InSiDDe: A Server for Designing Artificial Disordered Proteins.

InSiDDe (In Silico Disorder Design) is a program for the in silico design of intrinsically disordered proteins of desired length and disorder probability. The latter is assessed using IUPred and spans values ranging from 0.55 to 0.95 with 0.05 increments. One to ten artificial sequences per query, each made of 50 to 200 residues, can be generated by InSiDDe. We describe the rationale used to set up InSiDDe and show that an artificial sequence of 100 residues with an IUPred score of 0.6 designed by InSiDDe could be recombinantly expressed in E. coli at high levels without degradation when fused to a natural molecular recognition element (MoRE). In addition, the artificial fusion protein exhibited the expected behavior in terms of binding modulation of the specific partner recognized by the MoRE. To the best of our knowledge, InSiDDe is the first publicly available software for the design of intrinsically disordered protein (IDP) sequences. InSiDDE is publicly available online.

Predicting Conformational Disorder.

In the last two decades, it has become increasingly evident that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins are ubiquitous proteins that fulfill essential biological functions while lacking a stable 3D structure. Their conformational heterogeneity is encoded at the amino acid sequence level, thereby allowing intrinsically disordered proteins or regions to be recognized based on their sequence properties. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting disorder and identifying regions involved in induced folding.

How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe.

In the last 2 decades it has become increasingly evident that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins lack a stable 3D structure, are ubiquitous and fulfill essential biological functions. Their conformational heterogeneity is encoded in their amino acid sequences, thereby allowing intrinsically disordered proteins or regions to be recognized based on properties of these sequences. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to structural determination with X-ray crystallization. This article discusses a comprehensive selection of databases and methods currently employed to disseminate experimental and putative annotations of disorder, predict disorder and identify regions involved in induced folding. It also provides a set of detailed instructions that should be followed to perform computational analysis of disorder.

Conformational disorder.

In recent years it was shown that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins are ubiquitary proteins that fulfill essential biological functions while lacking a stable 3D structure. Despite the large abundance of disorder, disordered regions are still poorly detected. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental in delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting disorder and identifying regions involved in induced folding.

Practical application of bioinformatics by the multidisciplinary VIZIER consortium.

This review focuses on bioinformatics technologies employed by the EU-sponsored multidisciplinary VIZIER consortium (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 PROJECT: 2004-511960, active from 1 November 2004 to 30 April 2009), to achieve its goals. From the management of the information flow of the project, to bioinformatics-mediated selection of RNA viruses and prediction of protein targets, to the analysis of 3D protein structures and antiviral compounds, these technologies provided a communication framework and integrated solutions for steady and timely advancement of the project. RNA viruses form a large class of major pathogens that affect humans and domestic animals. Such RNA viruses as HIV, Influenza virus and Hepatitis C virus are of prime medical concern today, but the identities of viruses that will threaten human population tomorrow are far from certain. To contain outbreaks of common or newly emerging infections, prototype drugs against viruses representing the Virus Universe must be developed. This concept was championed by the VIZIER project which brought together experts in diverse fields to produce a concerted and sustained effort for identifying and validating targets for antivirus therapy in dozens of RNA virus lineages.

MeDor: a metaserver for predicting protein disorder.

BACKGROUND: We have previously shown that using multiple prediction methods improves the accuracy of disorder predictions. It is, however, a time-consuming procedure, since individual outputs of multiple predictions have to be retrieved, compared to each other and a comprehensive view of the results can only be obtained through a manual, fastidious, non-automated procedure. We herein describe a new web metaserver, MeDor, which allows fast, simultaneous analysis of a query sequence by multiple predictors and provides a graphical interface with a unified view of the outputs. RESULTS: MeDor was developed in Java and is freely available and downloadable at: http://www.vazymolo.org/MeDor/index.html. Presently, MeDor provides a HCA plot and runs a secondary structure prediction, a prediction of signal peptides and transmembrane regions and a set of disorder predictions. MeDor also enables the user to customize the output and to retrieve the sequence of specific regions of interest. CONCLUSION: As MeDor outputs can be printed, saved, commented and modified further on, this offers a dynamic support for the analysis of protein sequences that is instrumental for delineating domains amenable to structural and functional studies.