Understanding the Interactions of Ubiquitin-Specific Protease 7 with Its Substrates through Molecular Dynamics Simulations: Insights into the Role of Its C-Terminal Domains in Substrate Recognition.

Ubiquitin-specific protease 7 (USP7) is a deubiquitinase enzyme that plays a critical role in regulating various cellular processes by cleaving ubiquitin molecules from target proteins. The C-terminal loop (CTL) motif is a specific region at the C-terminal end of the USP7 enzyme. Recent experiments suggest that the CTL motif plays a role in USP7's catalytic activity by contributing to the enzyme's structural stability, substrate recognition, and catalytic efficiency. The objective of this work is to elucidate these roles through the utilization of computational methods for molecular simulations. For this, we conducted extensive molecular dynamics (MD) simulations to investigate the conformational dynamics and protein-protein interactions within the USP7 enzyme-substrate complex with the substrate consisting of the ubiquitin tagged with the fluorescent label rhodamine 110-gly (Ub-Rho). Our results demonstrate that the CTL motif plays a crucial role in stabilizing the Ubl domains' conformation and augmenting the stability of active conformations within the enzyme-substrate complex. Conversely, the absence of the CTL motif results in increased flexibility and variability in Ubl domains' motion, leading to a reduced percentage of active conformations. Furthermore, our analysis of protein-protein interactions highlights the significance of the CTL motif in anchoring the Ubl45 domains to the catalytic domain (CD), thereby facilitating stable interactions with the substrate. Overall, our findings provide valuable insights into the conformational dynamics and protein-protein interactions inherent in the USP7 enzyme-substrate complex. These insights shed light on some mechanistic details of USP7 concerning the substrate's recognition before its catalytic action.

Linking triphenylphosphonium cation to a bicyclic hydroquinone improves their antiplatelet effect via the regulation of mitochondrial function.

Platelets are the critical target for preventing and treating pathological thrombus formation. However, despite current antiplatelet therapy, cardiovascular mortality remains high, and cardiovascular events continue in prescribed patients. In this study, first results were obtained with ortho-carbonyl hydroquinones as antiplatelet agents; we found that linking triphenylphosphonium cation to a bicyclic ortho-carbonyl hydroquinone moiety by a short alkyl chain significantly improved their antiplatelet effect by affecting the mitochondrial functioning. The mechanism of action involves uncoupling OXPHOS, which leads to an increase in mitochondrial ROS production and a decrease in the mitochondrial membrane potential and OCR. This alteration disrupts the energy production by mitochondrial function necessary for the platelet activation process. These effects are responsive to the complete structure of the compounds and not to isolated parts of the compounds tested. The results obtained in this research can be used as the basis for developing new antiplatelet agents that target mitochondria.

Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking.

The papain-like protease (PLpro) found in coronaviruses that can be transmitted from animals to humans is a critical target in respiratory diseases linked to Severe Acute Respiratory Syndrome (SARS-CoV). Researchers have proposed designing PLpro inhibitors. In this study, a set of 89 compounds, including recently reported 2-phenylthiophenes with nanomolar inhibitory potency, were investigated as PLpro noncovalent inhibitors using advanced molecular modeling techniques. To develop the work with these inhibitors, multiple structures of the SARS-CoV-2 PLpro binding site were generated using a molecular sampling method. These structures were then clustered to select a group that represents the flexibility of the site. Subsequently, models of the protein-ligand complexes were created for the set of inhibitors within the chosen conformations. The quality of the complex models was assessed using LigRMSD software to verify similarities in the orientations of the congeneric series and interaction fingerprints to determine the recurrence of chemical interactions. With the multiple models constructed, a protocol was established to choose one per ligand, optimizing the correlation between the calculated docking energy values and the biological activities while incorporating the effect of the binding site's flexibility. A strong correlation (R2 = 0.922) was found when employing this flexible docking protocol.

Exploring the electronic and steric effects on the dimerization of intramolecular frustrated Lewis pairs: a comparison between aminoboranes and aminoalanes.

