AMALPHI: A Machine Learning Platform for Predicting Drug-Induced PhospholIpidosis.

Drug-induced phospholipidosis (PLD) involves the accumulation of phospholipids in cells of multiple tissues, particularly within lysosomes, and it is associated with prolonged exposure to druglike compounds, predominantly cationic amphiphilic drugs (CADs). PLD affects a significant portion of drugs currently in development and has recently been proven to be responsible for confounding antiviral data during drug repurposing for SARS-CoV-2. In these scenarios, it has become crucial to identify potential safe drug candidates in advance and distinguish them from those that may lead to false in vitro antiviral activity. In this work, we developed a series of machine learning classifiers with the aim of predicting the PLD-inducing potential of drug candidates. The models were built on a high-quality chemical collection comprising 545 curated small molecules extracted from ChEMBL v30. The most effective model, obtained using the balanced random forest algorithm, achieved high performance, including an AUC value computed in validation as high as 0.90. The model was made freely available through a user-friendly web platform named AMALPHI (https://www.ba.ic.cnr.it/softwareic/amalphiportal/), which can represent a valuable tool for medicinal chemists interested in conducting an early evaluation of PLD inducer potential.

GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.

This study introduces a new de novo design algorithm called GENERA that combines the capabilities of a deep-learning algorithm for automated drug-like analogue design, called DeLA-Drug, with a genetic algorithm for generating molecules with desired target-oriented properties. Specifically, GENERA was applied to the angiotensin-converting enzyme 2 (ACE2) target, which is implicated in many pathological conditions, including COVID-19. The ability of GENERA to de novo design promising candidates for a specific target was assessed using two docking programs, PLANTS and GLIDE. A fitness function based on the Pareto dominance resulting from computed PLANTS and GLIDE scores was applied to demonstrate the algorithm's ability to perform multiobjective optimizations effectively. GENERA can quickly generate focused libraries that produce better scores compared to a starting set of known ACE-2 binders. This study is the first to utilize a DL-based algorithm designed for analogue generation as a mutational operator within a GA framework, representing an innovative approach to target-oriented de novo design.

hERG stereoselective modulation by mexiletine-derived ureas: Molecular docking study, synthesis, and biological evaluation.

Long QT syndrome (LQTS) is a disorder of cardiac electrophysiology resulting in life-threatening arrhythmias; nowadays, only a few drugs are available for the management of LQTS. Focusing our attention on LQT2, one of the most common subtypes of LQTS caused by mutations in the human ether-à-go-go-related gene (hERG), in the present work, the stereoselectivity of the recently discovered mexiletine-derived urea 8 was investigated on the hERG potassium channel. According to preliminary in silico predictions, in vitro studies revealed a stereoselective behavior, with the meso form showing the greatest hERG opening activity. In addition, functional studies on guinea pig isolated left atria, aorta, and ileum demonstrated that 8 does not present any cardiac or intestinal liability in our ex vivo studies. Due to its overall profile, (R,S)-8 paves the way for the design and development of a new series of compounds potentially useful in the treatment of both congenital and drug-induced forms of LQTS.

DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of similar-to-bioactive compounds. DeLA-Drug captures the syntax of SMILES strings of more than 1 million compounds belonging to the ChEMBL28 database and, by employing a new strategy called sampling with substitutions (SWS), generates molecules starting from a single user-defined query compound. Remarkably, the algorithm preserves druglikeness and synthetic accessibility of the known bioactive compounds present in the ChEMBL28 repository. The absence of any time-demanding fine-tuning procedure enables DeLA-Drug to perform a fast generation of focused libraries for further high-throughput screening and makes it a suitable tool for performing de novo design even in low-data regimes. To provide a concrete idea of its applicability, DeLA-Drug was applied to the cannabinoid receptor subtype 2 (CB2R), a known target involved in different pathological conditions such as cancer and neurodegeneration. DeLA-Drug, available as a free web platform (http://www.ba.ic.cnr.it/softwareic/deladrugportal/), can help medicinal chemists interested in generating analogues of compounds already available in their laboratories and, for this reason, good candidates for an easy and low-cost synthesis.

A Comparative Molecular Dynamics Study of Selected Point Mutations in the Shwachman-Bodian-Diamond Syndrome Protein SBDS.

