Effect of the Water Model in Simulations of Protein-Protein Recognition and Association

Advanced sampling simulations of coupled folding and binding of phage P22 N-peptide to boxB RNA

Protein-RNA interactions are crucially important for numerous cellular processes and often involve coupled folding and binding of peptide segments upon association. The Nut-utilization site (N)-protein of bacteriophages contains an N-terminal arginine-rich motif that undergoes such a folding transition upon binding to the boxB RNA hairpin loop target structure. Molecular dynamics free energy simulations were used to calculate the absolute binding free energy of the N-peptide of bacteriophage P22 in complex with the boxB RNA hairpin motif at different salt concentrations and using two different water force field models. We obtained good agreement with experiment also at different salt concentrations for the TIP4P-D water model that has a stabilizing effect on unfolded protein structures. It allowed us to estimate the free energy contribution resulting from restricting the molecules' spatial and conformational freedom upon binding, which makes a large opposing contribution to binding. In a second set of umbrella sampling simulations to dissociate/associate the complex along a separation coordinate, we analyzed the onset of preorientation of the N-peptide and onset of structure formation relative to the RNA and its dependence on the salt concentration. Peptide orientation and conformational transitions are significantly coupled to the first contact formation between peptide and RNA. The initial contacts are mostly formed between peptide residues and the boxB hairpin loop nucleotides. A complete transition to an α-helical bound peptide conformation occurs only at a late stage of the binding process a few angstroms before the complexed state has been reached. However, the N-peptide orients also at distances beyond the contact distance such that the sizable positive charge points toward the RNA's center-of-mass. Our result may have important implications for understanding protein- and peptide-RNA complex formation frequently involving coupled folding and association processes.

In silico approaches supporting drug repurposing for Leishmaniasis: a scoping review

The shortage of treatment options for leishmaniasis, especially those easy to administer and viable for deployment in the world's poorest regions, highlights the importance of employing these strategies to cost-effectively investigate repurposing candidates. This scoping review aims to map the studies using in silico methodologies for drug repurposing against leishmaniasis. This study followed JBI recommendations for scoping reviews. Articles were searched on PubMed, Scopus, and Web of Science databases using keywords related to leishmaniasis and in silico methods for drug discovery, without publication date restrictions. The selection was based on primary studies involving computational methods for antileishmanial drug repurposing. Information about methodologies, obtained data, and outcomes were extracted. After the full-text appraisal, 34 studies were included in this review. Molecular docking was the preferred method for evaluating repurposing candidates (n=25). Studies reported 154 unique ligands and 72 different targets, sterol 14-alpha demethylase and trypanothione reductase being the most frequently reported. In silico screening was able to correctly pinpoint some known active pharmaceutical classes and propose previously untested drugs. Fifteen drugs investigated in silico exhibited low micromolar inhibition (IC50 < 10 µM) of Leishmania spp. in vitro. In conclusion, several in silico repurposing candidates are yet to be investigated in vitro and in vivo. Future research could expand the number of targets screened and employ advanced methods to optimize drug selection, offering new starting points for treatment development. See also the graphical abstract(Fig. 1).

The Influence of Ionic Environment on Nucleosome-Mica Interactions Revealed via Molecular Dynamics Simulations

Mica serves as a crucial substrate in Atomic Force Microscopy (AFM) studies for visualizing and characterizing nucleosomes. Nucleosomes interact with the negatively charged mica surface via adsorbed cations. However, the specific influences of monovalent and divalent cations on nucleosome adsorption to the mica surface remain unclear. In this study, we investigated the binding of nucleosomes to the mica surface in the presence of monovalent potassium ions and divalent magnesium ions using molecular dynamics simulations. We also explored the impact of pre-treated mica surfaces on nucleosome binding and structure. Our findings reveal that nucleosome-mica interactions vary depending on the cations present, resulting in distinct effects on nucleosome structure. Notably, nucleosomes bind effectively to a mica surface in the presence of potassium ions with minimal structural perturbations.

PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.

Lessons Learned from Multiobjective Automatic Optimizations of Classical Three-Site Rigid Water Models Using Microscopic and Macroscopic Target Experimental Observables

The development of accurate water models is of primary importance for molecular simulations. Despite their intrinsic approximations, three-site rigid water models are still ubiquitously used to simulate a variety of molecular systems. Automatic optimization approaches have been recently used to iteratively refine three-site water models to fit macroscopic (average) thermodynamic properties, providing state-of-the-art three-site models that still present some deviations from the liquid water properties. Here, we show the results obtained by automatically optimizing three-site rigid water models to fit a combination of microscopic and macroscopic experimental observables. We use Swarm-CG, a multiobjective particle-swarm-optimization algorithm, for training the models to reproduce the experimental radial distribution functions of liquid water at various temperatures (rich in microscopic-level information on, e.g., the local orientation and interactions of the water molecules). We systematically analyze the agreement of these models with experimental observables and the effect of adding macroscopic information to the training set. Our results demonstrate how adding microscopic-rich information in the training of water models allows one to achieve state-of-the-art accuracy in an efficient way. Limitations in the approach and in the approximated description of water in these three-site models are also discussed, providing a demonstrative case useful for the optimization of approximated molecular models, in general.

Investigation of the interaction behavior between quercetin and pepsin by spectroscopy and MD simulation methods

The ability of a therapeutic compound to bind to proteins is critical for characterizing its therapeutic impacts. We have selected quercetin (Qu), a most common flavonoid found in plants and vegetables among therapeutic molecules that are known to have anti-inflammatory, antioxidant, anti-genotoxic, and anti-cancer effects. The current study aimed to see how quercetin interacts with pepsin in an aqueous environment under physiological conditions. Absorbance and emission spectroscopy, circular dichroism (CD), and kinetic methods, as well as molecular dynamic (MD) simulation and docking, were applied to study the effects of Qu on the structure, dynamics, and kinetics of pepsin. Stern-Volmer (K_sv) constants were computed for the pepsin-quercetin complex at three temperatures, showing that Qu reduces enzyme emission spectra using a static quenching. With Qu binding, the V_max and the k_cat/K_m values decreased. UV-vis absorption spectra, fluorescence emission spectroscopy, and CD result indicated that Qu binding to pepsin leads to microenvironmental changes around the enzyme, which can alter the enzyme's secondary structure. Therefore, quercetin caused alterations in the function and structure of pepsin. Thermodynamic parameters, MD binding, and docking simulation analysis showed that non-covalent reactions, including the hydrophobic forces, played a key role in the interaction of Qu with pepsin. The findings conclude of spectroscopic experiments were supported by molecular dynamics simulations and molecular docking results.

Temperature dependence of thermodynamic, dynamical, and dielectric properties of water models

We investigate the temperature dependence of thermodynamic (density and isobaric heat capacity), dynamical (self-diffusion coefficient and shear viscosity), and dielectric properties of several water models, such as the commonly employed TIP3P water model, the well-established four-point water model TIP4P-2005, and the recently developed four-point water model TIP4P-D. We focus on the temperature range of interest for the field of computational biophysics and soft matter (280–350 K). The four-point water models lead to a spectacularly improved agreement with experimental data, strongly suggesting that the use of more modern parameterizations should be favored compared to the more traditional TIP3P for modeling temperature-dependent phenomena in biomolecular systems.

Molecular dynamics simulations of structural and dynamical aspects of DNA hydration water

Water is a remarkable liquid, both because of it is intriguing but also because of its importance. Water plays a key role on the structure and function of biological molecules, but on the other hand also the structure and dynamics of water are deeply influenced by its interactions with biological molecules, specially at low temperatures, where water's anomalies are enhanced. Here we present extensive molecular dynamics simulations of water hydrating a oligonucleotide down to very low temperatures (supercooled water), comparing four water models and analyzing the water structure and dynamics in different domains: water in the minor groove, water in the major groove and bulk water. We found that the water in the grooves is slowed down by the interactions with the nucleic acid and a hints of a dynamic transition regarding translational and orientational dynamics were found, specially for the water models TIP4P/2005 and TIP4P-Ew, which also showed the closest agreement with available experimental data. The behavior of water in such extreme conditions is relevant for the study of cryopreservation of biological tissues.

Identification of Novel Cannabinoid CB2 Receptor Agonists from Botanical Compounds and Preliminary Evaluation of Their Anti-Osteoporotic Effects

As cannabinoid CB2 receptors (CB2R) possess various pharmacological effects—including anti-epilepsy, analgesia, anti-inflammation, anti-fibrosis, and regulation of bone metabolism—without the psychoactive side effects induced by cannabinoid CB1R activation, they have become the focus of research and development of new target drugs in recent years. The present study was intended to (1) establish a double luciferase screening system for a CB2R modulator; (2) validate the agonistic activities of the screened compounds on CB2R by determining cAMP accumulation using HEK293 cells that are stably expressing CB2R; (3) predict the binding affinity between ligands and CB2 receptors and characterize the binding modes using molecular docking; (4) analyze the CB2 receptors–ligand complex stability, conformational behavior, and interaction using molecular dynamics; and (5) evaluate the regulatory effects of the screened compounds on bone metabolism in osteoblasts and osteoclasts. The results demonstrated that the screening system had good stability and was able to screen cannabinoid CB2R modulators from botanical compounds. Altogether, nine CB2R agonists were identified by screening from 69 botanical compounds, and these CB2R agonists exhibited remarkable inhibitory effects on cAMP accumulation and good affinity to CB2R, as evidenced by the molecular docking and molecular dynamics. Five of the nine CB2R agonists could stimulate osteoblastic bone formation and inhibit osteoclastic bone resorption. All these findings may provide useful clues for the development of novel anti-osteoporotic drugs and help elucidate the mechanism underlying the biological activities of CB2R agonists identified from the botanical materials.

Accurate Description of Protein-Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model

We used the PACSAB protein model, based on the implicit solvation approach, to simulate protein–protein recognition and study the effect of helical structure on the association of aggregating peptides. After optimization, the PACSAB force field was able to reproduce correctly both the correct binding interface in ubiquitin dimerization and the conformational ensemble of the disordered protein activator for hormone and retinoid receptor (ACTR). The PACSAB model allowed us to predict the native binding of ACTR with its binding partner, reproducing the refolding upon binding mechanism of the disordered protein.

Influence of water models on water movement through AQP1

Water diffusion through membrane proteins is a key aspect of cellular function. Essential processes of cellular metabolism are driven by osmotic pressure, which depends on water channels. Membrane proteins such as aquaporins (AQPs) are responsible for enabling water permeation through the cell membrane. AQPs are highly selective, allowing only water and relatively small polar molecules to cross the membrane. Experimentally, estimation of water flux through membrane proteins is still a challenge, and hence, accurate simulations of water permeation are of particular importance. We present a numerical study of water diffusion through AQP1 comparing three water models: TIP3P, OPC, and TIP4P/2005. Bulk diffusion, diffusion permeability, and osmotic permeability are computed and compared among all models. The results show that there are significant differences between TIP3P (a particularly widespread model for simulations of biological systems) and the more recently developed TIP4P/2005 and OPC models. We demonstrate that OPC and TIP4P/2005 reproduce protein-water interactions and dynamics in very good agreement with experimental data. From this study, we find that the choice of the water model has a significant effect on the computed water dynamics as well as its molecular behavior within a biological nanopore.