The dimerization of intramolecular aminoborane and aminoalane frustrated Lewis pairs was investigated using density functional theory. We systematically varied the substituents to gradually increase their bulkiness, including H, CH3, t-Bu, Ph, and Mes groups. Starting from the most stable conformer of the monomers, a frustrated Lewis pair or classic Lewis adduct, we studied the dimerization process for all systems, revealing significant variations in the Gibbs free energy. Dimerization was favored in four aminoboranes and six aminoalanes, depending on the specific combinations of substituents. Applying an energy decomposition analysis, we found that the preparation energy of the monomers and the non-orbital interactions between them are the primary contributors to the observed energetic differences, showing a clear linear relationship. Additionally, we analyzed the electronic effects by increasing the acidity of the Lewis acid, observing a shift toward endergonic and exergonic directions in aminoboranes and aminoalanes, respectively. This shift was attributed to the stabilization of a classic Lewis adduct. This study underscores three crucial factors influencing dimer formation: (i) substituent size, (ii) stabilization of the classic Lewis adduct conformation, and (iii) covalent radii of the Lewis centers. Understanding these factors is essential for designing FLPs and preventing unwanted dimerization that could affect their catalytic performance in H2 activation processes.

Multicomponent synthesis and photophysical study of novel α,ß-unsaturated carbonyl depsipeptides and peptoids.

Multicomponent reactions were performed to develop novel α,ß-unsaturated carbonyl depsipeptides and peptoids incorporating various chromophores such as cinnamic, coumarin, and quinolines. Thus, through the Passerini and Ugi multicomponent reactions (P-3CR and U-4CR), we obtained thirteen depsipeptides and peptoids in moderate to high yield following the established protocol and fundamentally varying the electron-rich carboxylic acid as reactants. UV/Vis spectroscopy was utilized to study the photophysical properties of the newly synthesized compounds. Differences between the carbonyl-substituted chromophores cause differences in electron delocalization that can be captured in the spectra. The near UV regions of all the compounds exhibited strong absorption bands. Compounds P2, P5, U2, U5, and U7 displayed absorption bands in the range of 250-350 nm, absorbing radiation in this broad region of the electromagnetic spectrum. A photostability study for U5 showed that its molecular structure does not change after exposure to UV radiation. Fluorescence analysis showed an incipient emission of U5, while U6 showed blue fluorescence under UV radiation. The photophysical properties and electronic structure were also determined by TD-DFT theoretical study.

Computational study of the binding orientation and affinity of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-1 considering the protein flexibility by using molecular dynamics and cross-docking.

The papain-like protease (PLpro) from zoonotic coronaviruses (CoVs) has been identified as a target with an essential role in viral respiratory diseases caused by Severe Acute Respiratory Syndrome-associated coronaviruses (SARS-CoVs). The design of PLpro inhibitors has been proposed as an alternative to developing potential drugs against this disease. In this work, 67 naphthalene-derived compounds as noncovalent PLpro inhibitors were studied using molecular modeling methods. Structural characteristics of the bioactive conformations of these inhibitors and their interactions at the SARS-CoV-1 PLpro binding site were reported here in detail, taking into account the flexibility of the protein residues. Firstly, a molecular docking protocol was used to obtain the orientations of the inhibitors. After this, the orientations were compared, and the recurrent interactions between the PLpro residues and ligand chemical groups were described (with LigRMSD and interaction fingerprints methods). In addition, efforts were made to find correlations between docking energy values and experimentally determined binding affinities. For this, the PLpro was sampled by using Gaussian Accelerated Molecular Dynamics (GaMD), generating multiple conformations of the binding site. Diverse protein conformations were selected and a cross-docking experiment was performed, yielding models of the 67 naphthalene-derived compounds adopting different binding modes. Representative complexes for each ligand were selected to obtain the highest correlation between docking energies and activities. A good correlation (R 2 = 0.948) was found when this flexible docking protocol was performed.

Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients.

Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that mixed strain populations are common in the opportunistic pathogen P. aeruginosa. Crucially, resistance evolves rapidly in patients colonized by multiple strains through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by single strains due to selection for novel resistance mutations. However, strong trade-offs between resistance and growth rate occur in mixed strain populations, suggesting that within-host diversity can also drive the loss of resistance in the absence of antibiotic treatment. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment.

Assessing mitochondria-targeted acyl hydroquinones on the mitochondrial platelet function and cytotoxic activity: Role of the linker length.

