MolGpka: A Web Server for Small Molecule pKa Prediction Using a Graph-Convolutional Neural Network
p K a is an important property in the lead optimization process since the charge state of a
molecule in physiologic pH plays a critical role in its biological activity, solubility, membrane …
molecule in physiologic pH plays a critical role in its biological activity, solubility, membrane …
Epik: pKa and Protonation State Prediction through Machine Learning
RC Johnston, K Yao, Z Kaplan, M Chelliah… - Journal of chemical …, 2023 - ACS Publications
Epik version 7 is a software program that uses machine learning for predicting the p K a
values and protonation state distribution of complex, druglike molecules. Using an ensemble …
values and protonation state distribution of complex, druglike molecules. Using an ensemble …
[HTML][HTML] Quantum chemical package Jaguar: A survey of recent developments and unique features
Y Cao, T Balduf, MD Beachy, MC Bennett… - The Journal of …, 2024 - pubs.aip.org
This paper is dedicated to the quantum chemical package Jaguar, which is commercial
software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific …
software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific …
Recent Progress in the Endosomal Escape Mechanism and Chemical Structures of Polycations for Nucleic Acid Delivery
Nucleic acid‐based therapies are seeing a spiralling surge. Stimuli‐responsive polymers,
especially pH‐responsive ones, are gaining widespread attention because of their ability to …
especially pH‐responsive ones, are gaining widespread attention because of their ability to …
Rapid and Accurate Prediction of pKa Values of C–H Acids Using Graph Convolutional Neural Networks
R Roszak, W Beker, K Molga… - Journal of the American …, 2019 - ACS Publications
The ability to estimate the acidity of C–H groups within organic molecules in non-aqueous
solvents is important in synthetic planning to correctly predict which protons will be …
solvents is important in synthetic planning to correctly predict which protons will be …
An allosteric modulator binds to a conformational hub in the β2 adrenergic receptor
X Liu, J Kaindl, M Korczynska, A Stößel… - Nature chemical …, 2020 - nature.com
Most drugs acting on G-protein-coupled receptors target the orthosteric binding pocket
where the native hormone or neurotransmitter binds. There is much interest in finding …
where the native hormone or neurotransmitter binds. There is much interest in finding …
Bridging Machine Learning and Thermodynamics for Accurate pKa Prediction
Integrating scientific principles into machine learning models to enhance their predictive
performance and generalizability is a central challenge in the development of AI for Science …
performance and generalizability is a central challenge in the development of AI for Science …
Affinity and selectivity assessment of covalent inhibitors by free energy calculations
LM Mihalovits, GG Ferenczy… - Journal of Chemical …, 2020 - ACS Publications
Covalent inhibitors have been gaining increased attention in drug discovery due to their
beneficial properties such as long residence time, high biochemical efficiency, and …
beneficial properties such as long residence time, high biochemical efficiency, and …
Conserved water networks identification for drug design using density clustering approaches on positional and orientational data
This work describes the development and testing of a method for the identification and
classification of conserved water molecules and their networks from molecular dynamics …
classification of conserved water molecules and their networks from molecular dynamics …
Improved chemical prediction from scarce data sets via latent space enrichment
NC Iovanac, BM Savoie - The Journal of Physical Chemistry A, 2019 - ACS Publications
Modern machine learning provides promising methods for accelerating the discovery and
characterization of novel chemical species. However, in many areas experimental data …
characterization of novel chemical species. However, in many areas experimental data …