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Although thymidylate synthase (TYMS) inhibitors have served as components of chemotherapy regimens, the currently available inhibitors induce TYMS overexpression or alter folate transport/metabolism feedback pathways that tumor cells exploit for drug resistance, limiting overall benefit. Here we report a small molecule TYMS inhibitor that i) exhibited enhanced antitumor activity as compared with current fluoropyrimidines and antifolates without inducing TYMS overexpression, ii) is structurally distinct from classical antifolates, iii) extended survival in both pancreatic xenograft tumor models and an hTS/Ink4a/Arf null genetically engineered mouse tumor model, and iv) is well tolerated with equal efficacy using either intraperitoneal or oral administration. Mechanistically, we verify the compound is a multifunctional nonclassical antifolate, and using a series of analogs, we identify structural features allowing direct TYMS inhibition while maintaining the ability to inhibit dihydrofolate reductase. Collectively, this work identifies nonclassical antifolate inhibitors that optimize inhibition of thymidylate biosynthesis with a favorable safety profile, highlighting the potential for enhanced cancer therapy.

Langerin is a mammalian C-type lectin expressed on Langerhans cells in the skin. As an innate immune cell receptor, Langerin is involved in coordinating innate and adaptive immune responses against various incoming threats. We have previously reported a series of thiazolopyrimidines as murine Langerin ligands. Prompted by the observation that its human homologue exhibits different binding specificities for these small molecules, we report here our investigations to define their exact binding site. By using structural comparison and molecular dynamics simulations, we showed that the nonconserved short loops have a high degree of conformational flexibility between the human and murine homologues. Sequence analysis and mutational studies indicated that a pair of residues are essential for the recognition of the thiazolopyrimidines. Taking solvent paramagnetic relaxation enhancement NMR studies together with a series of peptides occupying the same site, we could define the cleft between the short and long loops as the allosteric binding site for these aromatic heterocycles.

Dendritic cells (DC) are antigen-presenting cells coordinating the interplay of the innate and the adaptive immune response. The endocytic C-type lectin receptors DC-SIGN and Langerin display expression profiles restricted to distinct DC subtypes and have emerged as prime targets for next-generation immunotherapies and anti-infectives. Using heteromultivalent liposomes copresenting mannosides bearing aromatic aglycones with natural glycan ligands, we serendipitously discovered striking cooperativity effects for DC-SIGN + but not for Langerin + cell lines. Mechanistic investigations combining NMR spectroscopy with molecular docking and molecular dynamics simulations led to the identification of a secondary binding pocket for the glycomimetics. This pocket, located remotely of DC-SIGN's carbohydrate bindings site, can be leveraged by heteromultivalent avidity enhancement. We further present preliminary evidence that the aglycone allosterically activates glycan recognition and thereby contributes to DC-SIGN-specific cell targeting. Our findings have important implications for both translational and basic glycoscience, showcasing heteromultivalent targeting of DCs to improve specificity and supporting potential allosteric regulation of DC-SIGN and CLRs in general.

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Serral, Castello, Sosa, Pardo, Palumbo, Modenutti, Palomino, Lazarowski, Auzmendi, Ramos, Nicolás, Turjanski, Martí and Fernández Do Porto.)

HIV-1 is characterized by its ability to mutate and recombine even at polymerase (pol) gene. However, pol-gene diversity is limited due to functional constraints. The aim of this study was to characterize longitudinally, by next-generation sequencing (NGS), HIV-1 variants based on pol-gene sequences, at intra- and inter-host level, from acute/early to chronic stages of infection, in the absence of antiretroviral therapy. Ten men who have sex with men (MSM) were recruited during primary infection and yearly followed for five years. Even after a maximum of a five-year follow-up period, the phylogenetic analysis of HIV-1 pol-gene sequences showed a host-defined structured pattern, with a predominance of purifying selection forces during the follow-up. MSM had been acutely infected by different HIV-1 variants mainly ascribed to pure subtype B, or BF recombinant variants and showed different genetic mosaicism patterns that last until the chronic stage, representing a major challenge for prevention strategies., (© 2020 The Author(s).)