INTRODUCTION: The use of triphenylphosphonium cation (TPP+) linked to phenolic compounds by alkyl chains has a significant relevance as a mitochondrial delivery strategy in biomedicine because it affects mitochondrial bioenergetics in models of noncommunicable diseases such as cancer and cardiovascular-related conditions. Studies indicate that a long alkyl chain (10-12 carbon) increases the mitochondrial accumulation of TPP+-linked drugs. In contrast, other studies show that these compounds are consistently toxic to micromolar concentrations (as observed in platelets). In the present study, we evaluated the in vitro effect of three series of triphenylphosphonium-linked acyl hydroquinones derivates on the metabolism and function of human platelets using 3-9 carbons for the alkyl linker. Those were assessed to determine the role of the length of the alkyl chain linker on platelet toxicity. METHODS: Human platelets were exposed in vitro to different concentrations (2-40 µM) of every compound; cellular viability, phosphatidylserine exposition, mitochondrial membrane potential (ΔΨm), intracellular calcium release, and intracellular ROS generation were assessed by flow cytometry. An in silico energetic profile was generated with Umbrella sampling molecular dynamics (MD). RESULTS AND CONCLUSIONS: There was an increase in cytotoxic activity directly related to the length of the acyl chain and lipophilicity, as seen by three techniques, and this was consistent with a decrease in ΔΨm. The in silico energetic profiles point out that the permeability of the mitochondrial membrane may be involved in the cytotoxicity of phosphonium salts. This information may be relevant for the design of new TPP+ -based drugs with a safe cardiovascular profile.

Gut to lung translocation and antibiotic mediated selection shape the dynamics of Pseudomonas aeruginosa in an ICU patient.

Bacteria have the potential to translocate between sites in the human body, but the dynamics and consequences of within-host bacterial migration remain poorly understood. Here we investigate the link between gut and lung Pseudomonas aeruginosa populations in an intensively sampled ICU patient using a combination of genomics, isolate phenotyping, host immunity profiling, and clinical data. Crucially, we show that lung colonization in the ICU was driven by the translocation of P. aeruginosa from the gut. Meropenem treatment for a suspected urinary tract infection selected for elevated resistance in both the gut and lung. However, resistance was driven by parallel evolution in the gut and lung coupled with organ specific selective pressures, and translocation had only a minor impact on AMR. These findings suggest that reducing intestinal colonization of Pseudomonas may be an effective way to prevent lung infections in critically ill patients.

JAZ is essential for ligand specificity of the COI1/JAZ co-receptor.

Jasmonates are phytohormones that regulate defense and developmental processes in land plants. Despite the chemical diversity of jasmonate ligands in different plant lineages, they are all perceived by COI1/JAZ co-receptor complexes, in which the hormone acts as a molecular glue between the COI1 F-box and a JAZ repressor. It has been shown that COI1 determines ligand specificity based on the receptor crystal structure and the identification of a single COI1 residue, which is responsible for the evolutionary switch in ligand binding. In this work, we show that JAZ proteins contribute to ligand specificity together with COI1. We propose that specific features of JAZ proteins, which are conserved in bryophytes and lycophytes, enable perception of dn-OPDA ligands regardless the size of the COI1 binding pocket. In vascular plant lineages beyond lycophytes, JAZ evolved to limit binding to JA-Ile, thus impeding dn-OPDA recognition by COI1.

MDSCAN: RMSD-based HDBSCAN clustering of long molecular dynamics.

MOTIVATION: The term clustering designates a comprehensive family of unsupervised learning methods allowing to group similar elements into sets called clusters. Geometrical clustering of molecular dynamics (MD) trajectories is a well-established analysis to gain insights into the conformational behavior of simulated systems. However, popular variants collapse when processing relatively long trajectories because of their quadratic memory or time complexity. From the arsenal of clustering algorithms, HDBSCAN stands out as a hierarchical density-based alternative that provides robust differentiation of intimately related elements from noise data. Although a very efficient implementation of this algorithm is available for programming-skilled users (HDBSCAN*), it cannot treat long trajectories under the de facto molecular similarity metric RMSD. RESULTS: Here, we propose MDSCAN, an HDBSCAN-inspired software specifically conceived for non-programmers users to perform memory-efficient RMSD-based clustering of long MD trajectories. Methodological improvements over the original version include the encoding of trajectories as a particular class of vantage-point tree (decreasing time complexity), and a dual-heap approach to construct a quasi-minimum spanning tree (reducing memory complexity). MDSCAN was able to process a trajectory of 1 million frames using the RMSD metric in about 21 h with <8 GB of RAM, a task that would have taken a similar time but more than 32 TB of RAM with the accelerated HDBSCAN* implementation generally used. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of MDSCAN are free and publicly available on GitHub (https://github.com/LQCT/MDScan.git) and as a PyPI package (https://pypi.org/project/mdscan/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A new era for the design of TRPV1 antagonists and agonists with the use of structural information and molecular docking of capsaicin-like compounds.

