Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

R Akbar, H Bashour, P Rawat, PA Robert, E Smorodina… - MAbs, 2022 - Taylor & Francis
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …

Trends in industrialization of biotherapeutics: a survey of product characteristics of 89 antibody-based biotherapeutics

KP Martin, C Grimaldi, R Grempler, S Hansel, S Kumar - MAbs, 2023 - Taylor & Francis
There is considerable interest in the pharmaceutical industry toward development of
antibody-based biotherapeutics because they can selectively bind diverse receptors and …

AMYPred-FRL is a novel approach for accurate prediction of amyloid proteins by using feature representation learning

P Charoenkwan, S Ahmed, C Nantasenamat… - Scientific reports, 2022 - nature.com
Amyloid proteins have the ability to form insoluble fibril aggregates that have important
pathogenic effects in many tissues. Such amyloidoses are prominently associated with …

[HTML][HTML] Accelerating therapeutic protein design with computational approaches toward the clinical stage

Z Chen, X Wang, X Chen, J Huang, C Wang… - Computational and …, 2023 - Elsevier
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine.
However, clinical translation of therapeutic protein is still largely hindered by different …

Stability of protein pharmaceuticals: Recent advances

MC Manning, RE Holcomb, RW Payne… - Pharmaceutical …, 2024 - Springer
There have been significant advances in the formulation and stabilization of proteins in the
liquid state over the past years since our previous review. Our mechanistic understanding of …

[HTML][HTML] Protein Condensates and Protein Aggregates: In Vitro, in the Cell, and In Silico

K Venko, E Žerovnik - Frontiers in Bioscience-Landmark, 2023 - imrpress.com
Similar to other polypeptides and electrolytes, proteins undergo phase transitions, obeying
physicochemical laws. They can undergo liquid-to-gel and liquid-to-liquid phase transitions …

[HTML][HTML] Interpretable molecular encodings and representations for machine learning tasks

M Weckbecker, A Anžel, Z Yang, G Hattab - Computational and Structural …, 2024 - Elsevier
Molecular encodings and their usage in machine learning models have demonstrated
significant breakthroughs in biomedical applications, particularly in the classification of …

Recombinant multiepitope proteins expressed in Escherichia coli cells and their potential for immunodiagnosis

AAM Gonçalves, AJ Ribeiro, CAA Resende… - Microbial Cell …, 2024 - Springer
Recombinant multiepitope proteins (RMPs) are a promising alternative for application in
diagnostic tests and, given their wide application in the most diverse diseases, this review …

Prediction of aggregation of biologically-active peptides with the UNRES coarse-grained model

I Biskupek, C Czaplewski, J Sawicka, E Iłowska… - Biomolecules, 2022 - mdpi.com
The UNited RESidue (UNRES) model of polypeptide chains was applied to study the
association of 20 peptides with sizes ranging from 6 to 32 amino-acid residues. Twelve of …

Computationally-aided modeling of Hsp70–client interactions: past, present, and future

EB Nordquist, EM Clerico, J Chen… - The Journal of Physical …, 2022 - ACS Publications
Hsp70 molecular chaperones play central roles in maintaining a healthy cellular proteome.
Hsp70s function by binding to short peptide sequences in incompletely folded client …