Mutual information analysis of mutation,nonlinearity, and triple interactions in proteins

Mutations are the cause of several diseases as well as the underlying force of evolution. A thorough understanding of their biophysical consequences is essential. We present a computational framework for evaluating different levels of mutual information (MI) and its dependence on mutation. We used molecular dynamics trajectories of the third PDZ domain and its different mutations. Nonlinear MI between all residue pairs are calculated by tensor Hermite polynomials up to the fifth order and compared with results from multivariate Gaussian distribution of joint probabilities. We show that MI is written as the sum of a Gaussian and a nonlinear component. Results for the PDZ domain show that the Gaussian term gives a sufficiently accurate representation of MI when compared with nonlinear terms up to the fifth order. Changes in MI between residue pairs show the characteristic patterns resulting from specific mutations. Emergence of new peaks in the MI versus residue index plots of mutated PDZ shows how mutation may change allosteric pathways. Triple correlations are characterized by evaluating MI between triplets of residues. We observed that certain triplets are strongly affected by mutation. Susceptibility of residues to perturbation is obtained by MI and discussed in terms of linear response theory.     

Creating artificial human genomes using generative neural networks

Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create realistic synthetic data is still under-exploited in genetics and absent from population genetics. Yet a known limitation in the field is the reduced access to many genetic databases due to concerns about violations of individual privacy, although they would provide a rich resource for data mining and integration towards advancing genetic studies. In this study, we demonstrated that deep generative adversarial networks (GANs) and restricted Boltzmann machines (RBMs) can be trained to learn the complex distributions of real genomic datasets and generate novel high-quality artificial genomes (AGs) with none to little privacy loss. We show that our generated AGs replicate characteristics of the source dataset such as allele frequencies, linkage disequilibrium, pairwise haplotype distances and population structure. Moreover, they can also inherit complex features such as signals of selection. To illustrate the promising outcomes of our method, we showed that imputation quality for low frequency alleles can be improved by data augmentation to reference panels with AGs and that the RBM latent space provides a relevant encoding of the data, hence allowing further exploration of the reference dataset and features for solving supervised tasks. Generative models and AGs have the potential to become valuable assets in genetic studies by providing a rich yet compact representation of existing genomes and high-quality, easy-access and anonymous alternatives for private databases.     

In Vitro Genotoxic and Antigenotoxic Effects of Ten Novel Synthesized 4-Thiazolidinone Derivatives

Heterocyclic compounds are found in a variety of drug molecules, and bioactive natural products. 4-Thiazolidinones (4-TZDs), which represent an important class of heterocyclic compounds, are of great interest today with their diverse bioactivities. In this study, ten novel 4-TZD derivatives ( C1 – C10 ) were synthesized, characterized by spectroscopic techniques, and their genotoxic, and antigenotoxic properties were investigated in vitro using the Ames Salmonella/microsome mutagenicity assay in the concentration range of 0.2–1.0 mM/plate. The results revealed that none of the compounds were mutagenic on the three different Salmonella typhimurium strains up to the highest concentration tested. Furthermore, in our study, C1 , C4 , C6 , and C9 showed significant, ranging from moderate to strong, antigenotoxic effects against mutagen-induced DNA damage at relatively higher doses. Among these, C4 had the best potential to inhibit the number of revertant colonies induced by 9-aminoacridine (9-AA), with a maximum inhibition rate of 47.9 % for 1.0 mM/plate. As a result, preliminary knowledge about the safety of the use of ten novel synthesized 4-TZD compounds likely to exhibit many bioactivities was obtained in this study. In addition, the significant in vitro antimutagenic activity of some derivatives increases the importance of studies for the development of new pharmacological agents for cancer prevention.     

Optothermally Controlled Charge Transfer Plasmons in Au-Ge<Subscript>2</Subscript>Sb<Subscript>2</Subscript>Te<Subscript>5</Subscript> Core-Shell Dimers

Functional and reversible plasmonic resonances across the visible and near-infrared spectrum have opened new avenues for developing advanced next-generation nanophotonic devices. In this study, by using optothermally controlled phase-change material (PCM) for plasmonic nanostructures, we successfully induced highly tunable charge transfer plasmon (CTP) resonance modes. To this end, we have chosen a two-member dimer assembly consisting of gold cores and Ge₂Sb₂Te₅ (GST) shells in distant, touching, and overlapping regimes. We show that switching between amorphous (dielectric) and crystalline (conductive) phases of GST allows for achieving tunable dipolar and CTP resonances and enables an effective interplay between these modes along the near-infrared spectrum. By analyzing electromagnetically calculated spectral responses for the dimer antenna in tunneling and direct charge transfer regimes, we confirmed that the induced CTPs in touching and overlapping regimes are highly controllable and pronounced in comparison to the quantum tunneling regime. We also use the precise, fast, and controllable switching between dipolar and CTP resonant modes to develop a telecommunication switch based on a simple metallodielectric dimer. The proposed structures can help designing optothermally controlled devices without morphological variations in the geometry of the design, and having strong potential for advanced plasmon modulation and fast data routing.     

Synthesis of Peptide Mediated Au Core–Ag Shell Nanoparticles as Surface-Enhanced Raman Scattering Labels

As the fundamental understanding of metal–light interactions gains solid grounds, further research has been devoted to construct novel structures that take full advantage of such unique interactions, which is called plasmonics. In this report, the preparation of Au–Ag core–shell structures obtained by coating the Au surface with peptide and Raman reporter molecule and depositing an Ag layer on it is reported. The prepared Au–Ag NPs are tested for their surface-enhanced Raman scattering (SERS) performance. The negatively charged peptides with three different lengths, which are 3 (P1), 15 (P2), and 21 (P3) amino acid long, were chemically attached to 13 nm AuNPs along with Raman reporter molecule, carboxytetramethylrhodamine, and these modified AuNPs were coated with three different shell thickness of Ag metal. The prepared Au–Ag NPs were tested for their SERS performance and found that the Au–Ag NPs prepared with P2 and thickest shell performs best as SERS label.