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BACKGROUND: Congenital hypopituitarism (CH) and its associated syndromes, septo-optic dysplasia (SOD) and holoprosencephaly (HPE), are midline defects that cause significant morbidity for affected people. Variants in 67 genes are associated with CH, but a vast majority of CH cases lack a genetic diagnosis. Whole exome and whole genome sequencing of CH patients identifies sequence variants in genes known to cause CH, and in new candidate genes, but many of these are variants of uncertain significance (VUS). METHODS: The International Mouse Phenotyping Consortium (IMPC) is an effort to establish gene function by knocking-out all genes in the mouse genome and generating corresponding phenotype data. We used mouse embryonic imaging data generated by the Deciphering Mechanisms of Developmental Disorders (DMDD) project to screen 209 embryonic lethal and sub-viable knockout mouse lines for pituitary malformations. RESULTS: Of the 209 knockout mouse lines, we identified 51 that have embryonic pituitary malformations. These genes not only represent new candidates for CH, but also reveal new molecular pathways not previously associated with pituitary organogenesis. We used this list of candidate genes to mine whole exome sequencing data of a cohort of patients with CH, and we identified variants in two unrelated cases for two genes, MORC2 and SETD5, with CH and other syndromic features. CONCLUSIONS: The screening and analysis of IMPC phenotyping data provide proof-of-principle that recessive lethal mouse mutants generated by the knockout mouse project are an excellent source of candidate genes for congenital hypopituitarism in children.

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Histidine kinases (HKs) are a central part of bacterial environmental-sensing two-component systems. They provide their hosts with the ability to respond to a wide range of physical and chemical signals. HKs are multidomain proteins consisting of at least a sensor domain, dimerization and phosphorylation domain (DHp), and a catalytic domain. They work as homodimers and the existence of two different autophosphorylation mechanisms (cis and trans) has been proposed as relevant for pathway specificity. Although several HKs have been intensively studied, a precise sequence-to-structure explanation of why and how either cis or trans phosphorylation occurs is still unavailable nor is there any evolutionary analysis on the subject. In this work, we show that AlphaFold can accurately determine whether an HK dimerizes in a cis or trans structure. By modeling multiple HKs we show that both cis- and trans-acting HKs are common in nature and the switch between mechanisms has happened multiple times in the evolutionary history of the family. We then use AlphaFold modeling to explore the molecular determinants of the phosphorylation mechanism. We conclude that it is the difference in lengths of the helices surrounding the DHp loop that determines the mechanism. We also show that very small changes in these helices can cause a mechanism switch. Despite this, previous evidence shows that for a particular HK the phosphorylation mechanism is conserved. This suggests that the phosphorylation mechanism participates in system specificity and mechanism switching provides these systems with a way to diverge.

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Energetic local frustration offers a biophysical perspective to interpret the effects of sequence variability on protein families. Here we present a methodology to analyze local frustration patterns within protein families and superfamilies that allows us to uncover constraints related to stability and function, and identify differential frustration patterns in families with a common ancestry. We analyze these signals in very well studied protein families such as PDZ, SH3, ɑ and ß globins and RAS families. Recent advances in protein structure prediction make it possible to analyze a vast majority of the protein space. An automatic and unsupervised proteome-wide analysis on the SARS-CoV-2 virus demonstrates the potential of our approach to enhance our understanding of the natural phenotypic diversity of protein families beyond single protein instances. We apply our method to modify biophysical properties of natural proteins based on their family properties, as well as perform unsupervised analysis of large datasets to shed light on the physicochemical signatures of poorly characterized proteins such as the ones belonging to emergent pathogens.

