MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search.

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.

Correction: Molecular modelling of the HCMV IL-10 protein isoforms and analysis of their interaction with the human IL-10 receptor.

[This corrects the article DOI: 10.1371/journal.pone.0277953.].

Molecular modelling of the HCMV IL-10 protein isoforms and analysis of their interaction with the human IL-10 receptor.

The human cytomegalovirus (HCMV) UL111A gene encodes several homologs of the cellular interleukin 10 (cIL-10). Alternative splicing in the UL111A region produces two relatively well-characterized transcripts designated cmvIL-10 (isoform A) and LAcmvIL-10 (isoform B). The cmvIL-10 protein is the best characterized, both structurally and functionally, and has many immunosuppressive activities similar to cIL-10, while LAcmvIL-10 has more restricted biological activities. Alternative splicing also results in five less studied UL111A transcripts encoding additional proteins homologous to cIL-10 (isoforms C to G). These transcripts were identified during productive HCMV infection of MRC-5 cells with the high passage laboratory adapted AD169 strain, and the structure and properties of the corresponding proteins are largely unknown. Moreover, it is unclear whether these protein isoforms are able to bind the cellular IL-10 receptor and induce signalling. In the present study, we investigated the expression spectrum of UL111A transcripts in fully permissive MRC-5 cells and semi permissive U251 cells infected with the low passage HCMV strain TB40E. We identified a new spliced transcript (H) expressed during productive infection. Using computational methods, we carried out molecular modelling studies on the three-dimensional structures of the HCMV IL-10 proteins encoded by the transcripts detected in our work (cmvIL-10 (A), LAcmvIL-10 (B), E, F and H) and on their interaction with the human IL-10 receptor (IL-10R1). The modelling predicts clear differences between the isoform structures. Furthermore, the in silico simulations (molecular dynamics simulation and normal-mode analyses) allowed us to evaluate regions that contain potential receptor binding sites in each isoform. The analyses demonstrate that the complexes between the isoforms and IL-10R1 present different types of molecular interactions and consequently different affinities and stabilities. The knowledge about structure and expression of specific viral IL-10 isoforms has implications for understanding of their properties and role in HCMV immune evasion and pathogenesis.

Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods.

Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.

Virtual screening and in vitro assays of novel hits as promising DPP-4 inhibitors.

Diabetes is a metabolic disorder that presents hyperglycemia and vascular complications due to the non-production of insulin or its inappropriate use by the body. One of the strategies to treat diabetes is the inhibition of dipeptidyl peptidase-4 (DPP-4) and it is interesting to conduct virtual screening studies to search for new inhibitors of the DPP-4 enzyme. This study involves a virtual screening using the crystallographic structure of DPP-4 and a compound subset from the ZINC database. To filter this compound subset, we used some physicochemical properties, positioning at the three DPP-4 binding sites, molecular interactions, and ADME-Tox properties. The conformations of ligands obtained from AutoDock Vina were analyzed using a consensus with other algorithms (AutoDock and GOLD). The compounds selected from virtual screening were submitted to biological assays using the "DPPIV-Glo™ protease assay". Cytotoxicity tests were also performed. One promising compound (ZINC1572309) established interactions with important residues at the binding site. The results of the ADME-Tox prediction for ZINC1572309 were compared with a reference drug (sitagliptin). The cytotoxicity of sitagliptin and ZINC1572309 were evaluated using the XTT short-term cytotoxic assay, including normal and tumor cell lines to observe the cellular response to inhibitor treatment at different genetic bases. Both compounds (ZINC1572309 and the reference drug - sitagliptin) also inhibited DPP-4 activity, suggesting interesting biological effects of the selected compound at non-cytotoxic concentrations. Therefore, from in silico and in vitro studies, a potential hit as DPP-4 inhibitor was discovered and it can be structurally optimized to achieve suitable activity and pharmacokinetic profiles.

Nifuroxazide as JAK2 inhibitor: A binding mode proposal and Hel cell proliferation assay.

Nifuroxazide has been employed as an anti-diarrheic agent since 1966, but in the last decade has brought to the research spotlight again due to its recently described antitumoral activity through the JAK2 inhibitory potential. Since 2008, more than 70 papers have been published about the issue and more are expected to the following years. Herein we discuss the findings of molecular modelling studies which were performed to elucidate the potential binding mode of this drug into the JAK2 ATP recognition site and also into the allosteric region near the catalytic site. Molecular modelling followed by dynamics simulations indicated the NFZ could bind at both sites, such as a Type II kinase inhibitor since residues from both ATP and modulatory site would exhibit contacts with the drug when in a stable complex. Synthesis of NFZ and its sulfur bioisosteric analogue GPQF-63 were performed and experimental assays against HEL cells indicate the potential of NFZ and, mainly of its analogue GPQF-63 in acting as inhibitors of cell growth. HEL-cells present the JAK2 V617F mutation which leads to an enhanced JAK/STAT pathway and they have never been tested by the NFZ activity before. A mechanistic approach was also performed and revealed that both compounds induce cell apoptosis.Taken together, both the theoretical and experimental approaches point out the N-acylhydrazones as good starting points in the search for JAK2 modulatory small molecules which could then, be studied as promising leads toward new alternatives to control the JAK-STAT pathway related pathologies. This is the first study, as far as we have known, to propose a potential binding mode for NFZ as well as reporting the activity of this drug against HEL cells, which are a usual cellular model to human erythroleukemia and other myeloproliferative diseases.

