Systems analysis of steroid induced osteonecrosis shows role for heme and vitamin D in pathogenesis

In silico energetic and molecular dynamic simulations studies demonstrate potential effect of the point mutations with implications for protein engineering in BDNF

Protein engineering by directed evolution is time-consuming. Hence, in silico techniques like FoldX-Yasara for ∆∆G calculation, and SNPeffect for predicting propensity for aggregation, amyloid formation, and chaperone binding are employed to design proteins. Here, we used in silico techniques to engineer BDNF-NTF3 interaction and validated it using mutations with known functional implications for NGF dimer. The structures of three mutants representing a positive, negative, or neutral ∆∆G involving two interface residues in BDNF and two mutations representing a neutral and positive ∆∆G in NGF, which is aligned with BDNF, were selected for molecular dynamics (MD) simulation. Our MD results conclude that the secondary structure of individual protomers of the positive and negative mutants displayed a similar or different conformation from the NTF3 monomer, respectively. The positive mutants showed fewer hydrophobic interactions and higher hydrogen bonds compared to the wild-type, negative, and neutral mutants with similar SASA, suggesting solvent-mediated disruption of hydrogen-bonded interactions. Similar results were obtained for mutations with known functional implications for NGF and BDNF. The results suggest that mutations with known effects in homologous proteins could help in validation, and in silico directed evolution experiments could be a viable alternative to the experimental technique used for protein engineering.

Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.

Systems biology approach delineates critical pathways associated with disease progression in rheumatoid arthritis

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease leading to inflammation, cartilage cell death, synoviocyte proliferation, and increased and impaired differentiation of osteoclasts and osteoblasts leading to joint erosions and deformities. Transcriptomics, proteomics, and metabolomics datasets were analyzed to identify the critical pathways that drive the RA pathophysiology. Single nucleotide polymorphisms (SNPs) associated with RA were analyzed for the functional implications, clinical outcomes, and blood parameters later validated by literature. SNPs associated with RA were grouped into pathways that drive the immune response and cytokine production. Further gene set enrichment analysis (GSEA) was performed on gene expression omnibus (GEO) data sets of peripheral blood mononuclear cells (PBMCs), synovial macrophages, and synovial biopsies from RA patients showed enrichment of Th1, Th2, Th17 differentiation, viral and bacterial infections, metabolic signalling and immunological pathways with potential implications for RA. The proteomics data analysis presented pathways with genes involved in immunological signaling and metabolic pathways, including vitamin B12 and folate metabolism. Metabolomics datasets analysis showed significant pathways like amino-acyl tRNA biosynthesis, metabolism of amino acids (arginine, alanine aspartate, glutamate, glutamine, phenylalanine, and tryptophan), and nucleotide metabolism. Furthermore, our commonality analysis of multi-omics datasets identified common pathways with potential implications for joint remodeling in RA. Disease-modifying anti-rheumatic drugs (DMARDs) and biologics treatments were found to modulate many of the pathways that were deregulated in RA. Overall, our analysis identified molecular signatures associated with the observed symptoms, joint erosions, potential biomarkers, and therapeutic targets in RA. Communicated by Ramaswamy H. Sarma.

Nucleotides modulate synoviocyte proliferation and osteoclast differentiation in macrophages with potential implications for rheumatoid arthritis

P2 receptors are nucleotide-activated receptors involved in inflammation, cell proliferation osteoblastogenesis, osteoclastogenesis and their function. They can be potential role players in the pathophysiology of rheumatoid arthritis (RA). Our analysis of gene expression datasets of synovial tissue biopsy from the GEO database shows changes in the expression levels of P2 receptors. HIG-82, a synovial fibroblast cell line and RAW 264.7, a macrophage cell line are good in vitro models to study RA. Nucleotide addition experiments showed UDP Glucose significantly increased the proliferation of synovial fibroblasts (HIG-82). Similarly, nucleotides such as Adenosine tri-phosphate (ATP), Adenosine di-phosphate (ADP), Uridine tri-phosphate (UTP), Uridine di-phosphate (UDP) and Uridine diphosphoglucose (UDPG) induced elevated reactive oxygen species (ROS) and tartrate Resistant Acid Phosphatase (TRAP) activity in RAW264.7 cells. The ADP-induced TRAP could be inhibited by clopidogrel a P2Y₁₂ inhibitor. ATP, ADP, UTP, UDP and UDPG also induced osteoclastogenesis as evident from fused multinucleate cells and expression of osteoclast markers (TRAP, Cathepsin K [CTSK]) as determined by Q-PCR. Apyrase (APY) a nucleotidase and an enzyme that is used to modulate extracellular nucleotide concentration is sufficient to induce osteoclastogenesis. Taken together our results show that nucleotides modulate synoviocyte proliferation and macrophage differentiation into osteoclast and play an important role in RA. Nucleotide receptors might be potential therapeutic targets in RA.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03052-8.