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Impaired nuclear transport induced by juvenile ALS causing P525L mutation in NLS domain of FUS: A molecular mechanistic study

Basu, Sushmita (Elsevier, 2022-04)

Amyotrophic lateral sclerosis (ALS) and fronto-temporal lobar degeneration (FTLD) are progressive neurological disorders affecting motor neurons. Cellular aggregates of fused in sarcoma (FUS) protein are found in cytoplasm ...

qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids

Basu, Sushmita (Wiley, 2022-12)

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since ...

Computational prediction of disordered binding regions

Basu, Sushmita (Elsevier, 2023)

One of the key features of intrinsically disordered regions (IDRs) is their ability to interact with a broad range of partner molecules. Multiple types of interacting IDRs were identified including molecular recognition ...

Real-time observation of macroscopic helical morphologies under optical microscope: a curious case of π–π stacking driven molecular self-assembly of an organic gelator devoid of hydrogen bonding

Basu, Sushmita (Wiley, 2022-12)

Supramolecular assemblies such as tubules/helix/double helix/helical tape etc. are usually submicron objects preventing direct observation under optical microscope. Chiral-pure form of these assemblies is important for ...

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction

Basu, Sushmita (OUP, 2023-05)

Intrinsic disorder in proteins is relatively abundant in nature and essential for a broad spectrum of cellular functions. While disorder can be accurately predicted from protein sequences, as it was empirically demonstrated ...

CoMemMoRFPred: sequence-based prediction of MemMoRFs by combining predictors of intrinsic disorder, MoRFs and disordered lipid-binding regions

Basu, Sushmita (Elsevier, 2023-11)

Molecular recognition features (MoRFs) are a commonly occurring type of intrinsically disordered regions (IDRs) that undergo disorder-to-order transition upon binding to partner molecules. We focus on recently characterized ...

DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options

Basu, Sushmita (OUP, 2023-11)

The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality ...

HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins

Basu, Sushmita (OUP, 2023-12)

Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically ...

flDPnn2: accurate and fast predictor of intrinsic disorder in proteins

Basu, Sushmita (Elsevier, 2024-09)

Prediction of the intrinsic disorder in protein sequences is an active research area, with well over 100 predictors that were released to date. These efforts are motivated by the functional importance and high levels of ...

DescribePROT database of residue-level protein structure and function annotations

Basu, Sushmita (Springer, 2024-11)

DescribePROT is a freely available online database of structural and functional descriptors of proteins at the amino acid level. It provides access to 13 diverse descriptors that include sequence conservation, putative ...

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses

Basu, Sushmita (Elsevier, 2024-12)

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. ...

Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences

Basu, Sushmita (OUP, 2025-01)

Computational prediction of nucleic acid-binding residues in protein sequences is an active field of research, with over 80 methods that were released in the past 2 decades. We identify and discuss 87 sequence-based ...

pLMMoRF: A web server that accurately predicts membrane-interacting molecular recognition features by employing a protein language model

Basu, Sushmita (Elsevier, 2025-09)

Interactions between proteins and lipids are crucial for numerous cellular processes. Some of the lipid interacting segments in protein sequences are intrinsically disordered regions (IDRs), which may gain secondary ...

Prediction of intrinsic disorder functions with DEPICTER2

Basu, Sushmita (Springer Nature, 2025-07)

DEPICTER2 is a modern web server that provides convenient access to a broad selection of sequence-based predictions of intrinsic disorder and disorder functions. It incorporates six state-of-the-art methods that include ...

MERIT: accurate prediction of multi ligand-binding residues with hybrid deep transformer network, evolutionary couplings and transfer learning

Basu, Sushmita (Elsevier, 2025-08)

Multi-ligand binding residues (MLBRs) are amino acids in protein sequences that interact with multiple different ligands that include proteins, peptides, nucleic acids, and a variety of small molecules. MLBRs are implicated ...

Prediction of nucleic acid binding residues in protein sequences: recent advances and future prospects

Basu, Sushmita (Elsevier, 2025-10)

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. ...

Comparative assessment of binding residue predictions in intrinsically disordered regions

Basu, Sushmita (Wiley, 2025-09)

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 ...

flDPnn3: Fast and accurate prediction of intrinsic disorder in protein sequences

Basu, Sushmita (Elsevier, 2026-01)

flDPnn3 provides fast and highly accurate predictions of intrinsic disorder. Compared to its earlier versions, it uses a more sophisticated sequence-derived profile as input, covering a modern protein language model and ...

Cisplatin-induced oxidative stress regulates YAP to modulate epigenome promoting survival of osteosarcoma cells

Chowdhury, Rajdeep; Chowdhury, Shibasish; Mukherjee, Sudeshna (2025-08)

The widely used chemotherapeutic drug cisplatin (CDDP) is an integral part of the pre-operative chemotherapy protocol for high-grade osteosarcoma (OS). However, despite an aggressive treatment regimen, drug refractoriness ...

LncRNA YIYA enhances pancreatic cancer proliferation under high-glucose conditions through RAS–PKM2–mediated metabolic reprogramming that reinforces the Warburg phenotype

Mukherjee, Sudeshna; Chowdhury, Rajdeep (2025)

Diabetes and the resulting hyperglycemia are metabolic complications frequently linked to pancreatic cancer (PC). In this study, we observe that the long non-coding RNA (lncRNA)-YIYA, which resides in a genomic region ...

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