Extended Zinc AMBER Force Field (EZAFF)

Identification of Inhibitors for Flagellar Assembly Protein FliN of Uropathogenic Escherichia coli using Virtual Screening and Molecular Dynamics Simulation Study

Escherichia coli (E. coli) is a gram-negative bacterial pathogen that poses a significant clinical and epidemiologic challenge. The selection pressure brought by the insufficient use of antibiotics has resulted in the emergence of multi-drug-resistant E. coli in the past ten years. Computational and bioinformatics methods for screening inhibitors have significantly contributed to discovering novel antibacterial agents. One possible target for novel anti-virulence drugs is motility. Motility inhibitors are generally effective at concentrations lower than those required for the antibacterial properties of traditional antibiotics, and they are likely to exert less selective pressure than current medicines. Motility may be essential for bacteria to survive, find nutrients, and escape unfavorable environments and biofilm formation. The FliN is a protein forming the bulk of the C ring of the flagella and is present in multiple copies (more than 100) in bacteria. Its absence in mammals makes it an attractive drug target for drug discovery. Two-thousand seven hundred seventy-eight natural compounds from the ZINC library were screened against FliN (PDB ID: 4YXB) using PyRx AutoDock Vina, and the top compounds were selected for secondary screening after sorting the results based on their binding energy. Based on interactional analysis, binding energy (- 7.78 kcal/mol), and inhibition constant (1.98 µM), ZINC000000619481 was the best inhibitor. This compound binds exactly as per the defined active site residues of the receptor protein. Also, molecular dynamics was performed. The eigenvalue of the selected complex was 1.241657e-05. There were no ADME properties outside of the specified range for the identified hit; it fitted exactly to the binding site of the FliN receptor well and was found to be stable in MD simulation studies. Further in vitro and in vivo studies are needed to confirm its anti-bacterial activity and use as a potential antimicrobial drug against urinary tract infections caused by E. coli.

Modeling Zinc Complexes Using Neural Networks

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Force Fields for High Concentration Aqueous KOH Solutions and Zincate Ions

Motivated by increasing interest in electrochemical devices that include highly alkaline electrolytes, we investigated two force fields for potassium hydroxide (KOH) at high concentrations in water. The "FNB" model uses the SPC/E water model, while the "FHM" model uses the TIP4P/2005 water model. We also developed parameters to describe zincate ions in these solutions. The density and viscosity of KOH using the FHM model are in better agreement with experiment than the values from the FNB model. Comparing the properties of the zincate solutions to the available experimental data, we find that both force fields agree reasonably well, although the FHM parameters give a better prediction of the viscosity. The developed force field parameters can be used in future simulations of zincate/KOH solutions in combination with other species of interest.

Viral RNA Replication Suppression of SARS-CoV-2: Atomistic Insights into Inhibition Mechanisms of RdRp Machinery by ddhCTP

The nonstructural protein 12, known as RNA-dependent RNA polymerase (RdRp), is essential for both replication and repair of the viral genome. The RdRp of SARS-CoV-2 has been used as a promising candidate for drug development since the inception of the COVID-19 spread. In this work, we performed an in silico investigation on the insertion of the naturally modified pyrimidine nucleobase ddhCTP into the SARS-CoV-2 RdRp active site, in a comparative analysis with the natural one (CTP). The modification in ddhCTP involves the removal of the 3'-hydroxyl group that prevents the addition of subsequent nucleotides into the nascent strand, acting as an RNA chain terminator inhibitor. Quantum mechanical investigations helped to shed light on the mechanistic source of RdRp activity on the selected nucleobases, and comprehensive all-atom simulations provided insights about the structural rearrangements occurring in the active-site region when inorganic pyrophosphate (PPi) is formed. Subsequently, the intricate pathways for the release of PPi, the catalytic product of RdRp, were investigated using Umbrella Sampling simulations. The results are in line with the available experimental data and contribute to a more comprehensive point of view on such an important viral enzyme.

Development of a Fluctuating Charge Model for Zinc-Containing Metalloproteins

Metalloproteins widely exist in biology and play important roles in various processes. To accurately simulate metalloprotein systems, modeling polarization and charge transfer effects is vital. The fluctuating charge (FQ) model can efficiently generate atomic charges and simulate the charge transfer effect; it has been developed for a wide range of applications, but few models have been specifically tailored for metalloproteins. In this study, we present a fluctuating charge model specifically for zinc-containing metalloproteins based on the extended charge equilibration (EQeq) scheme. Our model was parametrized to reproduce CM5 charges instead of RESP/CHELPG charges because the former is less dependent on the conformation or basis set, does not suffer from unphysical charges for buried atoms, and is still being able to well reproduce the molecular dipoles. During our study, we found that adding the Pauling-bond-order-like term (referred to as the "+C term" in a previous study) between the zinc ion and ligating atoms significantly improves the model's performance. Although our model was trained for four-coordinated zinc sites only, our results indicated it can well describe the atomic charges in diverse zinc sites. Morever, our model was used to generate partial charges for the metal sites in three different zinc-containing metalloproteins (with four-, five-, and six-coordinated metal sites, respectively). These charges exhibited performance comparable to that of the RESP charges in molecular dynamics (MD) simulations. Additional tests indicated our model could also well reproduce the CM5 charges when geometric changes were involved. Those results indicate that our model can efficiently calculate the atomic charges for metal sites and well simulate the charge transfer effect, which marks an important step toward developing versatile polarizable force fields for metalloproteins.

