flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions

G Hu, A Katuwawala, K Wang, Z Wu… - Nature …, 2021 - nature.com
Identification of intrinsic disorder in proteins relies in large part on computational predictors,
which demands that their accuracy should be high. Since intrinsic disorder carries out a …

Improving peptide-protein docking with AlphaFold-Multimer using forced sampling

I Johansson-Åkhe, B Wallner - Frontiers in bioinformatics, 2022 - frontiersin.org
Protein interactions are key in vital biological processes. In many cases, particularly in
regulation, this interaction is between a protein and a shorter peptide fragment. Such …

Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence

Z Ardern, S Chakraborty, F Lenk… - FEMS Microbiology …, 2023 - academic.oup.com
Annotating protein sequences according to their biological functions is one of the key steps
in understanding microbial diversity, metabolic potentials, and evolutionary histories …

Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration

S Ayyadevara, A Ganne, M Balasubramaniam… - Metabolic Brain …, 2022 - Springer
A protein's structure is determined by its amino acid sequence and post-translational
modifications, and provides the basis for its physiological functions. Across all organisms …

rawMSA: end-to-end deep learning using raw multiple sequence alignments

C Mirabello, B Wallner - PloS one, 2019 - journals.plos.org
In the last decades, huge efforts have been made in the bioinformatics community to
develop machine learning-based methods for the prediction of structural features of proteins …

RFAmyloid: a web server for predicting amyloid proteins

M Niu, Y Li, C Wang, K Han - International journal of molecular sciences, 2018 - mdpi.com
Amyloid is an insoluble fibrous protein and its mis-aggregation can lead to some diseases,
such as Alzheimer's disease and Creutzfeldt–Jakob's disease. Therefore, the identification …

Targeting intrinsically disordered proteins through dynamic interactions

J Chen, X Liu, J Chen - Biomolecules, 2020 - mdpi.com
Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and
have attracted significant interest in understanding if and how they may be targeted using …

Leveraging machine learning models for peptide–protein interaction prediction

S Yin, X Mi, D Shukla - RSC Chemical Biology, 2024 - pubs.rsc.org
Peptides play a pivotal role in a wide range of biological activities through participating in up
to 40% protein–protein interactions in cellular processes. They also demonstrate remarkable …

ELM-MHC: an improved MHC identification method with extreme learning machine algorithm

Y Li, M Niu, Q Zou - Journal of proteome research, 2019 - ACS Publications
The major histocompatibility complex (MHC) is a term for all gene groups of a major
histocompatibility antigen. It binds to peptide chains derived from pathogens and displays …

[HTML][HTML] Inner-view of nanomaterial incited protein conformational changes: insights into designable interaction

A Mukhopadhyay, S Basu, S Singha, HK Patra - Research, 2018 - spj.science.org
Nanoparticle bioreactivity critically depends upon interaction between proteins and
nanomaterials (NM). The formation of the “protein corona”(PC) is the effect of such …