A dynamical view of protein-protein complexes: Studies by molecular dynamics simulations

A whole-cell platform for discovering synthetic cell adhesion molecules in bacteria

Developing programmable bacterial cell-cell adhesion is of significant interest due to its versatile applications. Current methods that rely on presenting cell adhesion molecules (CAMs) on bacterial surfaces are limited by the lack of a generalizable strategy to identify such molecules targeting bacterial membrane proteins in their natural states. Here, we introduce a whole-cell screening platform designed to discover CAMs targeting bacterial membrane proteins within a synthetic bacteria-displayed nanobody library. Leveraging the potency of the bacterial type IV secretion system-a contact-dependent DNA delivery nanomachine-we have established a positive feedback mechanism to selectively enrich for bacteria displaying nanobodies that target antigen-expressing cells. Our platform successfully identified functional CAMs capable of recognizing three distinct outer membrane proteins (TraN, OmpA, OmpC), demonstrating its efficacy in CAM discovery. This approach holds promise for engineering bacterial cell-cell adhesion, such as directing the antibacterial activity of programmed inhibitor cells toward target bacteria in mixed populations.

Inactivation mechanisms on pectin methylesterase by high pressure processing combined with its recombinant inhibitor

High pressure processing (HPP) juice often experiences cloud loss during storage, caused by the activity of pectin methylesterase (PME). The combination of HPP with natural pectin methylesterase inhibitor (PMEI) could improve juice stability. However, extracting natural PMEI is challenging. Gene recombination technology offers a solution by efficiently expressing recombinant PMEI from Escherichia coli and Pichia pastoris. Experimental and molecular dynamics simulation were conducted to investigate changes in activity, structure, and interaction of PME and recombinant PMEI during HPP. The results showed PME retained high residual activity, while PMEI demonstrated superior pressure resistance. Under HPP, PMEI's structure remained stable, while the N-terminus of PME's α-helix became unstable. Additionally, the helix at the junction with the PME/PMEI complex changed, thereby affecting its binding. Furthermore, PMEI competed with pectin for active sites on PME, elucidating. The potential mechanism of PME inactivation through the synergistic effects of HPP and PMEI.

Exploring the Conformational Ensembles of Protein-Protein Complex with Transformer-Based Generative Model

Protein-protein interactions are the basis of many protein functions, and understanding the contact and conformational changes of protein-protein interactions is crucial for linking the protein structure to biological function. Although difficult to detect experimentally, molecular dynamics (MD) simulations are widely used to study the conformational ensembles and dynamics of protein-protein complexes, but there are significant limitations in sampling efficiency and computational costs. In this study, a generative neural network was trained on protein-protein complex conformations obtained from molecular simulations to directly generate novel conformations with physical realism. We demonstrated the use of a deep learning model based on the transformer architecture to explore the conformational ensembles of protein-protein complexes through MD simulations. The results showed that the learned latent space can be used to generate unsampled conformations of protein-protein complexes for obtaining new conformations complementing pre-existing ones, which can be used as an exploratory tool for the analysis and enhancement of molecular simulations of protein-protein complexes.

An atomistic model of myosin interacting heads motif dynamics and their modification by 2'-deoxy-ADP

The contraction of striated muscle is driven by cycling myosin motor proteins embedded within the thick filaments of sarcomeres. In addition to cross-bridge cycling with actin, these myosin proteins can enter an inactive, sequestered state in which the globular S1 heads rest along the thick filament surface and are unable to perform motor activities. Structurally, this state is called the interacting heads motif (IHM) and is a critical conformational state of myosin that regulates muscle contractility and energy expenditure. Structural perturbation of the sequestered state via missense mutations can pathologically disrupt the mechanical performance of muscle tissue. Thus, the IHM state has become a target for therapeutic intervention. An ATP analogue called 2'-deoxy-ATP (dATP) is a potent myosin activator which destabilizes the IHM. Here we use molecular dynamics simulations to study the molecular mechanisms by which dATP modifies the structure and dynamics of myosin in a sequestered state. Simulations with IHM containing ADP.Pi in both nucleotide binding pockets revealed residual dynamics in an otherwise 'inactive' and 'sequestered' state of a motor protein. Replacement of ADP.Pi by dADP.Pi triggered a series of structural changes that modify the protein-protein interface that stabilizes the sequestered state, and changes to this interface were accompanied by allosteric changes in remote regions of the protein complex. A comparative analysis of these dynamics predicted new structural sites that may affect IHM stability.

Dynamics of Protein-RNA Interfaces Using All-Atom Molecular Dynamics Simulations

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

Identifying inflammation-related targets of natural lactones using network pharmacology, molecular modeling and in vitro approaches

Natural lactones have been used in traditional and folklore medicine for centuries owing to their anti-inflammatory properties. The study uses a multifaceted approach to identify lead anti-inflammatory lactones from the SISTEMATX natural products database. The study analyzed the natural lactone database, revealing 18 lactones linked to inflammation targets. The primary targets were PTGES, PTGS1, COX-2, ALOX5 and IL1B. STX 12273 was the best hit, with the lowest binding energy and potential for inhibiting the COX-2 enzyme. The study suggested natural lactone, STX 12273, from the SISTEMATX database with anti-inflammatory potential and postulated its use for inflammation treatment or prevention.Communicated by Ramaswamy H. Sarma.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.