Kavindri Ranasinghe
YOU?
Author Swipe
View article: Basic Stability Tests of Machine Learning Potentials for Molecular Simulations in Computational Drug Discovery
Basic Stability Tests of Machine Learning Potentials for Molecular Simulations in Computational Drug Discovery Open
Neural network potentials trained on quantum-mechanical data can calculate molecular interactions with relatively high speed and accuracy. However, not all neural network potentials are suitable for molecular simulations, as they might exh…
View article: AQuaRef: Machine learning accelerated quantum refinement of protein structures
AQuaRef: Machine learning accelerated quantum refinement of protein structures Open
Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical restraints, which, in addition to being limited to kn…
View article: Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using a Neural Network Potential
Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using a Neural Network Potential Open
We present a comprehensive study investigating the potential gain in accuracy for calculating absolute solvation free energies (ASFE) using a neural network potential to describe the intramolecular energy of the solute. We calculated the A…
View article: Machine Learning of Reactive Potentials
Machine Learning of Reactive Potentials Open
In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological, and material sciences. The construction and training of MLPs enable fast and accurate simulations and analysis of the…
View article: Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using A Neural Network Potential
Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using A Neural Network Potential Open
We present a comprehensive study investigating the potential gain in accuracy for calculating absolute solvation free energies (ASFE) using a neural network potential to describe the intramolecular energy of the solute. We calculated the A…
View article: Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using A Neural Network Potential
Insights and Challenges in Correcting Force Field Based Solvation Free Energies Using A Neural Network Potential Open
We present a comprehensive study investigating the potential gain in accuracy for calculating absolute solvation free energies (ASFE) using a neural network potential for the intramolecular energies. We calculated ASFE using the Open Force…
View article: Machine Learning of Reactive Potentials
Machine Learning of Reactive Potentials Open
In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological and material sciences. The construction and training of MLPs enables fast and accurate simulations and analysis on the…
View article: Front Cover: Axially Chiral Cannabinols: A New Platform for Cannabinoid‐Inspired Drug Discovery (ChemMedChem 9/2020)
Front Cover: Axially Chiral Cannabinols: A New Platform for Cannabinoid‐Inspired Drug Discovery (ChemMedChem 9/2020) Open
The Front Cover is a representation of an axially-chiral-cannabinoid (ax-CBNs), a new cannabinoid family that is conceptualized, synthesized, and evaluated in this issue of ChemMedChem. The authors have hypothesized that cannabinoids with …
View article: Axially Chiral Cannabinols: A New Platform for Cannabinoid‐Inspired Drug Discovery
Axially Chiral Cannabinols: A New Platform for Cannabinoid‐Inspired Drug Discovery Open
Phytocannabinoids (and synthetic analogs thereof) are gaining significant attention as promising leads in modern medicine. Considering this, new directions for the design of phytocannabinoid‐inspired molecules is of immediate interest. In …
View article: Total Synthesis of Axially-Chiral Cannabinols: A New Platform for Cannabinoid-Based Drug Discovery
Total Synthesis of Axially-Chiral Cannabinols: A New Platform for Cannabinoid-Based Drug Discovery Open
Phytocannabinoids, molecules isolated from cannabis, are gaining attention as promising leads in modern medicine, including pain management. Considering the urgent need for combating the opioid crisis, new directions for the design of c…
View article: Total Synthesis of Axially-Chiral Cannabinols: A New Platform for Cannabinoid-Based Drug Discovery
Total Synthesis of Axially-Chiral Cannabinols: A New Platform for Cannabinoid-Based Drug Discovery Open
Phytocannabinoids, molecules isolated from cannabis, are gaining attention as promising leads in modern medicine, including pain management. Considering the urgent need for combating the opioid crisis, new directions for the design of cann…