Digital Alchemy: The Rise of Machine and Deep Learning in Small-Molecule Drug Discovery.

This review provides a comprehensive analysis of the transformative impact of artificial intelligence (AI) and machine learning (ML) on modern drug design, specifically focusing on how these advanced computational techniques address the inherent limitations of traditional small-molecule drug design methodologies. It begins by outlining the historical challenges of the drug discovery pipeline, including protracted timelines, exorbitant costs, and high clinical failure rates. Subsequently, it examines the core principles of structure-based virtual screening (SBVS) and ligand-based virtual screening (LBVS), establishing the critical bottlenecks that have historically impeded efficient drug development.

Asarum heterotropoides F. schmidt attenuates osteoarthritis via multi-target anti-inflammatory actions: A network pharmacology and experimental validation.

Ethnopharmacological Relevance: Asarum heterotropoides F. Schmidt (ARR) has a well-documented history of traditional use in East Asia for musculoskeletal pain disorders, including osteoarthritis (OA), attributed to its significant anti-inflammatory properties. While preliminary studies suggest potential anti-inflammatory effects, conclusive evidence regarding the ability of ARRs to modulate the multiple inflammatory pathologies involved in OA pathogenesis is currently lacking.

Deep Learning-Based Comparative Prediction and Functional Analysis of Intrinsically Disordered Regions in SARS-CoV-2.

This study explores the role of intrinsically disordered regions (IDRs) in the SARS-CoV-2 proteome and their potential as targets for small-molecule drug discovery. Experimentally validated intrinsic disordered regions from the literature were utilized to assess the prediction of intrinsic disorder across a selection of SARS-CoV-2 proteins. The disorder propensities of proteins using four deep learning-based disorder prediction models: ADOPT, PONDRVLXT, PONDRVSL2, and flDPnn, were analyzed.

Exploring the Role of BCL2 Interactome in Cancer: A Protein/Residue Interaction Network Analysis.

BCL2 is a critical regulator of intrinsic and extrinsic pathways of apoptosis that have been implicated in cancer progression and therapeutic resistance. In this study, the protein-protein interactions (PPIs) of BCL2 with potential binding partners and their role in cancer was investigated. A comprehensive PPI network for BCL2 has been generated by using the Protein Interactions Network Analysis (PINA) platform to identify key interactors.

Harnessing the Power of Machine Learning Guided Discovery of NLRP3 Inhibitors Towards the Effective Treatment of Rheumatoid Arthritis.

The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multidisciplinary approach combining machine learning, quantitative structure-activity relationship (QSAR) modeling, structure-activity landscape index (SALI), docking, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area MM/PBSA assays was employed to identify novel NLRP3 inhibitors.

Exploring the therapeutic potential of natural compounds against hepatocellular carcinoma (HCC): a computational approach.

Hepatocellular carcinoma (HCC) is the fifth leading cause of cancer related deaths globally. Despite advancements in treatment, drug resistance and adverse side effects have spurred the search for novel therapeutic strategies. This study aimed to investigate how the can inhibit key targets involved in HCC progression.

Mechanistic Exploration of Roxb. in Osteoarthritis: Insights from Network Pharmacology, Molecular Docking, and In Vitro Validation.

: Arthritis, a debilitating joint disease, remains a significant global health burden. This study uncovers the therapeutic potential of the medicinal plant Roxb. (SGR) in attenuating progression of disease by modulating immune responses.

Emerging Roles of Natural Compounds in Osteoporosis: Regulation, Molecular Mechanisms and Bone Regeneration.

Bone health is a critical aspect of overall well-being, and disorders such as osteoporosis pose significant challenges worldwide. East Asian Herbal Medicine (EAHM), with its rich history and holistic approach, offers promising avenues for enhancing bone regeneration. In this critical review article, we analyze the intricate mechanisms through which EAHM compounds modulate bone health.

Reining in Sternal Wound Infections: The Achilles' Heel of Bilateral Internal Thoracic Artery Grafting.

Although the survival advantage of bilateral internal thoracic artery grafting (BITA) is well known in patients undergoing coronary artery bypass grafting (CABG), this technique has not been widely adopted. This is mainly because of the increased risk of deep sternal wound infections (DSWI) associated with its use. However, in recent years the overall risk of DSWI has decreased.

Temporal profiling of redox-dependent heterogeneity in single cells.

Cellular redox status affects diverse cellular functions, including proliferation, protein homeostasis, and aging. Thus, individual differences in redox status can give rise to distinct sub-populations even among cells with identical genetic backgrounds. Here, we have created a novel methodology to track redox status at single cell resolution using the redox-sensitive probe Grx1-roGFP2.

Proteomic analysis of an environmental isolate of Rhodotorula mucilaginosa after arsenic and cadmium challenge: Identification of a protein expression signature for heavy metal exposure.

Unlabelled: A metal-resistant Rhodotorula mucilaginosa strain was isolated from an industrial wastewater. Effects on reduced/oxidized glutathione (GSSG/GSH), antioxidant enzymes and proteome were assessed on metal challenge (100mg/L). Increased GSH (mM/g) was found with CdCl2 (18.

Oxidative stress, glutathione level and antioxidant response to heavy metals in multi-resistant pathogen, Candida tropicalis.

In this study, we explored the multiple heavy metal-resistant yeast isolated from heavy metal-polluted environment. The isolated yeast showed maximum growth at 30 °C, pH 7.0, and the strain was identified as Candida tropicalis through 18S ribosomal RNA (rRNA) gene sequence analysis.

Redox proteomics changes in the fungal pathogen Trichosporon asahii on arsenic exposure: identification of protein responses to metal-induced oxidative stress in an environmentally-sampled isolate.

Trichosporon asahii is a yeast pathogen implicated in opportunistic infections. Cultures of an isolate collected from industrial wastewater were exposed for 2 days to 100 mg/L sodium arsenite (NaAsO2) and cadmium (CdCl2). Both metals reduced glutathione transferase (GST) activity but had no effect on superoxide dismutase or catalase.

Decolorization and detoxification of Synozol red HF-6BN azo dye, by Aspergillus niger and Nigrospora sp.

In the present investigation the fungi, Aspergillus niger and Nigrospora sp. were employed for decolorization of Synozol red HF-6BN. Decolorization study showed that Aspergillus niger and Nigrospora sp.