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

Atomistic molecular simulations of Aβ-Zn conformational ensembles

The amyloid-forming Aβ peptide is able to interact with metal cations to form very stable complexes that influence fibril formation and contribute to the onset of Alzheimer's disease. Multiple structures of peptides derived from Aβ in complex with different metals have been resolved experimentally to provide an atomic-level description of the metal-protein interactions. However, Aβ is intrinsically disordered, and hence more amenable to an ensemble description. Molecular dynamics simulations can now reach the timescales needed to generate ensembles for these type of complexes. However, this requires accurate force fields both for the protein and the protein-metal interactions. Here we use state-of-the-art methods to generate force field parameters for the Zn(II) cations in a set of complexes formed by different Aβ variants and combine them with the Amber99SB*-ILDN optimized force field. Upon comparison of NMR experiments with the simulation results, further optimized with a Bayesian/Maximum entropy approach, we provide an accurate description of the molecular ensembles for most Aβ-metal complexes. We find that the resulting conformational ensembles are more heterogeneous than the NMR models deposited in the Protein Data Bank.

Identification of novel inhibitors against Escherichia coli utilizing HisC as a target from histidine biosynthesis pathway

Escherichia coli is a gram-negative bacterial pathogen that poses a significant challenge both clinically and epidemiologically. Large numbers of multi-drug resistant E. coli have emerged in the last decade, because of the selection pressure generated by the inadequate use of antibiotics. Although research to combat antibiotic resistance has been going on extensively but still lags in the rate of development of newer antibiotics. Therefore, newer approaches are required to speed up the rate of discovery of antibiotics. Computational methods for screening of inhibitors have made a significant contribution to the discovery of novel antimicrobials. The present study utilized histidinol-phospho aminotransferase (HisC) as a target. HisC is an enzyme that plays a crucial role in the biosynthesis of histidine and its absence in mammals makes it an attractive drug target. A ZINC library of 5000 natural compounds was screened against HisC (PDB ID: 1FG7) using PyRx and the first 500 hits were selected for secondary screening after sorting the result on the basis of binding score. Fifteen compounds passed the secondary filter ADME and out of these five passed toxicity filters; the best among five hits was selected on the basis of its binding score and inhibition constants. Further, molecular dynamics simulations and free binding were computed of selected five compounds and two natural compounds ZINC402598829 and ZINC31157928 complexed with HisC were found as highly stable. Overall, our results indicated that these natural sources could be used as potential HisC inhibitors.Communicated by Ramaswamy H. Sarma.

Computed Protein-Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems

Understanding the thermodynamic signature of protein-peptide binding events is a major challenge in computational chemistry. The complexity generated by both components possessing many degrees of freedom poses a significant issue for methods that attempt to directly compute the enthalpic contribution to binding. Indeed, the prevailing assumption has been that the errors associated with such approaches would be too large for them to be meaningful. Nevertheless, we currently have no indication of how well the present methods would perform in terms of predicting the enthalpy of binding for protein-peptide complexes. To that end, we carefully assembled and curated a set of 11 protein-peptide complexes where there is structural and isothermal titration calorimetry data available and then computed the absolute enthalpy of binding. The initial "out of the box" calculations were, as expected, very modest in terms of agreement with the experiment. However, careful inspection of the outliers allows for the identification of key sampling problems such as distinct conformations of peptide termini not being sampled or suboptimal cofactor parameters. Additional simulations guided by these aspects can lead to a respectable correlation with isothermal titration calorimetry (ITC) experiments (R2 of 0.88 and an RMSE of 1.48 kcal/mol overall). Although one cannot know prospectively whether computed ITC values will be correct or not, this work shows that if experimental ITC data are available, then this in conjunction with computed ITC, can be used as a tool to know if the ensemble being simulated is representative of the true ensemble or not. That is important for allowing the correct interpretation of the detailed dynamics of the system with respect to the measured enthalpy. The results also suggest that computational calorimetry is becoming increasingly feasible. We provide the data set as a resource for the community, which could be used as a benchmark to help further progress in this area.

