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Accurate predictions of ligand binding affinities would greatly accelerate the first stages of drug discovery campaigns. However, using highly accurate interatomic potentials based on quantum mechanics (QM) in free energy methods has been so far largely unfeasible due to their prohibitive computational cost. Here, we present an efficient method to compute QM free energies from simulations using cheap reference potentials, such as force fields (FFs). This task has traditionally been out of reach due to the slow convergence of computing the correction from the FF to the QM potential. To overcome this bottleneck, we generalize targeted free energy methods to employ multiple maps-implemented with normalizing flow neural networks (NNs)-that maximize the overlap between the distributions. Critically, the method requires neither a separate expensive training phase for the NNs nor samples from the QM potential. We further propose a one-epoch learning policy to efficiently avoid overfitting, and we combine our approach with enhanced sampling strategies to overcome the pervasive problem of poor convergence due to slow degrees of freedom. On the drug-like molecules in the HiPen dataset, the method accelerates the calculation of the free energy difference of switching from an FF to a DFTB3 potential by three orders of magnitude compared to standard free energy perturbation and by a factor of eight compared to previously published nonequilibrium calculations. Our results suggest that our method, in combination with efficient QM/MM calculations, may be used in lead optimization campaigns in drug discovery and to study protein-ligand molecular recognition processes.
Assuntos
Proteínas , Teoria Quântica , Termodinâmica , Ligantes , EntropiaRESUMO
α-Synuclein (α-syn) phosphorylation at serine 129 (pS129α-syn) is substantially increased in Lewy body disease, such as Parkinson's disease (PD) and dementia with Lewy bodies (DLB). However, the pathogenic relevance of pS129α-syn remains controversial, so we sought to identify when pS129 modification occurs during α-syn aggregation and its role in initiation, progression and cellular toxicity of disease. Using diverse aggregation assays, including real-time quaking-induced conversion (RT-QuIC) on brain homogenates from PD and DLB cases, we demonstrated that pS129α-syn inhibits α-syn fibril formation and seeded aggregation. We also identified lower seeding propensity of pS129α-syn in cultured cells and correspondingly attenuated cellular toxicity. To build upon these findings, we developed a monoclonal antibody (4B1) specifically recognizing nonphosphorylated S129α-syn (WTα-syn) and noted that S129 residue is more efficiently phosphorylated when the protein is aggregated. Using this antibody, we characterized the time-course of α-syn phosphorylation in organotypic mouse hippocampal cultures and mice injected with α-syn preformed fibrils, and we observed aggregation of nonphosphorylated α-syn followed by later pS129α-syn. Furthermore, in postmortem brain tissue from PD and DLB patients, we observed an inverse relationship between relative abundance of nonphosphorylated α-syn and disease duration. These findings suggest that pS129α-syn occurs subsequent to initial protein aggregation and apparently inhibits further aggregation. This could possibly imply a potential protective role for pS129α-syn, which has major implications for understanding the pathobiology of Lewy body disease and the continued use of reduced pS129α-syn as a measure of efficacy in clinical trials.
Assuntos
Amiloide , Doença por Corpos de Lewy , Doença de Parkinson , Agregação Patológica de Proteínas , alfa-Sinucleína , Amiloide/metabolismo , Humanos , Doença por Corpos de Lewy/genética , Doença por Corpos de Lewy/metabolismo , Doença de Parkinson/genética , Doença de Parkinson/metabolismo , Fosforilação , Agregados Proteicos , Agregação Patológica de Proteínas/genética , Agregação Patológica de Proteínas/metabolismo , Serina/metabolismo , alfa-Sinucleína/genética , alfa-Sinucleína/metabolismoRESUMO
Many homodimeric enzymes tune their functions by exploiting either negative or positive cooperativity between subunits. In the SARS-CoV-2 Main protease (Mpro) homodimer, the latter has been suggested by symmetry in most of the 500 reported protease/ligand complex structures solved by macromolecular crystallography (MX). Here we apply the latter to both covalent and noncovalent ligands in complex with Mpro. Strikingly, our experiments show that the occupation of both active sites of the dimer originates from an excess of ligands. Indeed, cocrystals obtained using a 1:1 ligand/protomer stoichiometry lead to single occupation only. The empty binding site exhibits a catalytically inactive geometry in solution, as suggested by molecular dynamics simulations. Thus, Mpro operates through negative cooperativity with the asymmetric activity of the catalytic sites. This allows it to function with a wide range of substrate concentrations, making it resistant to saturation and potentially difficult to shut down, all properties advantageous for the virus' adaptability and resistance.