The Shwachman-Diamond Syndrome (SDS) is an autosomal recessive disease whose majority of patients display mutations in a ribosome assembly protein named Shwachman-Bodian-Diamond Syndrome protein (SBDS). A specific therapy for treating this rare disease is missing, due to the lack of knowledge of the molecular mechanisms responsible for its pathogenesis. Starting from the observation that SBDS single-point mutations, localized in different domains of the proteins, are responsible for an SDS phenotype, we carried out the first comparative Molecular Dynamics simulations on three SBDS mutants, namely R19Q, R126T and I212T. The obtained 450-ns long trajectories were compared with those returned by both the open and closed forms of wild type SBDS and strongly indicated that two distinct conformations (open and closed) are both necessary for the proper SBDS function, in full agreement with recent experimental observations. Our study supports the hypothesis that the SBDS function is governed by an allosteric mechanism involving domains I and III and provides new insights into SDS pathogenesis, thus offering a possible starting point for a specific therapeutic option.

Radiosynthesis and characterization of [18F]BS224: a next-generation TSPO PET ligand insensitive to the rs6971 polymorphism.

PURPOSE: Translocator protein 18-kDa (TSPO) positron emission tomography (PET) is a valuable tool to detect neuroinflammed areas in a broad spectrum of neurodegenerative diseases. However, the clinical application of second-generation TSPO ligands as biomarkers is limited because of the presence of human rs6971 polymorphism that affects their binding. Here, we describe the ability of a new TSPO ligand, [18F]BS224, to identify abnormal TSPO expression in neuroinflammation independent of the rs6971 polymorphism. METHODS: An in vitro competitive inhibition assay of BS224 was conducted with [3H]PK 11195 using membrane proteins isolated from 293FT cells expressing TSPO-wild type (WT) or TSPO-mutant A147T (Mut), corresponding to a high-affinity binder (HAB) and low-affinity binder (LAB), respectively. Molecular docking was performed to investigate the interaction of BS224 with the binding sites of rat TSPO-WT and TSPO-Mut. We synthesized a new 18F-labeled imidazopyridine acetamide ([18F]BS224) using boronic acid pinacol ester 6 or iodotoluene tosylate precursor 7, respectively, via aromatic 18F-fluorination. Dynamic PET scanning was performed up to 90 min after the injection of [18F]BS224 to healthy mice, and PET imaging data were obtained to estimate its absorbed doses in organs. To evaluate in vivo TSPO-specific uptake of [18F]BS224, lipopolysaccharide (LPS)-induced inflammatory and ischemic stroke rat models were used. RESULTS: BS224 exhibited a high affinity (Ki = 0.51 nM) and selectivity for TSPO. The ratio of IC50 values of BS224 for LAB to that for HAB indicated that the TSPO binding affinity of BS224 has low binding sensitivity to the rs6971 polymorphism and it was comparable to that of PK 11195, which is not sensitive to the polymorphism. Docking simulations showed that the binding mode of BS224 is not affected by the A147T mutation and consequently supported the observed in vitro selectivity of [18F]BS224 regardless of polymorphisms. With optimal radiochemical yield (39 ± 6.8%, decay-corrected) and purity (> 99%), [18F]BS224 provided a clear visible image of the inflammatory lesion with a high signal-to-background ratio in both animal models (BPND = 1.43 ± 0.17 and 1.57 ± 0.37 in the LPS-induced inflammatory and ischemic stroke rat models, respectively) without skull uptake. CONCLUSION: Our results suggest that [18F]BS224 may be a promising TSPO ligand to gauge neuroinflammatory disease-related areas in a broad range of patients irrespective of the common rs6971 polymorphism.

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.