Comparison of force fields to study the zinc-finger containing protein NPL4, a target for disulfiram in cancer therapy

Molecular dynamics (MD) simulations are a powerful approach to studying the structure and dynamics of proteins related to health and disease. Advances in the MD field allow modeling proteins with high accuracy. However, modeling metal ions and their interactions with proteins is still challenging. NPL4 is a zinc-binding protein and works as a cofactor for p97 to regulate protein homeostasis. NPL4 is of biomedical importance and has been proposed as the target of disulfiram, a drug recently repurposed for cancer treatment. Experimental studies proposed that the disulfiram metabolites, bis-(diethyldithiocarbamate)‑copper and cupric ions, induce NPL4 misfolding and aggregation. However, the molecular details of their interactions with NPL4 and consequent structural effects are still elusive. Here, biomolecular simulations can help to shed light on the related structural details. To apply MD simulations to NPL4 and its interaction with copper the first important step is identifying a suitable force field to describe the protein in its zinc-bound states. We examined different sets of non-bonded parameters because we want to study the misfolding mechanism and cannot rule out that the zinc may detach from the protein during the process and copper replaces it. We investigated the force-field ability to model the coordination geometry of the metal ions by comparing the results from MD simulations with optimized geometries from quantum mechanics (QM) calculations using model systems of NPL4. Furthermore, we investigated the performance of a force field including bonded parameters to treat copper ions in NPL4 that we obtained based on QM calculations.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules. However, as important as they are, molecular dynamics studies focused on DNA repair pathways are still becoming more widespread. Currently, there are no review articles compiling the advancements made in molecular dynamics approaches applied to NER and discussing: (i) how this technique is currently employed in the field of DNA repair, focusing on NER proteins; (ii) which technical setups are being employed, their strengths and limitations; (iii) which insights or information are they providing to understand the NER pathway or NER-associated proteins; (iv) which open questions would be suited for this technique to answer; and (v) where can we go from here. These questions become even more crucial considering the numerous 3D structures published regarding the NER pathway's proteins in recent years. In this work, we tackle each one of these questions, revising and critically discussing the results published in the context of the NER pathway.

Benchmarking biomolecular force field-based Zn2+ for mono- and bimetallic ligand binding sites

Zn²⁺ is one of the most versatile biologically available metal ions, but accurate modeling of Zn²⁺ -containing metalloproteins at the biomolecular force field level can be challenging. Since most Zn²⁺ models are parameterized in bulk solvent, in-depth knowledge about their performance in a protein environment is limited. Thus, we systematically investigate here the behavior of non-polarizable Zn²⁺ models for their ability to reproduce experimentally determined metal coordination and ligand binding in metalloproteins. The benchmarking is performed in challenging environments, including mono- (carbonic anhydrase II) and bimetallic (metallo-β-lactamase VIM-2) ligand binding sites. We identify key differences in the performance between the Zn²⁺ models with regard to the preferred ligating atoms (charged/non-charged), attraction of water molecules, and the preferred coordination geometry. Based on these results, we suggest suitable simulation conditions for varying Zn²⁺ site geometries that could guide the further development of biomolecular Zn²⁺ models.

Comparison of Empirical Zn2+ Models in Protein–DNA Complexes

Zinc ions are the second most abundant ions found in humans. Their role in proteins can be merely structural but also catalytic, owing to their transition metal character. Modelling their geometric–coordination versatility by empirical force fields is, thus, a challenging task. In this work, we evaluated three popular models, specifically designed to represent zinc ions with regard to their capability of preserving structural integrity. To this end, we performed molecular dynamics simulations of two zinc-containing protein–DNA complexes, which differed in their zinc coordination, i.e., four cysteines or two cysteines and two histidines. The most flexible non-bonded 12-6-4 Lennard–Jones-type model shows a preference for six-fold coordination of the Zn2+-ions in contradiction to the crystal structure. The cationic dummy atom model favours tetrahedral geometry, whereas the bonded extended zinc AMBER force field model, by construction, best preserves the initial geometry of a regular or slightly distorted tetrahedron. Our data renders the extended zinc AMBER force field the best model for structural zinc ions in a given geometry. In more complicated cases, though, more flexible models may be advantageous.

A modified bonded model approach for molecular dynamics simulations of New Delhi Metallo-β-lactamase

