Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics
Therapeutic monoclonal antibodies and their derivatives are key components of clinical
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
pipelines in the global biopharmaceutical industry. The availability of large datasets of …
Recent advances in predicting protein–protein interactions with the aid of artificial intelligence algorithms
Protein–protein interactions (PPIs) are essential in the regulation of biological functions and
cell events, therefore understanding PPIs have become a key issue to understanding the …
cell events, therefore understanding PPIs have become a key issue to understanding the …
Structural biology in the clouds: the WeNMR-EOSC ecosystem
RV Honorato, PI Koukos, B Jiménez-García… - Frontiers in molecular …, 2021 - frontiersin.org
Structural biology aims at characterizing the structural and dynamic properties of biological
macromolecules at atomic details. Gaining insight into three dimensional structures of …
macromolecules at atomic details. Gaining insight into three dimensional structures of …
SKEMPI 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation
J Jankauskaitė, B Jiménez-García, J Dapkūnas… - …, 2019 - academic.oup.com
Motivation Understanding the relationship between the sequence, structure, binding energy,
binding kinetics and binding thermodynamics of protein–protein interactions is crucial to …
binding kinetics and binding thermodynamics of protein–protein interactions is crucial to …
Prediction of protein–protein interaction using graph neural networks
Proteins are the essential biological macromolecules required to perform nearly all
biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation …
biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation …
[HTML][HTML] Membrane proteins structures: A review on computational modeling tools
Abstract Background Membrane proteins (MPs) play diverse and important functions in
living organisms. They constitute 20% to 30% of the known bacterial, archaean and …
living organisms. They constitute 20% to 30% of the known bacterial, archaean and …
Machine learning approaches for protein–protein interaction hot spot prediction: Progress and comparative assessment
S Liu, C Liu, L Deng - Molecules, 2018 - mdpi.com
Hot spots are the subset of interface residues that account for most of the binding free
energy, and they play essential roles in the stability of protein binding. Effectively identifying …
energy, and they play essential roles in the stability of protein binding. Effectively identifying …
SpotOn: high accuracy identification of protein-protein interface hot-spots
We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots
(HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated …
(HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated …
PPI-hotspotID: A Method for Detecting Protein-Protein Interaction Hot Spots from the Free Protein Structure
YC Chen, K Sargsyan, JD Wright, YH Chen, YS Huang… - eLife, 2024 - elifesciences.org
Experimental detection of residues critical for protein-protein interactions (PPI) is a
timeconsuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot …
timeconsuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot …
Machine learning as an effective method for identifying true single nucleotide polymorphisms in polyploid plants
Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers
since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid …
since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid …