Phosphorylation Mechanism Switching in Histidine Kinases Is a Tool for Fast Protein Evolution: Insights From AlphaFold Models.

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.

High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency.

Pituitary hormone deficiency occurs in ∼1:4,000 live births. Approximately 3% of the cases are due to mutations in the alpha isoform of POU1F1, a pituitary-specific transcriptional activator. We found four separate heterozygous missense variants in unrelated individuals with hypopituitarism that were predicted to affect a minor isoform, POU1F1 beta, which can act as a transcriptional repressor. These variants retain repressor activity, but they shift splicing to favor the expression of the beta isoform, resulting in dominant-negative loss of function. Using a high-throughput splicing reporter assay, we tested 1,070 single-nucleotide variants in POU1F1. We identified 96 splice-disruptive variants, including 14 synonymous variants. In separate cohorts, we found two additional synonymous variants nominated by this screen that co-segregate with hypopituitarism. This study underlines the importance of evaluating the impact of variants on splicing and provides a catalog for interpretation of variants of unknown significance in POU1F1.

Best Practices on QM/MM Simulations of Biological Systems.

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.

Solvent Sites Improve Docking Performance of Protein-Protein Complexes and Protein-Protein Interface-Targeted Drugs.

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.

Specificity and Reactivity of Mycobacterium tuberculosis Serine/Threonine Kinases PknG and PknB.

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.

A Remote Secondary Binding Pocket Promotes Heteromultivalent Targeting of DC-SIGN.

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.

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

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.

Structure and function of crocodilian hemoglobins and allosteric regulation by chloride, ATP, and CO2.

Hemoglobins (Hbs) of crocodilians are reportedly characterized by unique mechanisms of allosteric regulatory control, but there are conflicting reports regarding the importance of different effectors, such as chloride ions, organic phosphates, and CO2. Progress in understanding the unusual properties of crocodilian Hbs has also been hindered by a dearth of structural information. Here, we present the first comparative analysis of blood properties and Hb structure and function in a phylogenetically diverse set of crocodilian species. We examine mechanisms of allosteric regulation in the Hbs of 13 crocodilian species belonging to the families Crocodylidae and Alligatoridae. We also report new amino acid sequences for the α- and ß-globins of these taxa, which, in combination with structural analyses, provide insights into molecular mechanisms of allosteric regulation. All crocodilian Hbs exhibited a remarkably strong sensitivity to CO2, which would permit effective O2 unloading to tissues in response to an increase in metabolism during intense activity and diving. Although the Hbs of all crocodilians exhibit similar intrinsic O2-affinities, there is considerable variation in sensitivity to Cl- ions and ATP, which appears to be at least partly attributable to variation in the extent of NH2-terminal acetylation. Whereas chloride appears to be a potent allosteric effector of all crocodile Hbs, ATP has a strong, chloride-independent effect on Hb-O2 affinity only in caimans. Modeling suggests that allosteric ATP binding has a somewhat different structural basis in crocodilian and mammalian Hbs.

The Underlying Mechanism of HNO Production by the Myoglobin-Mediated Oxidation of Hydroxylamine.

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.

Kinase Activation by Small Conformational Changes.

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.

An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes.

Unraveling the structure of lectin-carbohydrate complexes is vital for understanding key biological recognition processes and development of glycomimetic drugs. Molecular Docking application to predict them is challenging due to their low affinity, hydrophilic nature and ligand conformational diversity. In the last decade several strategies, such as the inclusion of glycan conformation specific scoring functions or our developed solvent-site biased method, have improved carbohydrate docking performance but significant challenges remain, in particular, those related to receptor conformational diversity. In the present work we have analyzed conventional and solvent-site biased autodock4 performance concerning receptor conformational diversity as derived from different crystal structures (apo and holo), Molecular Dynamics snapshots and Homology-based models, for 14 different lectin-monosaccharide complexes. Our results show that both conventional and biased docking yield accurate lectin-monosaccharide complexes, starting from either apo or homology-based structures, even when only moderate (45%) sequence identity templates are available. An essential element for success is a proper combination of a middle-sized (10-100 structures) conformational ensemble, derived either from Molecular dynamics or multiple homology model building. Consistent with our previous works, results show that solvent-site biased methods improve overall performance, but that results are still highly system dependent. Finally, our results also show that docking can select the correct receptor structure within the ensemble, underscoring the relevance of joint evaluation of both ligand pose and receptor conformation.

Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening.

Virtual screening of large compound databases, looking for potential ligands of a target protein, is a major tool in computer-aided drug discovery. Throughout the years, different techniques such as similarity searching, pharmacophore matching, or molecular docking have been applied with the aim of finding hit compounds showing appreciable affinity. Molecular dynamics simulations in mixed solvents have been shown to identify hot spots relevant for protein-drug interaction, and implementations based on this knowledge were developed to improve pharmacophore matching of small molecules, binding free-energy estimations, and docking performance in terms of pose prediction. Here, we proved in a retrospective manner that cosolvent-derived pharmacophores from molecular dynamics (solvent sites) improve the performance of docking-based virtual screening campaigns. We applied a biased docking scheme based on solvent sites to nine relevant target proteins that have a set of known ligands or actives and compounds that are, presumably, nonbinders (decoys). Our results show improvement in virtual screening performance compared to traditional docking programs both at a global level, with up to 35% increase in areas under the receiver operating characteristic curve, and in early stages, with up to a 7-fold increase in enrichment factors at 1%. However, the improvement in pose prediction of actives was less profound. The presented application makes use of the AutoDock Bias method and is the only cosolvent-derived pharmacophore technique that employs its knowledge both in the ligand conformational search algorithm and the final affinity scoring for virtual screening purposes.

Structural and mechanistic comparison of the Cyclopropane Mycolic Acid Synthases (CMAS) protein family of Mycobacterium tuberculosis.

Tuberculosis (TB) is a chronic disease caused by the bacillus Mycobacterium tuberculosis(Mtb) and remains a leading cause of mortality worldwide. The bacteria has an external wall which protects it from being killed, and the enzymes involved in the biosynthesis of the cell wall components have been proposed as promising targets for future drug development efforts. Cyclopropane Mycolic Acid Synthases (CMAS) constitute a group of ten homologous enzymes which belong to the mycolic acid biosynthesis pathway. These enzymes have S-adenosyl-l-methionine (SAM) dependent methyltransferase activity with a peculiarity, each one of them has strong substrate selectivity and reaction specificity, being able to produce among other things cyclopropanes or methyl-alcohol groups from the lipid olefin group. How each CMAS processes its substrate and how the specificity and selectivity are encoded in the protein sequence and structure, is still unclear. In this work, by using a combination of modeling tools, including comparative modeling, docking, all-atom MD and QM/MM methodologies we studied in detail the reaction mechanism of cmaA2, mmaA4, and mmaA1 CMAS and described the molecular determinants that lead to different products. We have modeled the protein-substrate complex structure and determined the free energy pathway for the reaction. The combination of modeling tools at different levels of complexity allows having a complete picture of the CMAS structure-activity relationship.

Multiscale approach to the activation and phosphotransfer mechanism of CpxA histidine kinase reveals a tight coupling between conformational and chemical steps.

Sensor histidine kinases (SHKs) are an integral component of the molecular machinery that permits bacteria to adapt to widely changing environmental conditions. CpxA, an extensively studied SHK, is a multidomain homodimeric protein with each subunit consisting of a periplasmic sensor domain, a transmembrane domain, a signal-transducing HAMP domain, a dimerization and histidine phospho-acceptor sub-domain (DHp) and a catalytic and ATP-binding subdomain (CA). The key activation event involves the rearrangement of the HAMP-DHp helical core and translation of the CA towards the acceptor histidine, which presumably results in an autokinase-competent complex. In the present work we integrate coarse-grained, all-atom, and hybrid QM-MM computer simulations to probe the large-scale conformational reorganization that takes place from the inactive to the autokinase-competent state (conformational step), and evaluate its relation to the autokinase reaction itself (chemical step). Our results highlight a tight coupling between conformational and chemical steps, underscoring the advantage of CA walking along the DHp core, to favor a reactive tautomeric state of the phospho-acceptor histidine. The results not only represent an example of multiscale modelling, but also show how protein dynamics can promote catalysis.

Solvents to Fragments to Drugs: MD Applications in Drug Design.

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

HNO Is Produced by the Reaction of NO with Thiols.