The design of TRPV1 antagonists and agonists has reached a new era since TRPV1 structures at near-atomic resolution are available. Today, the ligand-binding forms of several classical antagonists and agonists are known; therefore, the specific role of key TRPV1's residues in binding of ligands can be elucidated. It is possible to place the well-defined pharmacophore of TRPV1 ligands, conformed by head, neck, and tail groups, in the right pocket regions of TRPV1. It will allow a more thorough use of molecular modelling methods to conduct more effective rational drug design protocols. In this work, important points about the interactions between TRPV1 and capsaicin-like compounds are spelled out, based on the known pharmacophore of the ligands and the already available TRPV1 structures. These points must be addressed to generate reliable poses of novel candidates and should be considered during the design of novel TRPV1 antagonists and agonists.

Pre-existing chromosomal polymorphisms in pathogenic E. coli potentiate the evolution of resistance to a last-resort antibiotic.

Bacterial pathogens show high levels of chromosomal genetic diversity, but the influence of this diversity on the evolution of antibiotic resistance by plasmid acquisition remains unclear. Here, we address this problem in the context of colistin, a 'last line of defence' antibiotic. Using experimental evolution, we show that a plasmid carrying the MCR-1 colistin resistance gene dramatically increases the ability of Escherichia coli to evolve high-level colistin resistance by acquiring mutations in lpxC, an essential chromosomal gene involved in lipopolysaccharide biosynthesis. Crucially, lpxC mutations increase colistin resistance in the presence of the MCR-1 gene, but decrease the resistance of wild-type cells, revealing positive sign epistasis for antibiotic resistance between the chromosomal mutations and a mobile resistance gene. Analysis of public genomic datasets shows that lpxC polymorphisms are common in pathogenic E. coli, including those carrying MCR-1, highlighting the clinical relevance of this interaction. Importantly, lpxC diversity is high in pathogenic E. coli from regions with no history of MCR-1 acquisition, suggesting that pre-existing lpxC polymorphisms potentiated the evolution of high-level colistin resistance by MCR-1 acquisition. More broadly, these findings highlight the importance of standing genetic variation and plasmid/chromosomal interactions in the evolutionary dynamics of antibiotic resistance.

Localized pmrB hypermutation drives the evolution of colistin heteroresistance.

Colistin has emerged as an important last line of defense for the treatment of infections caused by antibiotic-resistant gram-negative pathogens, but colistin resistance remains poorly understood. Here, we investigate the responses of ≈1,000 populations of a multi-drug-resistant (MDR) strain of P. aeruginosa to a high dose of colistin. Colistin exposure causes rapid cell death, but some populations eventually recover due to the growth of sub-populations of heteroresistant cells. Heteroresistance is unstable, and resistance is rapidly lost under culture in colistin-free medium. The evolution of heteroresistance is primarily driven by selection for heteroresistance at two hotspot sites in the PmrAB regulatory system. Localized hypermutation of pmrB generates colistin resistance at 103-104 times the background resistance mutation rate (≈2 × 10-5 per cell division). PmrAB provides resistance to antimicrobial peptides that are involved in host immunity, suggesting that this pathogen may have evolved a highly mutable pmrB as an adaptation to host immunity.

RCDPeaks: memory-efficient density peaks clustering of long molecular dynamics.

MOTIVATION: Density Peaks is a widely spread clustering algorithm that has been previously applied to Molecular Dynamics (MD) simulations. Its conception of cluster centers as elements displaying both a high density of neighbors and a large distance to other elements of high density, particularly fits the nature of a geometrical converged MD simulation. Despite its theoretical convenience, implementations of Density Peaks carry a quadratic memory complexity that only permits the analysis of relatively short trajectories. RESULTS: Here, we describe DP+, an exact novel implementation of Density Peaks that drastically reduces the RAM consumption in comparison to the scarcely available alternatives designed for MD. Based on DP+, we developed RCDPeaks, a refined variant of the original Density Peaks algorithm. Through the use of DP+, RCDPeaks was able to cluster a one-million frames trajectory using less than 4.5 GB of RAM, a task that would have taken more than 2 TB and about 3× more time with the fastest and less memory-hunger alternative currently available. Other key features of RCDPeaks include the automatic selection of parameters, the screening of center candidates and the geometrical refining of returned clusters. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of RCDPeaks are free and publicly available on GitHub (https://github.com/LQCT/RCDPeaks.git). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bitopic Sigma 1 Receptor Modulators to Shed Light on Molecular Mechanisms Underpinning Ligand Binding and Receptor Oligomerization.

