[HTML][HTML] On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins

K Lindorff-Larsen, BB Kragelund - Journal of Molecular Biology, 2021 - Elsevier
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and
many diverging properties. IDPs—and intrinsically disordered regions (IDRs) interspersed …

[HTML][HTML] Phase diagrams—Why they matter and how to predict them

PY Chew, A Reinhardt - The Journal of Chemical Physics, 2023 - pubs.aip.org
Understanding the thermodynamic stability and metastability of materials can help us to, for
example, gauge whether crystalline polymorphs in pharmaceutical formulations are likely to …

Pharmaceutical cocrystals: a perspective on development and scale-up of solution cocrystallization

A Saha, AA Ahangar, AA Dar, S Thirunahari… - Crystal Growth & …, 2023 - ACS Publications
Pharmaceutical cocrystals represent an emergent class of successful materials designed
based on crystal engineering principles, in which the limitations of the extant drugs are …

LLPSDB v2.0: an updated database of proteins undergoing liquid–liquid phase separation in vitro

X Wang, X Zhou, Q Yan, S Liao, W Tang, P Xu… - …, 2022 - academic.oup.com
Emerging evidences have suggested that liquid–liquid phase separation (LLPS) of proteins
plays a vital role both in a wide range of biological processes and in related diseases …

Theoretical and data-driven approaches for biomolecular condensates

KL Saar, D Qian, LL Good, AS Morgunov… - Chemical …, 2023 - ACS Publications
Biomolecular condensation processes are increasingly recognized as a fundamental
mechanism that living cells use to organize biomolecules in time and space. These …

PyUUL provides an interface between biological structures and deep learning algorithms

G Orlando, D Raimondi, R Duran-Romaña… - Nature …, 2022 - nature.com
Structural bioinformatics suffers from the lack of interfaces connecting biological structures
and machine learning methods, making the application of modern neural network …

Challenges in describing the conformation and dynamics of proteins with ambiguous behavior

J Roca-Martinez, T Lazar, J Gavalda-Garcia… - Frontiers in molecular …, 2022 - frontiersin.org
Traditionally, our understanding of how proteins operate and how evolution shapes them is
based on two main data sources: the overall protein fold and the protein amino acid …

Leveraging a large language model to predict protein phase transition: A physical, multiscale, and interpretable approach

M Frank, P Ni, M Jensen, MB Gerstein - Proceedings of the National …, 2024 - pnas.org
Protein phase transitions (PPTs) from the soluble state to a dense liquid phase (forming
droplets via liquid–liquid phase separation) or to solid aggregates (such as amyloids) play …

A sequence‐based model for identifying proteins undergoing liquid–liquid phase separation/forming fibril aggregates via machine learning

S Liao, Y Zhang, X Han, T Wang, X Wang… - Protein …, 2024 - Wiley Online Library
Liquid–liquid phase separation (LLPS) and the solid aggregate (also referred to as amyloid
aggregates) formation of proteins, have gained significant attention in recent years due to …

Evaluation of sequence-based predictors for phase-separating protein

S Liao, Y Zhang, Y Qi, Z Zhang - Briefings in Bioinformatics, 2023 - academic.oup.com
Liquid–liquid phase separation (LLPS) of proteins and nucleic acids underlies the formation
of biomolecular condensates in cell. Dysregulation of protein LLPS is closely implicated in a …