse virtual screening (IVS). This analysis revealed that chitinase enzymes can be potential targets for these compounds. Subsequently, we coupled molecular docking consensus analysis to screen the best chitinase inhibitor among acridine derivatives. We observed that 3 compounds displayed potential enhanced activity as fungal chitinase inhibitors, showing that compound 5 is the most active molecule, with an IC50 of 0.6 ng/µL. In addition, this compound demonstrated a good interaction with the active site of chitinases from Aspergillus fumigatus and Trichoderma harzianum. Additionally, molecular dynamics and free energy demonstrated complex stability for compound 5. Therefore, this study recommends IVS as a powerful tool for drug development. The potential applications are highlighted as this is the first report of spiro-acridine derivatives acting as chitinase inhibitors that can be potentially used as antifungal and antibacterial candidates.

Anticancer Activity of Chalcones and Its Derivatives: Review and In Silico Studies.

Chalcones are direct precursors in the biosynthesis of flavonoids. They have an α,ß-unsaturated carbonyl system which gives them broad biological properties. Among the biological properties exerted by chalcones, their ability to suppress tumors stands out, in addition to their low toxicity. In this perspective, the present work explores the role of natural and synthetic chalcones and their anticancer activity in vitro reported in the last four years from 2019 to 2023. Moreover, we carried out a partial least square (PLS) analysis of the biologic data reported for colon adenocarcinoma lineage HCT-116. Information was obtained from the Web of Science database. Our in silico analysis identified that the presence of polar radicals such as hydroxyl and methoxyl contributed to the anticancer activity of chalcones derivatives. We hope that the data presented in this work will help researchers to develop effective drugs to inhibit colon adenocarcinoma in future works.

Would the Development of a Multitarget Inhibitor of 3CLpro and TMPRSS2 be Promising in the Fight Against SARS-CoV-2?

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), responsible for generating COVID-19, has spread worldwide and was declared a pandemic by the World Health Organization (WHO) on 11 March 2020, being responsible for various damages to public health, social life, and the economy of countries. Its high infectivity and mutation rates have stimulated researchers and pharmaceutical companies to search for new therapies against this disease. These efforts resulted in several vaccines and the identification of Molnupiravir as an oral treatment for this disease. However, identifying new alternatives and critical information is necessary to fight against this devastating agent. The findings in recent years regarding the structure and biochemistry of SARS-CoV2 are remarkable. In anti-CoV drug discovery, various targets, such as structural, non-structural, and hostrelated proteins are explored. In fact, 3CLpro is the most used among non-structural proteins since this protease cleaves peptide sequences after the glutamine residue, and no human protease has this function. This makes this macromolecule an excellent drug target for discovering new compounds. Another promising target is the transmembrane protease serine 2 (TMPRSS2). Recent studies point to TMPRSS2 as one of the main targets responsible for viral entry related to the cleavage of the S protein. Similar to cathepsins, TMPRSS2 is also responsible for cleaving the spike protein SARS-CoV2, which binds to the ACE2 receptor. Thus, TMPRSS2 is one of the targets that may represent new alternatives in treating SARS-CoV2. In this context, would discovering a multitarget inhibitor be the new strategy in searching for drugs against SARS-CoV2? For many years, new drug discovery was based on the "one drug, one target" premise, where the biological action is related to interactions with only one biological target. However, this paradigm has been overcome as new evidence of multiple mechanisms of action for a single drug. Finally, this review will present a perspective on drug design based on a multitarget strategy against 3CLpro and TMPRSS2. We hope to provide new horizons for researchers worldwide searching for more effective drugs against this devastating agent.

Sentiment analysis in tweets: an assessment study from classical to modern word representation models.

With the exponential growth of social media networks, such as Twitter, plenty of user-generated data emerge daily. The short texts published on Twitter - the tweets - have earned significant attention as a rich source of information to guide many decision-making processes. However, their inherent characteristics, such as the informal, and noisy linguistic style, remain challenging to many natural language processing (NLP) tasks, including sentiment analysis. Sentiment classification is tackled mainly by machine learning-based classifiers. The literature has adopted different types of word representation models to transform tweets to vector-based inputs to feed sentiment classifiers. The representations come from simple count-based methods, such as bag-of-words, to more sophisticated ones, such as BERTweet, built upon the trendy BERT architecture. Nevertheless, most studies mainly focus on evaluating those models using only a small number of datasets. Despite the progress made in recent years in language modeling, there is still a gap regarding a robust evaluation of induced embeddings applied to sentiment analysis on tweets. Furthermore, while fine-tuning the model from downstream tasks is prominent nowadays, less attention has been given to adjustments based on the specific linguistic style of the data. In this context, this study fulfills an assessment of existing neural language models in distinguishing the sentiment expressed in tweets, by using a rich collection of 22 datasets from distinct domains and five classification algorithms. The evaluation includes static and contextualized representations. Contexts are assembled from Transformer-based autoencoder models that are also adapted based on the masked language model task, using a plethora of strategies.

Advances in Computational Methods to Discover New NS2B-NS3 Inhibitors Useful Against Dengue and Zika Viruses.

The Flaviviridae virus family consists of the genera Hepacivirus, Pestivirus, and Flavivirus, with approximately 70 viral types that use arthropods as vectors. Among these diseases, dengue (DENV) and zika virus (ZIKV) serotypes stand out, responsible for thousands of deaths worldwide. Due to the significant increase in cases, the World Health Organization (WHO) declared DENV a potential threat for 2019 due to being transmitted by infected travelers. Furthermore, ZIKV also has a high rate of transmissibility, highlighted in the outbreak in 2015, generating consequences such as Guillain-Barré syndrome and microcephaly. According to clinical outcomes, those infected with DENV can be asymptomatic, and in other cases, it can be lethal. On the other hand, ZIKV has severe neurological symptoms in newborn babies and adults. More serious symptoms include microcephaly, brain calcifications, intrauterine growth restriction, and fetal death. Despite these worrying data, no drug or vaccine is approved to treat these diseases. In the drug discovery process, one of the targets explored against these diseases is the NS2B-NS3 complex, which presents the catalytic triad His51, Asp75, and Ser135, with the function of cleaving polyproteins, with specificity for basic amino acid residues, Lys- Arg, Arg-Arg, Arg-Lys or Gln-Arg. Since NS3 is highly conserved in all DENV serotypes and plays a vital role in viral replication, this complex is an excellent drug target. In recent years, computer-aided drug discovery (CADD) is increasingly essential in drug discovery campaigns, making the process faster and more cost-effective, mainly explained by discovering new drugs against DENV and ZIKV. Finally, the main advances in computational methods applied to discover new compounds against these diseases will be presented here. In fact, molecular dynamics simulations and virtual screening is the most explored approach, providing several hit and lead compounds that can be used in further optimizations. In addition, fragment-based drug design and quantum chemistry/molecular mechanics (QM/MM) provides new insights for developing anti-DENV/ZIKV drugs. We hope that this review offers further helpful information for researchers worldwide and stimulates the use of computational methods to find a promising drug for treating DENV and ZIKV.