Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research

The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries

Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483–186, 2004; Nederveen et al. in Proteins 59:662–672, 2005; Saccenti and Rosato in J Biomol NMR 40:251–261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376–384, 2009; Sanderson in Nature 459:1038–1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were ‘cleaned’ in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

Virtual screening and evaluation of Ketol-Acid Reducto-Isomerase (KARI) as a putative drug target for Aspergillosis

Aspergillus is a leading causative agent for fungal morbidity and mortality in immuno-compromised patients. To identify a putative target to design or identify new antifungal drug, against Aspergillus is required. In our previous work, we have analyzed the various biochemical pathways, and we found Ketol Acid Reducto-Isomerase (KARI) an enzyme involves in the amino acid biosynthesis, could be a better target. This enzyme was found to be unique by comparing to host proteome through BLASTp analysis. A homology based model of KARI was generated by Swiss model server. The generated model had been validated by PROCHECK and WHAT IF programs. The Zinc library was generated within the limitation of the Lipinski rule of five, for docking study. Based on the dock-score six molecules have been studied for ADME/TOX analysis and subjected for pharmacophore model generation. The Zinc ID of the potential inhibitors is ZINC00720614, ZINC01068126, ZINC0923, ZINC02090678, ZINC00663057 and ZINC02284065 and found to be pharmacologically active agonist and antagonist of KARI. This study is an attempt to Insilco evaluation of the KARI as a drug target and the screened inhibitors could help in the development of the better drug against Aspergillus

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

Griseofulvin stabilizes microtubule dynamics, activates p53 and inhibits the proliferation of MCF-7 cells synergistically with vinblastine

<p>Abstract</p> <p>Background</p> <p>Griseofulvin, an antifungal drug, has recently been shown to inhibit proliferation of various types of cancer cells and to inhibit tumor growth in athymic mice. Due to its low toxicity, griseofulvin has drawn considerable attention for its potential use in cancer chemotherapy. This work aims to understand how griseofulvin suppresses microtubule dynamics in living cells and sought to elucidate the antimitotic and antiproliferative action of the drug.</p> <p>Methods</p> <p>The effects of griseofulvin on the dynamics of individual microtubules in live MCF-7 cells were measured by confocal microscopy. Immunofluorescence microscopy, western blotting and flow cytometry were used to analyze the effects of griseofulvin on spindle microtubule organization, cell cycle progression and apoptosis. Further, interactions of purified tubulin with griseofulvin were studied <it>in vitro </it>by spectrophotometry and spectrofluorimetry. Docking analysis was performed using autodock4 and LigandFit module of Discovery Studio 2.1.</p> <p>Results</p> <p>Griseofulvin strongly suppressed the dynamic instability of individual microtubules in live MCF-7 cells by reducing the rate and extent of the growing and shortening phases. At or near half-maximal proliferation inhibitory concentration, griseofulvin dampened the dynamicity of microtubules in MCF-7 cells without significantly disrupting the microtubule network. Griseofulvin-induced mitotic arrest was associated with several mitotic abnormalities like misaligned chromosomes, multipolar spindles, misegregated chromosomes resulting in cells containing fragmented nuclei. These fragmented nuclei were found to contain increased concentration of p53. Using both computational and experimental approaches, we provided evidence suggesting that griseofulvin binds to tubulin in two different sites; one site overlaps with the paclitaxel binding site while the second site is located at the αβ intra-dimer interface. In combination studies, griseofulvin and vinblastine were found to exert synergistic effects against MCF-7 cell proliferation.</p> <p>Conclusions</p> <p>The study provided evidence suggesting that griseofulvin shares its binding site in tubulin with paclitaxel and kinetically suppresses microtubule dynamics in a similar manner. The results revealed the antimitotic mechanism of action of griseofulvin and provided evidence suggesting that griseofulvin alone and/or in combination with vinblastine may have promising role in breast cancer chemotherapy.</p

Cross-Protective Potential of a Novel Monoclonal Antibody Directed against Antigenic Site B of the Hemagglutinin of Influenza A Viruses

The hemagglutinin (HA) of influenza A viruses has been classified into sixteen distinct subtypes (H1–H16) to date. The HA subtypes of influenza A viruses are principally defined as serotypes determined by neutralization or hemagglutination inhibition tests using polyclonal antisera to the respective HA subtypes, which have little cross-reactivity to the other HA subtypes. Thus, it is generally believed that the neutralizing antibodies are not broadly cross-reactive among HA subtypes. In this study, we generated a novel monoclonal antibody (MAb) specific to HA, designated MAb S139/1, which showed heterosubtypic cross-reactive neutralization and hemagglutination inhibition of influenza A viruses. This MAb was found to have broad reactivity to many other viruses (H1, H2, H3, H5, H9, and H13 subtypes) in enzyme-linked immunosorbent assays. We further found that MAb S139/1 showed neutralization and hemagglutination-inhibition activities against particular strains of H1, H2, H3, and H13 subtypes of influenza A viruses. Mutant viruses that escaped neutralization by MAb S139/1 were selected from the A/Aichi/2/68 (H3N2), A/Adachi/2/57 (H2N2), and A/WSN/33 (H1N1) strains, and sequence analysis of the HA genes of these escape mutants revealed amino acid substitutions at positions 156, 158, and 193 (H3 numbering). A molecular modeling study showed that these amino acids were located on the globular head of the HA and formed a novel conformational epitope adjacent to the receptor-binding domain of HA. Furthermore, passive immunization of mice with MAb S139/1 provided heterosubtypic protection. These results demonstrate that MAb S139/1 binds to a common antigenic site shared among a variety of HA subtypes and neutralizes viral infectivity in vitro and in vivo by affecting viral attachment to cells. The present study supports the notion that cross-reactive antibodies play some roles in heterosubtypic immunity against influenza A virus infection, and underscores the potential therapeutic utility of cross-reactive antibodies against influenza

Atomic resolution insight into host cell recognition by Toxoplasma gondii.

Accepted versio

Allosteric effects in cyclophilin mutants may be explained by changes in nano-microsecond time scale motions

The relationship between molecular motion and catalysis in enzymes is debated. Here, simulations of cyclophilin A and three catalytically-impaired mutants reveal a nanosecond-scale interconversion between active and inactive conformations, orders of magnitude faster than previously suggested

Inhibition of alpha-synuclein fibrillization by dopamine is mediated by interactions with five C-terminal residues and with E83 in the NAC region

The interplay between dopamine and alpha-synuclein (AS) plays a central role in Parkinson's disease (PD). PD results primarily from a severe and selective devastation of dopaminergic neurons in substantia nigra pars compacta. The neuropathological hallmark of the disease is the presence of intraneuronal proteinaceous inclusions known as Lewy bodies within the surviving neurons, enriched in filamentous AS. In vitro, dopamine inhibits AS fibril formation, but the molecular determinants of this inhibition remain obscure. Here we use molecular dynamic (MD) simulations to investigate the binding of dopamine and several of its derivatives onto conformers representative of an NMR ensemble of AS structures in aqueous solution. Within the limitations inherent to MD simulations of unstructured proteins, our calculations suggest that the ligands bind to the (125)YEMPS(129) region, consistent with experimental findings. The ligands are further stabilized by long-range electrostatic interactions with glutamate 83 (E83) in the NAC region. These results suggest that by forming these interactions with AS, dopamine may affect AS aggregation and fibrillization properties. To test this hypothesis, we investigated in vitro the effects of dopamine on the aggregation of mutants designed to alter or abolish these interactions. We found that point mutations in the (125)YEMPS(129) region do not affect AS aggregation, which is consistent with the fact that dopamine interacts non-specifically with this region. In contrast, and consistent with our modeling studies, the replacement of glutamate by alanine at position 83 (E83A) abolishes the ability of dopamine to inhibit AS fibrillization