Genome sequencing and analysis of black flounder (Paralichthys orbignyanus) reveals new insights into Pleuronectiformes genomic size and structure.

Black flounder (Paralichthys orbignyanus, Pleuronectiformes) is a commercially significant marine fish with promising aquaculture potential in Argentina. Despite extensive studies on Black flounder aquaculture, its limited genetic information available hampers the crucial role genetics plays in the development of this activity. In this study, we first employed Illumina sequencing technology to sequence the entire genome of Black flounder. Utilizing two independent libraries-one from a female and another from a male-with 150 bp paired-end reads, a mean insert length of 350 bp, and over 35 X-fold coverage, we achieved assemblies resulting in a genome size of ~ 538 Mbp. Analysis of the assemblies revealed that more than 98% of the core genes were present, with more than 78% of them having more than 50% coverage. This indicates a somehow complete and accurate genome at the coding sequence level. This genome contains 25,231 protein-coding genes, 445 tRNAs, 3 rRNAs, and more than 1,500 non-coding RNAs of other types. Black flounder, along with pufferfishes, seahorses, pipefishes, and anabantid fish, displays a smaller genome compared to most other teleost groups. In vertebrates, the number of transposable elements (TEs) is often correlated with genome size. However, it remains unclear whether the sizes of introns and exons also play a role in determining genome size. Hence, to elucidate the potential factors contributing to this reduced genome size, we conducted a comparative genomic analysis between Black flounder and other teleost orders to determine if the small genomic size could be explained by repetitive elements or gene features, including the whole genome genes and introns sizes. We show that the smaller genome size of flounders can be attributed to several factors, including changes in the number of repetitive elements, and decreased gene size, particularly due to lower amount of very large and small introns. Thus, these components appear to be involved in the genome reduction in Black flounder. Despite these insights, the full implications and potential benefits of genome reduction in Black flounder for reproduction and aquaculture remain incompletely understood, necessitating further research.

Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.

Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.

Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021.

Latin America is one of the regions in which the COVID-19 pandemic has a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia, and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1,534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.

Spatial and Seasonal Variations in the Bacterial Community of an Anthropogenic Impacted Urban Stream.

Environmental changes and human activities can alter the structure and diversity of aquatic microbial communities. In this work, we analyzed the bacterial community dynamics of an urban stream to understand how these factors affect the composition of river microbial communities. Samples were taken from a stream situated in Buenos Aires, Argentina, which flows through residential, peri-urban horticultural, and industrial areas. For sampling, two stations were selected: one influenced by a series of industrial waste treatment plants and horticultural farms (PL), and the other influenced by residential areas (R). Microbial communities were analyzed by sequence analysis of 16S rRNA gene amplicons along an annual cycle. PL samples showed high nutrient content compared with R samples. The diversity and richness of the R site were more affected by seasonality than those of the PL site. At the amplicon sequence variants level, beta diversity analysis showed a differentiation between cool-season (fall and winter) and warm-season (spring and summer) samples, as well as between PL and R sites. This demonstrated that there is spatial and temporal heterogeneity in the composition of the bacterial community, which should be considered if a bioremediation strategy is applied. The taxonomic composition analysis also revealed a differential seasonal cycle of phototrophs and chemoheterotrophs between the sampling sites, as well as different taxa associated with each sampling site. This analysis, combined with a comparative analysis of global rivers, allowed us to determine the genera Arcobacter, Simplicispira, Vogesella, and Sphingomonas as potential bioindicators of anthropogenic disturbance.

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

INTRODUCTION: Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown. MATERIAL AND METHODS: We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina. RESULTS: We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination. DISCUSSION: Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

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.

Cosolvent Sites-Based Discovery of Mycobacterium Tuberculosis Protein Kinase G Inhibitors.

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.

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.

Pathway Driven Target Selection in Klebsiella pneumoniae: Insights Into Carbapenem Exposure.

Carbapenem-resistant Klebsiella pneumoniae (CR-KP) represents an emerging threat to public health. CR-KP infections result in elevated morbidity and mortality. This fact, coupled with their global dissemination and increasingly limited number of therapeutic options, highlights the urgency of novel antimicrobials. Innovative strategies linking genome-wide interrogation with multi-layered metabolic data integration can accelerate the early steps of drug development, particularly target selection. Using the BioCyc ontology, we generated and manually refined a metabolic network for a CR-KP, K. pneumoniae Kp13. Converted into a reaction graph, we conducted topological-based analyses in this network to prioritize pathways exhibiting druggable features and fragile metabolic points likely exploitable to develop novel antimicrobials. Our results point to the aptness of previously recognized pathways, such as lipopolysaccharide and peptidoglycan synthesis, and casts light on the possibility of targeting less explored cellular functions. These functions include the production of lipoate, trehalose, glycine betaine, and flavin, as well as the salvaging of methionine. Energy metabolism pathways emerged as attractive targets in the context of carbapenem exposure, targeted either alone or in conjunction with current therapeutic options. These results prompt further experimental investigation aimed at controlling this highly relevant pathogen.