Modelling metalloproteins using the classical force fields is challenging. Several methods have been devised to model metalloproteins in force fields. Of these methods, the bonded model, combined with Restrained Electrostatic Potential (RESP) charge fitting, proved its superiority. The latter method was facilitated by the development of the python-based Metal Centre Parameter Builder (MCPB.py) AmberTool. However, the standard bonded model method offered by the MCPB.py tool may not be appropriate for validating and refining the binding modes predicted by docking when crystal structures are lacking. That is because the representation of coordination interactions between any bound ligand and metal ions by covalent bonds can hinder the flexibility of the ligand. Therefore, a new modification to the standard bonded model approach is proposed here. Molecular dynamics (MD) simulations based on the new modified bonded model (MBM) approach avoid the bias caused by coordination bonds and, unlike hybrid QM/MM MD, allow for sufficient sampling of the binding mode given the currently available computational power. The MBM MD approach reproduced the studied crystal structure conformations of New Delhi Metallo-β-lactamase 1 (NDM-1). Furthermore, the MBM approach described the binding interactions of intact β-lactams with NDM-1 reasonably, and predicted a non-productive binding mode for the poor NDM-1 substrate aztreonam whilst predicting productive binding modes for known good substrates. This study presents a useful MD method for metallo-β-lactamases and provides better understanding of β-lactam substrates recognition by NDM-1. The proposed MBM approach might also be useful in the investigation of other metal-containing protein targets.

Molecular Dynamics and Structural Studies of Zinc Chloroquine Complexes

Chloroquine (CQ) is a first-choice drug against malaria and autoimmune diseases. It has been co-administered with zinc against SARS-CoV-2 and soon dismissed because of safety issues. The structural features of Zn-CQ complexes and the effect of CQ on zinc distribution in cells are poorly known. In this study, state-of-the-art computations combined with experiments were leveraged to solve the structural determinants of zinc-CQ interactions in solution and the solid state. NMR, ESI-MS, and X-ray absorption and diffraction methods were combined with ab initio molecular dynamics calculations to address the kinetic lability of this complex. Within the physiological pH range, CQ binds Zn²⁺ through the quinoline ring nitrogen, forming [Zn(CQH)Cl_x(H₂O)_3-x]^(3+)-x (x = 0, 1, 2, and 3) tetrahedral complexes. The Zn(CQH)Cl₃ species is stable at neutral pH and at high chloride concentrations typical of the extracellular medium, but metal coordination is lost at a moderately low pH as in the lysosomal lumen. The pentacoordinate complex [Zn(CQH)(H₂O)₄]³⁺ may exist in the absence of chloride. This in vitro/in silico approach can be extended to other metal-targeting drugs and bioinorganic systems.

Non-bonding energy directed designing of HDAC2 inhibitors through molecular dynamics simulation

Designing an inhibitor having strong affinity in the active site pocket is the cherished goal of structure based drug designing. To achieve this, it is considerably important to predict which structural scaffold is better suited for change to increase affinity. We have explored five HDAC2 co-crystals having PDB ligand code-SHH (vorinostat), LLX, 20Y, IWX (BRD4884) and 6EZ (BRD7232). For analyzing protein-ligand interaction at an atomistic level, we have employed the NAMD molecular dynamics (MD) package. The obtained 100 ns long MD trajectories were subjected to quantitative estimations of non-bonding energies (NBEs) for inferring their interactions with the whole protein or its composite active site (CAS). In addition, relative ΔG_bind was calculated to rank the inhibitors. These inhibitors' NBEs reveal that the phenyl moieties are the major structural scaffold where modifications should be attempted. We designed new compounds (NCs) via introducing hydroxyl groups at 4,5 position of the phenyl moiety of 6EZ, called NC1. Improvement in NC1 further encouraged us for CAP modification by isochromane and isoindoline moieties in place of oxabicyclooctane in NC1, resulting in NC2 and NC3. We also explored trifluoromethyl oxadiazole in 6EZ (NC4 and NC5) and SHH (NC6 and NC7). This moiety acts as a ZBG in NC4 while acting as a part of the foot-pocket in the rest. NC2 and NC6 have highest favorable NBEs among all studied ligands due increased favorable electrostatic contribution. We expect these NBEs data will provide atomistic level insights and benefit in designing new and improved HDAC2 inhibitors. Communicated by Ramaswamy H. Sarma.

Variable Regions of p53 Isoforms Allosterically Hard Code DNA Interaction

Allosteric regulation of protein activity pervades biology as the "second secret of life." We have been examining the allosteric regulation and mutant reactivation of the tumor suppressor protein p53. We have found that generalizing the definition of allosteric effector to include entire proteins and expanding the meaning of binding site to include the interface of a transcription factor with its DNA to be useful in understanding the modulation of protein activity. Here, we cast the variable regions of p53 isoforms as allosteric regulators of p53 interactions with its consensus DNA. We implemented molecular dynamics simulations and our lab's new techniques of molecular dynamics (MD) sectors and MD-Markov state models to investigate the effects of nine naturally occurring splice variant isoforms of p53. We find that all of the isoforms differ from wild type in their dynamic properties and how they interact with the DNA. We consider the implications of these findings on allostery and cancer treatment.