Assuntos
COVID-19 , Humanos , SARS-CoV-2/metabolismo , Ligantes , Proteases 3C de Coronavírus/metabolismo , Simulação de Dinâmica Molecular , Inibidores de Proteases/química , Simulação de Acoplamento MolecularRESUMO
MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.
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Various single nucleotide polymorphisms (SNPs) in the oxytocin receptor (OXTR) gene have been associated with behavioral traits, autism spectrum disorder (ASD) and other diseases. The non-synonymous SNP rs4686302 results in the OXTR variant A218T and has been linked to core characteristics of ASD, trait empathy and preterm birth. However, the molecular and intracellular mechanisms underlying those associations are still elusive. Here, we uncovered the molecular and intracellular consequences of this mutation that may affect the psychological or behavioral outcome of oxytocin (OXT)-treatment regimens in clinical studies, and provide a mechanistic explanation for an altered receptor function. We created two monoclonal HEK293 cell lines, stably expressing either the wild-type or A218T OXTR. We detected an increased OXTR protein stability, accompanied by a shift in Ca2+ dynamics and reduced MAPK pathway activation in the A218T cells. Combined whole-genome and RNA sequencing analyses in OXT-treated cells revealed 7823 differentially regulated genes in A218T compared to wild-type cells, including 429 genes being associated with ASD. Furthermore, computational modeling provided a molecular basis for the observed change in OXTR stability suggesting that the OXTR mutation affects downstream events by altering receptor activation and signaling, in agreement with our in vitro results. In summary, our study provides the cellular mechanism that links the OXTR rs4686302 SNP with genetic dysregulations associated with aspects of ASD.
Assuntos
Transtorno do Espectro Autista , Nascimento Prematuro , Transtorno do Espectro Autista/tratamento farmacológico , Feminino , Células HEK293 , Humanos , Recém-Nascido , Ocitocina/metabolismo , Gravidez , Nascimento Prematuro/tratamento farmacológico , Receptores de Ocitocina/genética , Receptores de Ocitocina/metabolismo , Relação Estrutura-AtividadeRESUMO
Human NEET proteins contain two [2Fe-2S] iron-sulfur clusters, bound to three Cys residues and one His residue. They exist in two redox states. Recently, these proteins have revealed themselves as attractive drug targets for mitochondrial dysfunction-related diseases, such as type 2 diabetes, Wolfram syndrome 2, and cancers. Unfortunately, the lack of information and mechanistic understanding of ligands binding to the whole functional, cytoplasmatic domain has limited rational drug design approaches. Here, we use an enhanced sampling technique, volume-based metadynamics, recently developed by a team involving some of us, to predict the poses and affinity of the 2-benzamido-4-(1,2,3,4-tetrahydronaphthalen-2-yl)-thiophene-3-carboxylate ligand to the entire surface of the cytoplasmatic domain of the human NEET protein mitoNEET (mNT) in an aqueous solution. The calculations, based on the recently published X-ray structure of the complex, are consistent with the measured affinity. The calculated free energy landscape revealed that the ligand can bind in multiple sites and with poses other than the one found in the X-ray. This difference is likely to be caused by crystal packing effects that allow the ligand to interact with multiple adjacent NEET protein copies. Such extra contacts are of course absent in the solution; therefore, the X-ray pose is only transient in our calculations, where the binding free energy correlates with the number of contacts. We further evaluated how the reduction and protonation of the Fe-bound histidine, as well as temperature, can affect ligand binding. Both such modifications introduce the possibility for the ligand to bind in an area of the protein other than the one observed in the X-ray, with no or little impact on affinity. Overall, our study can provide insights on the molecular recognition mechanisms of ligand binding to mNT in different oxidative conditions, possibly helping rational drug design of NEET ligands.
