Although intrinsically disordered proteins (IDPs) are widespread in nature and play diverse and important roles in biology, they have to date been little characterized structurally. Auspiciously, intensified efforts using NMR spectroscopy have started to uncover the breadth of their conformational landscape. In particular, polypeptide backbone chemical shifts are emerging as powerful descriptors of local dynamic deviations from the "random coil" state toward canonical types of secondary structure. These digressions, in turn, can be connected to functional or dysfunctional protein states, for example, in adaptive molecular recognition and protein aggregation. Here we describe a first inventory of IDP backbone (15)N, (1)H(N), (1)H(α), (13)C(O), (13)C(β), and (13)C(α) chemical shifts using data obtained for a set of 14 proteins of unrelated sequence and function. Singular value decomposition was used to parametrize this database of 6903 measured shifts collectively in terms of 20 amino acid-specific random coil chemical shifts and 40 sequence-dependent left- and right-neighbor correction factors, affording the ncIDP library. For natively unfolded proteins, random coil backbone chemical shifts computed from the primary sequence displayed root-mean-square deviations of 0.65, 0.14, 0.12, 0.50, 0.36, and 0.41 ppm from the experimentally measured values for the (15)N, (1)H(N), (1)H(α), (13)C(O), (13)C(β), and (13)C(α) chemical shifts, respectively. The ncIDP prediction accuracy is significantly higher than that obtained with libraries for small peptides or "coil" regions of folded proteins.

NMR spectroscopy offers the unique possibility to relate the structural propensities of disordered proteins and loop segments of folded peptides to biological function and aggregation behaviour. Backbone chemical shifts are ideally suited for this task, provided that appropriate reference data are available and idiosyncratic sensitivity of backbone chemical shifts to structural information is treated in a sensible manner. In the present paper, we describe methods to detect structural protein changes from chemical shifts, and present an online tool [ncSPC (neighbour-corrected Structural Propensity Calculator)], which unites aspects of several current approaches. Examples of structural propensity calculations are given for two well-characterized systems, namely the binding of α-synuclein to micelles and light activation of photoactive yellow protein. These examples spotlight the great power of NMR chemical shift analysis for the quantitative assessment of protein disorder at the atomic level, and further our understanding of biologically important problems.

The cyanobacterium Synechococcus sp. PCC 7002 carries two genes, petJ1 and petJ2, for proteins related to soluble, cytochrome c6 electron transfer proteins. PetJ1 was purified from the cyanobacterium, and both cytochromes were expressed with heme incorporation in Escherichia coli. The expressed PetJ1 displayed spectral and biochemical properties virtually identical to those of PetJ1 from Synechococcus. PetJ1 is a typical cytochrome c6 but contains an unusual KDGSKSL insertion. PetJ2 isolated from E. coli exhibited absorbance spectra characteristic of cytochromes, although the alpha, beta, and gamma bands were red-shifted relative to those of PetJ1. Moreover, the surface electrostatic properties and redox midpoint potential of PetJ2 (pI 9.7; E(m,7) = 148 +/- 1.7 mV) differed substantially from those of PetJ1 (pI 3.8; E(m,7) = 319 +/- 1.6 mV). These data indicate that the PetJ2 cytochrome could not effectively replace PetJ1 as an electron acceptor for the cytochrome bf complex in photosynthesis. Phylogenetic comparisons against plant, algal, bacterial, and cyanobacterial genomes revealed two novel and widely distributed clusters of previously uncharacterized, cyanobacterial c 6-like cytochromes. PetJ2 belongs to a group that is distinct from both c6 cytochromes and the enigmatic chloroplast c 6A cytochromes. We tentatively designate the PetJ2 group as c6C cytochromes and the other new group as c6B cytochromes. Possible functions of these cytochromes are discussed.

Intrinsically disordered proteins (IDP) are important in a broad range of biological functions and are involved in many diseases. An understanding of intrinsic disorder is key to develop drugs against IDPs. Experimental characterization of IDPs are expensive and less efficient and demand the development of computational tools. Here, we present ADOPT, a new predictor of protein disorder. ADOPT is a deep bidirectional transformer, which extracts dense residue level representations from Facebook’s Evolutionary Scale Modeling (ESM) library. Using the experimentally designed CheZod database as a training and test dataset for protein disorder, it predicts Z scores and protein disorder with new state-of-the-art performance in a few seconds. We show that ADOPT offers substantial improvement in comparison to previous predictors with a Spearman correlation coefficient between experimental and computational Z scores of 0.69. We identify the coordinates which are relevant for the prediction performance and show that good performance can already gained with less than 100 features. We believe that ADOPT will be a useful tool for all experimental scientists working with intrinsically disordered proteins. It is available as a standalone package at https://github.com/PeptoneInc/ADOPT.git.