Drug-induced blockade of the human ether-à-go-go-related gene (hERG) channel is today considered the main cause of cardiotoxicity in postmarketing surveillance. Hence, several ligand-based approaches were developed in the last years and are currently employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates. Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support vector machines were applied to integrate docking scores and protein-ligand interaction fingerprints. A total of 396 models were trained and validated based on: (i) high-quality experimental bioactivity information returned by 8337 curated compounds extracted from ChEMBL (version 25) and (ii) structural predictor data. Molecular docking simulations were performed using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and two published homology models selected for comparison. Interestingly, some classifiers return performances comparable to ligand-based models in terms of area under the ROC curve (AUCMAX = 0.86 ± 0.01) and negative predictive values (NPVMAX = 0.81 ± 0.01), thus putting forward the herein proposed computational workflow as a valuable tool for predicting hERG-related cardiotoxicity without the limitations of ligand-based models, typically affected by low interpretability and a limited applicability domain. From a methodological point of view, our study represents the first example of a successful integration of docking scores and protein-ligand interaction fingerprints (IFs) through a support vector machine (SVM) LASSO regularized strategy. Finally, the study highlights the importance of using hERG structural models accounting for ligand-induced fit effects and allowed us to select the best-performing protein conformation (made available in the Supporting Information, SI) to be employed for a reliable structure-based prediction of hERG-related cardiotoxicity.

More Is Always Better Than One: The N-Terminal Domain of the Spike Protein as Another Emerging Target for Hampering the SARS-CoV-2 Attachment to Host Cells.

Although the approved vaccines are proving to be of utmost importance in containing the Coronavirus disease 2019 (COVID-19) threat, they will hardly be resolutive as new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, a single-stranded RNA virus) variants might be insensitive to the immune response they induce. In this scenario, developing an effective therapy is still a dire need. Different targets for therapeutic antibodies and diagnostics have been identified, among which the SARS-CoV-2 spike (S) glycoprotein, particularly its receptor-binding domain, has been defined as crucial. In this context, we aim to focus attention also on the role played by the S N-terminal domain (S1-NTD) in the virus attachment, already recognized as a valuable target for neutralizing antibodies, in particular, building on a cavity mapping indicating the presence of two druggable pockets and on the recent literature hypothesizing the presence of a ganglioside-binding domain. In this perspective, we aim at proposing S1-NTD as a putative target for designing small molecules hopefully able to hamper the SARS-CoV-2 attachment to host cells.

Silver (I) N-Heterocyclic Carbene Complexes: A Winning and Broad Spectrum of Antimicrobial Properties.

The evolution of antibacterial resistance has arisen as the main downside in fighting bacterial infections pushing researchers to develop novel, more potent and multimodal alternative drugs.Silver and its complexes have long been used as antimicrobial agents in medicine due to the lack of silver resistance and the effectiveness at low concentration as well as to their low toxicities compared to the most commonly used antibiotics. N-Heterocyclic Carbenes (NHCs) have been extensively employed to coordinate transition metals mainly for catalytic chemistry. However, more recently, NHC ligands have been applied as carrier molecules for metals in anticancer applications. In the present study we selected from literature two NHC-carbene based on acridinescaffoldand detailed nonclassicalpyrazole derived mono NHC-Ag neutral and bis NHC-Ag cationic complexes. Their inhibitor effect on bacterial strains Gram-negative and positivewas evaluated. Imidazolium NHC silver complex containing the acridine chromophore showed effectiveness at extremely low MIC values. Although pyrazole NHC silver complexes are less active than the acridine NHC-silver, they represent the first example of this class of compounds with antimicrobial properties. Moreover all complexesare not toxic and they show not significant activity againstmammalian cells (Hek lines) after 4 and 24 h. Based on our experimental evidence, we are confident that this promising class of complexes could represent a valuable starting point for developing candidates for the treatment of bacterial infections, delivering great effectiveness and avoiding the development of resistance mechanisms.

A New Approach for Drug Target and Bioactivity Prediction: The Multifingerprint Similarity Search Algorithm (MuSSeL).

We present MuSSeL, a multifingerprint similarity search algorithm, able to predict putative drug targets for a given query small molecule as well as to return a quantitative assessment of its bioactivity in terms of Ki or IC50 values. Predictions are automatically made exploiting a large collection of high quality experimental bioactivity data available from ChEMBL (version 22.1) combining, in a consensus-like approach, predictions resulting from a similarity search performed using 13 different fingerprint definitions. Importantly, the herein proposed algorithm is also effective in detecting and handling activity cliffs. A calibration set including small molecules present in the last updated version of ChEMBL (version 23) was employed to properly tune the algorithm parameters. Three randomly built external sets were instead challenged for model performances. The potential use of MuSSeL was also challenged by a prospective exercise for the prediction of five bioactive compounds taken from articles published in the Journal of Medicinal Chemistry just few months ago. The paper emphasizes the importance of implementing multifingerprint consensus strategies to increase the confidence in prediction of similarity search algorithms and provides a fast and easy-to-run tool for drug target and bioactivity prediction.

