Garbage in, garbage out: how reliable training data improved a virtual screening approach against SARS-CoV-2 MPro.

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have the power to integrate, process and analyze multiple data in a short time. However, these initiatives may yield unrealistic results if the applied models are not inferred from reliable data and the resulting predictions are not confirmed by experimental evidence. Methods: We undertook a drug discovery campaign against the essential major protease (MPro) from SARS-CoV-2, which relied on an in silico search strategy -performed in a large and diverse chemolibrary- complemented by experimental validation. The computational method comprises a recently reported ligand-based approach developed upon refinement/learning cycles, and structure-based approximations. Search models were applied to both retrospective (in silico) and prospective (experimentally confirmed) screening. Results: The first generation of ligand-based models were fed by data, which to a great extent, had not been published in peer-reviewed articles. The first screening campaign performed with 188 compounds (46 in silico hits and 100 analogues, and 40 unrelated compounds: flavonols and pyrazoles) yielded three hits against MPro (IC50 ≤ 25 µM): two analogues of in silico hits (one glycoside and one benzo-thiazol) and one flavonol. A second generation of ligand-based models was developed based on this negative information and newly published peer-reviewed data for MPro inhibitors. This led to 43 new hit candidates belonging to different chemical families. From 45 compounds (28 in silico hits and 17 related analogues) tested in the second screening campaign, eight inhibited MPro with IC50 = 0.12-20 µM and five of them also impaired the proliferation of SARS-CoV-2 in Vero cells (EC50 7-45 µM). Discussion: Our study provides an example of a virtuous loop between computational and experimental approaches applied to target-focused drug discovery against a major and global pathogen, reaffirming the well-known "garbage in, garbage out" machine learning principle.

Antitumor activity of new chemical compounds in triple negative mammary adenocarcinoma models.

AIM: According to the need for the development of new anticancer agents, we have synthetized novel bioactive compounds and aimed to determine their antitumor action. MATERIALS & METHODS: We describe in vitro studies evaluating the effect of 35 novel chemical compounds on two triple negative murine mammary adenocarcinoma tumors. RESULTS & CONCLUSION: Three compounds were selected because of their high antitumor activity and their low toxicity to normal cells. Their effect on tumor cells apoptosis, clonogenicity and migratory capacity, were determined. We found that the selected compounds showed inhibition of viability and clonogenic capacity, and promotion of apoptosis. They also decreased the migratory capacity of tumor cells. The results obtained suggest the likelihood of their future use as antitumor and/or antimetastatic agents.

Synthesis of propargylamines via the A3 multicomponent reaction and their biological evaluation as potential anticancer agents.

Propargylamines have gained importance in the area of anticancer research. We synthesized 1-substituted propargylic tertiary amines using the A3-coupling as the key step. Both, solution and solid-phase protocols, were used to provide a library of 1-substituted propargylic tertiary amines with interesting structural diversity. The triple negative breast cancer subtype is the most aggressive and it lacks effective therapeutic options, while pancreatic cancer is one of the neoplasms with worse prognosis and limited therapeutic possibilities. The development of tumor-selective drugs has always been a major challenge in cancer treatment. From our library, two propargylamines displayed a high degree of cytotoxic selectivity. These levels of selectivity give a very interesting perspective for further development of 1-substituted propargylic tertiary amines as new potential chemotherapeutic antitumor agents.

Engineering multilayer chemical networks.

Dynamic multilevel systems emerged in the last few years as new platforms to study thermodynamic systems. In this work, unprecedented fully communicated three-level systems are studied. First, different conditions were screened to selectively activate thiol/dithioacetal, thiol/thioester, and thiol/disulfide exchanges, individually or in pairs. Some of those conditions were applied, sequentially, to build multilayer dynamic systems wherein information, in the form of relative amounts of building blocks, can be directionally transmitted between different exchange pools. As far as we know, this is the first report of one synthetic dynamic chemical system where relationships between layers can be changed through network operations.

Molecular Networks in Dynamic Multilevel Systems.

Dynamic multilevel systems can be assembled from molecular building blocks through two or more reversible reactions that form covalent bonds. Molecular networks of dynamic multilevel systems can exhibit different connectivities between nodes. The design and creation of molecular networks in multilevel systems require control of the crossed reactivity of the functional groups (how to connect nodes) and the conditions of the reactions (when to connect nodes). In recent years, the combination of orthogonal and communicating reactions, which can be simultaneous or individually activated, has produced a variety of systems that have given rise to macrocycles and cages, as well as molecular motors and multicomponent architectures on surfaces. A given set of reactions can lead to systems with unique responsiveness, compositions, and functions as a result of the relative reactivities. In this Concept article, different molecular networks from synthetic systems that can be produced by combinations of different reaction types are discussed. Moreover, applications of this chemistry are highlighted, and future perspectives are envisioned.

Light Modulates Metabolic Pathways and Other Novel Physiological Traits in the Human Pathogen Acinetobacter baumannii.

Light sensing in chemotrophic bacteria has been relatively recently ascertained. In the human pathogen Acinetobacter baumannii, light modulates motility, biofilm formation, and virulence through the blue-light-sensing-using flavin (BLUF) photoreceptor BlsA. In addition, light can induce a reduction in susceptibility to certain antibiotics, such as minocycline and tigecycline, in a photoreceptor-independent manner. In this work, we identified new traits whose expression levels are modulated by light in this pathogen, which comprise not only important determinants related to pathogenicity and antibiotic resistance but also metabolic pathways, which represents a novel concept for chemotrophic bacteria. Indeed, the phenylacetic acid catabolic pathway and trehalose biosynthesis were modulated by light, responses that completely depend on BlsA. We further show that tolerance to some antibiotics and modulation of antioxidant enzyme levels are also influenced by light, likely contributing to bacterial persistence in adverse environments. Also, we present evidence indicating that surfactant production is modulated by light. Finally, the expression of whole pathways and gene clusters, such as genes involved in lipid metabolism and genes encoding components of the type VI secretion system, as well as efflux pumps related to antibiotic resistance, was differentially induced by light. Overall, our results indicate that light modulates global features of the A. baumannii lifestyle.IMPORTANCE The discovery that nonphototrophic bacteria respond to light constituted a novel concept in microbiology. In this context, we demonstrated that light could modulate aspects related to bacterial virulence, persistence, and resistance to antibiotics in the human pathogen Acinetobacter baumannii In this work, we present the novel finding that light directly regulates metabolism in this chemotrophic bacterium. Insights into the mechanism show the involvement of the photoreceptor BlsA. In addition, tolerance to antibiotics and catalase levels are also influenced by light, likely contributing to bacterial persistence in adverse environments, as is the expression of the type VI secretion system and efflux pumps. Overall, a profound influence of light on the lifestyle of A. baumannii is suggested to occur.