On the Recognition of Natural Substrate CTP and Endogenous Inhibitor ddhCTP of SARS-CoV-2 RNA-Dependent RNA Polymerase: A Molecular Dynamics Study

The novel coronavirus SARS-CoV-2 is the causative agent of the COVID-19 outbreak that is affecting the entire planet. As the pandemic is still spreading worldwide, with multiple mutations of the virus, it is of interest and of help to employ computational methods for identifying potential inhibitors of the enzymes responsible for viral replication. Attractive antiviral nucleotide analogue RNA-dependent RNA polymerase (RdRp) chain terminator inhibitors are investigated with this purpose. This study, based on molecular dynamics (MD) simulations, addresses the important aspects of the incorporation of an endogenously synthesized nucleoside triphosphate, ddhCTP, in comparison with the natural nucleobase cytidine triphosphate (CTP) in RdRp. The ddhCTP species is the product of the viperin antiviral protein as part of the innate immune response. The absence of the ribose 3'-OH in ddhCTP could have important implications in its inhibitory mechanism of RdRp. We built an in silico model of the RNA strand embedded in RdRp using experimental methods, starting from the cryo-electron microscopy structure and exploiting the information obtained by spectrometry on the RNA sequence. We determined that the model was stable during the MD simulation time. The obtained results provide deeper insights into the incorporation of nucleoside triphosphates, whose molecular mechanism by the RdRp active site still remains elusive.

Modeling Gd3+ Complexes for Molecular Dynamics Simulations: Toward a Rational Optimization of MRI Contrast Agents

The correct parametrization of lanthanide complexes is of the utmost importance for their characterization using computational tools such as molecular dynamics simulations. This allows the optimization of their properties for a wide range of applications, including medical imaging. Here we present a systematic study to establish the best strategies for the correct parametrization of lanthanide complexes using [Gd(DOTA)]^- as a reference, which is used as a contrast agent in MRI. We chose the bonded model to parametrize the lanthanide complexes, which is especially important when considering the study of the complex as a whole (e.g., for the study of the dynamics of its interaction with proteins or membranes). We followed two strategies: a so-called heuristic approach employing strategies already published by other authors and another based on the more recent MCPB.py tool. Adjustment of the Lennard-Jones parameters of the metal was required. The final topologies obtained with both strategies were able to reproduce the experimental ion to oxygen distance, vibrational frequencies, and other structural properties. We report a new strategy to adjust the Lennard-Jones parameters of the metal ion in order to capture dynamic properties such as the residence time of the capping water (τ_m). For the first time, the correct assessment of the τ_m value for Gd-based complexes was possible by recording the dissociative events over up to 10 μs all-atom simulations. The MCPB.py tool allowed the accurate parametrization of [Gd(DOTA)]^- in a simpler procedure, and in this case, the dynamics of the water molecules in the outer hydration sphere was also characterized. This sphere was divided into the first hydration layer, an intermediate region, and an outer hydration layer, with a residence time of 18, 10 and 19 ps, respectively, independent of the nonbonded parameters chosen for Gd³⁺. The Lennard-Jones parameters of Gd³⁺ obtained here for [Gd(DOTA)]^- may be used with similarly structured gadolinium MRI contrast agents. This allows the use of molecular dynamics simulations to characterize and optimize the contrast agent properties. The characterization of their interaction with membranes and proteins will permit the design of new targeted contrast agents with improved pharmacokinetics.

Repurposing of FDA approved drugs against uropathogenic Escherichia coli: In silico, in vitro, and in vivo analysis

Urinary tract infections (UTIs) are a serious health concern worldwide. Treatment of UTIs is becoming a challenge as uropathogenic Escherichia coli (UPEC), which is the most common etiological agent, has developed resistance to the main classes of antibiotics. Small molecules that interfere with metabolic processes rather than growth are attractive alternatives to conventional antibiotics. Repurposing of already known drugs for treating infectious diseases could be an attractive avenue for finding novel therapeutics against infections caused by UPEC. Virtual screenings enable the rapid and economical identification of target ligands from large libraries of compounds, reducing the cost and time of traditional drug discovery. Moreover, the drugs that have been approved by the FDA have low cytotoxicity and good pharmacological characteristics. In this work, we targeted the HisC enzyme of the histidine biosynthetic pathway as enzymes of this pathway are absent in humans. We screened the library of FDA-approved drugs against HisC via molecular docking, and four hits (Docetaxel, Suramin, Digitoxin, and Nystatin) showing the highest binding energy were selected. These were further tested for antibacterial activity, which was observed only for Docetaxel (MIC value of 640 μg/ml); therefore, Docetaxel was further tested for its efficacy in vivo in murine catheter UTI model and antibiofilm activity using crystal violet staining and scanning electron microscopy. Docetaxel inhibited biofilm formation and reduced the bacterial load in urine, kidney, and bladder. Docking studies revealed that Docetaxel acts by blocking the binding site of HisC to the native substrate by competitive inhibition. Docetaxel may be a potential new inhibitor for UPEC with antibacterial and antibiofilm capability.