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During the second half of the 20th century, following structural biology hallmark works on DNA and proteins, biochemists shifted their questions from "what does this molecule look like?" to "how does this process work?". Prompted by the theoretical and practical developments in computational chemistry, this led to the emergence of biomolecular simulations and, along with the 2013 Nobel Prize in Chemistry, to the development of hybrid QM/MM methods. QM/MM methods are necessary whenever the problem we want to address involves chemical reactivity and/or a change in the system's electronic structure, with archetypal examples being the studies of an enzyme's reaction mechanism and a metalloprotein's active site. In the last decades QM/MM methods have seen an increasing adoption driven by their incorporation in widely used biomolecular simulation software. However, properly setting up a QM/MM simulation is not an easy task, and several issues need to be properly addressed to obtain meaningful results. In the present work, we describe both the theoretical concepts and practical issues that need to be considered when performing QM/MM simulations. We start with a brief historical perspective on the development of these methods and describe when and why QM/MM methods are mandatory. Then we show how to properly select and analyze the performance of the QM level of theory, the QM system size, and the position and type of the boundaries. We show the relevance of performing prior QM model system (or QM cluster) calculations in a vacuum and how to use the corresponding results to adequately calibrate those derived from QM/MM. We also discuss how to prepare the starting structure and how to select an adequate simulation strategy, including those based on geometry optimizations as well as free energy methods. In particular, we focus on the determination of free energy profiles using multiple steered molecular dynamics (MSMD) combined with Jarzynski's equation. Finally, we describe the results for two illustrative and complementary examples: the reaction performed by chorismate mutase and the study of ligand binding to hemoglobins. Overall, we provide many practical recommendations (or shortcuts) together with important conceptualizations that we hope will encourage more and more researchers to incorporate QM/MM studies into their research projects.

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Phosphorylation carries chemical information in biological systems. In two-component systems (TCSs), the sensor histidine kinase and the response regulator are connected through phosphoryl transfer reactions that may be uni- or bidirectional. Directionality enables the construction of complex regulatory networks that optimize signal propagation and ensure the forward flow of information. We combined x-ray crystallography, hybrid quantum mechanics/molecular mechanics (QM/MM) simulations, and systems-integrative kinetic modeling approaches to study phosphoryl flow through the Bacillus subtilis thermosensing TCS DesK-DesR. The allosteric regulation of the histidine kinase DesK was critical to avoid back transfer of phosphoryl groups and futile phosphorylation-dephosphorylation cycles by isolating phosphatase, autokinase, and phosphotransferase activities. Interactions between the kinase's ATP-binding domain and the regulator's receiver domain placed the regulator in two distinct positions in the phosphotransferase and phosphatase complexes, thereby determining whether a key glutamine residue in DesK was properly situated to assist in the dephosphorylation reaction. Moreover, an energetically unfavorable phosphotransferase conformation when DesK was not phosphorylated minimized reverse phosphoryl transfer. DesR dimerization and a dissociative phosphoryl transfer reaction also enforced the direction of phosphoryl flow. Shorter or longer distances between the phosphoryl acceptor and donor residues shifted the phosphoryl transfer equilibrium by modulating the stabilizing effect of the Mg2+ cofactor. These mechanisms control the directionality of signal transmission and show how structure-encoded allostery stores and transmits information in signaling systems.

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Neutrophils play major roles against bacteria and fungi infections not only due to their microbicide properties but also because they release mediators like Interleukin-1 beta (IL-1ß) that contribute to orchestrate the inflammatory response. This cytokine is a leaderless protein synthesized in the cytoplasm as a precursor (pro-IL-1ß) that is proteolytically processed to its active isoform and released from human neutrophils by secretory autophagy. In most myeloid cells, pro-IL-1ß is processed by caspase-1 upon inflammasome activation. Here we employed neutrophils from both healthy donors and patients with a gain-of-function (GOF) NLRP3-mutation to dissect IL-1ß processing in these cells. We found that although caspase-1 is required for IL-1ß secretion, it undergoes rapid inactivation, and instead, neutrophil serine proteases play a key role in pro-IL-1ß processing. Our findings bring to light distinctive features of the regulation of caspase-1 activity in human neutrophils and reveal new molecular mechanisms that control human neutrophil IL-1ß secretion.

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Protein-protein interactions (PPIs) are essential, and modulating their function through PPI-targeted drugs is an important research field. PPI sites are shallow protein surfaces readily accessible to the solvent, thus lacking a proper pocket to fit a drug, while their lack of endogenous ligands prevents drug design by chemical similarity. The development of PPI-blocking compounds is, therefore, a tough challenge. Mixed solvent molecular dynamics has been shown to reveal protein-ligand interaction hot spots in protein active sites by identifying solvent sites (SSs). Furthermore, our group has shown that SSs significantly improve protein-ligand docking. In the present work, we extend our analysis to PPI sites. In particular, we analyzed water, ethanol, and phenol-derived sites in terms of their capacity to predict protein-drug and protein-protein interactions. Subsequently, we show how this information can be incorporated to improve both protein-ligand and protein-protein docking. Finally, we highlight the presence of aromatic clusters as key elements of the corresponding interactions.