Azanone (nitroxyl, HNO) is a highly reactive compound whose biological role is still a matter of debate. One possible route for its formation is NO reduction by biological reductants. These reactions have been historically discarded due to the negative redox potential for the NO,H+/HNO couple. However, the NO to HNO conversion mediated by vitamins C, E, and aromatic alcohols has been recently shown to be feasible from a chemical standpoint. Based on these precedents, we decided to study the reaction of NO with thiols as potential sources of HNO. Using two complementary approaches, trapping by a Mn porphyrin and an HNO electrochemical sensor, we found that under anaerobic conditions aliphatic and aromatic thiols (as well as selenols) are able to convert NO to HNO, albeit at different rates. Further mechanistic analysis using ab initio methods shows that the reaction between NO and the thiol produces a free radical adduct RSNOH•, which reacts with a second NO molecule to produce HNO and a nitrosothiol. The nitrosothiol intermediate reacts further with RSH to produce a second molecule of HNO and RSSR, as previously reported.

CG2AA: backmapping protein coarse-grained structures.

UNLABELLED: Coarse grain (CG) models allow long-scale simulations with a much lower computational cost than that of all-atom simulations. However, the absence of atomistic detail impedes the analysis of specific atomic interactions that are determinant in most interesting biomolecular processes. In order to study these phenomena, it is necessary to reconstruct the atomistic structure from the CG representation. This structure can be analyzed by itself or be used as an onset for atomistic molecular dynamics simulations. In this work, we present a computer program that accurately reconstructs the atomistic structure from a CG model for proteins, using a simple geometrical algorithm. AVAILABILITY AND IMPLEMENTATION: The software is free and available online at http://www.ic.fcen.uba.ar/cg2aa/cg2aa.py SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: lula@qi.fcen.uba.ar.

A quantitative model for oxygen uptake and release in a family of hemeproteins.

MOTIVATION: Hemeproteins have many diverse functions that largely depend on the rate at which they uptake or release small ligands, like oxygen. These proteins have been extensively studied using either simulations or experiments, albeit only qualitatively and one or two proteins at a time. RESULTS: We present a physical-chemical model, which uses data obtained exclusively from computer simulations, to describe the uptake and release of oxygen in a family of hemeproteins, called truncated hemoglobins (trHbs). Through a rigorous statistical analysis we demonstrate that our model successfully recaptures all the reported experimental oxygen association and dissociation kinetic rate constants, thus allowing us to establish the key factors that determine the rates at which these hemeproteins uptake and release oxygen. We found that internal tunnels as well as the distal site water molecules control ligand uptake, whereas oxygen stabilization by distal site residues controls ligand release. Because these rates largely determine the functions of these hemeproteins, these approaches will also be important tools in characterizing the trHbs members with unknown functions. CONTACT: lboechi@ic.fcen.uba.ar SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tyrosine oxidation and nitration in transmembrane peptides is connected to lipid peroxidation.

Tyrosine nitration is an oxidative post-translational modification that can occur in proteins associated to hydrophobic bio-structures such as membranes and lipoproteins. In this work, we have studied tyrosine nitration in membranes using a model system consisting of phosphatidylcholine liposomes with pre-incorporated tyrosine-containing 23 amino acid transmembrane peptides. Tyrosine residues were located at positions 4, 8 or 12 of the amino terminal, resulting in different depths in the bilayer. Tyrosine nitration was accomplished by exposure to peroxynitrite and a peroxyl radical donor or hemin in the presence of nitrite. In egg yolk phosphatidylcholine liposomes, nitration was highest for the peptide with tyrosine at position 8 and dramatically increased as a function of oxygen levels. Molecular dynamics studies support that the proximity of the tyrosine phenolic ring to the linoleic acid peroxyl radicals contributes to the efficiency of tyrosine oxidation. In turn, α-tocopherol inhibited both lipid peroxidation and tyrosine nitration. The mechanism of tyrosine nitration involves a "connecting reaction" by which lipid peroxyl radicals oxidize tyrosine to tyrosyl radical and was fully recapitulated by computer-assisted kinetic simulations. Altogether, this work underscores unique characteristics of the tyrosine oxidation and nitration process in lipid-rich milieu that is fueled via the lipid peroxidation process.

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family.

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends.