The development of an Amber-compatible organosilane force field for drug-like small molecules

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.

Graphite-Based Bio-Mimetic Nanopores for Protein Sequencing and Beyond

Protein sequencing using nanopores represents the next frontier in bio-analytics. However, linearizing unfolded proteins and controlling their translocation speed through solid-state nanopores pose significant challenges in protein sequencing. In order to address these issues, this work proposes a biomimetic graphite-based nanopore construction. These nanopores feature a nanometer-sized pore with a constriction zone, mimicking the structure of the α-hemolysin protein pore. Our all-atom Molecular Dynamics simulations demonstrate the high practical potential of these nanopores by revealing how their charge state renders them complete ion-selective and generates an electro-osmotic flow. This study shows that this nanopore construction can detect peptides at the single amino acid level by analyzing the ionic current traces generated as peptides traverse the nanopore. The novelty of the proposed nanopore lies in its ability to modulate the hydrodynamic drag induced by electro-osmotic flow, relative to the electro-phoretic force. This investigation reveals that tuning these forces helps to linearize translocating peptides and extend the residence time of individual amino acids at the constriction zone of the pore. This significantly enhances the detection and sequencing efficiency of the pore. Furthermore, the high relevance of the proposed nanopores is underscored for seawater desalination through electrodialysis and extends to ion separation under salinity gradients.

Enhanced Thermal Conductivity of Thermoplastic Polyimide Nanocomposites: Effect of Using Hexagonal Nanoparticles

Thermoplastic polyimides have garnered significant interest in the electronic and electrical industries owing to their performance characteristics. However, their relatively low thermal conductivity coefficients pose a challenge. To address this issue, this study focused on the properties of nanocomposites comprising two thermoplastic semicrystalline polyimides R-BAPB and BPDA-P3, one amorphous polyimide ULTEMTM, and hexagonal nanoparticles. Polyimide R-BAPB was synthesized based on 1,3-bis-(3',4-dicarboxyphenoxy)benzene (dianhydride R) and 4,4'-bis-(4'-aminophenoxy)biphenyl (BAPB diamine); polyimide BPDA-P3 was synthesized based on 3,3',4,4'-biphenyltetracarboxylic dianhydride (BPDA) and diamine 1,4-bis[4-(4-aminophenoxy)phenoxy]benzene (P3); and amorphous polyimide ULTEMTM was commercially produced by Sabic Innovative Plastics. Using microsecond-scale all-atom molecular dynamics simulations, the effects of incorporating hexagonal nanoparticles with enhanced thermal conductivity, such as graphene, graphene oxide, and boron nitride, on the structural and thermophysical characteristics of these materials were examined. The formation of stacked aggregates was found for graphene and hexagonal boron nitride nanoparticles. It was observed that graphene oxide nanoparticles exhibited a dispersion in polyimide binders that was higher than those in graphene and hexagonal boron nitride nanoparticles, leading to reduced translational mobility of polymer chains. Consequently, the decrease in polyimide chain mobility correlated with an increase in the glass transition temperature of the nanocomposites. Aggregates of nanoparticles formed a pathway for phonon transport, resulting in improved thermal conductivity in polyimide nanocomposites. An increase in the thermal conductivity coefficient of polyimide nanocomposites was observed when the concentration of graphene, graphene oxide, and hexagonal boron nitride nanofillers increased. The enhancement in thermal conductivity was found to be strongest when graphene nanoparticles were added.

The role of silicon in drug discovery: a review

This review aims to highlight the role of silicon in drug discovery. Silicon and carbon are often regarded as being similar with silicon located directly beneath carbon in the same group in the periodic table. That being noted, in many instances a clear dichotomy also exists between silicon and carbon, and these differences often lead to vastly different physiochemical and biological properties. As a result, the utility of silicon in drug discovery has attracted significant attention and has grown rapidly over the past decade. This review showcases some recent advances in synthetic organosilicon chemistry and examples of the ways in which silicon has been employed in the drug-discovery field.

Discovery of 4-(Arylethynyl)piperidine Derivatives as Potent Nonsaccharide O-GlcNAcase Inhibitors for the Treatment of Alzheimer's Disease

Inhibiting O-GlcNAcase and thereby up-regulation of the O-GlcNAc levels of tau was a potential approach for discovering AD treatments. Herein, a series of novel highly potent OGA inhibitors embracing a 4-(arylethynyl)piperidine moiety was achieved by capitalizing on the substrate recognition domain. Extensive structure-activity relationships resulted in compound 81 with significant enzymatic inhibition (IC50 = 4.93 ± 2.05 nM) and cellular potency (EC50 = 7.47 ± 3.96 nM in PC12 cells). It markedly increased the protein O-GlcNAcylation levels and reduced the phosphorylation on Ser199, Thr205, and Ser396 of tau in the OA-injured SH-SY5Y cell model, suggesting its potential role for AD treatment. In fact, an in vivo efficacy of ameliorating cognitive impairment was observed following treatment of APP/PS1 mice with compound 81 (100 mg/kg). Additionally, the appropriate plasma PK and beneficial BBB penetration properties were also observed. Compound 81 deserves to be further explored as an anti-AD agent.

Peptide Drug Design Using Alchemical Free Energy Calculation: An Application and Validation on Agonists of Ghrelin Receptor

With recent large-scale applications and validations, the relative binding free energy (RBFE) calculated using alchemical free energy methods has been proven to be an accurate measure to probe the binding of small-molecule drug candidates. On the other hand, given the flexibility of peptides, it is of great interest to find out whether sufficient sampling could be achieved within the typical time scale of such calculation, and a similar level of accuracy could be reached for peptide drugs. However, the systematic evaluation of such calculations on protein-peptide systems has been less reported. Most reported studies of peptides were restricted to a limited number of data points or lacking experimental support. To demonstrate the applicability of the alchemical free energy method for protein-peptide systems in a typical real-world drug discovery project, we report an application of the thermodynamic integration (TI) method to the RBFE calculation of ghrelin receptor and its peptide agonists. Along with the calculation, the synthesis and in vitro EC50 activity of relamorelin and 17 new peptide derivatives were also reported. A cost-effective criterion to determine the data collection time was proposed for peptides in the TI simulation. The average of three TI repeats yielded a mean absolute error of 0.98 kcal/mol and Pearson's correlation coefficient (R) of 0.77 against the experimental free energy derived from the in vitro EC50 activity, showing good repeatability of the proposed method and a slightly better agreement than the results obtained from the arbitrary time frames up to 20 ns. Although it is limited by having one target and a deduced binding pose, we hope that this study can add some insights into alchemical free energy calculation of protein-peptide systems, providing theoretical assistance to the development of peptide drugs.

Discovery of Quinazoline-2,4(1H,3H)-dione Derivatives Containing a Piperizinone Moiety as Potent PARP-1/2 Inhibitors─Design, Synthesis, In Vivo Antitumor Activity, and X-ray Crystal Structure Analysis

PARP-1/2 inhibitors have become an important therapeutic strategy for the treatment of HR-deficient tumors. However, discovery of new inhibitors with an improved and distinct pharmacological file still need enormous explorations. Herein, a series of novel highly potent PARP-1/2 inhibitors bearing an N-substituted piperazinone moiety were achieved. In particular, Cpd36 was identified as a distinct PARP inhibitor, showing remarkable enzymatic activity not only toward PARP-1 (IC50 = 0.94 nM) and PARP-2 (IC50 = 0.87 nM) but also toward PARP-7 (IC50 = 0.21 nM), as well as high selectivity over other PARP isoforms. Furthermore, Cpd36 was orally bioavailable and significantly repressed the tumor growth in both breast cancer and prostate cancer xenograft model. The crystal structures of Cpd36 within PARP-1 and PARP-2 together with the predicted binding mode within PARP-7 revealed its binding features and provided insightful information for further developing highly potent and selective PARP-1 and/or PARP-7 inhibitors.

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host–Guest Binding: III. Force-Field Comparison, Three-Trajectory Realization and Further Dielectric Augmentation

Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: II. regression and dielectric constant

End-point free energy calculations as a powerful tool have been widely applied in protein-ligand and protein-protein interactions. It is often recognized that these end-point techniques serve as an option of intermediate accuracy and computational cost compared with more rigorous statistical mechanic models (e.g., alchemical transformation) and coarser molecular docking. However, it is observed that this intermediate level of accuracy does not hold in relatively simple and prototypical host-guest systems. Specifically, in our previous work investigating a set of carboxylated-pillar[6]arene host-guest complexes, end-point methods provide free energy estimates deviating significantly from the experimental reference, and the rank of binding affinities is also incorrectly computed. These observations suggest the unsuitability and inapplicability of standard end-point free energy techniques in host-guest systems, and alteration and development are required to make them practically usable. In this work, we consider two ways to improve the performance of end-point techniques. The first one is the PBSA_E regression that varies the weights of different free energy terms in the end-point calculation procedure, while the second one is considering the interior dielectric constant as an additional variable in the end-point equation. By detailed investigation of the calculation procedure and the simulation outcome, we prove that these two treatments (i.e., regression and dielectric constant) are manipulating the end-point equation in a somehow similar way, i.e., weakening the electrostatic contribution and strengthening the non-polar terms, although there are still many detailed differences between these two methods. With the trained end-point scheme, the RMSE of the computed affinities is improved from the standard ~ 12 kcal/mol to ~ 2.4 kcal/mol, which is comparable to another altered end-point method (ELIE) trained with system-specific data. By tuning PBSA_E weighting factors with the host-specific data, it is possible to further decrease the prediction error to ~ 2.1 kcal/mol. These observations along with the extremely efficient optimized-structure computation procedure suggest the regression (i.e., PBSA_E as well as its GBSA_E extension) as a practically applicable solution that brings end-point methods back into the library of usable tools for host-guest binding. However, the dielectric-constant-variable scheme cannot effectively minimize the experiment-calculation discrepancy for absolute binding affinities, but is able to improve the calculation of affinity ranks. This phenomenon is somehow different from the protein-ligand case and suggests the difference between host-guest and biomacromolecular (protein-ligand and protein-protein) systems. Therefore, the spectrum of tools usable for protein-ligand complexes could be unsuitable for host-guest binding, and numerical validations are necessary to screen out really workable solutions in these 'prototypical' situations.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure

Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.

Relative Binding Free Energy between Chemically Distant Compounds Using a Bidirectional Nonequilibrium Approach

In the context of advanced hit-to-lead drug design based on atomistic molecular dynamics simulations, we propose a dual topology alchemical approach for calculating the relative binding free energy (RBFE) between two chemically distant compounds. The method (termed NE-RBFE) relies on the enhanced sampling of the end-states in bulk and in the bound state via Hamiltonian Replica Exchange, alchemically connected by a series of independent and fast nonequilibrium (NE) simulations. The technique has been implemented in a bidirectional fashion, applying the Crooks theorem to the NE work distributions for RBFE predictions. The dissipation of the NE process, negatively affecting accuracy, has been minimized by introducing a smooth regularization based on shifted electrostatic and Lennard-Jones non bonded potentials. As a challenging testbed, we have applied our method to the calculation of the RBFEs in the recent host-guest SAMPL international contest, featuring a macrocyclic host with guests varying in the net charge, volume, and chemical fingerprints. Closure validation has been successfully verified in cycles involving compounds with disparate Tanimoto coefficients, volume, and net charge. NE-RBFE is specifically tailored for massively parallel facilities and can be used with little or no code modification on most of the popular software packages supporting nonequilibrium alchemical simulations, such as Gromacs, Amber, NAMD, or OpenMM. The proposed methodology bypasses most of the entanglements and limitations of the standard single topology RBFE approach for strictly congeneric series based on free-energy perturbation, such as slowly relaxing cavity water, sampling issues along the alchemical stratification, and the need for highly overlapping molecular fingerprints.

SAMPL9 blind predictions using nonequilibrium alchemical approaches

We present our blind predictions for the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL), ninth challenge, focusing on the binding of WP6 (carboxy-pillar[6]arene) with ammonium/diammonium cationic guests. Host-guest binding free energies have been calculated using the recently developed virtual double system single box approach, based on the enhanced sampling of the bound and unbound end-states followed by fast switching nonequilibrium alchemical simulations [M. Macchiagodena et al., J. Chem. Theory Comput. 16, 7160 (2020)]. As far as Pearson and Kendall coefficients are concerned, performances were acceptable and, in general, better than those we submitted for calixarenes, cucurbituril-like open cavitand, and beta-cyclodextrines in previous SAMPL host-guest challenges, confirming the reliability of nonequilibrium approaches for absolute binding free energy calculations. In comparison with previous submissions, we found a rather large mean signed error that we attribute to the way the finite charge correction was addressed through the assumption of a neutralizing background plasma.

Implementation and Optimization of the Embedded Cluster Reference Interaction Site Model with Atomic Charges

In this work, we implemented the embedded cluster reference interaction site model (EC-RISM) originally developed by Kloss, Heil, and Kast (J. Phys. Chem. B2008, 112, 4337–4343). This method combines quantum mechanical calculations with the 3D reference interaction site model (3D-RISM). Numerous options, such as buffer, grid space, basis set, charge model, water model, closure relation, and so forth, were investigated to find the best settings. Additionally, the small point charges, which are derived from the solvent distribution from the 3D-RISM solution to represent the solvent in the QM calculation, were neglected to reduce the overhead without the loss of accuracy. On the MNSOL[a], MNSOL, and FreeSolv databases, our implemented and optimized method provides solvation free energies in water with 5.70, 6.32, and 6.44 kJ/mol root-mean-square deviations, respectively, but with different settings, 5.22, 6.08, and 6.63 kJ/mol can also be achieved. Only solvent models containing fitting parameters, like COSMO-RS and EC-RISM with universal correction and directly used electrostatic potential, perform better than our EC-RISM implementation with atomic charges.