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Pubertal delay in males is frequently due to constitutional delay of growth and puberty, but pathologic hypogonadism should be considered. After general illnesses and primary testicular failure are ruled out, the main differential diagnosis is central (or hypogonadotropic) hypogonadism, resulting from a defective function of the gonadotropin-releasing hormone (GnRH)/gonadotropin axis. Ciliopathies arising from defects in non-motile cilia are responsible for developmental disorders affecting the sense organs and the reproductive system. WDR11-mediated signaling in non-motile cilia is critical for fetal development of GnRH neurons. Only missense variants of WDR11 have been reported to date in patients with central hypogonadism, suggesting that nonsense variants could lead to more complex phenotypes. We report the case of a male patient presenting with delayed puberty due to Kallmann syndrome (central hypogonadism associated with hyposmia) in whom the next-generation sequencing analysis identified a novel heterozygous base duplication, leading to a frameshift and a stop codon in the N-terminal region of WDR11. The variant was predicted to undergo nonsense-mediated decay and classified as probably pathogenic following the American College of Medical Genetics and Genomics (ACMG) criteria. This is the first report of a variant in the WDR11 N-terminal region predicted to lead to complete expression loss that, contrary to expectations, led to a mild form of ciliopathy resulting in isolated Kallmann syndrome.

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Computer-aided drug discovery methods play a major role in the development of therapeutically important small molecules, but their performance needs to be improved. Molecular dynamics simulations in mixed solvents are useful in understanding protein-ligand recognition and improving molecular docking predictions. In this work, we used ethanol as a cosolvent to find relevant interactions for ligands toward protein kinase G, an essential protein of Mycobacterium tuberculosis (Mtb). We validated the hot spots by screening a database of fragment-like compounds and another one of known kinase inhibitors. Next, we performed a pharmacophore-guided docking simulation and found three low micromolar inhibitors, including one with a novel chemical scaffold that we expanded to four derivative compounds. Binding affinities were characterized by intrinsic fluorescence quenching assays, isothermal titration calorimetry, and the analysis of melting curves. The predicted binding mode was confirmed by X-ray crystallography. Finally, the compounds significantly inhibited the viability of Mtb in infected THP-1 macrophages.

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Gliomas are the most frequent solid tumors in children. Among these, high-grade gliomas are less common in children than in adults, though they are similar in their aggressive clinical behavior. In adults, glioblastoma is the most lethal tumor of the central nervous system. Insulin-like growth factor 1 receptor (IGF1R) plays an important role in cancer biology, and its nuclear localization has been described as an adverse prognostic factor in different tumors. Previously, we have demonstrated that, in pediatric gliomas, IGF1R nuclear localization is significantly associated with high-grade tumors, worst clinical outcome, and increased risk of death. Herein we explore the role of IGF1R intracellular localization by comparing two glioblastoma cell lines that differ only in their IGF1R capacity to translocate to the nucleus. In vitro, IGF1R nuclear localization enhances glioblastoma cell motility and metabolism without affecting their proliferation. In vivo, IGF1R has the capacity to translocate to the nucleus and allows not only a higher proliferation rate and the earlier development of tumors but also renders the cells sensitive to OSI906 therapy. With this work, we provide evidence supporting the implications of the presence of IGF1R in the nucleus of glioma cells and a potential therapeutic opportunity for patients harboring gliomas with IGF1R nuclear localization.