Accelerating Drug Discovery by Early Protein Drug Target Prediction Based on a Multi-Fingerprint Similarity Search.

In this continuing work, we have updated our recently proposed Multi-fingerprint Similarity Search algorithm (MuSSel) by enabling the generation of dominant ionized species at a physiological pH and the exploration of a larger data domain, which included more than half a million high-quality small molecules extracted from the latest release of ChEMBL (version 24.1, at the time of writing). Provided with a high biological assay confidence score, these selected compounds explored up to 2822 protein drug targets. To improve the data accuracy, samples marked as prodrugs or with equivocal biological annotations were not considered. Notably, MuSSel performances were overall improved by using an object-relational database management system based on PostgreSQL. In order to challenge the real effectiveness of MuSSel in predicting relevant therapeutic drug targets, we analyzed a pool of 36 external bioactive compounds published in the Journal of Medicinal Chemistry from October to December 2018. This study demonstrates that the use of highly curated chemical and biological experimental data on one side, and a powerful multi-fingerprint search algorithm on the other, can be of the utmost importance in addressing the fate of newly conceived small molecules, by strongly reducing the attrition of early phases of drug discovery programs.

A novel KCNA1 mutation in a patient with paroxysmal ataxia, myokymia, painful contractures and metabolic dysfunctions.

Episodic ataxia type 1 (EA1) is a human dominant neurological syndrome characterized by continuous myokymia, episodic attacks of ataxic gait and spastic contractions of skeletal muscles that can be triggered by emotional stress and fatigue. This rare disease is caused by missense mutations in the KCNA1 gene coding for the neuronal voltage gated potassium channel Kv1.1, which contributes to nerve cell excitability in the cerebellum, hippocampus, cortex and peripheral nervous system. We identified a novel KCNA1 mutation, E283K, in an Italian proband presenting with paroxysmal ataxia and myokymia aggravated by painful contractures and metabolic dysfunctions. The E283K mutation is located in the S3-S4 extracellular linker belonging to the voltage sensor domain of Kv channels. In order to test whether the E283K mutation affects Kv1.1 biophysical properties we transfected HEK293 cells with WT or mutant cDNAs alone or in a 1:1 combination, and recorded relative potassium currents in the whole-cell configuration of patch-clamp. Mutant E283K channels display voltage-dependent activation shifted by 10mV toward positive potentials and kinetics of activation slowed by ~2 fold compared to WT channels. Potassium currents resulting from heteromeric WT/E283K channels show voltage-dependent gating and kinetics of activation intermediate between WT and mutant homomeric channels. Based on homology modeling studies of the mutant E283K, we propose a molecular explanation for the reduced voltage sensitivity and slow channel opening. Overall, our results suggest that the replacement of a negatively charged residue with a positively charged lysine at position 283 in Kv1.1 causes a drop of potassium current that likely accounts for EA-1 symptoms in the heterozygous carrier.

Comparative molecular dynamics study of neuromyelitis optica-immunoglobulin G binding to aquaporin-4 extracellular domains.

Neuromyelitis optica (NMO) is an inflammatory demyelinating disease of the central nervous system in which most patients have serum autoantibodies (called NMO-IgG) that bind to astrocyte water channel aquaporin-4 (AQP4). A potential therapeutic strategy in NMO is to block the interaction of NMO-IgG with AQP4. Building on recent observation that some single-point and compound mutations of the AQP4 extracellular loop C prevent NMO-IgG binding, we carried out comparative Molecular Dynamics (MD) investigations on three AQP4 mutants, TP137-138AA, N153Q and V150G, whose 295-ns long trajectories were compared to that of wild type human AQP4. A robust conclusion of our modeling is that loop C mutations affect the conformation of neighboring extracellular loop A, thereby interfering with NMO-IgG binding. Analysis of individual mutations suggested specific hydrogen bonding and other molecular interactions involved in AQP4-IgG binding to AQP4.

Multidisciplinary study of a new ClC-1 mutation causing myotonia congenita: a paradigm to understand and treat ion channelopathies.