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Diabetes Mellitus Tipo 2 , Proteínas Ferro-Enxofre , Neoplasias , Humanos , Proteínas Ferro-Enxofre/química , Ligantes , Proteínas Mitocondriais/metabolismo , OxirreduçãoRESUMO
We provide a molecular-level description of the thermodynamics and mechanistic aspects of drug permeation through the cell membrane. As a case study, we considered the antimalaria FDA approved drug chloroquine. Molecular dynamics simulations of the molecule (in its neutral and protonated form) were performed in the presence of different lipid bilayers, with the aim of uncovering key aspects of the permeation process, a fundamental step for the drug's action. Free energy values obtained by well-tempered metadynamics simulations suggest that the neutral form is the only permeating protomer, consistent with experimental data. H-bond interactions of the drug with water molecules and membrane headgroups play a crucial role for permeation. The presence of the transmembrane potential, investigated here for the first time in a drug permeation study, does not qualitatively affect these conclusions.
Assuntos
Bicamadas Lipídicas , Simulação de Dinâmica Molecular , Membrana Celular/metabolismo , Bicamadas Lipídicas/química , Água/química , Termodinâmica , Físico-QuímicaRESUMO
The α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) are neurotransmitter-activated cation channels ubiquitously expressed in vertebrate brains. The regulation of calcium flux through the channel pore by RNA-editing is linked to synaptic plasticity while excessive calcium influx poses a risk for neurodegeneration. Unfortunately, the molecular mechanisms underlying this key process are mostly unknown. Here, we investigated calcium conduction in calcium-permeable AMPAR using Molecular Dynamics (MD) simulations with recently introduced multisite force-field parameters for Ca2+. Our calculations are consistent with experiment and explain the distinct calcium permeability in different RNA-edited forms of GluA2. For one of the identified metal binding sites, multiscale Quantum Mechanics/Molecular Mechanics (QM/MM) simulations further validated the results from MD and revealed small but reproducible charge transfer between the metal ion and its first solvation shell. In addition, the ion occupancy derived from MD simulations independently reproduced the Ca2+ binding profile in an X-ray structure of an NaK channel mimicking the AMPAR selectivity filter. This integrated study comprising X-ray crystallography, multisite MD, and multiscale QM/MM simulations provides unprecedented insights into Ca2+ permeation mechanisms in AMPARs, and paves the way for studying other biological processes in which Ca2+ plays a pivotal role.
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Cálcio , Receptores de Glutamato , Cálcio/metabolismo , Receptores de Glutamato/química , Receptores de Glutamato/metabolismo , Canais Iônicos/metabolismo , Transdução de Sinais , Simulação de Dinâmica MolecularRESUMO
MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of the QM region. This can be a tedious procedure prone to human error, especially when dealing with large QM regions. Here, we present MiMiCPy, a user-friendly tool that automatizes the preparation of MiMiC input files. It is written in Python 3 with an object-oriented approach. The main subcommand PrepQM can be used to generate MiMiC inputs directly from the command line or through a PyMOL/VMD plugin for visually selecting the QM region. Many other subcommands are also provided for debugging and fixing MiMiC input files. MiMiCPy is designed with a modular structure that allows seamless extensions to new program formats depending on the requirements of MiMiC.
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Teoria Quântica , Software , Humanos , Simulação de Dinâmica MolecularRESUMO
The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of â¼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.
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Simulação de Dinâmica Molecular , Proteínas , Ligantes , Proteínas/química , Desenho de Fármacos , Descoberta de Drogas , Teoria QuânticaRESUMO
Chloroquine (CQ) is a first-choice drug against malaria and autoimmune diseases. It has been co-administered with zinc against SARS-CoV-2 and soon dismissed because of safety issues. The structural features of Zn-CQ complexes and the effect of CQ on zinc distribution in cells are poorly known. In this study, state-of-the-art computations combined with experiments were leveraged to solve the structural determinants of zinc-CQ interactions in solution and the solid state. NMR, ESI-MS, and X-ray absorption and diffraction methods were combined with ab initio molecular dynamics calculations to address the kinetic lability of this complex. Within the physiological pH range, CQ binds Zn2+ through the quinoline ring nitrogen, forming [Zn(CQH)Clx(H2O)3-x](3+)-x (x = 0, 1, 2, and 3) tetrahedral complexes. The Zn(CQH)Cl3 species is stable at neutral pH and at high chloride concentrations typical of the extracellular medium, but metal coordination is lost at a moderately low pH as in the lysosomal lumen. The pentacoordinate complex [Zn(CQH)(H2O)4]3+ may exist in the absence of chloride. This in vitro/in silico approach can be extended to other metal-targeting drugs and bioinorganic systems.
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COVID-19 , Complexos de Coordenação , Humanos , Cloroquina/farmacologia , Cloroquina/química , Simulação de Dinâmica Molecular , Zinco/química , Cloretos , Tratamento Farmacológico da COVID-19 , SARS-CoV-2 , MetaisRESUMO
Structure-based drug design protocols may encounter difficulties to investigate poses when the biomolecular targets do not exhibit typical binding pockets. In this study, by providing two concrete examples from our labs, we suggest that the combination of metadynamics free energy methods (validated against affinity measurements), along with experimental structural information (by X-ray crystallography and NMR), can help to identify the poses of ligands on protein surfaces. The simulation workflow proposed here was implemented in a widely used code, namely GROMACS, and it could straightforwardly be applied to various drug-design campaigns targeting ligands' binding to protein surfaces.
Assuntos
Desenho de Fármacos , Proteínas de Membrana , Simulação por Computador , Fenômenos Biofísicos , Ligantes , Ligação Proteica , Simulação de Dinâmica Molecular , Sítios de LigaçãoRESUMO
The RNA-binding protein human antigen R (HuR) regulates stability, translation, and nucleus-to-cytoplasm shuttling of its target mRNAs. This protein has been progressively recognized as a relevant therapeutic target for several pathologies, like cancer, neurodegeneration, as well as inflammation. Inhibitors of mRNA binding to HuR might thus be beneficial against a variety of diseases. Here, we present the rational identification of structurally novel HuR inhibitors. In particular, by combining chemoinformatic approaches, high-throughput virtual screening, and RNA-protein pulldown assays, we demonstrate that the 4-(2-(2,4,6-trioxotetrahydropyrimidin-5(2H)-ylidene)hydrazineyl)benzoate ligand exhibits a dose-dependent HuR inhibition effect in binding experiments. Importantly, the chemical scaffold is new with respect to the currently known HuR inhibitors, opening up a new avenue for the design of pharmaceutical agents targeting this important protein.
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Benzoatos , Bioensaio , Proteína Semelhante a ELAV 1 , Humanos , Núcleo Celular , Peso Molecular , Proteínas de Ligação a RNA/antagonistas & inibidores , Proteína Semelhante a ELAV 1/antagonistas & inibidoresRESUMO
The Chloride Channel (CLC) family includes proton-coupled chloride and fluoride transporters. Despite their similar protein architecture, the former exchange two chloride ions for each proton and are inhibited by fluoride, whereas the latter efficiently transport one fluoride in exchange for one proton. The combination of structural, mutagenesis, and functional experiments with molecular simulations has pinpointed several amino acid changes in the permeation pathway that capitalize on the different chemical properties of chloride and fluoride to fine-tune protein function. Here we summarize recent findings on fluoride inhibition and transport in the two prototypical members of the CLC family, the chloride/proton transporter from Escherichia coli (CLC-ec1) and the fluoride/proton transporter from Enterococcus casseliflavus (CLCF-eca).