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Mycobacterium tuberculosis (Mtb), the causative agent of Tuberculosis, has 11 eukaryotic-like serine/threonine protein kinases, which play essential roles in cell growth, signal transduction, and pathogenesis. Protein kinase G (PknG) regulates the carbon and nitrogen metabolism by phosphorylation of the glycogen accumulation regulator (GarA) protein at Thr21. Protein kinase B (PknB) is involved in cell wall synthesis and cell shape, as well as phosphorylates GarA but at Thr22. While PknG seems to be constitutively activated and recognition of GarA requires phosphorylation in its unstructured tail, PknB activation is triggered by phosphorylation of its activation loop, which allows binding of the forkhead-associated domain of GarA. In the present work, we used molecular dynamics and quantum-mechanics/molecular mechanics simulations of the catalytically competent complex and kinase activity assays to understand PknG/PknB specificity and reactivity toward GarA. Two hydrophobic residues in GarA, Val24 and Phe25, seem essential for PknG binding and allow specificity for Thr21 phosphorylation. On the other hand, phosphorylated residues in PknB bind Arg26 in GarA and regulate its specificity for Thr22. We also provide a detailed analysis of the free energy profile for the phospho-transfer reaction and show why PknG has a constitutively active conformation not requiring priming phosphorylation in contrast to PknB. Our results provide new insights into these two key enzymes relevant for Mtb and the mechanisms of serine/threonine phosphorylation in bacteria.

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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.

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The interaction between a protein and its ligands is one of the basic and most important processes in biological chemistry. Docking methods aim to predict the molecular 3D structure of protein-ligand complexes starting from coordinates of the protein and the ligand separately. They are widely used in both industry and academia, especially in the context of drug development projects. AutoDock4 is one of the most popular docking tools and, as for any docking method, its performance is highly system dependent. Knowledge about specific protein-ligand interactions on a particular target can be used to successfully overcome this limitation. Here, we describe how to apply the AutoDock Bias protocol, a simple and elegant strategy that allows users to incorporate target-specific information through a modified scoring function that biases the ligand structure towards those poses (or conformations) that establish selected interactions. We discuss two examples using different bias sources. In the first, we show how to steer dockings towards interactions derived from crystal structures of the receptor with different ligands; in the second example, we define and apply hydrophobic biases derived from Molecular Dynamics simulations in mixed solvents. Finally, we discuss general concepts of biased docking, its performance in pose prediction, and virtual screening campaigns as well as other potential applications.

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Background: Oculocutaneous albinism (OCA) is a Mendelian disorder characterized by hypopigmentation of the skin, hair, and eyes, hypoplastic fovea, and low vision, known to be caused by mutations in the Tyrosinase (TYR) gene. Among the known TYR variants, some reduce but do not completely eliminate tyrosinase activity, allowing residual production of melanin and resulting in a contradictory assignment as either pathogenic or benign, preventing a precise clinical diagnostic.Materials and Methods: In the present work, we performed Whole Exome Sequencing and subsequent Sanger sequencing in a young male clinically diagnosed with OCA.Results: Whole-exome sequencing analysis revealed the identification of two variants in trans in TYR. The first, corresponds to a known pathogenic variant G47D, while the second S192Y, was considered a polymorphism due to its relatively high frequency in the European population.Conclusion: The lack of other pathogenic variants in TYR, the reported reduced enzymatic activity (ca. 40% respect to wt) for S192Y, together with the structural in-silico analysis strongly suggest that both reported variants are jointly disease-causing and that S192Y should be considered as likely pathogenic, especially when it is found in trans with a null variant.

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Interferon-stimulated gene 15 (ISG15) was the first ubiquitin-like modifier protein identified that acts by protein conjugation (ISGylation) and is thought to modulate IFN-induced inflammation. Here, we report a new patient from a non-consanguineous Argentinian family, who was followed for recurrent ulcerative skin lesions, cerebral calcifications and lung disease. Whole Exome Sequencing (WES) revealed two novel compound heterozygous variants (c.285del and c.299_312del, NM_005101.4 GRCh37(hg19), both classified as pathogenic according to ACMG criteria) in the ISG15 gene, resulting in a complete deficiency due to disruption of the second ubiquitin domain of the corresponding protein. The clinical phenotype of this patient is unique given the presence of recurrent pulmonary manifestations and the absence of mycobacterial infections, thus resulting in a phenotype distinct from that previously described in patients with biallelic loss-of-function (LOF) ISG15 variants. This case highlights the role of ISG15 as an immunomodulating factor whose LOF variants result in heterogeneous clinical presentations.

