Computational protocol: Prothymosin-α Variants Elicit Anti-HIV-1 Response via TLR4 Dependent and Independent Pathways

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Protocol publication

[…] Disorder in different ProTα variants was evaluated by a family of PONDR predictors: PONDR® VSL2B, which is one of the most accurate stand-alone disorder predictors []; PONDR® VL3, which possesses high accuracy in finding long intrinsically disordered protein regions (IDPRs) []; PONDR® VLXT, which, although not being the most accurate predictor, provides high sensitivity to local sequence peculiarities that are often associated with disorder-based interaction sites []; and PONDR-FIT, which represents a metapredictor that, being moderately more accurate than each of the individual component predictors, is one of the most accurate disorder predictors []. In these analyses, scores above 0.5 correspond to disordered residues/regions. [...] Potential binding sites in disordered regions can be identified by the ANCHOR algorithm []. This approach relies on the pairwise energy estimation approach developed for the general disorder prediction method IUPred []. It is based on the hypothesis that long regions of disorder contain localized potential binding sites that cannot form enough favorable intrachain interactions to fold on their own, but are likely to gain stabilizing energy by interacting with a globular protein partner []. The ANCHOR algorithm suggests that certain regions of a protein have significant potential to be a binding site for an appropriate but typically unidentified partner protein called ANCHOR-indicated binding sites (AIBSs). [...] PTM sites in different ProTα variants were identified using a unified sequence-based predictor of 23 types of PTM sites that is available at []. Only sites predicted to be modified with high confidence (possessing score ≥0.9) were considered in this study. […]

Pipeline specifications

Software tools PONDR-FIT, IUPred, ModPred
Applications PTM analysis, Protein structure analysis
Organisms Mus musculus, Human immunodeficiency virus 1, Homo sapiens
Diseases HIV Infections