A multiscale approach to predict the binding mode of metallo beta-lactamase inhibitors

Antibiotic resistance is a major threat to global public health. β-lactamases, which catalyze breakdown of β-lactam antibiotics, are a principal cause. Metallo β-lactamases (MBLs) represent a particular challenge because they hydrolyze almost all β-lactams and to date no MBL inhibitor has been approved for clinical use. Molecular simulations can aid drug discovery, for example, predicting inhibitor complexes, but empirical molecular mechanics (MM) methods often perform poorly for metalloproteins. Here we present a multiscale approach to model thiol inhibitor binding to IMP-1, a clinically important MBL containing two catalytic zinc ions, and predict the binding mode of a 2-mercaptomethyl thiazolidine (MMTZ) inhibitor. Inhibitors were first docked into the IMP-1 active site, testing different docking programs and scoring functions on multiple crystal structures. Complexes were then subjected to molecular dynamics (MD) simulations and subsequently refined through QM/MM optimization with a density functional theory (DFT) method, B3LYP/6-31G(d), increasing the accuracy of the method with successive steps. This workflow was tested on two IMP-1:MMTZ complexes, for which it reproduced crystallographically observed binding, and applied to predict the binding mode of a third MMTZ inhibitor for which a complex structure was crystallographically intractable. We also tested a 12-6-4 nonbonded interaction model in MD simulations and optimization with a SCC-DFTB QM/MM approach. The results show the limitations of empirical models for treating these systems and indicate the need for higher level calculations, for example, DFT/MM, for reliable structural predictions. This study demonstrates a reliable computational pipeline that can be applied to inhibitor design for MBLs and other zinc-metalloenzyme systems.

Inhibition of Histone Deacetylases 1, 2, and 3 Enhances Clearance of Cholesterol Accumulation in Niemann-Pick C1 Fibroblasts

Niemann-Pick disease type C1 (NPC1) is a rare genetic cholesterol storage disorder caused by mutations in the NPC1 gene. Mutations in this transmembrane late endosome protein lead to loss of normal cholesterol efflux from late endosomes and lysosomes. It has been shown that broad spectrum histone deacetylase inhibitors (HDACi's) such as Vorinostat correct the cholesterol accumulation phenotype in the majority of NPC1 mutants tested in cultured cells. In order to determine the optimal specificity for HDACi correction of the mutant NPC1s, we screened 76 HDACi's of varying specificity. We tested the ability of these HDACi's to correct the excess accumulation of cholesterol in patient fibroblast cells that homozygously express NPC1^I1061T, the most common mutation. We determined that inhibition of HDACs 1, 2, and 3 is important for correcting the defect, and combined inhibition of all three is needed to achieve the greatest effect, suggesting a need for multiple effects of the HDACi treatments. Identifying the specific HDACs involved in the process of regulating cholesterol trafficking in NPC1 will help to focus the search for more specific druggable targets.

Parametrization of Trivalent and Tetravalent Metal Ions for the OPC3, OPC, TIP3P-FB, and TIP4P-FB Water Models

Commonly seen in rare-earth chemistry and materials science, highly charged metal ions play key roles in many chemical processes. Computer simulations have become an important tool for scientific research nowadays. Meaningful simulations require reliable parameters. In the present work, we parametrized 18 M(III) and 6 M(IV) metal ions for four new water models (OPC3, OPC, TIP3P-FB, TIP4P-FB) in conjunction with each of the 12-6 and 12-6-4 nonbonded models. Similar to what was observed previously, issues with the 12-6 model can be fixed by using the 12-6-4 model. Moreover, the four new water models showed comparable performance or considerable improvement over the previous water models (TIP3P, SPC/E, and TIP4P_EW) in the same category (3-point or 4-point water models, respectively). Finally, we reported a study of a metalloprotein system demonstrating the capability of the 12-6-4 model to model metalloproteins. The reported parameters will facilitate accurate simulations of highly charged metal ions in aqueous solution.

AMBER force field parameters for the Zn (II) ions of the tunneling-fold enzymes GTP cyclohydrolase I and 6-pyruvoyl tetrahydropterin synthase

The folate biosynthesis pathway is an essential pathway for cell growth and survival. Folate derivatives serve as a source of the one-carbon units in several intracellular metabolic reactions. Rapidly dividing cells rely heavily on the availability of folate derivatives for their proliferation. As a result, drugs targeting this pathway have shown to be effective against tumor cells and pathogens, but drug resistance against the available antifolate drugs emerged quickly. Therefore, there is a need to develop new treatment strategies and identify alternative metabolic targets. The two de novo folate biosynthesis pathway enzymes, GTP cyclohydrolase I (GCH1) and 6-pyruvoyl tetrahydropterin synthase (PTPS), can provide an alternative strategy to overcome the drug resistance that emerged in the two primary targeted enzymes dihydrofolate reductase and dihydropteroate synthase. Both GCH1 and PTPS enzymes contain Zn²⁺ ions in their active sites, and to accurately study their dynamic behaviors using all-atom molecular dynamics (MD) simulations, appropriate parameters that can describe their metal sites should be developed and validated. In this study, force field parameters of the GCH1 and PTPS metal centers were generated using quantum mechanics (QM) calculations and then validated through MD simulations to ensure their accuracy in describing and maintaining the Zn²⁺ ion coordination environment. The derived force field parameters will provide accurate and reliable MD simulations involving these two enzymes for future in-silico identification of drug candidates against the GCH1 and PTPS enzymes. Communicated by Ramaswamy H. Sarma.

Upgraded AMBER Force Field for Zinc-Binding Residues and Ligands for Predicting Structural Properties and Binding Affinities in Zinc-Proteins

We developed a novel force field in the context of AMBER parameterization for glutamate and aspartate zinc(II)-binding residues. The interaction between the zinc ion and the coordinating atoms is represented by a spherical nonbonded parameterization. The polarization effect due to the zinc ion has been taken into account by redefining the atomic charges on the residues through accurate quantum mechanical calculations. The new zinc-binding ASP and GLU residues, along with the CYS and HIS zinc-binding residues, parameterized in a recent work [Macchiagodena M.;J. Chem. Inf. Model.2019, 59, 3803-3816], allow users to reliably simulate 96% of the Zn-proteins available in the Protein Data Bank. The upgraded force field for zinc(II)-bound residues has been tested performing molecular dynamics simulations with an explicit solvent and comparing the structural information with experimental data for five different proteins binding zinc(II) with GLU, ASP, HIS, and CYS. We further validated our approach by evaluating the binding free energy of (R)-2-benzyl-3-nitropropanoic acid to carboxypeptidase A using a recently developed nonequilibrium alchemical method. We demonstrated that in this setting it is crucial to take into account polarization effects also on the metal-bound inhibitor.

Upgrading and Validation of the AMBER Force Field for Histidine and Cysteine Zinc(II)-Binding Residues in Sites with Four Protein Ligands

We developed and validated a novel force field in the context of the AMBER parameterization for the simulation of zinc(II)-binding proteins. The proposed force field assumes nonbonded spherical interactions between the central zinc(II) and the coordinating residues. A crucial innovative aspect of our approach is to account for the polarization effects of the cation by redefining the atomic charges of the coordinating residues and an adjustment of Lennard-Jones parameters of Zn-interacting atoms to reproduce mean distance distributions. The optimal transferable parametrization was obtained by performing accurate quantum mechanical calculations on a training set of high-quality protein structures, encompassing the most common folds of zinc(II) sites. The addressed sites contain a zinc(II) ion tetra-coordinated by histidine and cysteine residues and represent about 70% of all physiologically relevant zinc(II) sites in the Protein Data Bank. Molecular dynamics simulations with explicit solvent, carried out on several zinc(II)-binding proteins not included in the training set, show that our model for zinc(II) sites preserves the tetra-coordination of the metal site with remarkable stability, yielding zinc(II)-X mean distances similar to experimental data. Finally, the model was tested by evaluating the zinc(II)-binding affinities, using the alchemical free energy perturbation approach. The calculated dissociation constants correlate satisfactorily with the experimental counterpart demonstrating the validity and transferability of the proposed parameterization for zinc(II)-binding proteins.

New Zinc Ion Parameters Suitable for Classical MD Simulations of Zinc Metallopeptidases

The main aim of this work was to find parameters for the zinc ion in human dipeptidyl peptidase III (DPP III) active site that would enable its reliable modeling. Since the parameters publicly available failed to reproduce the zinc ion coordination in the enzyme, we developed a new set of the hybrid bonded/nonbonded parameters for the zinc ion suitable for molecular modeling of the human DPP III, dynamics, and ligand binding. The parameters allowed exchange of the water molecules coordinating the zinc ion and proved to be robust enough to enable reliable modeling not only of human DPP III and its orthologues but also of the other zinc-dependent peptidases with the zinc ion coordination similar to that in dipeptidyl peptidases III, i.e., peptidases with the zinc ion coordinated with two histidines and one glutamate. The new parameters were tested on a set of 21 different systems comprising 8 different peptidases, 5 DPP III orthologues, thermolysin, neprilysin, and aminopeptidase N, and the results are summarized in the second part of the article.

