Network-Derived Radioresistant Breast Cancer Target with Candidate Inhibitors from Brown Algae: A Sequential Assessment from Target Selection to Quantum Chemical Calculation.

Despite significant progress in early detection and treatment, a few aggressive breast cancers still exhibit resistance to therapy. This study aimed to identify a therapeutic target for radioresistant breast cancer (RRbc) through a protein network from breast cancer genes and to evaluate potent phytochemicals against the identified target. Our approach includes the integration of differential expression genes from expression datasets to create a protein network and to use survival analysis to identify the crucial RRbc protein in order to discover a therapeutic target. Next, the phytochemicals sourced from brown algae were screened through molecular docking, ADME (absorption, distribution, metabolism, and excretion), molecular dynamics (MD) simulation, MM-GBSA, and quantum mechanics against the identified target. As a result of our protein network investigation, the proto-oncogene c-KIT (KIT) protein was identified as a potent radioresistant breast cancer target. Further, phytochemical screening establishes that nahocol-A1 from brown algae has high binding characteristics (-8.56 kcal/mol) against the KIT protein. Then, quantum chemical analysis of nahocol-A1 provided insights into its electronic properties favorable for protein binding. Also, MD simulation comprehends the conformational stability of the KIT-nahocol-A1 complex. Overall, our findings suggest nahocol-A1 could serve as a promising therapeutic candidate for radioresistant breast cancer.

Virtual screening, molecular dynamics and density functional theory on pain inhibitors against TRPV1 associating inflammatory conditions.

Transient receptor potential vanilloid 1 protein (TRPV1) is expressed widely in skin and sensory neurons that contribute to pain/heat sensation in the human system. TRPV1 gene polymorphisms are susceptible to multiple diseases and it is considered a therapeutic target for various inflammatory conditions. Among the TRPV1 variants, rs8065080 (1911 A > G) plays a vital role in painful osteoarthritis and migraine. The presence of rs8065080 polymorphism may render drug efficacy. This study aimed to identify better antagonists against wild-type and variant TRPV1 that may help in the relief of pain/inflammation. We constructed suitable TRPV1 protein structures for wild-type and rs8065080 variant through a homology modelling approach. A total of 3363 anti-inflammatory compounds with high chemical diversity and good drug-like properties were collected and screened against the generated structures. Molecular docking showed that nobilamide B had the highest binding affinity (-5.83 kcal/mol) towards the wild-type. Whereas, isoquinoline analogue displayed highest binding potency with the variant TRPV1 (-11.65 kcal/mol). Besides those, C18H15F3N4O showed affinity towards both wild-type (-5.53 kcal/mol) and variant TRPV1 (-9.75 kcal/mol). Then, molecular dynamic simulation revealed stable conformation in wild-type and variant TRPV1 upon binding of nobilmaide B, isoquinoline analogue and C18H15F3N4O. Additionally, density functional theory (DFT) using B3LYP hybrid function showed high chemical reactiveness of nobilamie B, isoquinoline analogue and C18H15F3N4O. Overall, our systematic investigations provide, C18H15F3N4O could be a potential analgesic inhibiting both wild-type and variant TRPV1 against inflammatory conditions.

New Ways to Protect the Host from SARS-CoV-2? Lung Microbiome Metabolites Inhibit STAT3 and Modulate the Immunological Network.

COVID-19 caused by the SARS-CoV-2 infection is a systemic disease that affects multiple organs, biological pathways, and cell types. A systems biology approach would benefit the study of COVID-19 in the pandemic as well as the endemic state. Notably, patients with COVID-19 have dysbiosis of lung microbiota whose functional relevance to the host is largely unknown. We carried out a systems biology investigation of the impact of lung microbiome-derived metabolites on host immune system during COVID-19. RNAseq was performed to identify the host-specific pro- and anti-inflammatory differentially expressed genes (DEGs) in bronchial epithelium and alveolar cells during SARS-CoV-2 infection. The overlapping DEGs were harnessed to construct an immune network while their key transcriptional regulator was deciphered. We identified 68 overlapping genes from both cell types to construct the immune network, and Signal Transducer and Activator of Transcription 3 (STAT3) was found to regulate the majority of the network proteins. Furthermore, thymidine diphosphate produced from the lung microbiome had the highest affinity with STAT3 (-6.349 kcal/mol) than the known STAT3 inhibitors (n = 410), with an affinity ranging from -5.39 to 1.31 kcal/mol. In addition, the molecular dynamic studies showed distinguishable changes in the behavior of the STAT3 complex when compared with free STAT3. Overall, our results provide new observations on the importance of lung microbiome metabolites that regulate the host immune system in patients with COVID-19, and may open up new avenues for preventive medicine and therapeutics innovation.