Point mutation I634A in the glucocorticoid receptor causes embryonic lethality by reduced ligand binding.

The glucocorticoid (GC) receptor (GR) is essential for normal development and in the initiation of inflammation. Healthy GRdim/dim mice with reduced dimerization propensity due to a point mutation (A465T) at the dimer interface of the GR DNA-binding domain (DBD) (here GRD/D) have previously helped to define the functions of GR monomers and dimers. Since GRD/D retains residual dimerization capacity, here we generated the dimer-nullifying double mutant GRD+L/D+L mice, featuring an additional mutation (I634A) in the ligand-binding domain (LBD) of GR. These mice are perinatally lethal, as are GRL/L mice (these mice have the I634A mutation but not the A465T mutation), displaying improper lung and skin formation. Using embryonic fibroblasts, high and low doses of dexamethasone (Dex), nuclear translocation assays, RNAseq, dimerization assays, and ligand-binding assays (and Kd values), we found that the lethal phenotype in these mice is due to insufficient ligand binding. These data suggest there is some correlation between GR dimerization potential and ligand affinity. We conclude that even a mutation as subtle as I634A, at a position not directly involved in ligand interactions sensu stricto, can still influence ligand binding and have a lethal outcome.

Mechanistic Insights into Binding of Ligands with Thiazolidinedione Warhead to Human Histone Deacetylase 4.

Recently, we have reported that non-hydroxamate thiazolidinedione (TZD) analogs are capable of inhibiting human deacetylase 4 (HDAC4). This study aims at the dissection of the molecular determinants and kinetics of the molecular recognition of TZD ligands by HDAC4. For this purpose, a structure activity relationship analysis of 225 analogs was combined with a comprehensive study of the enzyme and binding kinetics of a variety of HDAC4 mutant variants. The experimental data were rationalized by docking to the two major conformations of HDAC4. TZD ligands are competitive inhibitors and bind via a two-step mechanism involving principal molecular recognition and induced fit. The residence time of 24 g is (34 ± 3) min and thus much larger than that of the canonical pan-HDAC inhibitor SAHA ((5 ± 2) min). Importantly, the binding kinetics can be tuned by varying the structure of the CAP group.

Mutational spectrum of GNAL, THAP1 and TOR1A genes in isolated dystonia: study in a population from Spain and systematic literature review.

OBJECTIVE: We aimed to investigate the prevalence of TOR1A, GNAL and THAP1 variants as the cause of dystonia in a cohort of Spanish patients with isolated dystonia and in the literature. METHODS: A population of 2028 subjects (including 1053 patients with different subtypes of isolated dystonia and 975 healthy controls) from southern and central Spain was included. The genes TOR1A, THAP1 and GNAL were screened using a combination of high-resolution melting analysis and direct DNA resequencing. In addition, an extensive literature search to identify original articles (published before 10 August 2020) reporting mutations in TOR1A, THAP1 or GNAL associated to dystonia was performed. RESULTS: Pathogenic or likely pathogenic variants in TOR1A, THAP1 and GNAL were identified in 0.48%, 0.57% and 0.29% of our patients, respectively. Five patients carried the variation p.Glu303del in TOR1A. A very rare variant in GNAL (p.Ser238Asn) was found as a putative risk factor for dystonia. In the literature, variations in TOR1A, THAP1 and GNAL accounted for about 6%, 1.8% and 1.1% of published dystonia patients, respectively. CONCLUSIONS: There is a different genetic contribution to dystonia of these three genes in our patients (about 1.3% of patients) and in the literature (about 3.6% of patients), probably due the high proportion of adult-onset cases in our cohort. As regards age at onset, site of dystonia onset, and final distribution, in our population there is a clear differentiation between DYT-TOR1A and DYT-GNAL, with DYT-THAP1 likely to be an intermediate phenotype.

Interaction between γC87 and γR242 residues participates in energy coupling between catalysis and proton translocation in Escherichia coli ATP synthase.