The sigma 1 receptor (S1R) is an enigmatic ligand-operated chaperone involved in many important biological processes, and its functions are not fully understood yet. Herein, we developed a novel series of bitopic S1R ligands as versatile tools to investigate binding processes, allosteric modulation, and the oligomerization mechanism. These molecules have been prepared in the enantiopure form and subjected to a preliminary biological evaluation, while in silico investigations helped to rationalize the results. Compound 7 emerged as the first bitopic S1R ligand endowed with low nanomolar affinity (Ki = 2.6 nM) reported thus far. Computational analyses suggested that 7 may stabilize the open conformation of the S1R by simultaneously binding the occluded primary binding site and a peripheral site on the cytosol-exposed surface. These findings pave the way to new S1R ligands with enhanced activity and/or selectivity, which could also be used as probes for the identification of a potential allosteric site.

BitQT: a graph-based approach to the quality threshold clustering of molecular dynamics.

MOTIVATION: Classical Molecular Dynamics (MD) is a standard computational approach to model time-dependent processes at the atomic level. The inherent sparsity of increasingly huge generated trajectories demands clustering algorithms to reduce other post-simulation analysis complexity. The Quality Threshold (QT) variant is an appealing one from the vast number of available clustering methods. It guarantees that all members of a particular cluster will maintain a collective similarity established by a user-defined threshold. Unfortunately, its high computational cost for processing big data limits its application in the molecular simulation field. RESULTS: In this work, we propose a methodological parallel between QT clustering and another well-known algorithm in the field of Graph Theory, the Maximum Clique Problem. Molecular trajectories are represented as graphs whose nodes designate conformations, while unweighted edges indicate mutual similarity between nodes. The use of a binary-encoded RMSD matrix coupled to the exploitation of bitwise operations to extract clusters significantly contributes to reaching a very affordable algorithm compared to the few implementations of QT for MD available in the literature. Our alternative provides results in good agreement with the exact one while strictly preserving the collective similarity of clusters. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of BitQT are free and publicly available on GitHub (https://github.com/LQCT/BitQT.git) and ReadTheDocs (https://bitqt.readthedocs.io/en/latest/), respectively. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational Modeling to Explain Why 5,5-Diarylpentadienamides are TRPV1 Antagonists.

Several years ago, the crystallographic structures of the transient receptor potential vanilloid 1 (TRPV1) in the presence of agonists and antagonists were reported, providing structural information about its chemical activation and inactivation. TRPV1's activation increases the transport of calcium and sodium ions, leading to the excitation of sensory neurons and the perception of pain. On the other hand, its antagonistic inactivation has been explored to design analgesic drugs. The interactions between the antagonists 5,5-diarylpentadienamides (DPDAs) and TRPV1 were studied here to explain why they inactivate TRPV1. The present work identified the structural features of TRPV1-DPDA complexes, starting with a consideration of the orientations of the ligands inside the TRPV1 binding site by using molecular docking. After this, a chemometrics analysis was performed (i) to compare the orientations of the antagonists (by using LigRMSD), (ii) to describe the recurrent interactions between the protein residues and ligand groups in the complexes (by using interaction fingerprints), and (iii) to describe the relationship between topological features of the ligands and their differential antagonistic activities (by using a quantitative structure-activity relationship (QSAR) with 2D autocorrelation descriptors). The interactions between the DPDA groups and the residues Y511, S512, T550, R557, and E570 (with a recognized role in the binding of classic ligands), and the occupancy of isoquinoline or 3-hydroxy-3,4-dihydroquinolin-2(1H)-one groups of the DPDAs in the vanilloid pocket of TRPV1 were clearly described. Based on the results, the structural features that explain why DPDAs inactivate TRPV1 were clearly exposed. These features can be considered for the design of novel TRPV1 antagonists.

Rapid evolution and host immunity drive the rise and fall of carbapenem resistance during an acute Pseudomonas aeruginosa infection.

It is well established that antibiotic treatment selects for resistance, but the dynamics of this process during infections are poorly understood. Here we map the responses of Pseudomonas aeruginosa to treatment in high definition during a lung infection of a single ICU patient. Host immunity and antibiotic therapy with meropenem suppressed P. aeruginosa, but a second wave of infection emerged due to the growth of oprD and wbpM meropenem resistant mutants that evolved in situ. Selection then led to a loss of resistance by decreasing the prevalence of low fitness oprD mutants, increasing the frequency of high fitness mutants lacking the MexAB-OprM efflux pump, and decreasing the copy number of a multidrug resistance plasmid. Ultimately, host immunity suppressed wbpM mutants with high meropenem resistance and fitness. Our study highlights how natural selection and host immunity interact to drive both the rapid rise, and fall, of resistance during infection.