KoBaMIN: a knowledge-based minimization web server for protein structure refinement

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Whole genome sequencing identifies novel mutations in malaria parasites resistant to artesunate (ATN) and to ATN + mefloquine combination

Introduction

The global evolution of resistance to Artemisinin-based Combination Therapies (ACTs) by malaria parasites, will severely undermine our ability to control this devastating disease.

Methods

Here, we have used whole genome sequencing to characterize the genetic variation in the experimentally evolved Plasmodium chabaudi parasite clone AS-ATNMF1, which is resistant to artesunate + mefloquine.

Results and discussion

Five novel single nucleotide polymorphisms (SNPs) were identified, one of which was a previously undescribed E738K mutation in a 26S proteasome subunit that was selected for under artesunate pressure (in AS-ATN) and retained in AS-ATNMF1. The wild type and mutated three-dimensional (3D) structure models and molecular dynamics simulations of the P. falciparum 26S proteasome subunit Rpn2 suggested that the E738K mutation could change the toroidal proteasome/cyclosome domain organization and change the recognition of ubiquitinated proteins. The mutation in the 26S proteasome subunit may therefore contribute to altering oxidation-dependent ubiquitination of the MDR-1 and/or K13 proteins and/or other targets, resulting in changes in protein turnover. In light of the alarming increase in resistance to artemisin derivatives and ACT partner drugs in natural parasite populations, our results shed new light on the biology of resistance and provide information on novel molecular markers of resistance that may be tested (and potentially validated) in the field.

Differential gene expression analysis of RAGE-S100A6 complex for target selection and the design of novel inhibitors for anticancer drug discovery

Receptor for advanced glycation end products (RAGE), a member of the immunoglobulin family, interactions with its ligands trigger downstream signaling and induce an inflammatory response linked to diabetes, inflammation, carcinogenesis, cardiovascular disease, and a variety of other human disorders. The interaction of RAGE and S100A6 has been associated with a variety of malignancies. For the control of RAGE-related illnesses, there is a great demand for more specialized drug options. To identify the most effective target for combating human malignancies associated with RAGE-S100A6 complex, we conducted single and differential gene expression analyses of S100A6 and RAGE, comparing normal and malignant tissues. Further, a structure-based virtual screening was conducted using the ZINC15 database. The chosen compounds were then subjected to a molecular docking investigation on the RAGE active site region, recognized by the various cancer-related RAGE ligands. An optimized RAGE structure was screened against a library of drug-like molecules. The screening results suggested that three promising compounds were presented as the top acceptable drug-like molecules with a high binding affinity at the RAGE V-domain catalytic region. We depicted that these compounds may be potential RAGE inhibitors and could be used to produce a successful medication against human cancer and other RAGE-related diseases based on their various assorted parameters, binding energy, hydrogen bonding, ADMET characteristics, etc. MD simulation on a time scale of 50 ns was used to test the stability of the RAGE-inhibitor complexes. Therefore, targeting RAGE and its ligands using these drug-like molecules may be an effective therapeutic approach.

Molecular insights into the differential efflux mechanism of Rv1634 protein, a multidrug transporter of major facilitator superfamily in Mycobacterium tuberculosis

Currently, multidrug-resistant tuberculosis (MDR-TB) is a public health crisis and a major health security threat globally. In Mycobacterium tuberculosis (Mtb), major facilitator superfamily (MFS) is the largest group of secondary active transporters. Along with the transport of their natural substrates, MFS proteins were involved in a drug efflux mechanism that ultimately lead to resistance against available anti-TB drugs in Mtb. In the present study, the three-dimensional structure model of an MFS protein, Rv1634, a probable multidrug transporter from Mtb, was generated using homology modeling. The protein structure model was found in inward-open conformation having 14 transmembrane helices. In addition, a central transport channel was deduced across the protein, and a single binding pocket was identified halfway through the central cavity by structural alignment with the homologous protein structures. Further, Rv1634 protein was studied based on the differential structural behavior of apo and ligand-bound forms. All the protein systems were inserted into a phospholipid bilayer to characterize the conformational dynamics of the protein using molecular dynamics (MD) simulations. Detailed analysis of the MD trajectories showed the diverse substrate specificity of the binding pocket for the antibiotics that caused differential movement in the ciprofloxacin and norfloxacin, to which Mtb strains have now become resistant. The expulsion of the drugs outside the bacterial cell occurs through the alternating-access mechanism of N and C-terminal domains, which is intriguing and essential to the understanding the drug resistance mechanism in pathogenic bacteria.

MMP inhibition attenuates hypertensive eccentric cardiac hypertrophy and dysfunction by preserving troponin I and dystrophin

PURPOSE

Cardiac transition from concentric (C-LVH) to eccentric left ventricle hypertrophy (E-LVH) is a maladaptive response of hypertension. Matrix metalloproteinases (MMPs), in particular MMP-2, may contribute to tissue remodeling by proteolyzing extra- and intracellular proteins. Troponin I and dystrophin are two potential targets of MMP-2 examined in this study and their proteolysis would impair cardiac contractile function. We hypothesized that MMP-2 contributes to the decrease in troponin I and dystrophin in the hypertensive heart and thereby controls the transition from C-LVH to E-LVH and cardiac dysfunction.

METHODS

Male Wistar rats were divided into sham or two kidney-1 clip (2K-1C) hypertensive groups and treated with water (vehicle) or doxycycline (MMP inhibitor, 15 mg/kg/day) by gavage from the tenth to the sixteenth week post-surgery. Tail-cuff plethysmography, echocardiography, gelatin zymography, confocal microscopy, western blot, mass spectrometry, in silico protein analysis and immunofluorescence were performed.

RESULTS

6 out of 23 2K-1C rats (26%) had E-LVH followed by reduced ejection fraction. The remaining had C-LVH with preserved cardiac function. Doxycycline prevented the transition from C-LVH to E-LVH. MMP activity is increased in C-LVH and E-LVH hearts which was inhibited by doxycycline. This effect was associated with an increase in troponin I cleavage products and a decline in dystrophin in the left ventricle of E-LVH rats, which was prevented by doxycycline.

CONCLUSION

Hypertension causes increased cardiac MMP-2 activity which proteolyzes troponin I and dystrophin, contributing to the transition from C-LVH to E-LVH and cardiac dysfunction.

Development of Stable Chimeric IL-15 for Trans-Presentation by the Antigen Presenting Cells

IL-15 is one of the important biologics considered for vaccine adjuvant and treatment of cancer. However, a short half-life and poor bioavailability limit its therapeutic potential. Herein, we have structured IL-15 into a chimeric protein to improve its half-life enabling greater bioavailability for longer periods. We have covalently linked IL-15 with IgG2 base to make the IL-15 a stable chimeric protein, which also increased its serum half-life by 40 fold. The dimeric structure of this kind of IgG based biologics has greater stability, resistance to proteolytic cleavage, and less frequent dosing schedule with minimum dosage for achieving the desired response compared to that of their monomeric forms. The structured chimeric IL-15 naturally forms a dimer, and retains its affinity for binding to its receptor, IL-15Rβ. Moreover, with the focused action of the structured chimeric IL-15, antigen-presenting cells (APC) would transpresent chimeric IL-15 along with antigen to the T cell, that will help the generation of quantitatively and qualitatively better antigen-specific memory T cells. In vitro and in vivo studies demonstrate the biological activity of chimeric IL-15 with respect to its ability to induce IL-15 signaling and modulating CD8⁺ T cell response in favor of memory generation. Thus, a longer half-life, dimeric nature, and anticipated focused transpresentation by APCs to the T cells will make chimeric IL-15 a super-agonist for memory CD8⁺ T cell responses.

Targeting FGL2, a molecular drug target for glioblastoma, with natural compounds through virtual screening method

Background: Fibroleukin-2 protein (FGL2) causes redevelopment of brain tumors. Inhibition of these proteins has shown to improve glioblastoma prognosis and treatment efficacy. Aim: The current study gathered recently exploited natural compounds that suppress glioblastoma proliferation in vitro, tested against FGL2 protein. Method: Twenty-five compounds were explored through a virtual screening platform. Results: Three natural compounds (betanine, hesperetin and ovatodiolide) hit the active site of FGL2. Furthermore, the influence of these compounds was also assessed using in silico gene expression, and ADMET tools showed downregulation of some genes, which caused rapid tumor development while possessing a moderate acute toxicity and pharmacokinetic profile. Conclusion: Our study presents three compounds that are good candidates for evaluation in FGL2 mutated glioblastoma animal models.

Computational Methods for the Elucidation of Protein Structure and Interactions

Biologists are increasingly aware of the importance of protein structure in revealing function. The computational tools now exist which allow researchers to model unknown proteins simply on the basis of their primary sequence. However, for the non-specialist bioinformatician, there is a dazzling array of terminology, acronyms, and competing computer software available for this process. This review is intended to highlight the key stages of computational protein structure prediction, as well as explain the reasons behind some of the procedures and list some established workarounds for common pitfalls. Thereafter follows a review of five one-stop servers for start-to-finish structure prediction.

Antifungal Drug Repurposing

Control of fungal pathogens is increasingly problematic due to the limited number of effective drugs available for antifungal therapy. Conventional antifungal drugs could also trigger human cytotoxicity associated with the kidneys and liver, including the generation of reactive oxygen species. Moreover, increased incidences of fungal resistance to the classes of azoles, such as fluconazole, itraconazole, voriconazole, or posaconazole, or echinocandins, including caspofungin, anidulafungin, or micafungin, have been documented. Of note, certain azole fungicides such as propiconazole or tebuconazole that are applied to agricultural fields have the same mechanism of antifungal action as clinical azole drugs. Such long-term application of azole fungicides to crop fields provides environmental selection pressure for the emergence of pan-azole-resistant fungal strains such as Aspergillus fumigatus having TR34/L98H mutations, specifically, a 34 bp insertion into the cytochrome P450 51A (CYP51A) gene promoter region and a leucine-to-histidine substitution at codon 98 of CYP51A. Altogether, the emerging resistance of pathogens to currently available antifungal drugs and insufficiency in the discovery of new therapeutics engender the urgent need for the development of new antifungals and/or alternative therapies for effective control of fungal pathogens. We discuss the current needs for the discovery of new clinical antifungal drugs and the recent drug repurposing endeavors as alternative methods for fungal pathogen control.

Myocardial MMP-2 contributes to SERCA2a proteolysis during cardiac ischaemia-reperfusion injury

AIMS

Matrix metalloproteinase-2 (MMP-2) is a zinc-dependent protease which contributes to cardiac contractile dysfunction when activated during myocardial ischaemia-reperfusion (IR) injury. MMP-2 is localized to several subcellular sites inside cardiac myocytes; however, its role in the sarcoplasmic reticulum (SR) is unknown. The Ca2+ ATPase SERCA2a, which pumps cytosolic Ca2+ into the SR to facilitate muscle relaxation, is degraded in cardiac IR injury; however, the protease responsible for this is unclear. We hypothesized that MMP-2 contributes to cardiac contractile dysfunction by proteolyzing SERCA2a, thereby impairing its activity in IR injury.

METHODS AND RESULTS

Isolated rat hearts were subjected to IR injury in the presence or absence of the selective MMP inhibitor ARP-100, or perfused aerobically as a control. Inhibition of MMP activity with ARP-100 significantly improved the recovery of cardiac mechanical function and prevented the increase of a 70 kDa SERCA2a degradation fragment following IR injury, although 110 kDa SERCA2a and phospholamban levels appeared unchanged. Electrophoresis of IR heart samples followed by LC-MS/MS confirmed the presence of a SERCA2a fragment of ∼70 kDa. MMP-2 activity co-purified with SR-enriched microsomes prepared from the isolated rat hearts. Endogenous SERCA2a in SR-enriched microsomes was proteolyzed to ∼70 kDa products when incubated in vitro with exogenous MMP-2. MMP-2 also cleaved purified porcine SERCA2a in vitro. SERCA activity in SR-enriched microsomes was decreased by IR injury; however, this was not prevented with ARP-100.

CONCLUSION

This study shows that MMP-2 activity is found in SR-enriched microsomes from heart muscle and that SERCA2a is proteolyzed by MMP-2. The cardioprotective actions of MMP inhibition in myocardial IR injury may include the prevention of SERCA2a degradation.

A Zinc-Dependent Metalloproteinase of Brucella abortus Is Required in the Intracellular Adaptation of Macrophages

Brucella abortus is a pathogen that survives in macrophages. Several virulence factors participate in this process, including the open reading frame (ORF) BAB1_0270 codifying for a zinc-dependent metalloproteinase (ZnMP). Here, its contribution in the intracellular adaptation of B. abortus was analyzed by infecting RAW264.7 macrophages with the mutant B. abortus Δ270 strain. Results showed that this ZnMP did not participated in either the adherence or the initial intracellular traffic of B. abortus in macrophages. Nevertheless, its deletion significantly increased the co-localization of B. abortus Δ270 with phagolysosomal cathepsin D and reduced its co-localization with calnexin present in endoplasmic reticulum (RE)-derived vesicles. Although B. abortus Δ270 showed an upregulated expression of genes involved in virulence (vjbR, hutC, bvrR, virB1), it was insufficient to reach a successful intracellular replication within macrophages. Furthermore, its attenuation favored in macrophages infected the production of high levels of cytokines (TNF-α and IL-6) and co-stimulatory proteins (CD80 and CD86), signals required in T cell activation. Finally, its deletion significantly reduced the ability of B. abortus Δ270 to adapt, grow and express several virulence factors under acidic conditions. Based on these results, and considering that this ZnMP has homology with ImmA/IrrE proteases, we discuss its role in the virulence of this pathogen, concluding that ZnMP is required in the intracellular adaptation of B. abortus 2308 during the infection of macrophages.

refineD: improved protein structure refinement using machine learning based restrained relaxation

MOTIVATION

Protein structure refinement aims to bring moderately accurate template-based protein models closer to the native state through conformational sampling. However, guiding the sampling towards the native state by effectively using restraints remains a major issue in structure refinement.

RESULTS

Here, we develop a machine learning based restrained relaxation protocol that uses deep discriminative learning based binary classifiers to predict multi-resolution probabilistic restraints from the starting structure and subsequently converts these restraints to be integrated into Rosetta all-atom energy function as additional scoring terms during structure refinement. We use four restraint resolutions as adopted in GDT-HA (0.5, 1, 2 and 4 Å), centered on the Cα atom of each residue that are predicted by ensemble of four deep discriminative classifiers trained using combinations of sequence and structure-derived features as well as several energy terms from Rosetta centroid scoring function. The proposed method, refineD, has been found to produce consistent and substantial structural refinement through the use of cumulative and non-cumulative restraints on 150 benchmarking targets. refineD outperforms unrestrained relaxation strategy or relaxation that is restrained to starting structures using the FastRelax application of Rosetta or atomic-level energy minimization based ModRefiner method as well as molecular dynamics (MD) simulation based FG-MD protocol. Furthermore, by adjusting restraint resolutions, the method addresses the tradeoff that exists between degree and consistency of refinement. These results demonstrate a promising new avenue for improving accuracy of template-based protein models by effectively guiding conformational sampling during structure refinement through the use of machine learning based restraints.

AVAILABILITY AND IMPLEMENTATION

http://watson.cse.eng.auburn.edu/refineD/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials

Small-molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations such as improper treatment of the interactions of essential components in the chemical environment of the binding pocket (e.g., cofactors, metal ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and the inability to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm, that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample biologically relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions, and cofactor interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind, Astex, and PINC proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions such that the statistical score of the best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best-docked pose with biological activity. CANDOCK along with all structures and scripts used for benchmarking is available at https://github.com/chopralab/candock_benchmark.

Molecular Modeling of the Interaction Between Stem Cell Peptide and Immune Receptor in Plants

Molecular docking enables comprehensive exploration of interactions between chemical moieties and proteins. Modeling and docking approaches are useful to determine the three-dimensional (3D) structure of experimentally uncrystallized proteins and subsequently their interactions with various inhibitors and activators or peptides. Here, we describe a protocol for carrying out molecular modeling and docking of stem cell peptide CLV3p on plant innate immune receptor FLS2.

An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan G protein-coupled receptors (GPCRs) involving human immunodeficiency virus (HIV) infection, colonic inflammation, and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability to inhibit cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) than in normal tissues. Among 33 cancer types, GPR15 expression was significantly positively correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), and lung adenocarcinoma (LUAD) and significantly negatively correlated with stomach adenocarcinoma (STAD). This study also revealed that commonly upregulated gene sets in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD, and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted structure-based virtual screening. The top eight hit compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provides novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

Structural and Functional Analysis of human lung cancer risk associated hOGG1 variant Ser326Cys in DNA repair gene by molecular dynamics simulation

Oxidative damaged DNA base lesions are repaired through human 8-oxoguanine DNA glycosylase gene (hOGG1) mediated pathways. A recent report based on the meta-analysis has suggested that the DNA Repair Gene hOGG1 variant Ser326Cys [3p26.2; allele S/C in nucleotide position αHelix2 Ser⇒Cys326] was associated with Lung Cancer risk in Caucasian population will alter the level Zhong et al., 2012. To the best of our knowledge, there has not been any such comprehensive in-silico investigation that validates the functional and structural impact of non-synonymous Lung Cancer Risk Associated Protein Domain (LCRAPD) mutation Ser326Cys (rs1052133) by molecular dynamics (MD) simulation approach following prediction of hOGG1 protein before and after the mutation. Further to the native and mutant protein structures, the amino acid residue and its secondary structure were observed through a solvent accessibility model for protein stability confirmation at the point of mutation. Taken together, this study suggests that the protein functional and structural studies could be a reasonable approach for investigating the impact of nsSNPs in future studies. In addition, 4295 patients samples incorporate with the analysis that genomic data types from cBioPortal. In the result, 4295 cases (91.5%) had alterations in all genes but the frequency of alterations in our targeted hOGG1 gene was shown with and without case alteration in the ratio (Logrank Test P-Value: 0.670) Kaplan-Meier by the number of patients at risk of the survival function.

Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein

Immunoinformatics is a new critical field with several tools and databases that conduct the eyesight of experimental selection and facilitate analysis of the great amount of immunologic data obtained from experimental researches and helps to design and introducing new hypothesis. Given these visages, immunoinformatics seems to be the way that develop and progress the immunological research. Bioinformatics methods and applications are successfully employed in vaccine informatics to assist different sites of the preclinical, clinical, and post-licensure vaccine enterprises. On the other hand, the progression of molecular biology and immunology caused epitope vaccines have become the focus of research on molecular vaccines. Moreover, reverse vaccinology could improve vaccine production and vaccination protocols by in silico prediction of protein-vaccine candidates from genome sequences. B- and T-cell immune epitopes could be predicted by immunoinformatics algorithms and computational methods to improve the vaccine design, protective immunity analysis, assessment of vaccine safety and efficacy, and immunization modeling. This review aims to discuss the power of computational approaches in vaccine design and their relevance to the development of effective vaccines. Furthermore, the various divisions of this field and available tools in each item are introduced and reviewed.

Natural Alkaloid Berberine Activity against Pseudomonas aeruginosa MexXY-Mediated Aminoglycoside Resistance: In Silico and in Vitro Studies

The multidrug efflux system MexXY-OprM, inside the resistance-nodulation-division family, is a major determinant of aminoglycoside resistance in Pseudomonas aeruginosa. In the fight aimed to identify potential efflux pump inhibitors among natural compounds, the alkaloid berberine emerged as a putative inhibitor of MexXY-OprM. In this work, we elucidated its interaction with the extrusor protein MexY and assessed its synergistic activity with aminoglycosides. In particular, we built an in silico model for the MexY protein in its trimeric association using both AcrB (E. coli) and MexB (P. aeruginosa) as 3D templates. This model has been stabilized in the bacterial cytoplasmic membrane using a molecular dynamics approach and used for ensemble docking to obtain the binding site mapping. Then, through dynamic docking, we assessed its binding affinity and its synergism with aminoglycosides focusing on tobramycin, which is widely used in the treatment of pulmonary infections. In vitro assays validated the data obtained: the results showed a 2-fold increase of the inhibitory activity and 2-4 log increase of the killing activity of the association berberine-tobramycin compared to those of tobramycin alone against 13/28 tested P. aeruginosa clinical isolates. From hemolytic assays, we preliminarily assessed berberine's low toxicity.

Computational Study of the Binding Modes of Diverse DPN Analogues on Estrogen Receptors (ER) and the Biological Evaluation of a New Potential Antiestrogenic Ligand

Estrogen (17β-estradiol) is essential for normal growth and differentiation in the mammary gland. In the last three decades, previous investigations have revealed that Estrogen Receptor Alpha (ERα) plays a critical role in breast cancer. More recently, observations regarding the widespread expression of ERβ-like proteins in normal and neoplastic mammary tissues have suggested that ERβ is also involved in the mentioned pathology. Design of new drugs both steroidal and nonsteroidal that target any of these receptors represents a promise to treat breast cancer although it remains a challenge due to the sequence similarity between their catalytic domains. In this work, we propose a new set of compounds that could effectively target the estrogen receptors ERα and ERβ. These ligands were designed based on the chemical structure of the ERβ-selective agonist Diarylpropionitrile (DPN). The designed ligands were submitted to in silico ADMET studies, yielding in a filtered list of ligands that showed better drug-like properties. Molecular dynamics simulations of both estrogen receptors and docking analysis were carried-out employing the designed compounds, from which two were chosen due to their promising characteristics retrieved from theoretical results (docking analysis or targeting receptor predictions). They were chemically synthetized and during the process, two precursor ligands were also obtained. These four ligands were subjected to biological studies from which it could be detected that compound mol60b dislplayed inhibitory activity and its ability to activate the transcription via an estrogenic mechanism of action was also determined. Interestinly, this observation can be related to theoretical binding free energy calculations, where the complex: ERβ-mol60b showed the highest energy ΔGbind value in comparison to others.

ReFOLD: a server for the refinement of 3D protein models guided by accurate quality estimates

ReFOLD is a novel hybrid refinement server with integrated high performance global and local Accuracy Self Estimates (ASEs). The server attempts to identify and to fix likely errors in user supplied 3D models of proteins via successive rounds of refinement. The server is unique in providing output for multiple alternative refined models in a way that allows users to quickly visualize the key residue locations, which are likely to have been improved. This is important, as global refinement of a full chain model may not always be possible, whereas local regions, or individual domains, can often be much improved. Thus, users may easily compare the specific regions of the alternative refined models in which they are most interested e.g. key interaction sites or domains. ReFOLD was used to generate hundreds of alternative refined models for the CASP12 experiment, boosting our group's performance in the main tertiary structure prediction category. Our successful refinement of initial server models combined with our built-in ASEs were instrumental to our second place ranking on Template Based Modeling (TBM) and Free Modeling (FM)/TBM targets. The ReFOLD server is freely available at: http://www.reading.ac.uk/bioinf/ReFOLD/.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php.

Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework

Paracoccidioidomycosis (PCM) is the most prevalent endemic mycosis in Latin America. The disease is caused by fungi of the genus Paracoccidioides and mainly affects low-income rural workers after inhalation of fungal conidia suspended in the air. The current arsenal of chemotherapeutic agents requires long-term administration protocols. In addition, chemotherapy is related to a significantly increased frequency of disease relapse, high toxicity, and incomplete elimination of the fungus. Due to the limitations of current anti-PCM drugs, we developed a computational drug repurposing-chemogenomics approach to identify approved drugs or drug candidates in clinical trials with anti-PCM activity. In contrast to the one-drug-one-target paradigm, our chemogenomics approach attempts to predict interactions between drugs, and Paracoccidioides protein targets. To achieve this goal, we designed a workflow with the following steps: (a) compilation and preparation of Paracoccidioides spp. genome data; (b) identification of orthologous proteins among the isolates; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Paracoccidioides essential targets using validated genes from Saccharomyces cerevisiae; (e) homology modeling and molecular docking studies; and (f) experimental validation of selected candidates. We prioritized 14 compounds. Two antineoplastic drug candidates (vistusertib and BGT-226) predicted to be inhibitors of phosphatidylinositol 3-kinase TOR2 showed antifungal activity at low micromolar concentrations (<10 μM). Four antifungal azole drugs (bifonazole, luliconazole, butoconazole, and sertaconazole) showed antifungal activity at low nanomolar concentrations, validating our methodology. The results suggest our strategy for predicting new anti-PCM drugs is useful. Finally, we could recommend hit-to-lead optimization studies to improve potency and selectivity, as well as pharmaceutical formulations to improve oral bioavailability of the antifungal azoles identified.

Toll-like receptor 6 expression, sequence variants, and their association with colorectal cancer risk

This is the first study to examine the potential correlation of the rs3796508 and rs5743810 SNPs of the TLR6 gene in patients with colorectal cancer (CRC) in a subset of the Saudi population. TLR6 gene expression was studied by real-time PCR assaysin 10 matching normal and cancer colon tissues. TLR6 expression at the protein level was determined by immunohistochemistry. A case-control search was conductedon 115 case patients and 102 controls. All samples were genotyped with the TaqMan assay for the TLR6 gene. Odds ratios and 95% confidence interval were computed from logistic regression models after adjusting for age, sex, and tumor localization. Our findings showed a decrease in TLR6 expression (p <0.001) in colon cancer tissues when compared to normal colon tissues. Global analysis revealed no significant association between the TLR6 rs3796508 and rs5743810 and CRC in this population. However, the Val/Met genotype of rs3796508 had a significantly higher frequency in the control group than in the cases for the male group (OR= 0.095, and p= 0.03385) or the volunteers aged more than 57 years OR= 0.152; and p= 0.04069, respectively). Two non-synonymous single nucleotide polymorphisms (SNP; S249P and V327M) were common in a few patients and were predicted as damaging by SIFT and Polyphen and were further analyzed for their protein stability and function using advanced bioinformatics tools. The results suggest that TLR6 rs3796508 has a crucial role as a protective factor against colorectal cancer in the older Saudi male population.

Methods for the Refinement of Protein Structure 3D Models

The refinement of predicted 3D protein models is crucial in bringing them closer towards experimental accuracy for further computational studies. Refinement approaches can be divided into two main stages: The sampling and scoring stages. Sampling strategies, such as the popular Molecular Dynamics (MD)-based protocols, aim to generate improved 3D models. However, generating 3D models that are closer to the native structure than the initial model remains challenging, as structural deviations from the native basin can be encountered due to force-field inaccuracies. Therefore, different restraint strategies have been applied in order to avoid deviations away from the native structure. For example, the accurate prediction of local errors and/or contacts in the initial models can be used to guide restraints. MD-based protocols, using physics-based force fields and smart restraints, have made significant progress towards a more consistent refinement of 3D models. The scoring stage, including energy functions and Model Quality Assessment Programs (MQAPs) are also used to discriminate near-native conformations from non-native conformations. Nevertheless, there are often very small differences among generated 3D models in refinement pipelines, which makes model discrimination and selection problematic. For this reason, the identification of the most native-like conformations remains a major challenge.

Modeling the Tertiary Structure of the Rift Valley Fever Virus L Protein

A tertiary structure governs, to a great extent, the biological activity of a protein in the living cell and is consequently a central focus of numerous studies aiming to shed light on cellular processes central to human health. Here, we aim to elucidate the structure of the Rift Valley fever virus (RVFV) L protein using a combination of in silico techniques. Due to its large size and multiple domains, elucidation of the tertiary structure of the L protein has so far challenged both dry and wet laboratories. In this work, we leverage complementary perspectives and tools from the computational-molecular-biology and bioinformatics domains for constructing, refining, and evaluating several atomistic structural models of the L protein that are physically realistic. All computed models have very flexible termini of about 200 amino acids each, and a high proportion of helical regions. Properties such as potential energy, radius of gyration, hydrodynamics radius, flexibility coefficient, and solvent-accessible surface are reported. Structural characterization of the L protein enables our laboratories to better understand viral replication and transcription via further studies of L protein-mediated protein-protein interactions. While results presented a focus on the RVFV L protein, the following workflow is a more general modeling protocol for discovering the tertiary structure of multidomain proteins consisting of thousands of amino acids.

Rational protein design of Bacillus sp. MN chitosanase for altered substrate binding and production of specific chitosan oligomers

Background

Partially acetylated chito-oligosaccharides (paCOS) have a variety of potential applications in different fields, but to harness their benefits, pure paCOS or well-defined paCOS mixtures are essential. For example, if one could produce fully acetylated (A₄) and fully deacetylated (D₄) tetramers in abundance, all possible variants of tetrameric paCOS could be generated reliably from them. A promising approach for generating defined paCOS is by enzymatic depolymerization of chitosan polymers using chitosanases, since these enzymes' subsite specificities directly influence the composition of the paCOS produced; however, enzymatic production of e.g. D₄ is challenging because the substrate is generally hydrolyzed further by most chitosanases. To overcome this, chitosanases could potentially be engineered so that upon hydrolyzing chitosan, they are unable to hydrolyze certain substrates, leaving well-defined oligomers intact in the hydrolysate.

Results

For this purpose, we performed rational protein engineering on the extensively studied GH 8 chitosanase CSN from Bacillus sp. MN. By specifically targeting residues with a predicted function in substrate binding, we created new muteins incapable of efficiently hydrolyzing the fully deacetylated tetramer D₄, and we were able to demonstrate efficient large-scale production of D₄ with an altered version of CSN. Furthermore, we were able to uncover differences in the substrate positioning and subsite specificities of the muteins, which result in altered paCOS mixtures produced from partially acetylated chitosan polymers, with possibly altered bioactivities.

Conclusion

The value of protein engineering as a tool for the more efficient production of pure oligomers and potentially bioactive paCOS mixtures was demonstrated by the results and the suitability of specific muteins for the large-scale production of strictly defined, pure paCOS in a batch process was shown using the example of D₄.

Structural and biochemical insight into mode of action and subsite specificity of a chitosan degrading enzyme from Bacillus spec. MN

Chitosans, partially de-N-acetylated derivatives of chitin, are multifunctional biopolymers. In nature, biological activities of partially acetylated chitosan polymers are mediated in part by their oligomeric breakdown products, which are generated in situ by the action of chitosanolytic enzymes. Understanding chitosanolytic enzymes, therefore, can lead to the production of chitosan oligomers with fully defined structures that may confer specific bioactivities. To address whether defined oligomer products can be produced via chitosanolytic enzymes, we here characterized a GH8 family chitosanase from Bacillus spec. MN, determining its mode of action and product profiles. We found that the enzyme has higher activity towards polymers with lower degree of acetylation. Oligomeric products were dominated by GlcN₃, GlcN₃GlcNAc₁, and GlcN₄GlcNAc₁. The product distribution from oligomers were GlcN₃ > GlcN₂. Modeling and simulations show that the binding site comprises subsites ranging from (-3) to (+3), and a putative (+4) subsite, with defined preferences for GlcN or GlcNAc at each subsite. Flexible loops at the binding site facilitate enzyme-substrate interactions and form a cleft at the active site which can open and close. The detailed insight gained here will help to engineer enzyme variants to produce tailored chitosan oligomers with defined structures that can then be used to probe their specific biological activities.

Identifying Protein Features Responsible for Improved Drug Repurposing Accuracies Using the CANDO Platform: Implications for Drug Design

Drug repurposing is a valuable tool for combating the slowing rates of novel therapeutic discovery. The Computational Analysis of Novel Drug Opportunities (CANDO) platform performs shotgun repurposing of 2030 indications/diseases using 3733 drugs/compounds to predict interactions with 46,784 proteins and relating them via proteomic interaction signatures. The accuracy is calculated by comparing interaction similarities of drugs approved for the same indications. We performed a unique subset analysis by breaking down the full protein library into smaller subsets and then recombining the best performing subsets into larger supersets. Up to 14% improvement in accuracy is seen upon benchmarking the supersets, representing a 100⁻1000-fold reduction in the number of proteins considered relative to the full library. Further analysis revealed that libraries comprised of proteins with more equitably diverse ligand interactions are important for describing compound behavior. Using one of these libraries to generate putative drug candidates against malaria, tuberculosis, and large cell carcinoma results in more drugs that could be validated in the biomedical literature compared to using those suggested by the full protein library. Our work elucidates the role of particular protein subsets and corresponding ligand interactions that play a role in drug repurposing, with implications for drug design and machine learning approaches to improve the CANDO platform.

Reoptimized UNRES Potential for Protein Model Quality Assessment

Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful.

Dissecting KMT2D missense mutations in Kabuki syndrome patients

Kabuki syndrome is a rare autosomal dominant condition characterized by facial features, various organs malformations, postnatal growth deficiency and intellectual disability. The discovery of frequent germline mutations in the histone methyltransferase KMT2D and the demethylase KDM6A revealed a causative role for histone modifiers in this disease. However, the role of missense mutations has remained unexplored. Here, we expanded the mutation spectrum of KMT2D and KDM6A in KS by identifying 37 new KMT2D sequence variants. Moreover, we functionally dissected 14 KMT2D missense variants, by investigating their impact on the protein enzymatic activity and the binding to members of the WRAD complex. We demonstrate impaired H3K4 methyltransferase activity in 9 of the 14 mutant alleles and show that this reduced activity is due in part to disruption of protein complex formation. These findings have relevant implications for diagnostic and counseling purposes in this disease.

Chikungunya virus: genomic microevolution in Eastern India and its in-silico epitope prediction

This is the first study reporting whole genome sequences of two CHIKV strains (KJ679577 and KJ679578) isolated from Eastern Indian patients sera during 2010-2011 outbreak, both of which were of ECSA genotype, but from different subgroups: Indian Ocean outbreak and ECSA subtypes. Furthermore, viral sequences were analyzed using different in-silico approaches to identify potential genetic variations that might have functional implications on various aspects of virus replication, viral protein functionality, immunogenicity and transmission. Epitope prediction analysis revealed 70.9% increase in number of MHC Class-II interacting epitopes of KJ679578 and 25-28% increase in Class-I interacting epitopes of KJ679577 and KJ679578 compared to that of EF027141 (CHIKV of Asian genotype circulating in India during 1973, after which CHIKV infection disappeared from India for three decades). CHIKV peptides DLAKLAFKRSSKYDLECAQIPVHMKSDA and KVVLCGDPKQCGFFNMMQMKYNYNHNI were predicted to interact with maximum number of HLA Class-I (68 and 76.5%, respectively) and Class-II (47 and 100%, respectively) alleles present within Indian population with allele frequency of > 0.1 and were also recognized as predicted B-cell epitopes with BCPred score between 0.766 and 0.961 and with antigenicity ranging from 0.52 to 1.69; thus these peptides might be used to induce T- and B-cell-mediated immunity against CHIKV. Thus, the present study might help to bridge the gap between virus microevolution and its implication in host immunity by taking into account viral genetic and conformational changes. Predicted epitopes might be used as promising targets for peptide-based vaccine development and rapid diagnostics against CHIKV infection.

PREFMD: a web server for protein structure refinement via molecular dynamics simulations

Summary

Refinement of protein structure models is a long-standing problem in structural bioinformatics. Molecular dynamics-based methods have emerged as an avenue to achieve consistent refinement. The PREFMD web server implements an optimized protocol based on the method successfully tested in CASP11. Validation with recent CASP refinement targets shows consistent and more significant improvement in global structure accuracy over other state-of-the-art servers.

Availability and implementation

PREFMD is freely available as a web server at http://feiglab.org/prefmd. Scripts for running PREFMD as a stand-alone package are available at https://github.com/feiglab/prefmd.git.

Contact

feig@msu.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Protein-engineering of chitosanase from Bacillus sp. MN to alter its substrate specificity

Partially acetylated chitosan oligosaccharides (paCOS) have various potential applications in agriculture, biomedicine, and pharmaceutics due to their suitable bioactivities. One method to produce paCOS is partial chemical hydrolysis of chitosan polymers, but that leads to poorly defined mixtures of oligosaccharides. However, the effective production of defined paCOS is crucial for fundamental research and for developing applications. A more promising approach is enzymatic depolymerization of chitosan using chitinases or chitosanases, as the substrate specificity of the enzyme determines the composition of the oligomeric products. Protein-engineering of these enzymes to alter their substrate specificity can overcome the limitations associated with naturally occurring enzymes and expand the spectrum of specific paCOS that can be produced. Here, engineering the substrate specificity of Bacillus sp. MN chitosanase is described for the first time. Two muteins with active site substitutions can accept N-acetyl-D-glucosamine units at their subsite (-2), which is impossible for the wildtype enzyme.

Structural complexity and functional diversity of plant NADPH oxidases

Plant NADPH oxidases also known as respiratory burst oxidase homologs (Rbohs) are a family of membrane-bound enzymes that play diverse roles in the defense response and morphogenetic processes via regulated generation of reactive oxygen species. Rbohs are associated with a variety of functions, although the reason for this is not clear. To evaluate using bioinformatics, the possible mechanisms for the observed functional diversity within the plant kingdom, 127 Rboh protein sequences representing 26 plant species were analyzed. Multiple clusters were identified with gene duplications that were both dicot as well as monocot-specific. The N-terminal sequences were observed to be highly variable. The conserved cysteine (equivalent of Cys890) in C-terminal of AtRbohD suggested that the redox-based modification like S-nitrosylation may regulate the activity of other Rbohs. Three-dimensional models corresponding to the N-terminal domain for Rbohs from Arabidopsis thaliana and Oryza sativa were constructed and molecular dynamics studies were carried out to study the role of Ca2+ in the folding of Rboh proteins. Certain mutations indicated possibly affect the structure and function of the plant NADPH oxidases, thereby providing the rationale for further experimental validation.

Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform

BACKGROUND

Traditional drug discovery approaches focus on a limited set of target molecules for treatment against specific indications/diseases. However, drug absorption, dispersion, metabolism, and excretion (ADME) involve interactions with multiple protein systems. Drugs approved for particular indication(s) may be repurposed as novel therapeutics for others. The severely declining rate of discovery and increasing costs of new drugs illustrate the limitations of the traditional reductionist paradigm in drug discovery.

METHODS

We developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform based on a hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for therapeutic repurposing and discovery. We compiled a library of compounds that are human ingestible with minimal side effects, followed by an 'all-compounds' vs 'all-proteins' fragment-based multitarget docking with dynamics screen to construct compound-proteome interaction matrices that were then analyzed to determine similarity of drug behavior. The proteomic signature similarity of drugs is then ranked to make putative drug predictions for all indications in a shotgun manner.

RESULTS

We have previously applied this platform with success in both retrospective benchmarking and prospective validation, and to understand the effect of druggable protein classes on repurposing accuracy. Here we use the CANDO platform to analyze and determine the contribution of multitargeting (polypharmacology) to drug repurposing benchmarking accuracy. Taken together with the previous work, our results indicate that a large number of protein structures with diverse fold space and a specific polypharmacological interactome is necessary for accurate drug predictions using our proteomic and evolutionary drug discovery and repurposing platform.

CONCLUSION

These results have implications for future drug development and repurposing in the context of polypharmacology.

Structural insights into leishmanolysins encoded on chromosome 10 of Leishmania (Viannia) braziliensis

BACKGROUND

Leishmanolysins have been described as important parasite virulence factors because of their roles in the infection of promastigotes and resistance to host’s defenses. Leishmania (Viannia) braziliensis contains several leishmanolysin genes in its genome, especially in chromosome 10. However, the functional impact of such diversity is not understood, but may be attributed partially to the lack of structural data for proteins from this parasite.

OBJECTIVES

This works aims to compare leishmanolysin sequences from L. (V.) braziliensis and to understand how the diversity impacts in their structural and dynamic features.

METHODS

Leishmanolysin sequences were retrieved from GeneDB. Subsequently, 3D models were built using comparative modeling methods and their dynamical behavior was studied using molecular dynamic simulations.

FINDINGS

We identified three subgroups of leishmanolysins according to sequence variations. These differences directly affect the electrostatic properties of leishmanolysins and the geometry of their active sites. We identified two levels of structural heterogeneity that might be related to the ability of promastigotes to interact with a broad range of substrates.

MAIN CONCLUSION

Altogether, the structural plasticity of leishmanolysins may constitute an important evolutionary adaptation rarely explored when considering the virulence of L. (V.) braziliensis parasites.

A conserved NAD+ binding pocket that regulates protein-protein interactions during aging

DNA repair is essential for life, yet its efficiency declines with age for reasons that are unclear. Numerous proteins possess Nudix homology domains (NHDs) that have no known function. We show that NHDs are NAD⁺ (oxidized form of nicotinamide adenine dinucleotide) binding domains that regulate protein-protein interactions. The binding of NAD⁺ to the NHD domain of DBC1 (deleted in breast cancer 1) prevents it from inhibiting PARP1 [poly(adenosine diphosphate-ribose) polymerase], a critical DNA repair protein. As mice age and NAD⁺ concentrations decline, DBC1 is increasingly bound to PARP1, causing DNA damage to accumulate, a process rapidly reversed by restoring the abundance of NAD⁺ Thus, NAD⁺ directly regulates protein-protein interactions, the modulation of which may protect against cancer, radiation, and aging.

A family of archaea-like carboxylesterases preferentially expressed in the symbiotic phase of the mychorrizal fungus Tuber melanosporum

An increasing number of esterases is being revealed by (meta) genomic sequencing projects, but few of them are functionally/structurally characterized, especially enzymes of fungal origin. Starting from a three-member gene family of secreted putative “lipases/esterases” preferentially expressed in the symbiotic phase of the mycorrhizal fungus Tuber melanosporum (“black truffle”), we show here that these enzymes (TmelEST1-3) are dimeric, heat-resistant carboxylesterases capable of hydrolyzing various short/medium chain p-nitrophenyl esters. TmelEST2 was the most active (kcat = 2302 s⁻¹ for p-nitrophenyl-butyrate) and thermally stable (T₅₀ = 68.3 °C), while TmelEST3 was the only one displaying some activity on tertiary alcohol esters. X-ray diffraction analysis of TmelEST2 revealed a classical α/β hydrolase-fold structure, with a network of dimer-stabilizing intermolecular interactions typical of archaea esterases. The predicted structures of TmelEST1 and 3 are overall quite similar to that of TmelEST2 but with some important differences. Most notably, the much smaller volume of the substrate-binding pocket and the more acidic electrostatic surface profile of TmelEST1. This was also the only TmelEST capable of hydrolyzing feruloyl-esters, suggestinng a possible role in root cell-wall deconstruction during symbiosis establishment. In addition to their potential biotechnological interest, TmelESTs raise important questions regarding the evolutionary recruitment of archaea-like enzymes into mesophilic subterranean fungi such as truffles.

Effect of solvent and protein dynamics in ligand recognition and inhibition of aminoglycoside adenyltransferase 2″-Ia

The aminoglycoside modifying enzyme (AME) ANT(2″)-Ia is a significant target for next generation antibiotic development. Structural studies of a related aminoglycoside-modifying enzyme, ANT(3″)(9), revealed this enzyme contains dynamic, disordered, and well-defined segments that modulate thermodynamically before and after antibiotic binding. Characterizing these structural dynamics is critical for in situ screening, design, and development of contemporary antibiotics that can be implemented in a clinical setting to treat potentially lethal, antibiotic resistant, human infections. Here, the first NMR structural ensembles of ANT(2″)-Ia are presented, and suggest that ATP-aminoglycoside binding repositions the nucleotidyltransferase (NT) and C-terminal domains for catalysis to efficiently occur. Residues involved in ligand recognition were assessed by site-directed mutagenesis. In vitro activity assays indicate a critical role for I129 toward aminoglycoside modification in addition to known catalytic D44, D46, and D48 residues. These observations support previous claims that ANT aminoglycoside sub-class promiscuity is not solely due to binding cleft size, or inherent partial disorder, but can be controlled by ligand modulation on distinct dynamic and thermodynamic properties of ANTs under cellular conditions. Hydrophobic interactions in the substrate binding cleft, as well as solution dynamics in the C-terminal tail of ANT(2″)-Ia, advocate toward design of kanamycin-derived cationic lipid aminoglycoside analogs, some of which have already shown antimicrobial activity in vivo against kanamycin and gentamicin-resistant P. aeruginosa. This data will drive additional in silico, next generation antibiotic development for future human use to combat increasingly prevalent antimicrobial resistance.

Oligomerization and chaperone-like activity of Drosophila melanogaster small heat shock protein DmHsp27 and three arginine mutants in the alpha-crystallin domain

The small Hsp DmHsp27 from Drosophila melanogaster is one of the few small heat shock proteins (sHsps) found within the nucleus. We report that its dimerization is independent of disulfide bond formation and seems to rely on salt bridges. Unlike metazoan sHsps, DmHsp27 forms two populations of oligomers not in equilibrium. Mutations at highly conserved arginine residues in mammalian sHsps have been reported to be associated with protein conformational defects and intracellular aggregation. Independent mutation of three highly conserved arginines (R122, R131, and R135) to glycine in DmHsp27 results in only one population of higher molecular weight form. In vitro, the chaperone-like activity of wild-type DmHsp27 was comparable with that of its two isolated populations and to the single population of the R122G, R131G, and R135G using luciferase as substrate. However, using insulin, the chaperone-like activity of wild-type DmHsp27 was lower than that of R122G and R131G mutants. Altogether, the results characterize wild-type DmHsp27 and its alpha-crystallin domain (ACD) arginine mutants and may give insight into protection mechanism of sHsps.

Structural basis for the regulatory interactions of proapoptotic Par-4

Par-4 is a unique proapoptotic protein with the ability to induce apoptosis selectively in cancer cells. The X-ray crystal structure of the C-terminal domain of Par-4 (Par-4_CC), which regulates its apoptotic function, was obtained by MAD phasing. Par-4 homodimerizes by forming a parallel coiled-coil structure. The N-terminal half of Par-4_CC contains the homodimerization subdomain. This structure includes a nuclear export signal (Par-4_NES) sequence, which is masked upon dimerization indicating a potential mechanism for nuclear localization. The heteromeric-interaction models specifically showed that charge interaction is an important factor in the stability of heteromers of the C-terminal leucine zipper subdomain of Par-4 (Par-4_LZ). These heteromer models also displayed NES masking capacity and therefore the ability to influence intracellular localization.

Computational protein structure refinement: Almost there, yet still so far to go

Protein structures are essential in modern biology yet experimental methods are far from being able to catch up with the rapid increase in available genomic data. Computational protein structure prediction methods aim to fill the gap while the role of protein structure refinement is to take approximate initial template-based models and bring them closer to the true native structure. Current methods for computational structure refinement rely on molecular dynamics simulations, related sampling methods, or iterative structure optimization protocols. The best methods are able to achieve moderate degrees of refinement but consistent refinement that can reach near-experimental accuracy remains elusive. Key issues revolve around the accuracy of the energy function, the inability to reliably rank multiple models, and the use of restraints that keep sampling close to the native state but also limit the degree of possible refinement. A different aspect is the question of what exactly the target of high-resolution refinement should be as experimental structures are affected by experimental conditions and different biological questions require varying levels of accuracy. While improvement of the global protein structure is a difficult problem, high-resolution refinement methods that improves local structural quality such as favorable stereochemistry and the avoidance of atomic clashes are much more successful.

Histone deacetylase inhibition modulates histone acetylation at gene promoter regions and affects genome-wide gene transcription in Schistosoma mansoni

BACKGROUND

Schistosomiasis is a parasitic disease infecting hundreds of millions of people worldwide. Treatment depends on a single drug, praziquantel, which kills the Schistosoma spp. parasite only at the adult stage. HDAC inhibitors (HDACi) such as Trichostatin A (TSA) induce parasite mortality in vitro (schistosomula and adult worms), however the downstream effects of histone hyperacetylation on the parasite are not known.

METHODOLOGY/PRINCIPAL FINDINGS

TSA treatment of adult worms in vitro increased histone acetylation at H3K9ac and H3K14ac, which are transcription activation marks, not affecting the unrelated transcription repression mark H3K27me3. We investigated the effect of TSA HDACi on schistosomula gene expression at three different time points, finding a marked genome-wide change in the transcriptome profile. Gene transcription activity was correlated with changes on the chromatin acetylation mark at gene promoter regions. Moreover, combining expression data with ChIP-Seq public data for schistosomula, we found that differentially expressed genes having the H3K4me3 mark at their promoter region in general showed transcription activation upon HDACi treatment, compared with those without the mark, which showed transcription down-regulation. Affected genes are enriched for DNA replication processes, most of them being up-regulated. Twenty out of 22 genes encoding proteins involved in reducing reactive oxygen species accumulation were down-regulated. Dozens of genes encoding proteins with histone reader motifs were changed, including SmEED from the PRC2 complex. We targeted SmEZH2 methyltransferase PRC2 component with a new EZH2 inhibitor (GSK343) and showed a synergistic effect with TSA, significantly increasing schistosomula mortality.

CONCLUSIONS/SIGNIFICANCE

Genome-wide gene expression analyses have identified important pathways and cellular functions that were affected and may explain the schistosomicidal effect of TSA HDACi. The change in expression of dozens of histone reader genes involved in regulation of the epigenetic program in S. mansoni can be used as a starting point to look for possible novel schistosomicidal targets.

Study of intra-inter species protein-protein interactions for potential drug targets identification and subsequent drug design for Escherichia coli O104:H4 C277-11

Protein-protein interaction (PPI) and host-pathogen interactions (HPI) proteomic analysis has been successfully practiced for potential drug target identification in pathogenic infections. In this research, we attempted to identify new drug target based on PPI and HPI computation approaches and subsequently design new drug against devastating enterohemorrhagic Escherichia coli O104:H4 C277-11 (Broad), which causes life-threatening food borne disease outbreak in Germany and other countries in Europe in 2011. Our systematic in silico analysis on PPI and HPI of E. coli O104:H4 was able to identify bacterial D-galactose-binding periplasmic and UDP-N-acetylglucosamine 1-carboxyvinyltransferase as attractive candidates for new drug targets. Furthermore, computational three-dimensional structure modeling and subsequent molecular docking finally proposed [3-(5-Amino-7-Hydroxy-[1,2,3]Triazolo[4,5-D]Pyrimidin-2-Yl)-N-(3,5-Dichlorobenzyl)-Benzamide)] and (6-amino-2-[(1-naphthylmethyl)amino]-3,7-dihydro-8H-imidazo[4,5-g]quinazolin-8-one) as promising candidate drugs for further evaluation and development for E. coli O104:H4 mediated diseases. Identification of new drug target would be of great utility for humanity as the demand for designing new drugs to fight infections is increasing due to the developing resistance and side effects of current treatments. This research provided the basis for computer aided drug design which might be useful for new drug target identification and subsequent drug design for other infectious organisms.

Princeton_TIGRESS 2.0: High refinement consistency and net gains through support vector machines and molecular dynamics in double-blind predictions during the CASP11 experiment

Protein structure refinement is the challenging problem of operating on any protein structure prediction to improve its accuracy with respect to the native structure in a blind fashion. Although many approaches have been developed and tested during the last four CASP experiments, a majority of the methods continue to degrade models rather than improve them. Princeton_TIGRESS (Khoury et al., Proteins 2014;82:794-814) was developed previously and utilizes separate sampling and selection stages involving Monte Carlo and molecular dynamics simulations and classification using an SVM predictor. The initial implementation was shown to consistently refine protein structures 76% of the time in our own internal benchmarking on CASP 7-10 targets. In this work, we improved the sampling and selection stages and tested the method in blind predictions during CASP11. We added a decomposition of physics-based and hybrid energy functions, as well as a coordinate-free representation of the protein structure through distance-binning Cα-Cα distances to capture fine-grained movements. We performed parameter estimation to optimize the adjustable SVM parameters to maximize precision while balancing sensitivity and specificity across all cross-validated data sets, finding enrichment in our ability to select models from the populations of similar decoys generated for targets in CASPs 7-10. The MD stage was enhanced such that larger structures could be further refined. Among refinement methods that are currently implemented as web-servers, Princeton_TIGRESS 2.0 demonstrated the most consistent and most substantial net refinement in blind predictions during CASP11. The enhanced refinement protocol Princeton_TIGRESS 2.0 is freely available as a web server at http://atlas.engr.tamu.edu/refinement/. Proteins 2017; 85:1078-1098. © 2017 Wiley Periodicals, Inc.

High affinity binding of the peptide agonist TIP-39 to the parathyroid hormone 2 (PTH2) receptor requires the hydroxyl group of Tyr-318 on transmembrane helix 5

TIP39 ("tuberoinfundibular peptide of 39 residues") acts via the parathyroid hormone 2 receptor, PTH2, a Family B G protein-coupled receptor (GPCR). Despite the importance of GPCRs in human physiology and pharmacotherapy, little is known about the molecular details of the TIP39-PTH2 interaction. To address this, we utilised the different pharmacological profiles of TIP39 and PTH(1-34) at PTH2 and its related receptor PTH1: TIP39 being an agonist at the former but an antagonist at the latter, while PTH(1-34) activates both. A total of 23 site-directed mutations of PTH2, in which residues were substituted to the equivalent in PTH1, were made and pharmacologically screened for agonist activity. Follow-up mutations were analysed by radioligand binding and cAMP assays. A model of the TIP39-PTH2 complex was built and analysed using molecular dynamics. Only Tyr318-Ile displayed reduced TIP39 potency, despite having increased PTH(1-34) potency, and further mutagenesis and analysis at this site demonstrated that this was due to reduced TIP39 affinity at Tyr318-Ile (pIC50=6.01±0.03) compared with wild type (pIC50=7.81±0.03). The hydroxyl group of the Tyr-318's side chain was shown to be important for TIP39 binding, with the Tyr318-Phe mutant displaying 13-fold lower affinity and 35-fold lower potency compared with wild type. TIP39 truncated by up to 5 residues at the N-terminus was still sensitive to the mutations at Tyr-318, suggesting that it interacts with a region within TIP39(6-39). Molecular modelling and molecular dynamics simulations suggest that the selectivity is based on an interaction between the Tyr-318 hydroxyl group with the carboxylate side chain of Asp-7 of the peptide.

Molecular Analysis of Factor VIII and Factor IX Genes in Hemophilia Patients: Identification of Novel Mutations and Molecular Dynamics Studies

Background

Hemophilias A and B are X-linked bleeding disorders caused by mutations in the factor VIII and factor IX genes, respectively. Our objective was to identify the spectrum of mutations of the factor VIII and factor IX genes in Saudi Arabian population and determine the genotype and phenotype correlations by molecular dynamics (MD) simulation.

Methods

For genotyping, blood samples from Saudi Arabian patients were collected, and the genomic DNA was amplified, and then sequenced by Sanger method. For molecular simulations, we have used softwares such as CHARMM (Chemistry at Harvard Macromolecular Mechanics; http://www.charmm-gui.org) and GROMACS. In addition, the secondary structure was determined based on the solvent accessibility for the confirmation of the protein stability at the site of mutation.

Results

Six mutations (three novel and three known) were identified in factor VIII gene, and six mutations (one novel and five known) were identified in factor IX gene. The factor VIII novel mutations identified were c.99G>T, p. (W33C) in exon 1, c.2138 DelA, p. (N713Tfs*9) in eon14, also a novel mutation at splicing acceptor site of exon 23 c.6430 - 1G>A. In factor IX, we found a novel mutation c.855G>C, p. (E285D) in exon 8. These novel mutations were not reported in any factor VIII or factor IX databases previously. The deleterious effects of these novel mutations were confirmed by PolyPhen2 and SIFT programs.

Conclusion

The protein functional and structural studies and the models built in this work would be appropriate for predicting the effects of deleterious amino acid substitutions causing these genetic disorders. These findings are useful for genetic counseling in the case of consanguineous marriages which is more common in the Saudi Arabia.