Showing papers by "National Autonomous University of Mexico published in 2022"

Natural product drug discovery in the artificial intelligence era

Abstract: Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular "patterns" of these privileged structures for combinatorial design or target selectivity.

Innate immune memory in invertebrates: Concept and potential mechanisms

Abstract: Invertebrates are the protagonists of a recent paradigm shift because they now show that vertebrates are not the only group with immune memory. This review discusses the concept of immune priming, its characteristics, and differences with trained immunity and immune enhancement. We include an update of the current status of immune priming within generations in different groups of invertebrates which now include work in 5 Phyla: Ctenophora, Cnidaria, Mollusca, Nematoda, and Arthropoda. Clearly, few Phyla have been studied. We also resume and discuss the effector mechanism related to immune memory, including integrating viral elements into the genome, endoreplication, and epigenetics. The roles of other elements are incorporated, such as hemocytes, immune pathways, and metabolisms. We conclude that taking care of the experimental procedure will discern if results provide or do not support the invertebrates' immune memory and that regarding mechanisms, indeed, there are no studies on the immune memory mechanisms, this is how specificity is reached, and how and where the immune memory is stored and how is recall upon subsequent encounters. Finally, we discuss the possibility of having more than one mechanism working in different groups of invertebrates depending on the environmental conditions.

Innate immune memory in invertebrates: Concept and potential mechanisms

Abstract: Invertebrates are the protagonists of a recent paradigm shift because they now show that vertebrates are not the only group with immune memory. This review discusses the concept of immune priming, its characteristics, and differences with trained immunity and immune enhancement. We include an update of the current status of immune priming within generations in different groups of invertebrates which now include work in 5 Phyla: Ctenophora, Cnidaria, Mollusca, Nematoda, and Arthropoda. Clearly, few Phyla have been studied. We also resume and discuss the effector mechanism related to immune memory, including integrating viral elements into the genome, endoreplication, and epigenetics. The roles of other elements are incorporated, such as hemocytes, immune pathways, and metabolisms. We conclude that taking care of the experimental procedure will discern if results provide or do not support the invertebrates' immune memory and that regarding mechanisms, indeed, there are no studies on the immune memory mechanisms, this is how specificity is reached, and how and where the immune memory is stored and how is recall upon subsequent encounters. Finally, we discuss the possibility of having more than one mechanism working in different groups of invertebrates depending on the environmental conditions.

BIGDML—Towards accurate quantum machine learning force fields for materials

Abstract: Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and applicable to molecules, materials, and interfaces thereof. Currently, MLFFs often introduce tradeoffs that restrict their practical applicability to small subsets of chemical space or require exhaustive datasets for training. Here, we introduce the Bravais-Inspired Gradient-Domain Machine Learning (BIGDML) approach and demonstrate its ability to construct reliable force fields using a training set with just 10-200 geometries for materials including pristine and defect-containing 2D and 3D semiconductors and metals, as well as chemisorbed and physisorbed atomic and molecular adsorbates on surfaces. The BIGDML model employs the full relevant symmetry group for a given material, does not assume artificial atom types or localization of atomic interactions and exhibits high data efficiency and state-of-the-art energy accuracies (errors substantially below 1 meV per atom) for an extended set of materials. Extensive path-integral molecular dynamics carried out with BIGDML models demonstrate the counterintuitive localization of benzene--graphene dynamics induced by nuclear quantum effects and allow to rationalize the Arrhenius behavior of hydrogen diffusion coefficient in a Pd crystal for a wide range of temperatures.

Bacterial and Fungal Gut Dysbiosis and Clostridium difficile in COVID-19

Abstract: Gastrointestinal symptoms are common in Coronavirus Disease 2019 (COVID-19), related to infection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) of intestinal cells through the angiotensin converting enzyme 2 (ACE2) receptor in the brush border. Also, patients are treated with multiple antibiotics. Therefore, an increase in gut dysbiosis and in the prevalence of Clostridium difficile infection (CDI) is expected in patients with COVID-19.A PubMed search was conducted using the terms "gut microbiota," "gut mycobiota," "dysbiosis" AND "COVID-19"; "Clostridium difficile," "Clostridioides difficile" AND "COVID-19"; "probiotics," "bacteriotherapy AND COVID-19." Only case series, observational and experimental studies were included.A total of 384 papers were retrieved and 21 fulfilled selection criteria. Later, a new paper was identified, thus 22 papers were reviewed. Main findings: (1) gut bacterial dysbiosis has been found in fecal samples of COVID-19 patients, with enrichment of opportunistic organisms and decrease of beneficial commensals such as Faecalibacterium prausnitizii. Dysbiosis is related to inflammatory markers and illness severity. (2) There is evidence for abnormal gut barrier and bacterial translocation with a negative impact in the lungs. (3) Fungal dysbiosis correlating with pulmonary mycobiota, has also been found. (4) There is controversy in the CDI rates among COVID-19 patients versus controls and pandemic versus prepandemic era. (5) There is no available evidence yet to support bacteriotherapy in COVID-19. (6) Fecal microbiota transplantation (FMT) has been proposed for COVID-19, although there is no evidence to support it. Also, FMT can be safely used during the pandemic for CDI if strict screening protocols for donors and fecal product are implemented.In COVID-19 there is bacterial and fungal dysbiosis that correlates with systemic and pulmonary inflammation, and illness severity. Further investigations are warranted to determine the efficacy of bacteriotherapy and FMT for modulating gut dysbiosis in COVID-19.

Jets in common envelopes: a low-mass main-sequence star in a red giant

Abstract: ABSTRACT We present small-scale 3D hydrodynamical simulations of the evolution of a 0.3 M⊙ main-sequence (MS) star that launches two perpendicular jets within the envelope of a 0.88 M⊙ red giant (RG). Based on previous large-scale simulations, we study the dynamics of the jets either when the secondary star is grazing, when it has plunged-in, or when it is well within the envelope of the RG (in each stage for ∼11 d). The dynamics of the jets through the common envelope (CE) depend on the conditions of the environment as well as on their powering. In the grazing stage and the commencement of the plunge self-regulated jets need higher efficiencies to break out of the envelope of the RG. Deep inside the CE, on the time-scales simulated, jets are choked independently of whether they are self-regulated or constantly powered. Jets able to break out of the envelope of the RG in large-scale simulations, are choked in our small-scale simulations. The accreted angular momentum on to the secondary star is not large enough to form a disc. The mass accretion on to the MS star is 1–10 per cent of the Bondi–Hoyle–Littleton rate (∼10−3–10−1 M⊙ yr−1). High-luminosity emission, from X-rays to ultraviolet and optical, is expected if the jets break out of the CE. Our simulations illustrate the need for inclusion of more realistic accretion and jet models in the dynamical evolution of the CEs.