Rheumatoid arthritis treatment with zoledronic acid, a potentialinhibitorofGWAS-derived pharmacogenetics STAT3 and IL2 targets.

Rheumatoid arthritis (RA) is an inflammatory condition that primarily affects the joints and progress to affect other vital organs. Variety of drugs are being recommended to control the disease progression that benefits patients to perform day-to-day activities. Few of these RA drugs have noticeable side effects; therefore, it's crucial to choose the appropriate drug for treating RA with an understanding of the disease's pathophysiology. Herein, we investigated the RA genes from GWAS data to construct protein-protein interaction (PPI) network and to define appropriate drug targets for RA. The predicted drug targets were screened with the known RA drugs based on molecular docking. Further, the molecular dynamics simulations were performed to comprehend the conformational changes and stability of the targets upon binding of the selected top ranked RA drug. As a result, our constructed protein network from GWAS data revealed, STAT3 and IL2 could be potential pharmacogenetics targets that interlink most of the RA genes encoding proteins. These interlinked proteins of both the targets showed involvement in cell signaling, immune response, and TNF signaling pathway. Among the 192 RA drugs investigated, zoledronic acid had the lowest binding energy that inhibit both STAT3 (-6.307 kcal/mol) and IL2 (-6.231 kcal/mol). Additionally, STAT3 and IL2 trajectories on zoledronic acid binding exhibit notable differences in MD simulations as compared to a drug-free environment. Also, the in vitro assessment with the zoledronic acid confirms the outcome of our computational study. Overall, our study identify zoledronic acid could be potential inhibitor against these targets, that will benefits patients with RA. Comparative efficiency assessments between the RA drugs through clinical trials are needed to validate our findings in the treatment of RA.

Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia.

Beta-tubulin (TUBB) protein is one of the components of the microtubule cytoskeleton that plays a critical role in the central nervous system. Genetic variants of TUBB cause cortical dysplasia, a developmental brain defect implicated in axonal guidance and the neuron migration. In this study, we assess pathogenic variants (Q15K, Y222F, M299V, V353I, and E401K) of TUBB protein and compared with non-pathogenic variant G235S to determine their impact on protein dynamic to cause cortical dysplasia. Among the analyzed variants, Q15K, Y222F, M299V, and E401K were noticed to have deleterious effect. Then, variant structures were modeled and their affinity with their known cofactor Guanosine-5'-triphosphate (GTP) was assessed which showed diverse binding energies ranged between (-7.436 to -6.950 kcal/mol) for the variants compared to wild-type (-7.428 kcal/mol). Finally, the molecular dynamics simulation of each variant was investigated which showed difference in trajectory between the pathogenic and non-pathogenic variant. Our analysis suggests change in amino acid residue of TUBB structure has notably affects the protein flexibility and their interactions with known cofactor. Overall, our findings provide insight on the relationship between TUBB variants and their structural dynamics that may cause diverse effects leading to cortical dysplasia.

Asn215Ser, Ala143Thr, and Arg112Cys variants in α-galactosidase A protein confer stability loss in Fabry's disease.

Alpha galactosidase A (α-GalA) gene contains nine exons localized at the q-arm of the X chromosome. Generally, an α-GalA enzyme is involved in the removal of galactosyl moieties from the glycoproteins and glycolipids. Dysregulation results in the accumulation of glycoproteins as well as glycolipids in various organs leading to Fabry disease (FD). In this study, we examine the impact of Asn215Ser, Ala143Thr and Arg112Cys variants on the α-GalA protein structure contributing to functional dynamic changes in FD. The seven computational pathogenicity prediction methods were used to predict the effects of these variants on the α-GalA protein. The three-dimensional structure of α-GalA variants was modeled with the Swiss Model and Robetta server and validated using a variety of tools. Then, molecular dynamics (MD) simulation was performed to understand the stability and dynamic behavior of the wild-type and variants structures. Most of our analyzed pathogenicity prediction tools showed that Asn215Ser, Ala143Thr and Arg112Cys variants cause a deleterious effect on the α-GalA protein. Further, MD trajectory analysis showed the destabilizing effect of variants on α-GalA structure based on the root mean square deviation, root mean square fluctuation, solvent accessible surface area, the radius of gyration, hydrogen bond, cluster analysis and PCA analysis. This concludes that the presence of these variants could potentially affect the protein functional process of galactosyl moieties removal which might lead to Fabry disease.Communicated by Ramaswamy H. Sarma.

A comprehensive evaluation of mixed mode interactions of HEA and PPA HyperCel™ chromatographic media.

Mixed mode or multimodal chromatography has been developed for rational use of multiple interactions in a controlled manner, in contrast to non-specific interactions. Indeed, as the term "mixed mode" suggests, these resins allow different types of interactions within a single chromatographic medium. In this paper, HEA HyperCel™, PPA HyperCel™ mixed-mode chromatographic media have been studied. These mixed-mode sorbents typically involve hydrophobic pseudo-affinity interactions for binding and essentially ionic interactions (charge repulsion) for elution. We identified and characterized these different interactions in chromatographic experiments by exploiting specific properties of proteins using protein standards and complex mixtures. We highlighted the major intervention of at least two types of interactions in these media: hydrophobic and electrostatic interactions. We observed the behaviour of these resins at different pH, ionic strength, with different salts and buffers types and in the presence of different organic compounds.

Conditional activation of Pik3ca(H1047R) in a knock-in mouse model promotes mammary tumorigenesis and emergence of mutations.

Oncogenic mutations in PIK3CA, which encodes the phosphoinositide-3-kinase (PI3K) catalytic subunit p110α, occur in ∼25% of human breast cancers. In this study, we report the development of a knock-in mouse model for breast cancer where the endogenous Pik3ca allele was modified to allow tissue-specific conditional expression of a frequently found Pik3ca(H1047R) (Pik3ca(e20H1047R)) mutant allele. We found that activation of the latent Pik3ca(H1047R) allele resulted in breast tumors with multiple histological types. Whole-exome analysis of the Pik3ca(H1047R)-driven mammary tumors identified multiple mutations, including Trp53 mutations that appeared spontaneously during the development of adenocarinoma and spindle cell tumors. Further, we used this model to test the efficacy of GDC-0941, a PI3K inhibitor, in clinical development, and showed that the tumors respond to PI3K inhibition.