The role of ETFS amino acids on the stability and inhibition of p53-MDM2 complex of anticancer p53-derivatives peptides: Density functional theory and molecular docking studies.

Cancer is one of the leading causes of mortality in the world. Despite the existence of diverse antineoplastic treatments, these do not possess the expected efficacy in many cases. Knowledge of the molecular mechanisms involved in tumor processes allows the identification of a greater number of therapeutic targets employed in the study of new anticancer drugs. In the last decades, peptide-based therapy design using computational chemistry has gained importance in the field of oncology therapeutics. This work aims to evaluate the electronic structure, physicochemical properties, stability, and inhibition of ETFS amino acids and peptides derived from the p53-MDM2 binding domain with action in cancer cells; by means of chemical descriptors at the DFT-BHandHLYP level in an aqueous solution, and its intermolecular interactions through molecular docking studies. The results show that The ETFS fragment plays a critical role in the intermolecular interactions. Thus, the amino acids E17, T18 and S20 increase intermolecular interactions through hydrogen bonds and enhance structural stability. F19, W23 and V25 enhance the formation of the alpha-helix. The hydrogen bonds formed by the backbone atoms for PNC-27, PNC-27-B and PNC-28 stabilize the α-helices more than hydrogen bonds formed by the side chains atoms. Also, molecular docking indicated that the PNC27B-MDM2, PNC28B-MDM2, PNC27-MDM2 and PNC28A-MDM2 complexes show the best binding energy. Therefore, DFT and molecular docking studies showed that the proposed peptides: PNC-28B, PNC-27B and PNC-28A could inhibit the binding of MDM2 to the p53 protein, decreasing the translocation and degradation of p53 native protein.

Generalized Boussinesq-Scriven surface fluid model with curvature dissipation for liquid surfaces and membranes.

Curvature dissipation is relevant in synthetic and biological processes, from fluctuations in semi-flexible polymer solutions, to buckling of liquid columns, tomembrane cell wall functioning. We present a micromechanical model of curvature dissipation relevant to fluid membranes and liquid surfaces based on a parallel surface parameterization and a stress constitutive equation appropriate for anisotropic fluids and fluid membranes.The derived model, aimed at high curvature and high rate of change of curvature in liquid surfaces and membranes, introduces additional viscous modes not included in the widely used 2D Boussinesq-Scriven rheological constitutive equation for surface fluids.The kinematic tensors that emerge from theparallel surface parameterization are the interfacial rate of deformation and the surface co-rotational Zaremba-Jaumann derivative of the curvature, which are used to classify all possibledissipative planar and non-planar modes. The curvature dissipation function that accounts for bending, torsion and twist rates is derived and analyzed under several constraints, including the important inextensional bending mode.A representative application of the curvature dissipation model to the periodic oscillation in nano-wrinkled outer hair cells show how and why curvature dissipation decreases with frequency, and why the 100kHz frequency range is selected. These results contribute to characterize curvature dissipation in membranes and liquid surfaces.

Invited review liquid crystal models of biological materials and silk spinning.

A review of thermodynamic, materials science, and rheological liquid crystal models is presented and applied to a wide range of biological liquid crystals, including helicoidal plywoods, biopolymer solutions, and in vivo liquid crystals. The distinguishing characteristics of liquid crystals (self-assembly, packing, defects, functionalities, processability) are discussed in relation to biological materials and the strong correspondence between different synthetic and biological materials is established. Biological polymer processing based on liquid crystalline precursors includes viscoelastic flow to form and shape fibers. Viscoelastic models for nematic and chiral nematics are reviewed and discussed in terms of key parameters that facilitate understanding and quantitative information from optical textures and rheometers. It is shown that viscoelastic modeling the silk spinning process using liquid crystal theories sheds light on textural transitions in the duct of spiders and silk worms as well as on tactoidal drops and interfacial structures. The range and consistency of the predictions demonstrates that the use of mesoscopic liquid crystal models is another tool to develop the science and biomimetic applications of mesogenic biological soft matter.