Chemical genomics reveals histone deacetylases are required for core regulatory transcription

Identity determining transcription factors (TFs), or core regulatory (CR) TFs, are governed by cell-type specific super enhancers (SEs). Drugs to selectively inhibit CR circuitry are of high interest for cancer treatment. In alveolar rhabdomyosarcoma, PAX3-FOXO1 activates SEs to induce the expression of other CR TFs, providing a model system for studying cancer cell addiction to CR transcription. Using chemical genetics, the systematic screening of chemical matter for a biological outcome, here we report on a screen for epigenetic chemical probes able to distinguish between SE-driven transcription and constitutive transcription. We find that chemical probes along the acetylation-axis, and not the methylation-axis, selectively disrupt CR transcription. Additionally, we find that histone deacetylases (HDACs) are essential for CR TF transcription. We further dissect the contribution of HDAC isoforms using selective inhibitors, including the newly developed selective HDAC3 inhibitor LW3. We show HDAC1/2/3 are the co-essential isoforms that when co-inhibited halt CR transcription, making CR TF sites hyper-accessible and disrupting chromatin looping.

Core regulatory transcription factors are usually regulated by cell-type specific super enhancers (SEs). Here, the authors screen for chemical probes able to distinguish between SE-driven and promoter-driven transcription and find that histone deacetylases are selectively required for core regulatory transcription.

Spectral and Structural Variations of Biomimetic Light-Harvesting Nanotubes

Bioinspired, self-assembled nanotubes have been investigated by low-temperature, polarization-resolved single-tube spectroscopy. These assemblies are based on zinc chlorin monomers and are considered as model systems that resemble the secondary structural elements in the natural light-harvesting systems of green (non)sulfur bacteria. Compared to the natural systems, the spectral parameters extracted from the single-nanotube spectra feature distributions with significantly smaller widths, which is ascribed to a tremendous reduction of structural heterogeneity in the artificial systems. Employing quantum chemical molecular modeling the spectra of individual nanotubes can be explained consistently only for a molecular packing model that is fundamentally different from those considered so far for the natural systems. Subsequent theoretical simulations reveal that the remaining spectral variations between single nanotubes can be traced back to small variations of the mutual orientations of the monomer transition dipole moments that are far beyond the resolving power of high-resolution electron microscopy imaging techniques.

Molecular Dynamics Investigation into the Effect of Zinc(II) on the Structure and Membrane Interactions of the Antimicrobial Peptide Clavanin A

Clavanin A (ClavA) is an antimicrobial peptide (AMP) whose antimicrobial activity is enhanced in the presence of Zn(II) ions. The antimicrobial activity of ClavA has been shown to increase 16-fold in the presence of Zn(II) ions. In this study, we investigate the potential sources of this enhancement, namely, the effect of Zn(II) binding on the helical conformation of ClavA and on the ClavA interaction with a model for gram-negative bacterial membranes. In addition, we investigate the effect of Zn(II) on the membrane mechanical properties. We employed all-atom equilibrium molecular dynamics simulations initiated from both fully helical and random coil structures of ClavA. We observe that Zn(II) can stabilize an existing helical conformation in the Zn(II)-binding region, but we do not observe induction of helical conformations in systems initiated in random coil configurations. Zn(II) binding to ClavA provides more favorable electrostatics for membrane association in the C-terminal region. This is evidenced by longer and stronger C-terminal-lipid interactions. Zn(II) is also capable of modulating the membrane properties in a manner which favors ClavA insertion and the potential for enhanced translocation into the cell. This work provides insights into the role of divalent metal cations in the antimicrobial activity of ClavA. This information can be used for the development of synthetic AMPs containing motifs that can bind metals (metalloAMPs) for therapeutic and medical purposes.

Coupling between an electrostatic network and the Zn2+ binding site modulates Hv1 activation

The voltage sensor (VS) domain in Hv1 proton channels mediates a voltage-dependent and H+-selective "aqueous" conductance (GAQ) that is potently modulated by extracellular Zn2+ Although two conserved His residues are required for Zn2+ effects on GAQ gating, the atomic structure of the Zn2+ coordination site and mechanism by which extracellular Zn2+ stabilizes a closed-state conformation remain unknown. Here we use His mutagenesis to identify residues that increase Zn2+ potency and are therefore likely to participate in first solvation shell interactions with Zn2+ Experimental Zn2+-mapping data were then used to constrain the structure of a new resting-state Hv1 model (Hv1 F). Molecular dynamics (MD) simulations show how protein and water atoms directly contribute to octahedral Zn2+ coordination spheres in Zn2+-bound and -unbound Hv1 F models. During MD simulations, we observed correlated movements of Zn2+-interacting side chains and residues in a highly conserved intracellular Coulombic network (ICN) that contains highly conserved Arg "gating charges" in S4 as well as acidic "counter-charges" in S2 and S3 and is known to control VS activation, suggesting that occupancy of the extracellular Zn2+ site is conformationally coupled to reorganization of the ICN. To test this hypothesis, we neutralized an ICN Glu residue (E153) and show that in addition to shifting GAQ activation to more negative voltages, E153A also decreases Zn2+ potency. We speculate that extracellular gating-modifier toxins and other ligands may use a generally similar long-range conformational coupling mechanism to modulate VS activation in related ion channel proteins.