Myotonia congenita is an inherited disease that is characterized by impaired muscle relaxation after contraction caused by loss-of-function mutations in the skeletal muscle ClC-1 channel. We report a novel ClC-1 mutation, T335N, that is associated with a mild phenotype in 1 patient, located in the extracellular I-J loop. The purpose of this study was to provide a solid correlation between T335N dysfunction and clinical symptoms in the affected patient as well as to offer hints for drug development. Our multidisciplinary approach includes patch-clamp electrophysiology on T335N and ClC-1 wild-type channels expressed in tsA201 cells, Western blot and quantitative PCR analyses on muscle biopsies from patient and unaffected individuals, and molecular dynamics simulations using a homology model of the ClC-1 dimer. T335N channels display reduced chloride currents as a result of gating alterations rather than altered surface expression. Molecular dynamics simulations suggest that the I-J loop might be involved in conformational changes that occur at the dimer interface, thus affecting gating. Finally, the gene expression profile of T335N carrier showed a diverse expression of K+ channel genes, compared with control individuals, as potentially contributing to the phenotype. This experimental paradigm satisfactorily explained myotonia in the patient. Furthermore, it could be relevant to the study and therapy of any channelopathy.-Imbrici, P., Altamura, C., Camerino, G. M., Mangiatordi, G. F., Conte, E., Maggi, L., Brugnoni, R., Musaraj, K., Caloiero, R., Alberga, D., Marsano, R. M., Ricci, G., Siciliano, G., Nicolotti, O., Mora, M., Bernasconi, P., Desaphy, J.-F., Mantegazza, R., Camerino, D. C. Multidisciplinary study of a new ClC-1 mutation causing myotonia congenita: a paradigm to understand and treat ion channelopathies.

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

Challenging AQP4 druggability for NMO-IgG antibody binding using molecular dynamics and molecular interaction fields.

Neuromyelitis optica (NMO) is a multiple sclerosis-like immunopathology disease affecting optic nerves and the spinal cord. Its pathological hallmark is the deposition of a typical immunoglobulin, called NMO-IgG, against the water channel Aquaporin-4 (AQP4). Preventing NMO-IgG binding would represent a valuable molecular strategy for a focused NMO therapy. The recent observation that aspartate in position 69 (D69) is determinant for the formation of NMO-IgG epitopes prompted us to carry out intensive Molecular Dynamics (MD) studies on a number of single-point AQP4 mutants. Here, we report a domino effect originating from the point mutation at position 69: we find that the side chain of T62 is reoriented far from its expected position leaning on the lumen of the pore. More importantly, the strength of the H-bond interaction between L53 and T56, at the basis of the loop A, is substantially weakened. These events represent important pieces of a clear-cut mechanistic rationale behind the failure of the NMO-IgG binding, while the water channel function as well as the propensity to aggregate into OAPs remains unaltered. The molecular interaction fields (MIF)-based analysis of cavities complemented MD findings indicating a putative binding site comprising the same residues determining epitope reorganization. In this respect, docking studies unveiled an intriguing perspective to address the future design of small drug-like compounds against NMO. In agreement with recent experimental observations, the present study is the first computational attempt to elucidate NMO-IgG binding at the molecular level, as well as a first effort toward a less elusive AQP4 druggability.

Human Aquaporin-4 and Molecular Modeling: Historical Perspective and View to the Future.

Among the different aquaporins (AQPs), human aquaporin-4 (hAQP4) has attracted the greatest interest in recent years as a new promising therapeutic target. Such a membrane protein is, in fact, involved in a multiple sclerosis-like immunopathology called Neuromyelitis Optica (NMO) and in several disorders resulting from imbalanced water homeostasis such as deafness and cerebral edema. The gap of knowledge in its functioning and dynamics at the atomistic level of detail has hindered the development of rational strategies for designing hAQP4 modulators. The application, lately, of molecular modeling has proved able to fill this gap providing a breeding ground to rationally address compounds targeting hAQP4. In this review, we give an overview of the important advances obtained in this field through the application of Molecular Dynamics (MD) and other complementary modeling techniques. The case studies presented herein are discussed with the aim of providing important clues for computational chemists and biophysicists interested in this field and looking for new challenges.

Searching for Multi-Targeting Neurotherapeutics against Alzheimer's: Discovery of Potent AChE-MAO B Inhibitors through the Decoration of the 2H-Chromen-2-one Structural Motif.

The need for developing real disease-modifying drugs against neurodegenerative syndromes, particularly Alzheimer's disease (AD), shifted research towards reliable drug discovery strategies to unveil clinical candidates with higher therapeutic efficacy than single-targeting drugs. By following the multi-target approach, we designed and synthesized a novel class of dual acetylcholinesterase (AChE)-monoamine oxidase B (MAO-B) inhibitors through the decoration of the 2H-chromen-2-one skeleton. Compounds bearing a propargylamine moiety at position 3 displayed the highest in vitro inhibitory activities against MAO-B. Within this series, derivative 3h emerged as the most interesting hit compound, being a moderate AChE inhibitor (IC50 = 8.99 µM) and a potent and selective MAO-B inhibitor (IC50 = 2.8 nM). Preliminary studies in human neuroblastoma SH-SY5Y cell lines demonstrated its low cytotoxicity and disclosed a promising neuroprotective effect at low doses (0.1 µM) under oxidative stress conditions promoted by two mitochondrial toxins (oligomycin-A and rotenone). In a Madin-Darby canine kidney (MDCK)II-MDR1 cell-based transport study, Compound 3h was able to permeate the BBB-mimicking monolayer and did not result in a glycoprotein-p (P-gp) substrate, showing an efflux ratio = 0.96, close to that of diazepam.

Identification of a point mutation impairing the binding between aquaporin-4 and neuromyelitis optica autoantibodies.

Neuromyelitis optica (NMO) is characterized by the presence of pathogenic autoantibodies (NMO-IgGs) against supra-molecular assemblies of aquaporin-4 (AQP4), known as orthogonal array of particles (OAPs). NMO-IgGs have a polyclonal origin and recognize different conformational epitopes involving extracellular AQP4 loops A, C, and E. Here we hypothesize a pivotal role for AQP4 transmembrane regions (TMs) in epitope assembly. On the basis of multialignment analysis, mutagenesis, NMO-IgG binding, and cytotoxicity assay, we have disclosed the key role of aspartate 69 (Asp(69)) of TM2 for NMO-IgG epitope assembly. Mutation of Asp(69) to histidine severely impairs NMO-IgG binding for 85.7% of the NMO patient sera analyzed here. Although Blue Native-PAGE, total internal reflection fluorescence microscopy, and water transport assays indicate that the OAP Asp(69) mutant is similar in structure and function to the wild type, molecular dynamic simulations have revealed that the D(69)H mutation has the effect of altering the structural rearrangements of extracellular loop A. In conclusion, Asp(69) is crucial for the spatial control of loop A, the particular molecular conformation of which enables the assembly of NMO-IgG epitopes. These findings provide additional clues for new strategies for NMO treatment and a wealth of information to better approach NMO pathogenesis.

A new gating site in human aquaporin-4: Insights from molecular dynamics simulations.

Aquaporin-4 (AQP4) is the predominant water channel in different organs and tissues. An alteration of its physiological functioning is responsible for several disorders of water regulation and, thus, is considered an attractive target with a promising therapeutic and diagnostic potential. Molecular dynamics (MD) simulations performed on the AQP4 tetramer embedded in a bilayer of lipid molecules allowed us to analyze the role of spontaneous fluctuations occurring inside the pore. Following the approach by Hashido et al. [Hashido M, Kidera A, Ikeguchi M (2007) Biophys J 93: 373-385], our analysis on 200ns trajectory discloses three domains inside the pore as key elements for water permeation. Herein, we describe the gating mechanism associated with the well-known selectivity filter on the extracellular side of the pore and the crucial regulation ensured by the NPA motifs (asparagine, proline, alanine). Notably, on the cytoplasmic side, we find a putative gate formed by two residues, namely, a cysteine belonging to the loop D (C178) and a histidine from loop B (H95). We observed that the spontaneous reorientation of the imidazole ring of H95 acts as a molecular switch enabling H-bond interaction with C178. The occurrence of such local interaction seems to be responsible for the narrowing of the pore and thus of a remarkable decrease in water flux rate. Our results are in agreement with recent experimental observations and may represent a promising starting point to pave the way for the discovery of chemical modulators of AQP4 water permeability.