Giovanni Minervini

The RING 2.0 web server for high quality residue interaction networks

Residue interaction networks (RINs) are an alternative way of representing protein structures where nodes are residues and arcs physico–chemical interactions. RINs have been extensively and successfully used for analysing mutation effects, protein folding, domain–domain communication and catalytic activity. Here we present RING 2.0, a new version of the RING software for the identification of covalent and non-covalent bonds in protein structures, including π–π stacking and π–cation interactions. RING 2.0 is extremely fast and generates both intra and inter-chain interactions including solvent and ligand atoms. The generated networks are very accurate and reliable thanks to a complex empirical re-parameterization of distance thresholds performed on the entire Protein Data Bank. By default, RING output is generated with optimal parameters but the web server provides an exhaustive interface to customize the calculation. The network can be visualized directly in the browser or in Cytoscape. Alternatively, the RING-Viz script for Pymol allows visualizing the interactions at atomic level in the structure. The web server and RING-Viz, together with an extensive help and tutorial, are available from URL: http://protein.bio.unipd.it/ring.

RepeatsDB: a database of tandem repeat protein structures.

RepeatsDB (http://repeatsdb.bio.unipd.it/) is a database of annotated tandem repeat protein structures. Tandem repeats pose a difficult problem for the analysis of protein structures, as the underlying sequence can be highly degenerate. Several repeat types haven been studied over the years, but their annotation was done in a case-by-case basis, thus making large-scale analysis difficult. We developed RepeatsDB to fill this gap. Using state-of-the-art repeat detection methods and manual curation, we systematically annotated the Protein Data Bank, predicting 10 745 repeat structures. In all, 2797 structures were classified according to a recently proposed classification schema, which was expanded to accommodate new findings. In addition, detailed annotations were performed in a subset of 321 proteins. These annotations feature information on start and end positions for the repeat regions and units. RepeatsDB is an ongoing effort to systematically classify and annotate structural protein repeats in a consistent way. It provides users with the possibility to access and download high-quality datasets either interactively or programmatically through web services.

Bluues server

MOTIVATION Electrostatic calculations are an important tool for deciphering many functional mechanisms in proteins. Generalized Born (GB) models offer a fast and convenient computational approximation over other implicit solvent-based electrostatic models. Here we present a novel GB-based web server, using the program Bluues, to calculate numerous electrostatic features including pKa-values and surface potentials. The output is organized allowing both experts and beginners to rapidly sift the data. A novel feature of the Bluues server is that it explicitly allows to find electrostatic differences between wild-type and mutant structures. AVAILABILITY The Bluues server, examples and extensive help files are available for non-commercial use at URL: http://protein.bio.unipd.it/bluues/.

Ca2+ binding to F‐ATP synthase β subunit triggers the mitochondrial permeability transition

F‐ATP synthases convert the electrochemical energy of the H+ gradient into the chemical energy of ATP with remarkable efficiency. Mitochondrial F‐ATP synthases can also undergo a Ca2+‐dependent transformation to form channels with properties matching those of the permeability transition pore (PTP), a key player in cell death. The Ca2+ binding site and the mechanism(s) through which Ca2+ can transform the energy‐conserving enzyme into a dissipative structure promoting cell death remain unknown. Through in vitro, in vivo and in silico studies we (i) pinpoint the “Ca2+‐trigger site” of the PTP to the catalytic site of the F‐ATP synthase β subunit and (ii) define a conformational change that propagates from the catalytic site through OSCP and the lateral stalk to the inner membrane. T163S mutants of the β subunit, which show a selective decrease in Ca2+‐ATP hydrolysis, confer resistance to Ca2+‐induced, PTP‐dependent death in cells and developing zebrafish embryos. These findings are a major advance in the molecular definition of the transition of F‐ATP synthase to a channel and of its role in cell death.

Heterozygous Reelin Mutations Cause Autosomal-Dominant Lateral Temporal Epilepsy

Autosomal-dominant lateral temporal epilepsy (ADLTE) is a genetic epilepsy syndrome clinically characterized by focal seizures with prominent auditory symptoms. ADLTE is genetically heterogeneous, and mutations in LGI1 account for fewer than 50% of affected families. Here, we report the identification of causal mutations in reelin (RELN) in seven ADLTE-affected families without LGI1 mutations. We initially investigated 13 ADLTE-affected families by performing SNP-array linkage analysis and whole-exome sequencing and identified three heterozygous missense mutations co-segregating with the syndrome. Subsequent analysis of 15 small ADLTE-affected families revealed four additional missense mutations. 3D modeling predicted that all mutations have structural effects on protein-domain folding. Overall, RELN mutations occurred in 7/40 (17.5%) ADLTE-affected families. RELN encodes a secreted protein, Reelin, which has important functions in both the developing and adult brain and is also found in the blood serum. We show that ADLTE-related mutations significantly decrease serum levels of Reelin, suggesting an inhibitory effect of mutations on protein secretion. We also show that Reelin and LGI1 co-localize in a subset of rat brain neurons, supporting an involvement of both proteins in a common molecular pathway underlying ADLTE. Homozygous RELN mutations are known to cause lissencephaly with cerebellar hypoplasia. Our findings extend the spectrum of neurological disorders associated with RELN mutations and establish a link between RELN and LGI1, which play key regulatory roles in both the developing and adult brain.

Probing mammalian spermine oxidase enzyme-substrate complex through molecular modeling, site-directed mutagenesis and biochemical characterization

Spermine oxidase (SMO) and acetylpolyamine oxidase (APAO) are FAD-dependent enzymes that are involved in the highly regulated pathways of polyamine biosynthesis and degradation. Polyamine content is strictly related to cell growth, and dysfunctions in polyamine metabolism have been linked with cancer. Specific inhibitors of SMO and APAO would allow analyzing the precise role of these enzymes in polyamine metabolism and related pathologies. However, none of the available polyamine oxidase inhibitors displays the desired characteristics of selective affinity and specificity. In addition, repeated efforts to obtain structural details at the atomic level on these two enzymes have all failed. In the present study, in an effort to better understand structure–function relationships, SMO enzyme–substrate complex has been probed through a combination of molecular modeling, site-directed mutagenesis and biochemical studies. Results obtained indicate that SMO binds spermine in a similar conformation as that observed in the yeast polyamine oxidase FMS1-spermine complex and demonstrate a major role for residues His82 and Lys367 in substrate binding and catalysis. In addition, the SMO enzyme–substrate complex highlights the presence of an active site pocket with highly polar characteristics, which may explain the different substrate specificity of SMO with respect to APAO and provide the basis for the design of specific inhibitors for SMO and APAO.

Do Natural Proteins Differ from Random Sequences Polypeptides? Natural vs. Random Proteins Classification Using an Evolutionary Neural Network

Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random.

RAPHAEL: recognition, periodicity and insertion assignment of solenoid protein structures

MOTIVATION Repeat proteins form a distinct class of structures where folding is greatly simplified. Several classes have been defined, with solenoid repeats of periodicity between ca. 5 and 40 being the most challenging to detect. Such proteins evolve quickly and their periodicity may be rapidly hidden at sequence level. From a structural point of view, finding solenoids may be complicated by the presence of insertions or multiple domains. To the best of our knowledge, no automated methods are available to characterize solenoid repeats from structure. RESULTS Here we introduce RAPHAEL, a novel method for the detection of solenoids in protein structures. It reliably solves three problems of increasing difficulty: (1) recognition of solenoid domains, (2) determination of their periodicity and (3) assignment of insertions. RAPHAEL uses a geometric approach mimicking manual classification, producing several numeric parameters that are optimized for maximum performance. The resulting method is very accurate, with 89.5% of solenoid proteins and 97.2% of non-solenoid proteins correctly classified. RAPHAEL periodicities have a Spearman correlation coefficient of 0.877 against the manually established ones. A baseline algorithm for insertion detection in identified solenoids has a Q(2) value of 79.8%, suggesting room for further improvement. RAPHAEL finds 1931 highly confident repeat structures not previously annotated as solenoids in the Protein Data Bank records.

CDKN2A Unclassified Variants in Familial Malignant Melanoma: Combining Functional and Computational Approaches for Their Assessment

CDKN2A codes for two oncosuppressors by alternative splicing of two first exons: p16INK4a and p14ARF. Germline mutations are found in about 40% of melanoma‐prone families, and most of them are missense mutations mainly affecting p16INK4a. A growing number of p16INK4a variants of uncertain significance (VUS) are being identified but, unless their pathogenic role can be demonstrated, they cannot be used for identification of carriers at risk. Predicting the effect of these VUS by either a “standard” in silico approach, or functional tests alone, is rather difficult. Here, we report a protocol for the assessment of any p16INK4a VUS, which combines experimental and computational tools in an integrated approach. We analyzed p16INK4a VUS from melanoma patients as well as variants derived through permutation of conserved p16INK4a amino acids. Variants were expressed in a p16INK4a‐null cell line (U2‐OS) and tested for their ability to block proliferation. In parallel, these VUS underwent in silico prediction analysis and molecular dynamics simulations. Evaluation of in silico and functional data disclosed a high agreement for 15/16 missense mutations, suggesting that this approach could represent a pilot study for the definition of a protocol applicable to VUS in general, involved in other diseases, as well.

Assessment of phenolic herbicide toxicity and mode of action by different assays

A phytotoxicity assay based on seed germination/root elongation has been optimized and used to evaluate the toxic effects of some phenolic herbicides. The method has been improved by investigating the influence of experimental conditions. Lepidium sativum was chosen as the most suitable species, showing high germinability, good repeatability of root length measurements, and low sensitivity to seed pretreatment. DMSO was the most appropriate solvent carrier for less water-soluble compounds. Three dinitrophenols and three hydroxybenzonitriles were tested: dinoterb, DNOC, 2,4-dinitrophenol, chloroxynil, bromoxynil, and ioxynil. Toxicity was also determined using the Vibrio fischeri Microtox® test, and a highly significant correlation was found between EC50 values obtained by the two assays. Dinoterb was the most toxic compound. The toxicity of hydroxybenzonitriles followed the order: ioxynil >bromoxynil >chloroxynil; L. sativum exhibited a slightly higher sensitivity than V. fischeri to these compounds. A QSAR analysis highlighted the importance of hydrophobic, electronic, and hydrogen-bonding interactions, in accordance with a mechanism of toxic action based on protonophoric uncoupling of oxidative phosphorylation. The results suggest that the seed germination/root elongation assay with L. sativum is a valid tool for the assessment of xenobiotic toxicity and can be recommended as part of a test battery.