Structural modelling and thermostability of a serine protease inhibitor belonging to the Kunitz-BPTI family from the Rhipicephalus microplus tick.

rBmTI-A is a recombinant serine protease inhibitor that belongs to the Kunitz-BPTI family and that was cloned from Rhipicephalus microplus tick. rBmTI-A has inhibitory activities on bovine trypsin, human plasma kallikrein, human neutrophil elastase and plasmin with dissociation constants in nM range. It is characterized by two inhibitory domains and each domain presents six cysteines that form three disulfide bonds, which contribute to the high stability of its structure. Previous studies suggest that serine protease inhibitor rBmTI-A has a protective potential against pulmonary emphysema in mice and anti-inflammatory potential. Besides that, rBmTI-A presented a potent inhibitory activity against in vitro vessel formation. In this study, the tertiary structure of rBmTI-A was modeled. The structure stabilization was evaluated by molecular dynamics analysis. Circular dichroism spectroscopy data corroborated the secondary structure found by the homology modelling. Also, in circular dichroism data it was shown a thermostability of rBmTI-A until approximately 70 °C, corroborated by inhibitory assays toward trypsin.

Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods.

With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.

Unveiling functional motions based on point mutations in biased signaling systems: A normal mode study on nerve growth factor bound to TrkA.

Many receptors elicit signal transduction by activating multiple intracellular pathways. This transduction can be triggered by a non-specific ligand, which simultaneously activates all the signaling pathways of the receptors. However, the binding of one biased ligand preferentially trigger one pathway over another, in a process called biased signaling. The identification the functional motions related to each of these distinct pathways has a direct impact on the development of new effective and specific drugs. We show here how to detect specific functional motions by considering the case of the NGF/TrkA-Ig2 complex. NGF-mediated TrkA receptor activation is dependent on specific structural motions that trigger the neuronal growth, development, and survival of neurons in nervous system. The R221W mutation in the ngf gene impairs nociceptive signaling. We discuss how the large-scale structural effects of this mutation lead to the suppression of collective motions necessary to induce TrkA activation of nociceptive signaling. Our results suggest that subtle changes in the NGF interaction network due to the point mutation are sufficient to inhibit the motions of TrkA receptors putatively linked to nociception. The methodological approach presented in this article, based jointly on the normal mode analysis and the experimentally observed functional alterations due to point mutations provides an essential tool to reveal the structural changes and motions linked to the disease, which in turn could be necessary for a drug design study.

Integrated Protocol to Design Potential Inhibitors of Dipeptidyl Peptidase- 4 (DPP-4).

BACKGROUND: A strategy for the treatment of type II diabetes mellitus is the inhibition of the enzyme known as dipeptidyl peptidase-4 (DPP-4). AIMS: This study aims to investigate the main interactions between DPP-4 and a set of inhibitors, as well as proposing potential candidates to inhibit this enzyme. METHODS: We performed molecular docking studies followed by the construction and validation of CoMFA and CoMSIA models. The information provided from these models was used to aid in the search for new candidates to inhibit DPP-4 and the design of new bioactive ligands from structural modifications in the most active molecule of the studied series. RESULTS: We were able to propose a set of analogues with biological activity predicted by the CoMFA and CoMSIA models, suggesting that our protocol can be used to guide the design of new DPP-4 inhibitors as drug candidates to treat diabetes. CONCLUSION: Once the integration of the techniques mentioned in this article was effective, our strategy can be applied to design possible new DPP-4 inhibitors as candidates to treat diabetes.

Methyl divanillate: redox properties and binding affinity with albumin of an antioxidant and potential NADPH oxidase inhibitor.

Vanillic acid is a widely used food additive (flavouring agent, JECFA number: 959) with many reported beneficial biological effects. The same is true for its ester derivative (methyl vanillate, JECFA number: 159). Based on the increasing evidence that diapocynin, the dimer of apocynin (NADPH oxidase inhibitor), has some improved pharmacological properties compared to its monomer, here the dimer of methyl vanillate (MV), i.e., methyl divanillate (dimer of methyl vanillate, DMV) was synthesized and studied in the context of its redox properties and binding affinity with human serum albumin (HSA). We found that the antioxidant potency of DMV was significantly increased compared to MV. In this regard, the reduction of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical by DMV was 30-fold more effective compared to MV. Ferric ion reduction was 4-fold higher and peroxyl radical reduction was 2.7-fold higher. The interaction with HSA was significantly improved (Stern-Vomer constants, 3.8 × 105 mol-1 L and 2.3 × 104 mol-1 L, for DMV and MV, respectively). The complexation between DMV and HSA was also evidenced by induced circular dichroism (ICD) signal generation in the former due to its fixation in the asymmetric protein pocket. Density-functional calculations (TD-DFT) showed that the ICD spectrum was related to a DMV conformation bearing a dihedral angle of approximately -60°. Similar dihedral angles were obtained in the lowest and most populated DMV cluster poses obtained by molecular docking simulations. The computational studies and experimental displacement studies revealed that DMV binds preferentially at site I. In conclusion, besides being a powerful antioxidant, DMV is also a strong ligand of HSA. This is the first study on the chemical and biophysical properties of DMV, a compound with potential beneficial biological effects.

Interaction between 1-pyrenesulfonic acid and albumin: Moving inside the protein.

Due to the high sensitivity to alterations in microenvironment polarity of macromolecules, pyrene and its derivatives have long been applied in biosciences. Human serum albumin (HSA), besides its numerous physiological functions, is the main responsible by transport of endogenous and exogenous compounds in the circulatory system. Here, a comprehensive study was carry out to understand the interaction between HSA and the pyrene derivative 1-pyrenesulfonic acid (PMS), which showed a singular behaviour when bound to this protein. The complexation of PMS with HSA was studied by steady state, time-resolved and anisotropy fluorescence, induction of circular dichroism (ICD) and molecular docking. The fluorescence quenching of PMS by HSA was abnormal, being stronger at lower concentration of the quencher. Similar behaviour was obtained by measuring the ICD signal and fluorescence lifetime of PMS complexed in HSA. The displacement of PMS by site-specific drugs showed that this probe occupied both sites, but with higher affinity for site II. The movement of PMS between these main binding sites was responsible by the abnormal effect. Using the holo (PDB: ID 1A06) and apo (PDB: ID 1E7A) HSA structures, the experimental results were corroborated by molecular docking simulation. The abnormal spectroscopic behaviour of PMS is related to its binding in different regions in the protein. The movement of PMS into the protein can be traced by alteration in the spectroscopic signals. These findings bring a new point of view about the use of fluorescence quenching to characterize the interaction between albumin and ligands.

UDP-glucuronosyltransferases: Structure, Function and Drug Design Studies.

UDP-glucuronosyltransferases (UGTs) are important phase II metabolic enzymes responsible for approximately 40-70% of endo and xenobiotic reactions. It catalyzes the transfer of glucuronic acid to lipophilic substrates, converting them into hydrophilic compounds that are excreted. There are 22 active human UGTs that belong to 4 families. This review focuses on human UGTs, highlighting the most current issues in order to connect all information available and allowing a discussion on the challenges already solved and those in which we need to move forward. Although, several UGTs studies have been conducted, the most recent ones addressing drug-drug interactions and polymorphism issues, there are still bottlenecks to overcome. Tridimensional structure is difficult to obtain due to overexpression, purification, and crystallization problems as well as the action mechanism - since overlapping of substrate specificities renders impasses on the identification of which isoform is responsible for a particular drug metabolic pathway. For this reason, bioinformatic tools are gaining more space, since it is a faster and less expensive reliable methodology that complements in vitro and in vivo researches. Combinations of quantum and molecular methods have become increasingly common, leading to the incorporation of enzyme features comprising their structure, dynamics and chemical reactions. Breakthroughs related to the enzyme, not only enable the discovery of new drugs essential for the treatment of various diseases, but also provide an improved action of the existing drugs.

Structural Dynamics of DPP-4 and Its Influence on the Projection of Bioactive Ligands.

Dipeptidyl peptidase-4 (DPP-4) is a target to treat type II diabetes mellitus. Therefore, it is important to understand the structural aspects of this enzyme and its interaction with drug candidates. This study involved molecular dynamics simulations, normal mode analysis, binding site detection and analysis of molecular interactions to understand the protein dynamics. We identified some DPP-4 functional motions contributing to the exposure of the binding sites and twist movements revealing how the two enzyme chains are interconnected in their bioactive form, which are defined as chains A (residues 40-767) and B (residues 40-767). By understanding the enzyme structure, its motions and the regions of its binding sites, it will be possible to contribute to the design of new DPP-4 inhibitors as drug candidates to treat diabetes.

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons.

While PTEN-induced kinase 1 (PINK1) is well characterized for its role in mitochondrial homeostasis, much less is known concerning its ability to prevent synaptodendritic degeneration. Using unbiased proteomic methods, we identified valosin-containing protein (VCP) as a major PINK1-interacting protein. RNAi studies demonstrate that both VCP and its cofactor NSFL1C/p47 are necessary for the ability of PINK1 to increase dendritic complexity. Moreover, PINK1 regulates phosphorylation of p47, but not the VCP co-factor UFD1. Although neither VCP nor p47 interact directly with PKA, we found that PINK1 binds and phosphorylates the catalytic subunit of PKA at T197 [PKAcat(pT197)], a site known to activate the PKA holoenzyme. PKA in turn phosphorylates p47 at a novel site (S176) to regulate dendritic complexity. Given that PINK1 physically interacts with both the PKA holoenzyme and the VCP-p47 complex to promote dendritic arborization, we propose that PINK1 scaffolds a novel PINK1-VCP-PKA-p47 signaling pathway to orchestrate dendritogenesis in neurons. These findings highlight an important mechanism by which proteins genetically implicated in Parkinson's disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.