Dynamic Coupling and Entropy Changes in KRAS G12D Mutation: Insights into Molecular Flexibility, Allostery and Function.

The oncogenic G12D mutation in KRAS is a major driver of cancer progression, yet the complete mechanism by which this mutation alters protein dynamics and function remains incompletely understood. Here, we investigate how the G12D mutation alters KRAS's conformational landscape and residue-residue interactions using molecular dynamics simulations coupled with entropy calculations and mutual information (MI) analysis. We demonstrate that the mutation increases local entropy at key functional residues (D12, Y32, G60, and Q61), and introduces new peaks to the Ramachandran angles, disrupting the precise structural alignment necessary for GTP hydrolysis.

DFT Study of the Mechanism of Selective Hydrogenation of Acetylene by Rhodium Single-Atom Catalyst Supported on HY Zeolite.

The selectivity of acetylene hydrogenation by the Rh single-atom catalyst (SAC) supported on HY zeolite was investigated using density functional theory (DFT) and a 5/83T quantum mechanics/molecular mechanics (QM/MM) embedded cluster model. The calculated activation barrier (ΔG) for the oxidative addition of dihydrogen to the Rh metal center (15.9 kcal/mol) is lower in energy than that for the σ-bond metathesis of dihydrogen to the Rh-C bond (22.

Sis2 regulates yeast replicative lifespan in a dose-dependent manner.

Application of microfluidic platforms facilitated high-precision measurements of yeast replicative lifespan (RLS); however, comparative quantification of lifespan across strain libraries has been missing. Here we microfluidically measure the RLS of 307 yeast strains, each deleted for a single gene. Despite previous reports of extended lifespan in these strains, we found that 56% of them did not actually live longer than the wild-type; while the remaining 44% showed extended lifespans, the degree of extension was often different from what was previously reported.

Advancing CH/H separation with covalent organic frameworks by combining molecular simulations and machine learning.

A high-throughput computational screening approach combined with machine learning (ML) was introduced to unlock the potential of both synthesized and hypothetical COFs (hypoCOFs) for adsorption-based CH/H separation. We studied 597 synthesized COFs for adsorption of a CH/H mixture using Grand Canonical Monte Carlo (GCMC) simulations under pressure-swing adsorption (PSA) and vacuum-swing adsorption (VSA) conditions. Based on the simulation results, the CH/H selectivities, CH working capacities, adsorbent performance scores, and regenerabilities of the synthesized COFs were assessed and the structural properties of the top-performing COFs were identified.

MOF/COF hybrids as next generation materials for energy and biomedical applications.

The rapid increase in the number and variety of metal organic frameworks (MOFs) and covalent organic frameworks (COFs) has led to groundbreaking applications in the field of materials science and engineering. New MOF/COF hybrids combine the outstanding features of MOF and COF structures, such as high crystallinities, large surface areas, high porosities, the ability to decorate the structures with functional groups, and improved chemical and mechanical stabilities. These new hybrid materials offer promising performances for a wide range of applications including catalysis, energy storage, gas separation, and nanomedicine.

Synergistic Effect of Plasmonic Gold Nanoparticles Decorated Carbon Nanotubes in Quantum Dots/TiO for Optoelectronic Devices.

Here, a facile approach to enhance the performance of solar-driven photoelectrochemical (PEC) water splitting is described by means of the synergistic effects of a hybrid network of plasmonic Au nanoparticles (NPs) decorated on multiwalled carbon nanotubes (CNTs). The device based on TiO-Au:CNTs hybrid network sensitized with colloidal CdSe/(CdSe S )/(CdS) core/alloyed shell quantum dots (QDs) yields a saturated photocurrent density of 16.10 ± 0.

Improving CO Separation Performance of MIL-53(Al) by Incorporating 1--Butyl-3-Methylimidazolium Methyl Sulfate.

1--Butyl-3-methylimidazolium methyl sulfate is incorporated into MIL-53(Al). Detailed characterization is done by X-ray fluorescence, Brunauer-Emmett-Teller surface area, scanning electron microscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, and thermogravimetric analysis. Results show that ionic liquid (IL) interacts directly with the framework, significantly modifying the electronic environment of MIL-53(Al).

An Electrochemical Gelation Method for Patterning Conductive PEDOT:PSS Hydrogels.

Due to their high water content and macroscopic connectivity, hydrogels made from the conducting polymer PEDOT:PSS are a promising platform from which to fabricate a wide range of porous conductive materials that are increasingly of interest in applications as varied as bioelectronics, regenerative medicine, and energy storage. Despite the promising properties of PEDOT:PSS-based porous materials, the ability to pattern PEDOT:PSS hydrogels is still required to enable their integration with multifunctional and multichannel electronic devices. In this work, a novel electrochemical gelation ("electrogelation") method is presented for rapidly patterning PEDOT:PSS hydrogels on any conductive template, including curved and 3D surfaces.

Red Mud as an Efficient, Stable, and Cost-Free Catalyst for COx-Free Hydrogen Production from Ammonia.

Red mud, one of the mostly produced industrial wastes, was converted into a catalyst with exceptionally high and stable performance for hydrogen production from ammonia. Results showed that iron species produced after reduction of the HCl digested red mud were converted into ε-Fe2N during the induction period of ammonia decomposition reaction at 700 °C. The catalytic performance measurements indicated that the modified red mud catalyst provides a record high hydrogen production rate for a non-noble metal catalyst at this temperature.

Computational Methods for MOF/Polymer Membranes.

Metal-organic framework (MOF)/polymer mixed matrix membranes (MMMs) have received significant interest in the last decade. MOFs are incorporated into polymers to make MMMs that exhibit improved gas permeability and selectivity compared with pure polymer membranes. The fundamental challenge in this area is to choose the appropriate MOF/polymer combinations for a gas separation of interest.

Thermal Stability Limits of Imidazolium Ionic Liquids Immobilized on Metal-Oxides.

Thermal stability limits of 33 imidazolium ionic liquids (ILs) immobilized on three of the most commonly used high surface area metal-oxides, SiO2, γ-Al2O3, and MgO, were investigated. ILs were chosen from a family of 13 cations and 18 anions. Results show that the acidity of C2H of an imidazolium ring is one of the key factors controlling the thermal stability.

Modeling protein assemblies in the proteome.

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high- and low-resolution scales.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale.

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than "blind" docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures.

Constructing structural networks of signaling pathways on the proteome scale.

Proteins function through their interactions, and the availability of protein interaction networks could help in understanding cellular processes. However, the known structural data are limited and the classical network node-and-edge representation, where proteins are nodes and interactions are edges, shows only which proteins interact; not how they interact. Structural networks provide this information.

Expanding the conformational selection paradigm in protein-ligand docking.

Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein-protein, protein-DNA, protein-RNA, and protein-small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery.

Allostery and population shift in drug discovery.

Proteins can exist in a large number of conformations around their native states that can be characterized by an energy landscape. The landscape illustrates individual valleys, which are the conformational substates. From the functional standpoint, there are two key points: first, all functionally relevant substates pre-exist; and second, the landscape is dynamic and the relative populations of the substates will change following allosteric events.