STATISTICAL INSIGHT INTO THE BINDING REGIONS IN DISORDERED HUMAN PROTEOME

The human proteome contains a significant number of intrinsically disordered proteins (IDPs). They show unusual structural features that enable them to participate in diverse cellular functions and play significant roles in cell signaling and reorganization processes. In addition, the actions of IDPs, their functional cooperativity, conformational alterations and folding often accompany binding to a target macromolecule. Applying bioinformatics approaches and with the aid of statistical methodologies, we investigated the statistical parameters of binding regions (BRs) found in disordered human proteome. In this report, we detailed the bioinformatics analysis of binding regions found in the IDPs. Statistical models for the occurrence of BRs, their length distribution and percent occupancy in the parent proteins are shown. The frequency of BRs followed a Poisson distribution pattern with increasing expectancy with the degree of disorderedness. The length of the individual BRs also followed Poisson distribution with a mean of 6 residues, whereas, percentage of residues in BR showed a normal distribution pattern. We also explored the physicochemical properties such as the grand average of hydropathy (GRAVY) and the theoretical isoelectric points (pIs). The theoretical pIs of the BRs followed a bimodal distribution as in the parent proteins. However, the mean acidic/basic pIs were significantly lower/higher than that of the proteins, respectively. We further showed that the amino acid composition of BRs was enriched in hydrophobic residues such as Ala, Val, Ile, Leu and Phe compared to the average sequence content of the proteins. Sequences in a BR showed conformational adaptability mostly towards flexible coil structure and followed by helix, however, the ordered secondary structural conformation was significantly lower in BRs than the proteins. Combining and comparing these statistical information of BRs with other methods may be useful for high-throughput functional annotation of proteins, drug target identification and drug discovery linking protein disorder.