Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions

A Dhakal, C McKay, JJ Tanner… - Briefings in …, 2022 - academic.oup.com
New drug production, from target identification to marketing approval, takes over 12 years
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …

Forging the basis for developing protein–ligand interaction scoring functions

Z Liu, M Su, L Han, J Liu, Q Yang, Y Li… - Accounts of chemical …, 2017 - ACS Publications
Conspectus In structure-based drug design, scoring functions are widely used for fast
evaluation of protein–ligand interactions. They are often applied in combination with …

Machine Learning for Sequence and Structure-Based Protein–Ligand Interaction Prediction

Y Zhang, S Li, K Meng, S Sun - Journal of Chemical Information …, 2024 - ACS Publications
Developing new drugs is too expensive and time-consuming. Accurately predicting the
interaction between drugs and targets will likely change how the drug is discovered …

Developing computational model to predict protein-protein interaction sites based on the XGBoost algorithm

A Deng, H Zhang, W Wang, J Zhang, D Fan… - International journal of …, 2020 - mdpi.com
The study of protein-protein interaction is of great biological significance, and the prediction
of protein-protein interaction sites can promote the understanding of cell biological activity …

Human chorionic plate-derived mesenchymal stem cells transplantation restores ovarian function in a chemotherapy-induced mouse model of premature ovarian …

J Li, Q Yu, H Huang, W Deng, X Cao… - Stem Cell Research & …, 2018 - Springer
Background Previous studies have reported that transplantation of mesenchymal stem cells
(MSCs) from many human tissues could ameliorate ovarian dysfunction. However, no study …

Sequence-based prediction of protein–carbohydrate binding sites using support vector machines

G Taherzadeh, Y Zhou, AWC Liew… - Journal of chemical …, 2016 - ACS Publications
Carbohydrate-binding proteins play significant roles in many diseases including cancer.
Here, we established a machine-learning-based method (called sequence-based prediction …

Can we rely on computational predictions to correctly identify ligand binding sites on novel protein drug targets? Assessment of binding site prediction methods and a …

NK Broomhead, ME Soliman - Cell biochemistry and biophysics, 2017 - Springer
In the field of medicinal chemistry there is increasing focus on identifying key proteins whose
biochemical functions can firmly be linked to serious diseases. Such proteins become …

Active and allosteric site binding MM-QM studies of Methylidene tetracyclo derivative in PCSK9 protein intended to make a safe antilipidemic agent

N Irfan, P Vaithyanathan, H Anandaram… - Journal of …, 2024 - Taylor & Francis
Interaction of low-density lipoprotein receptors with proprotein convertase subtilisin/kexin
type 9 (PCSK9) plays a vital part in causing atherosclerosis. It is the hidden precursor of …

Development and characterization of novel hybrid hydrogel fibers

A Mirabedini, J Foroughi, T Romeo… - Macromolecular …, 2015 - Wiley Online Library
Biopolymeric continuous core‐sheath fibres, with an inner core of chitosan and alginate as
the sheath, were fabricated for the first time without using a template. Hereby, the necessary …

Developing Hispolon-based novel anticancer therapeutics against human (NF-κβ) using in silico approach of modelling, docking and protein dynamics

M Paul, MK Panda, H Thatoi - Journal of Biomolecular Structure …, 2019 - Taylor & Francis
Hispolon is a polyphenolic compound derived from black hoof mushroom (Phellinus linteus)
or shaggy bracket mushroom (Inonotus hispidus) which induces the inhibition of cancer …