Geobiology of Andean Microbial Ecosystems Discovered in Salar de Atacama, Chile.

The Salar de Atacama in the Chilean Central Andes harbors unique microbial ecosystems due to extreme environmental conditions, such as high altitude, low oxygen pressure, high solar radiation, and high salinity. Combining X-ray diffraction analyses, scanning electron microscopy and molecular diversity studies, we have characterized twenty previously unexplored Andean microbial ecosystems in eight different lakes and wetlands from the middle-east and south-east regions of this salt flat. The mats and microbialites studied are mainly formed by calcium carbonate (aragonite and calcite) and halite, whereas the endoevaporites are composed predominantly of gypsum and halite. The carbonate-rich mats and microbialites are dominated by Bacteroidetes and Proteobacteria phyla. Within the phylum Proteobacteria, the most abundant classes are Alphaproteobacteria, Gammaproteobacteria and Deltaproteobacteria. While in the phylum Bacteroidetes, the most abundant classes are Bacteroidia and Rhodothermia. Cyanobacteria, Chloroflexi, Planctomycetes, and Verrucomicrobia phyla are also well-represented in the majority of these systems. Gypsum endoevaporites, on the contrary, are dominated by Proteobacteria, Bacteroidetes, and Euryarchaeota phyla. The Cyanobacteria phylum is also abundant in these systems, but it is less represented in comparison to mats and microbialites. Regarding the eukaryotic taxa, diatoms are key structural components in most of the microbial ecosystems studied. The genera of diatoms identified were Achnanthes, Fallacia, Halamphora, Mastogloia, Navicula, Nitzschia, and Surirella. Normally, in the mats and microbialites, diatoms form nano-globular carbonate aggregates with filamentous cyanobacteria and other prokaryotic cells, suggesting their participation in the mineral precipitation process. This work expands our knowledge of the microbial ecosystems inhabiting the extreme environments from the Central Andes region, which is important to ensure their protection and conservation.

From Genome to Drugs: New Approaches in Antimicrobial Discovery.

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.

Five-year microevolution of a multidrug-resistant Mycobacterium tuberculosis strain within a patient with inadequate compliance to treatment.

BACKGROUND: Whole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution -the genetic variability of M. tuberculosis at short time scales- of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported. CASE PRESENTATION: In this work, we applied whole genome sequencing analysis for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium tuberculosis isolates obtained from a patient within 57-months of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patient, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy. CONCLUSIONS: This report highlights the relevance of whole-genome sequencing analysis in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.

Biased Docking for Protein-Ligand Pose Prediction.

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.

Six novel variants in the PKLR gene associated with pyruvate kinase deficiency in Argentinian patients.

BACKGROUND: Pyruvate kinase deficiency (PKD) is a rare recessive congenital hemolytic anemia caused by mutations in the PKLR gene. The disease shows a marked variability in clinical expression. We studied the molecular features of nine unrelated Argentinian patients with congenital hemolytic anemia associated with erythrocyte pyruvate kinase deficiency. DESIGN AND METHODS: Routine hematologic investigations were performed to rule out other causes of chronic hemolytic anemia. Sanger sequencing and in-sílico analysis were carried out to identify and characterize the genetics variants. RESULTS: Six different novel missense variants were detected among the 18 studied alleles: c.661 G > C (Asp221His), c.956 G > T (Gly319Val), c.1595 G > C (Arg532Pro), c.347 G > A (Arg116Gln), c.1232 G > T (Gly411Val), c.1021G > A (Gly341Ser). Structural implications of amino-acid substitutions were correlated with the clinical phenotypes seen in the probands. CONCLUSIONS: This is the first comprehensive report on molecular characterization of pyruvate kinase deficiency in Argentina and the second from South America that would contribute to our knowledge on the distribution and frequency of PKLR variants in our population but also offer new insights into the interpretation of the effect of PKLR variants and phenotype.

Oculocutaneous albinism type 1B associated with a functionally significant tyrosinase gene polymorphism detected with Whole Exome Sequencing.

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.

Development of an Improved Guanidine-Based Rac1 Inhibitor with in†vivo Activity against Non-Small Cell Lung Cancer.

The Rho GTPase Rac1 is involved in the control of cytoskeleton reorganization and other fundamental cellular functions. Aberrant activity of Rac1 and its regulators is common in human cancer. In particular, deregulated expression/activity of Rac GEFs, responsible for Rac1 activation, has been associated to a metastatic phenotype and drug resistance. Thus, the development of novel Rac1-GEF interaction inhibitors is a promising strategy for finding new preclinical candidates. Here, we studied structure-activity relationships within a new family of N,N'-disubstituted guanidine as Rac1 inhibitors. We found that compound 1D-142, presents superior antiproliferative activity in human cancer cell lines and higher potency as Rac1-GEF interaction inhibitor in vitro than parental compounds. In addition, 1D-142 reduces Rac1-mediated TNFα-induced NF-κB nuclear translocation during cell proliferation and migration in NSCLC. Notably, 1D-142 allowed us to show for the first time the application of a Rac1 inhibitor in a lung cancer animal model.

New one-pot synthesis of anti-tuberculosis compounds inspired on isoniazid.

A library of thirty N-substituted tosyl N'-acryl-hydrazones was prepared with p-toluenesulfonyl hydrazide, methyl propiolate and different aldehydes in a one-pot synthesis via an aza-Michael reaction. The scope of the reaction was studied, including aliphatic, isoprenylic, aromatic and carbocyclic aldehydes. The prepared collection was tested against Mycobacterium tuberculosis H37Rv. Nine analogs of the collection showed Minimum Inhibitory Concentration ≤10 µM, of which the most active members (MIC of 1.25 µM) were exclusively E isomers. In order to validate the mechanism of action of the most active acrylates, we tested their activity on a M. tuberculosis InhA over-expressing strain obtaining MIC that consistently doubled those obtained on the wild type strain. Additionally, the binding mode of those analogs on M. tuberculosis InhA was investigated by docking simulations. The results displayed a hydrogen bond interaction between the sulfonamide and Ile194 and the carbonyl of the methyl ester with Tyr 158 (both critical residues in the interaction with the fatty acyl chain substrate), where the main differences on the binding mode relays on the hydrophobicity of the nitrogen substituent. Additionally, chemoinformatic analysis was performed to evaluate in silico possible cytotoxicity risk and ADME-Tox profile. Based on their simple preparation and interesting antimycobacterial activity profile, the newly prepared aza-acrylates are promising candidates for antitubercular drug development.

A novel mutation in PSEN1 (p.Arg41Ser) in an Argentinian woman with early onset Parkinsonism.

INTRODUCTION: Mutations in presenilin-1 (PSEN1) account for the majority of cases of familial autosomal dominant early-onset Alzheimer's disease (AD) as well as in sporadic forms. Atypical presentations are reported including extrapyramidal signs. In the last years, a pleiotropic effect of some PSEN1 variants has been reported in Parkinson's disease (PD). OBJECTIVE: to report a new PSEN1 mutation characterized by early-onset Parkinsonism (EOPD) without dementia or classical AD biomarkers phenotype. PATIENT AND METHODS: An Argentinian 46 years old woman was diagnosed with EOPD at 35 years old with no family history of neurodegenerative disorders. Her medical history included iron deficiency and anemia since childhood. A brain MRI showed moderate frontal atrophy. 18FDG-PET and PiB-PET as well as CSF biomarkers were inconclusive for AD. Two neuropsychological examinations were compatible with a mild non amnestic cognitive impairment. Whole blood DNA was extracted and whole exome sequencing and analysis was performed. RESULTS AND CONCLUSION: A heterozygous novel missense PSEN1 mutation (position 14:73637540, A > T, pArg41Ser) was identified as a likely causative mutation in this patient. To the best of our knowledge, this case is the first PSEN1 mutation with a l-dopa responsive Parkinsonism lacking distinctive classical AD biomarkers. This case opens a new window to explore the pathophysiological link among PSEN1 and EOPDs and contributes to increase the phenotypes of PSEN1 variants.

Conformational and Reaction Dynamic Coupling in Histidine Kinases: Insights from Hybrid QM/MM Simulations.

Histidine kinases (HK) of bacterial two-component systems represent a hallmark of allosterism in proteins, being able to detect a signal through the sensor domain and transmit this information through the protein matrix to the kinase domain which, once active, autophosphorylates a specific histidine residue. Inactive-to-active transition results in a large conformational change that moves the kinase on top of the histidine. In the present work, we use several molecular simulation techniques (Molecular Dynamics, Hybrid QM/MM, and constant pH molecular dynamics) to study the activation and autophosphorylation reactions in L. plantarum WalK, a cis-acting HK. In agreement with previous results, we show that the chemical step requires tight coupling with the conformational step in order to maintain the histidine phosphoacceptor in the correct tautomeric state, with a reactive δ-nitrogen. During the conformational transition, the kinase domain is never released and walks along the HK helix axis, breaking and forming several conserved residue-based contacts. The phosphate transfer reaction is concerted in the transition state region and is catalyzed through the stabilization of the negative developing charge of transferring phosphate along the reaction.

Aromatic clusters in protein-protein and protein-drug complexes.

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.