TetraBASE: A Side Chain-Independent Statistical Energy for Designing Realistically Packed Protein Backbones

Exploring bioactive natural products for treating neurodegenerative diseases: a computational network medicine approach targeting the estrogen signaling pathway in amyotrophic lateral sclerosis and Parkinson's disease

Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) share overlapping molecular mechanisms, including estrogen signaling dysregulation, oxidative stress, and neuroinflammation. Standard treatments often lead to adverse effects due to unintended cross-talk with the estrogen signaling pathway. Identifying key regulatory genes and bioactive plant-derived compounds that modulate estrogen signaling without interfering with standard therapies offers a promising neuroprotective strategy. A network medicine and systems biology approach was used, beginning with the screening of 29 medicinal plants for ALS and 49 for PD, identifying 12 shared plants with neuroprotective potential. Bioactive compounds were screened for gene, protein, and pathway interactions, leading to target prediction (846 ALS-related and 690 PD-related targets) and disease association mining, which identified 93 overlapping genes (OGs). Protein-protein interaction (PPI) network analysis and MCODE clustering revealed ESR1, EGFR, and SRC as key hub-bottleneck (HB) genes, further validated via differential gene expression analysis. Gene ontology (GO) and pathway enrichment analyses revealed significant enrichment in estrogen signaling confirming the involvement of HB genes in neurodegenerative disease progression. Differential expression analysis confirmed ESR1 upregulation in ALS but downregulation in PD, suggesting a converse disease-specific regulatory pattern. Gene regulatory network (GRN) analysis identified hsa-miR-145-5p (ALS) and hsa-miR-181a-5p (PD) as key regulators, while FOXC1, GATA2, and TP53 emerged as crucial transcription factors (TFs) influencing disease progression. Molecular docking and MD simulations validated strong and stable interactions of Eupalitin (CYP19A1, -9.0 kcal/mol), Hesperetin (ESR1, -8.1 kcal/mol), and Sumatrol (PIK3CA, -8.9 kcal/mol). These phytochemicals, derived from Rosmarinus officinalis, Artemisia scoparia, Ocimum tenuiflorum, and Indigofera tinctoria, maintained stable hydrogen bonding and hydrophobic interactions for over 30% of a 25 ns simulation, supporting their therapeutic potential. The identification of ESR1, EGFR, and SRC as key targets, alongside estrogen signaling involvement, highlights the need for targeted nutraceutical interventions. These findings pave the way for safer, plant-based therapies that mitigate neurodegeneration while preserving estrogen signaling integrity, offering a promising adjuvant strategy alongside existing treatments.

Integrated systems pharmacology, molecular docking, and MD simulations investigation elucidating the therapeutic mechanisms of BHD in Alzheimer's disease treatment

Alzheimer's disease (AD) poses a longstanding health challenge, prompting a century-long exploration into its etiology and progression. Despite significant advancements in medical science, current AD treatments provide only symptomatic relief, urging a shift towards innovative paradigms. This study, departing from the amyloid hypothesis, integrates Systems Pharmacology, Molecular Docking and Molecular Dynamic Simulations to investigate a polyherbal phytoformulation (US 7,273,626 B2) rooted in Ayurveda for AD, consisting of Bacopa monnieri, Hippophae rhamnoides, and Dioscorea bulbifera (BHD). Diosgenin emerges as a crucial compound, aligning with previous studies, yet recognizing its limitations in explaining BHD's mechanism, this research delves into the intricate network of interactions. Protein-Protein Interaction (PPI) network analysis identifies hub genes (ALOX5, GSK3B, ACHE, SRC, AKT1, EGFR, PIK3R1, ESR1 and APP), suggesting a systems-level modulation of AD. Enrichment analyses unveil 370 AD-associated genes and key terms like "Cellular Response to Chemical Stimulus" and "Regulation of Biological Quality." KEGG pathway analysis underscores BHD's potential in Alzheimer's disease pathway (hsa05010), Endocrine resistance (hsa01522), and PI3K-Akt signaling (hsa04151). Molecular docking, carefully selecting compounds (Kaempferol, Quercetin, Myricetin, Isorhamnetin, Beta-Sitosterol, Stigmasterol, Emodin and Diosgenin) and top modulated targets, validates interactions with high dock scores, providing promising therapeutic avenues. Two core targets, Acetylcholinesterase (AChE) and Estrogen Receptor 1 (ESR1), were identified for further investigation due to their critical roles in Alzheimer's disease. To validate the molecular docking results, Molecular Dynamics (MD) simulations were performed on the AChE complexes with Myricetin, Beta-Sitosterol, and Stigmasterol, as well as the ESR1 complexes with Emodin, Diosgenin, and Beta-Sitosterol. These simulations were then compared to the interactions observed with the marketed drugs Donepezil and Estradiol, which are commonly used in Alzheimer's treatment. The MD simulations provided detailed insights into the stability and behavior of these complexes over time. The findings indicated that Myricetin and Emodin not only maintained stable interactions with AChE and ESR1 but also exhibited greater stability than Donepezil and Estradiol at specific time points and protein regions, as demonstrated by lower RMSD and RMSF values. These results suggest that natural compounds hold promise as potential therapeutic agents in the treatment of Alzheimer's disease, offering new avenues for drug development, while the formulation BHD shows potential as an adjuvant in integrative medicine alongside standard Alzheimer's treatments, effectively targeting related pathways and genes.

Increasing the efficiency and accuracy of the ABACUS protein sequence design method

Motivation

The ABACUS (a backbone-based amino acid usage survey) method uses unique statistical energy functions to carry out protein sequence design. Although some of its results have been experimentally verified, its accuracy remains improvable because several important components of the method have not been specifically optimized for sequence design or in contexts of other parts of the method. The computational efficiency also needs to be improved to support interactive online applications or the consideration of a large number of alternative backbone structures.

Results

We derived a model to measure solvent accessibility with larger mutual information with residue types than previous models, optimized a set of rotamers which can approximate the sidechain atomic positions more accurately, and devised an empirical function to treat inter-atomic packing with parameters fitted to native structures and optimized in consistence with the rotamer set. Energy calculations have been accelerated by interpolation between pre-determined representative points in high-dimensional structural feature spaces. Sidechain repacking tests showed that ABACUS2 can accurately reproduce the conformation of native sidechains. In sequence design tests, the native residue type recovery rate reached 37.7%, exceeding the value of 32.7% for ABACUS1. Applying ABACUS2 to designed sequences on three native backbones produced proteins shown to be well-folded by experiments.

Availability and implementation

The ABACUS2 sequence design server can be visited at http://biocomp.ustc.edu.cn/servers/abacus-design.php.

Supplementary information

Supplementary data are available at Bioinformatics online.