Functioning as a nanomotor, ATP synthase plays a vital role in the cellular energy metabolism. Interactions at the rotor and stator interface are critical to the energy transmission in ATP synthase. From mutational studies, we found that the γC87K mutation impairs energy coupling between proton translocation and nucleotide synthesis/hydrolysis. An additional glutamine mutation at γR242 (γR242Q) can restore efficient energy coupling to the γC87K mutant. Arrhenius plots and molecular dynamics simulations suggest that an extra hydrogen bond could form between the side chains of γC87K and ßTPE381 in the γC87K mutant, thus impeding the free rotation of the rotor complex. In the enzyme with γC87K/γR242Q double mutations, the polar moiety of γR242Q side chain can form a hydrogen bond with γC87K, so that the amine group in the side chain of γC87K will not hydrogen-bond with ßE381. As a conclusion, the intra-subunit interaction between positions γC87 and γR242 modulates the energy transmission in ATP synthase. This study should provide more information of residue interactions at the rotor and stator interface in order to further elucidate the energetic mechanism of ATP synthase.

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effects of amino acid substitutions, but such wet-lab work is prohibitive due to the time as well as financial resources needed to assess the effect of even a single amino acid substitution. Computational methods for predicting the effects of a mutation on a protein structure can complement wet-lab work, and varying approaches are available with promising accuracy rates. In this work we compare and assess the utility of several machine learning methods and their ability to predict the effects of single and double mutations. We in silico generate mutant protein structures, and compute several rigidity metrics for each of them. We use these as features for our Support Vector Regression (SVR), Random Forest (RF), and Deep Neural Network (DNN) methods. We validate the predictions of our in silico mutations against experimental Δ Δ G stability data, and attain Pearson Correlation values upwards of 0.71 for single mutations, and 0.81 for double mutations. We perform ablation studies to assess which features contribute most to a model's success, and also introduce a voting scheme to synthesize a single prediction from the individual predictions of the three models.

Structural and Biochemical Studies on the Reaction Mechanism of Uridine-Cytidine Kinase.

Uridine-cytidine kinase catalyzes phosphorylation of the pyrimidine nucleosides uridine and cytidine and plays an important role in nucleotide metabolism. However, the detailed molecular mechanism of these reactions remains to be elucidated. Here, we determined the structure of the ternary complex of Uridine-cytidine kinase from Thermus thermophilus HB8 with both cytidine and ß,γ-methyleneadenosine 5'-triphosphate, a non-hydrolysable ATP analogue. Substrate binding is accompanied by substantial domain movement that allows the substrate-binding cleft to close. The terminal phosphodiester bond of the ATP analogue is in an ideal location for an inline attack of the 5'-hydroxyl group of cytidine. Asp40 is located near the 5'-hydroxyl group of cytidine. Mutation of this conserved residue to Asn or Ala resulted in a complete loss of enzyme activity, which is consistent with the notion that Asp40 acts as a general base that activates the 5'-hydroxyl group of cytidine. The pH profile of the activity showed an apparent pK a value of 7.4. Based on this structure, a likely mechanism of the catalytic step is discussed.

Carbon distribution to toxic effect in toxin proteins.

The role of hydrophobic force in biological function through the formation of several local macro-molecular structures is evident. Carbon is the element that contributes to biological function in living systems. We show that carbon distribution is related to protein activity using an example. The carbon distribution profile is foreseen to help undestand unfolded and misfolded regions of protein structures. The carbon distribution profile in a toxin protein that is found associated with the toxic shock syndrome is described in this study. The carbon profile provides insight to the association of specific residues responsible for toxicity.

CARd: Carbon distribution analysis program for protein sequences.

Carbon distribution is responsible for stability and structure of proteins. Arrangement of carbon along the protein sequence is depends on how the amino acids are organized and is guided by mRNAs. An atomic level revision is important for understanding these codes. This will ultimately help in identification of disorders and suggest mutations. For this purpose a carbon distribution analysis program has been developed. This program captures the hydrophobic / hydrophilic / disordered regions in a protein. The program gives accurate results. The calculations are precise and sensitive to single amino acid resolution. This program is to help in mutational studies leading to protein stabilisation.