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Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help design protein-protein interaction inhibitors for therapy. Unfortunately, current machine learning methods to predict hot spots, suffer from limitations caused by gross errors in the data matrices. Here, we present a novel data pre-processing pipeline that overcomes this problem by recovering a low rank matrix with reduced noise using Robust Principal Component Analysis. Application to existing databases shows the predictive power of the method.
Assuntos
Aprendizado de Máquina , Análise de Componente Principal , Mapeamento de Interação de Proteínas/estatística & dados numéricos , Proteínas/química , Sítios de Ligação , Biologia Computacional/métodos , Bases de Dados de Proteínas , Humanos , Modelos Moleculares , Ligação Proteica , Domínios e Motivos de Interação entre Proteínas , Mapeamento de Interação de Proteínas/métodos , Proteínas/metabolismo , Curva ROCRESUMO
The main protease from SARS-CoV-2 is a homodimer. Yet, a recent 0.1-ms-long molecular dynamics simulation performed by D. E. Shaw's research group shows that it readily undergoes a symmetry-breaking event on passing from the solid state to aqueous solution. As a result, the subunits present distinct conformations of the binding pocket. By analyzing this long simulation, we uncover a previously unrecognized role of water molecules in triggering the transition. Interestingly, each subunit presents a different collection of long-lived water molecules. Enhanced sampling simulations performed here, along with machine learning approaches, further establish that the transition to the asymmetric state is essentially irreversible.
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SARS-CoV-2/enzimologia , Proteínas da Matriz Viral/química , Água/química , COVID-19/patologia , COVID-19/virologia , Cristalografia por Raios X , Humanos , Ligação de Hidrogênio , Simulação de Dinâmica Molecular , Estrutura Quaternária de Proteína , Subunidades Proteicas/química , Subunidades Proteicas/metabolismo , SARS-CoV-2/isolamento & purificação , Proteínas da Matriz Viral/metabolismoRESUMO
The NEET proteins constitute a unique class of [2Fe-2S] proteins. The metal ions bind to three cysteines and one histidine. The proteins' clusters exist in two redox states; the oxidized protein (containing two FeIII ions) can transfer the cluster to apo-acceptor protein(s), while the reduced form (containing one ferrous ion) remains bound to the protein frame. Here, we perform in silico and in vitro studies on human NEET proteins in both reduced and oxidized forms. Quantum chemical calculations on all available human NEET proteins structures suggest that reducing the cluster weakens the Fe-NHis and Fe-SCys bonds, similar to what is seen in other Fe-S proteins (e.g., ferredoxin and Rieske protein). We further show that the extra electron in the [2Fe-2S]+ clusters of one of the NEET proteins (mNT) is localized on the His-bound iron ion, consistently with our previous spectroscopic studies. Kinetic measurements demonstrate that the mNT [2Fe-2S]+ is released only by an increase in temperature. Thus, the reduced state of human NEET proteins [2Fe-2S] cluster is kinetically inert. This previously unrecognized kinetic inertness of the reduced state, along with the reactivity of the oxidized state, is unique across all [2Fe-2S] proteins. Finally, using a coevolutionary analysis, along with molecular dynamics simulations, we provide insight on the observed allostery between the loop L2 and the cluster region. Specifically, we show that W75, R76, K78, K79, F82 and G85 in the latter region share similar allosteric characteristics in both redox states.