Protein dynamics, folding, and thermodynamics represent a central aspect of biophysical chemistry. pH, temperature, and denaturant perturbations inform our understanding of diverse contributors to stability and rates. In this work, we performed a thermodynamic analysis using a combined experimental and computational approach to gain insights into the role of electrostatics in the folding reaction of a psychrophile frataxin variant from Psychromonas ingrahamii . This folding reaction is strongly modulated by pH with a single, narrow, and well-defined transition state with ∼80% compactness, ∼70% electrostatic interactions, and ∼60% hydration shell compared to the native state (α D = 0.82, α H = 0.67, and α Δ C p = 0.59). Our results are best explained by a two-proton/two-state model with very different p K a values of the native and denatured states (∼5.5 and ∼8.0, respectively). As a consequence, the stability strongly increases from pH 8.0 to 6.0 (|ΔΔ G °| = 5.2 kcal mol -1 ), mainly because of a decrease in the T Δ S °. Variation of Δ H ° and Δ S ° at pH below 7.0 is dominated by a change in Δ H f ⧧ and Δ S f ⧧ , while at pH above 7.0, it is governed by Δ H u ⧧ and Δ S u ⧧ . Molecular dynamics simulations showed that these pH modulations could be explained by the fluctuations of two regions, rich in electrostatic contacts, whose dynamics are pH-dependent and motions are strongly correlated. Results presented herein contribute to the understanding of the stability and dynamics of this frataxin variant, pointing to an intrinsic feature of the family topology to support different folding mechanisms.

Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Despite the existence of several bioinformatic algorithms and servers that predict if a SAS is pathogenic or not, they give little or no information at all on the reasons for pathogenicity prediction and on the actual predicted effect of the SAS on the protein function. Moreover, few actual methods take into account structural information when available for automated analysis. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ is a bioinformatic pipeline that incorporates structural information for the detailed analysis and prediction of SAS effect on protein function. It is an online tool which uses UniProt id and automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions, among others. We show that structural information, when available, can improve the SAS pathogenicity diagnosis and more important explain its causes. We show that VarQ is able to correctly reproduce previous analysis of RASopathies related mutations, saving extensive and time consuming manual curation. VarQ assessment was performed over a set of previously manually curated RASopathies (diseases that affects the RAS/MAPK signaling pathway) related variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/. Supporting Information & Tutorials may be found in the webpage of the tool.

Trichoderma koningiopsis strain POS7 produces significantly large amounts of cellulase enzymes in solid-state fermentation. The Illumina-based sequence analysis reveals an approximate genome size of 36.6 Mbp, with a G+C content of 48.82% for T. koningiopsis POS7. Based on ab initio prediction, 12,661 coding genes were annotated., (Copyright © 2017 Castrillo et al.)

Virtual screening is a powerful methodology to search for new small molecule inhibitors against a desired molecular target. Usually, it involves evaluating thousands of compounds (derived from large databases) in order to select a set of potential binders that will be tested in the wet-lab. The number of tested compounds is directly proportional to the cost, and thus, the best possible set of ligands is the one with the highest number of true binders, for the smallest possible compound set size. Therefore, methods that are able to trim down large universal data sets enriching them in potential binders are highly appreciated. Here we present LigQ, a free webserver that is able to (i) determine best structure and ligand binding pocket for a desired protein, (ii) find known binders, as well as potential ligands known to bind to similar protein domains, (iii) most importantly, select a small set of commercial compounds enriched in potential binders, and (iv) prepare them for virtual screening. LigQ was tested with several proteins, showing an impressive capacity to retrieve true ligands from large data sets, achieving enrichment factors of over 10%. LigQ is available at http://ligq.qb.fcen.uba.ar/ .