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Azanone (HNO, nitroxyl) is a highly reactive molecule that, in the past few years, has drawn significant interest because of its pharmacological properties. However, the understanding of how, when, and where endogenous HNO is produced remains a matter of discussion. In this study, we examined the ability of myoglobin to produce HNO via the peroxidation of hydroxylamine with H2O2 using both experimental and computational approaches. The production of HNO was confirmed using an azanone selective electrochemical method and by the detection of N2O using FTIR. The catalytic capacity of myoglobin was characterized by the determination of the turnover number. The reaction kinetics of the hydroxylamine peroxidation were studied by both electrochemical and UV-vis methods. Further evidence about the reaction mechanism was obtained by EPR spectroscopy. Additionally, quantum mechanical/molecular mechanics experiments were performed to calculate the energy barrier for HNO production and to gain insight into the reaction mechanism. Our results confirm that myoglobin produces HNO via the peroxidation of hydroxylamine with a great catalytic capacity. In addition, our mechanistic study allows us to state that the Mb ferryl state is the most likely intermediate that reacts with hydroxylamine, yielding important evidence for endogenous HNO generation.

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Protein kinases (PKs) are allosteric enzymes that play an essential role in signal transduction by regulating a variety of key cellular processes. Most PKs suffer conformational rearrangements upon phosphorylation that strongly enhance the catalytic activity. Generally, it involves the movement of the phosphorylated loop toward the active site and the rotation of the whole C-terminal lobe. However, not all kinases undergo such a large configurational change: The MAPK extracellular signal-regulated protein kinases ERK1 and ERK2 achieve a 50 000 fold increase in kinase activity with only a small motion of the C-terminal region. In the present work, we used a combination of molecular simulation tools to characterize the conformational landscape of ERK2 in the active (phosphorylated) and inactive (unphosphorylated) states in solution in agreement with NMR experiments. We show that the chemical reaction barrier is strongly dependent on ATP conformation and that the "active" low-barrier configuration is subtly regulated by phosphorylation, which stabilizes a key salt bridge between the conserved Lys52 and Glu69 belonging to helix-C and promotes binding of a second Mg ion. Our study highlights that the on-off switch embedded in the kinase fold can be regulated by small, medium, and large conformational changes.

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Aromatic rings are important residues for biological interactions and appear to a large extent as part of protein-drug and protein-protein interactions. They are relevant for both protein stability and molecular recognition processes due to their natural occurrence in aromatic aminoacids (Trp, Phe, Tyr and His) as well as in designed drugs since they are believed to contribute to optimizing both affinity and specificity of drug-like molecules. Despite the mentioned relevance, the impact of aromatic clusters on protein-protein and protein-drug complexes is still poorly characterized, especially in those that go beyond a dimer. In this work, we studied protein-drug and protein-protein complexes and systematically analyzed the presence and structure of their aromatic clusters. Our results show that aromatic clusters are highly prevalent in both protein-protein and protein-drug complexes, and suggest that protein-protein aromatic clusters have idealized interactions, probably because they were optimized by evolution, as compared to protein-drug clusters that were manually designed. Interestingly, the configuration, solvent accessibility and secondary structure of aromatic residues in protein-drug complexes shed light on the relation between these properties and compound affinity, allowing researchers to better design new molecules.

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Galectins (formerly known as "S-type lectins") are a subfamily of soluble proteins that typically bind ß-galactoside carbohydrates with high specificity. They are present in many forms of life, from nematodes and fungi to animals, where they perform a wide range of functions. Particularly in humans, different types of galectins have been described differing not only in their tissue expression but also in their cellular location, oligomerization, fold architecture and carbohydrate-binding affinity. This distinct yet sometimes overlapping distributions and physicochemical attributes make them responsible for a wide variety of both intra- and extracellular functions, including tremendous importance in immunity and disease. In this review, we aim to provide a general description of galectins most important structural features, with a special focus on the molecular determinants of their carbohydrate-recognition ability. For that purpose, we structurally compare the human galectins, in light of recent mutagenesis studies and novel X-ray structures. We also offer a detailed description on how to use the solvent structure surrounding the protein as a tool to get better predictions of galectin-carbohydrate complexes, with a potential application to the rational design of glycomimetic inhibitory compounds. Finally, using Gal-1 and Gal-3 as paramount examples, we review a series of recent advances in the development of engineered galectins and galectin inhibitors, aiming to dissect the structure-activity relationship through the description of their interaction at the molecular level.

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SUMMARY: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations. AVAILABILITY AND IMPLEMENTATION: AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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