Review Article
Photocatalytic degradation of drugs and dyes using a maching learning approach
The waste management industry uses an increasing number of mathematical prediction models to accurately forecast the behavior of organic pollutants during catalytic degradation.
Paper
Modeling the relative response factor of small molecules in positive electrospray ionization
This study introduces a novel computational method for modeling the ionization efficiency of small molecules in positive electrospray ionization, designed to facilitate the semi-quantification of chemicals in the absence of analytical standards.
Paper
In silico simulations of diffusion tensors and tortuosity in cells grown on 3D-printed scaffolds for tissue engineering
Tissue engineering is set to revolutionise regenerative medicine, drug discovery, and cancer biology.
Paper
Enhancing protein aggregation prediction: a unified analysis leveraging graph convolutional networks and active learning
A graph convolution neural network (GCN) model was developed to predict the aggregation propensity of human protein. The model was applied to protein structures derived from the AlphaFold 2.0 dataset, demonstrating its ability to accurately assess protein aggregation of human protein structure.
Paper
A practical post-Hartree-Fock approach describing open-shell metal cluster-support interactions. Application to Cu3 adsorption on benzene/coronene
A dispersion-corrected wave-function-based method (UMP2C) delivers accurate interaction energies between open-shell metal clusters and carbon-based supports, including those involving charge-transfer.
Paper
Identification of lead inhibitors for 3CLpro of SARS-CoV-2 target using machine learning based virtual screening, ADMET analysis, molecular docking and molecular dynamics simulations
Identification of novel drug candidate with appropriate pharmacokinetic properties and drug-likeness for SARS-CoV-2.
Paper
Reaction of methylene blue with OH radicals in the aqueous environment: mechanism, kinetics, products and risk assessment
Methylene blue in the environment is of moderate concern, depending on the ratio of safe to harmful breakdown products.
Paper
Pristine and aurum-decorated tungsten ditellurides as sensing materials for VOCs detection in exhaled human breath: DFT analysis
We employed DFT to evaluate the sensing capabilities of Au-decorated WTe2 TMDs nanosheets toward VOCs exhaled in human breath, which can serve as potential biomarkers for detecting specific physiological disorders.
Paper
Understanding the mechanisms of green tea EGCG against amyloid β oligomer neurotoxicity through computational studies
EGCG and EC bind to the same sites on AβOs. However, EGCG forms H-bond and π-interactions with key residues more efficiently, leading to drastic remodeling that results in full detoxification of AβOs, while EC only partially detoxifies the AβOs.
Paper
Exploring the potential of MB2 MBene family as promising anodes for Li-ion batteries
A series of 2D transition metal borides (MBenes) are reported and their properties as anode materials for LIBs are investigated.
Paper
Band gap engineering in lead free halide cubic perovskites GaGeX3 (X = Cl, Br, and I) based on first-principles calculations
Lead-free inorganic Ge-based perovskites GaGeX3 (X = Cl, Br, and I) are promising candidates for solar cell applications due to their structural, mechanical, electrical, and optical properties.
Paper
ADME profiling, molecular docking, DFT, and MEP analysis reveal cissamaline, cissamanine, and cissamdine from Cissampelos capensis L.f. as potential anti-Alzheimer's agents
Proaporphine alkaloids—cissamaline, cissamanine, and cissamdine—show promise against AD, with in silico studies highlighting their potential as new therapeutics.
Paper
Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning
A deep learning approach centered on electron density is suggested for predicting the binding affility between proteins and ligands. The approach is thoroughly assessed using various pertinent benchmarks.
About this collection
Welcome to RSC Advances Computational Chemistry year in review for 2024!
The articles in this collection have been selected as they have gained great attention within their first year of being published.
We hope you enjoy reading these articles and congratulations to all the authors whose articles are featured!