RSC Advances  

Predict SLC6 mutation clinical pathogenicity by calculating the amino acid descriptors in different ranges with rationalization analysis of the prediction.

An advanced machine learning workflow integrating the gradient boosting decision tree (GB) algorithm and the permutation feature importance (PFI) technique has been proposed to predict the corrosion inhibition efficiency (IE) of organic compounds.

A user-friendly LC-MS data-independent acquisition-based strategy using open software for access to the flavonoid content of complex mixtures.

Atlantic cod (Gadus morhua) is a good source for producing umami peptides, and 2 novel umami pentapeptides were first identified from which. The physicochemical properties, cytotoxicity, and taste mechanisms of 2 umami peptides were also explored.

Through in silico methods, three fungal metabolites, namely cochlactone A, antcamphin M, and methyl ganoderate E, exhibited potential multi-target inhibitory activity against African swine fever virus (ASFV) base excision repair proteins.

Engineering the substrate-binding-helix of the keto-reductase domain of TENS controls chain-length selectivity of the products.

Megan O’Mara, Sarah Rauscher and Stacey Wetmore introduce the RSC Advances themed collection on New insights into biomolecular systems from large-scale simulations.

Christella dentata (Forssk.) Brownsey & Jermy has been commonly used in traditional medicinal practices but its effects on multi-drug-resistant (MDR) bacteria have remained unexplored.

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.

Machine learning-powered in silico prediction of small molecule toxicity: a stacked model approach.

Network pharmacology, molecular docking, and molecular dynamics simulations identify quercetin 3-O-β-D-glucopyranosyl-(1→2)-rhamnopyranoside as a promising inhibitor of HRAS and VEGFA proteins, suggesting potential use of Drymaria cordata as a natural source for treating cervical cancer.

An integrated computational approach in search of potent hCA IX inhibitors.

We introduce introduces the PocketCFDM generative diffusion model, aimed at improving the prediction of small molecule poses in the protein binding pockets.

The level of heat resistance in microbial cells is an important factor in determining the energy consumption and product synthesis efficiency of fermentation processes.

Decoding arsenic's impact: data mining protein structures in the protein data bank through amino acid mapping.

In this review, we have discussed some features of protein aggregation during production, formulation and storage as well as stabilization strategies in protein engineering and computational methods to prevent aggregation.

After conducting an in silico analysis of the cryptic mdk cluster region and performing transcriptomic studies, an integrative Streptomyces BAC Vector containing the mdk gene sequence was constructed and heterologous expression yielded the angucyclic product seongomycin.

Using SARS-CoV-2 M^pro as a case study, Wasserstein distance and dimension reduction are applied to the analysis of MD data of flexible complexes. The resulting embedding map correlates ligand-induced conformational differences and binding affinity.