Department of Biological Sciences

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Has files: NoSubject: search.filters.subject.Intrinsically disordered regions (IDRs)

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    Effect of neighbouring residues in conformational plasticity of intrinsically disordered proteins
    (Elsevier, 2018-02) Basu, Sushmita
    Effect of neighbouring residues in conformational plasticity of intrinsically disordered regions. The concept of unstructured proteins has opened new avenues in the field of structural biology. Intrinsically disordered proteins (IDPs) are the new class of proteins which have been found to be a major player in many significant cellular functions. IDPs have been characterised by its physicochemical properties as well as its molecular interaction behaviour. Detailed study of IDPs can lead to a better understanding of protein folding and its functioning. To understand the source of disorderedness in the disordered regions (IDRs) in IDPs, we studied how the sequence environment of a disordered region correlates to its randomness. Here, we analysed the physicochemical and structural features like amino acid propensities, net charge, hydropathy index, secondary structure propensity, relative surface accessibility, interaction density and H-bonds to characterise the neighbours of the IDRs. Five residues, each towards N and C terminal of the disordered region are considered as the neighbours of IDRs. These neighbouring residues are found to be enriched in disorder promoting amino acids and have higher propensity to form loops than other secondary structures. Solvent accessibility of neighbouring residues also showed increasing trend as we move towards the IDRs. The variation of other parameters along with the above observation indicates that the neighbouring residues of IDRs induce a degree of flexibility to the adjoining IDRs. Based on our findings, we are designing an algorithm using random forest, which shall predict the disordered region based on its neighbouring sequences. The information on IDRs and its neighbours can be useful for proteins to be expressed or characterised for the first time. It can also provide a lead in understanding the molecular mechanism behind the polymorphic interactions that are involved with IDPs.
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    Do sequence neighbours of intrinsically disordered regions promote structural flexibility in intrinsically disordered proteins?
    (Elsevier, 2020-02) Basu, Sushmita
    Intrinsically disordered proteins (IDPs) are crucial players in various cellular activities. Several experimental and computational analyses have been conducted to study structural pliability and functional potential of IDPs. In spite of active research in past few decades, what induces structural disorder in IDPs and how is still elusive. Many studies testify that sequential and spatial neighbours often play important roles in determining structural and functional behaviour of proteins. Considering this fact, we assessed sequence neighbours of intrinsically disordered regions (IDRs) to understand if they have any role to play in inducing structural flexibility in IDPs. Our analysis includes 97% eukaryotic IDPs and 3% from bacteria and viruses. Physicochemical and structural parameters including amino acid propensity, hydrophobicity, secondary structure propensity, relative solvent accessibility, B-factor and atomic packing density are used to characterise the neighbouring residues of IDRs (NRIs). We show that NRIs exhibit a unique nature, which makes them stand out from both ordered and disordered residues. They show correlative occurrences of residue pairs like Ser-Thr and Gln-Asn, indicating their tendency to avoid strong biases of order or disorder promoting amino acids. We also find differential preferences of amino acids between N- and C-terminal neighbours, which might indicate a plausible directional effect on the dynamics of adjacent IDRs. We designed an efficient prediction tool using Random Forest to distinguish the NRIs from the ordered residues. Our findings will contribute to understand the behaviour of IDPs, and may provide potential lead in deciphering the role of IDRs in protein folding and assembly
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    Prediction of nucleic acid binding residues in protein sequences: recent advances and future prospects
    (Elsevier, 2025-10) Basu, Sushmita
    Computational prediction of DNA-binding residues (DBRs) and the RNA-binding residues (RBRs) in protein sequences is an active area of research, with about 90 predictors and 20 that were published over the last two years. The new predictors rely on sophisticated deep neural networks and protein language models, produce accurate predictions, and are conveniently available as code and/or web servers. However, we identified shortage of tools that predict these interactions in intrinsically disordered regions and tools capable of predicting residues that interact with specific RNA and DNA types. Moreover, cross-predictions between RBRs and DBRs should be quantified and minimized to ensure that future tools accurately differentiate between these two distinct types of nucleic acids.
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    Comparative assessment of binding residue predictions in intrinsically disordered regions
    (Wiley, 2025-09) Basu, Sushmita
    Dozens of impactful methods that predict intrinsically disordered regions (IDRs) in protein sequences that interact with proteins and/or nucleic acids were developed. Their training and assessment rely on the IDR-level binding annotations, while the equivalent structure-trained methods predict more granular annotations of binding amino acids (AA). We compiled a new benchmark dataset that annotates binding AA in IDRs and applied it to complete a first-of-its-kind assessment of predictions of the disordered binding residues. We evaluated a representative collection of 14 methods, used several hundred low-similarity test proteins, and focused on the challenging task of differentiating these binding residues from other disordered AA and considering ligand type-specific predictions (protein–protein vs. protein–nucleic acid interactions). We found that current methods struggle to accurately predict binding IDRs among disordered residues; however, better-than-random tools predict disordered binding residues significantly better than binding IDRs. We identified at least one relatively accurate tool for predicting disordered protein-binding and disordered nucleic acid-binding AA. Analysis of cross-predictions between interactions with protein and nucleic acids revealed that most methods are ligand-type-agnostic. Only two predictors of the nucleic acid-binding IDRs and two predictors of the protein-binding IDRs can be considered as ligand-type-specific. We also discussed several potential future directions that would move this field forward by producing more accurate methods that target the prediction of binding residues, reduce cross-predictions, and cover a broader range of ligand types.