A General Picture of Cucurbit[8]uril Host–Guest Binding: Recalibrating Bonded Interactions

Computational Modeling of Pharmaceuticals with an Emphasis on Crossing the Blood-Brain Barrier

The discovery and development of new pharmaceutical drugs is a costly, time-consuming, and highly manual process, with significant challenges in ensuring drug bioavailability at target sites. Computational techniques are highly employed in drug design, particularly to predict the pharmacokinetic properties of molecules. One major kinetic challenge in central nervous system drug development is the permeation through the blood-brain barrier (BBB). Several different computational techniques are used to evaluate both BBB permeability and target delivery. Methods such as quantitative structure-activity relationships, machine learning models, molecular dynamics simulations, end-point free energy calculations, or transporter models have pros and cons for drug development, all contributing to a better understanding of a specific characteristic. Additionally, the design (assisted or not by computers) of prodrug and nanoparticle-based drug delivery systems can enhance BBB permeability by leveraging enzymatic activation and transporter-mediated uptake. Neuroactive peptide computational development is also a relevant field in drug design, since biopharmaceuticals are on the edge of drug discovery. By integrating these computational and formulation-based strategies, researchers can enhance the rational design of BBB-permeable drugs while minimizing off-target effects. This review is valuable for understanding BBB selectivity principles and the latest in silico and nanotechnological approaches for improving CNS drug delivery.

True Dynamics of Pillararene Host-Guest Binding

Accurate modeling of host-guest systems is challenging in modern computational chemistry. It requires intermolecular interaction patterns to be correctly described and, more importantly, the dynamic behaviors of macrocyclic hosts to be accurately modeled. Pillar[n]arenes as a crucial family of macrocycles play a critical role in host-guest chemistry and biomedical applications. The carboxylated form with 6 or 7 repeating units is of high popularity due to increased solubility and the compatibility between cavity size and drugs. While prefitted transferable force fields are dominantly applied in host-guest modeling, their reliability and accuracy for macrocyclic hosts remain unjustified. In the current work, based on solid numerical evidence about energetics and dynamics, we prove that all transferable force fields fail to provide a correct description of host dynamics for the most popular carboxylated pillararenes. Therefore, all existing simulation reports on this host family could be biased due to the unsuitability of the force-field description. Such huge modeling problems do not occur in other host families that are relatively rigid (e.g., octa acids and cucurbiturils), highlighting the difficulties in modeling pillararene host-guest interactions. To pursue the true picture of the pillararene dynamics and host-guest binding, we fit high-quality molecule-specific parameters for the carboxylated pillararene based on ab initio calculations and perform an exhaustive conformational search of host-guest binding modes with advanced sampling techniques. We provide estimates of binding thermodynamics, report the true dynamic behavior of the WP6 host in the bound and unbound states, and reveal a general multimodal binding behavior of pillararene host-guest complexes. The current work serves as a critical step toward a reliable all-atom description of pillararene host-guest coordination.

All-Atom Perspective of the DENV-3 Methyltransferase Inhibition Mechanism

The Dengue virus (DENV) is an enveloped, single-stranded RNA virus with several antigenically distinct serotypes (DENV-1 to DENV-5). Dengue fever, as a major public health threat transmitted by mosquitoes, affects millions of people worldwide (especially in tropical and subtropical regions). Toward drug developments of DENV, the nonstructural protein 5 methyltransferase (MTase) serves as an attractive target. The MTase transforms S-adenosyl methionine to S-adenosyl homocysteine (SAH), which is thereby selected as the target with which external drugs compete with. In this work, using alanine scanning with generalized Born and interaction entropy (ASGB-IE), we provide an all-atom perspective of the protein-ligand interactions formed by DENV-3 MTase and SAH derivatives. Residues with consistently high contributions to stabilization are summarized, and the general DENV-3 MTase inhibition mechanism is elucidated. Additionally, the mutational impact on binding thermodynamics is found to be entropy-driven. We also highlight the advantage of the ASGB-IE method for affinity estimation compared to standard end-point protocols, which is highly related to the selection of interfacial residues in free energy estimation. Finally, we performed a thorough scan of the mutational space on critical sites (saturation mutagenesis) and identified 14 mutants causing resistance to the current inhibitors.

Conformational States of the GDP- and GTP-Bound HRAS Affected by A59E and K117R: An Exploration from Gaussian Accelerated Molecular Dynamics

The HRAS protein is considered a critical target for drug development in cancers. It is vital for effective drug development to understand the effects of mutations on the binding of GTP and GDP to HRAS. We conducted Gaussian accelerated molecular dynamics (GaMD) simulations and free energy landscape (FEL) calculations to investigate the impacts of two mutations (A59E and K117R) on GTP and GDP binding and the conformational states of the switch domain. Our findings demonstrate that these mutations not only modify the flexibility of the switch domains, but also affect the correlated motions of these domains. Furthermore, the mutations significantly disrupt the dynamic behavior of the switch domains, leading to a conformational change in HRAS. Additionally, these mutations significantly impact the switch domain's interactions, including their hydrogen bonding with ligands and electrostatic interactions with magnesium ions. Since the switch domains are crucial for the binding of HRAS to effectors, any alterations in their interactions or conformational states will undoubtedly disrupt the activity of HRAS. This research provides valuable information for the design of drugs targeting HRAS.

Screening Power of End-Point Free-Energy Calculations in Cucurbituril Host-Guest Systems

End-point free-energy methods as an indispensable component in virtual screening are commonly recognized as a tool with a certain level of screening power in pharmaceutical research. While a huge number of records could be found for end-point applications in protein-ligand, protein-protein, and protein-DNA complexes from academic and industrial reports, up to now, there is no large-scale benchmark in host-guest complexes supporting the screening power of end-point free-energy techniques. A good benchmark requires a data set of sufficient coverage of pharmaceutically relevant chemical space, a long-time sampling length supporting the trajectory approximation of the ensemble average, and a sufficient sample size of receptor-acceptor pairs to stabilize the performance statistics. In this work, selecting a popular family of macrocyclic hosts named cucurbiturils, we construct a large data set containing 154 host-guest pairs, perform extensive end-point sampling of several hundred nanosecond lengths for each system, and extract the free-energy estimates with a variety of end-point free-energy techniques, including the advanced three-trajectory dielectric-constant-variable regime proposed in our recent work. The best-performing end-point protocol employs GAFF2 for solute descriptions, the three-trajectory end-point sampling regime, and the MM/GBSA Hamiltonian in free-energy extraction, achieving a high ranking metrics of Kendall τ > 0.6, a Pearlman predictive index of ∼0.8, and a high scoring power of Pearson r > 0.8. The current project as the first large-scale systematic benchmark of end-point methods in host-guest complexes in academic publications provides solid evidence of the applicability of end-point techniques and direct guidance of computational setups in practical host-guest systems.

Host Dynamics under General-Purpose Force Fields

Macrocyclic hosts as prototypical receptors to gaseous and drug-like guests are crucial components in pharmaceutical research. The external guests are often coordinated at the center of these macromolecular containers. The formation of host-guest coordination is accompanied by the broken of host-water and host-ion interactions and sometimes also involves some conformational rearrangements of the host. A balanced description of various components of interacting terms is indispensable. However, up to now, the modeling community still lacks a general yet detailed understanding of commonly employed general-purpose force fields and the host dynamics produced by these popular selections. To fill this critical gap, in this paper, we profile the energetics and dynamics of four types of popular macrocycles, including cucurbiturils, pillararenes, cyclodextrins, and octa acids. The presented investigations of force field definitions, refitting, and evaluations are unprecedently detailed. Based on the valuable observations and insightful explanations, we finally summarize some general guidelines on force field parametrization and selection in host-guest modeling.

Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies

β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward the treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively determine the identification mechanism of BACE1 for three inhibitors, 60W, 954 and 60X. The analyses of MD trajectories indicated that the presence of three inhibitors influences the structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward the treatment of AD.