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Compostos Férricos , Proteínas Ferro-Enxofre , Ferredoxinas/metabolismo , Humanos , Ferro/metabolismo , Proteínas Ferro-Enxofre/metabolismo , OxirreduçãoRESUMO
Aberrant RNA-protein complexes are formed in a variety of diseases. Identifying the ligands that interfere with their formation is a valuable therapeutic strategy. Molecular simulation, validated against experimental data, has recently emerged as a powerful tool to predict both the pose and energetics of such ligands. Thus, the use of molecular simulation may provide insight into aberrant molecular interactions in diseases and, from a drug design perspective, may allow for the employment of less wet lab resources than traditional in vitro compound screening approaches. With regard to basic research questions, molecular simulation can support the understanding of the exact molecular interaction and binding mode. Here, we focus on examples targeting RNA-protein complexes in neurodegenerative diseases and viral infections. These examples illustrate that the strategy is rather general and could be applied to different pharmacologically relevant approaches. We close this study by outlining one of these approaches, namely the light-controllable association of small molecules with RNA, as an emerging approach in RNA-targeting therapy.
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Peptídeos/farmacologia , Proteínas de Ligação a RNA/metabolismo , RNA/metabolismo , Bibliotecas de Moléculas Pequenas/farmacologia , Desenho de Fármacos , Humanos , Ligantes , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Processos Fotoquímicos , Ligação Proteica/efeitos dos fármacos , RNA/química , Proteínas de Ligação a RNA/químicaRESUMO
The translocator protein (TSPO) is a 18kDa transmembrane protein, ubiquitously present in human mitochondria. It is overexpressed in tumor cells and at the sites of neuroinflammation, thus representing an important biomarker, as well as a promising drug target. In mammalian TSPO, there are cholesterol-binding motifs, as well as a binding cavity able to accommodate different chemical compounds. Given the lack of structural information for the human protein, we built a model of human (h) TSPO in the apo state and in complex with PK11195, a molecule routinely used in positron emission tomography (PET) for imaging of neuroinflammatory sites. To better understand the interactions of PK11195 and cholesterol with this pharmacologically relevant protein, we ran molecular dynamics simulations of the apo and holo proteins embedded in a model membrane. We found that: (i) PK11195 stabilizes hTSPO structural fold; (ii) PK11195 might enter in the binding site through transmembrane helices I and II of hTSPO; (iii) PK11195 reduces the frequency of cholesterol binding to the lower, N-terminal part of hTSPO in the inner membrane leaflet, while this impact is less pronounced for the upper, C-terminal part in the outer membrane leaflet, where the ligand binding site is located; (iv) very interestingly, cholesterol most frequently binds simultaneously to the so-called CRAC and CARC regions in TM V in the free form (residues L150-X-Y152-X(3)-R156 and R135-X(2)-Y138-X(2)-L141, respectively). However, when the protein is in complex with PK11195, cholesterol binds equally frequently to the CRAC-resembling motif that we observed in TM I (residues L17-X(2)-F20-X(3)-R24) and to CRAC in TM V. We expect that the CRAC-like motif in TM I will be of interest in future experimental investigations. Thus, our MD simulations provide insight into the structural features of hTSPO and the previously unknown interplay between PK11195 and cholesterol interactions with this pharmacologically relevant protein.
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Colesterol/química , Isoquinolinas/química , Estrutura Secundária de Proteína , Receptores de GABA/ultraestrutura , Sítios de Ligação/genética , Transporte Biológico/genética , Humanos , Ligantes , Mitocôndrias/genética , Mitocôndrias/ultraestrutura , Modelos Moleculares , Simulação de Dinâmica Molecular , Ligação Proteica/genética , Domínios Proteicos/genética , Dobramento de Proteína , Receptores de GABA/químicaRESUMO
CLC channels and transporters conduct or transport various kinds of anions, with the exception of fluoride, which acts as an effective inhibitor. Here, we performed sub-nanosecond DFT-based QM/MM simulations of the E. coli anion/proton exchanger ClC-ec1 and observed that fluoride binds incoming protons within the selectivity filter, with excess protons shared with the gating glutamate E148. Depending on E148 conformation, the competition for the proton can involve either a direct F-/E148 interaction or the modulation of water molecules bridging the two anions. The direct interaction locks E148 in a conformation that does not allow for proton transport, and thus inhibits protein function.