Novel Dual‐Site‐Binding Neuraminidase Inhibitor from Virtual Screening by Pharmacophore and Molecular Dynamics Methods

Neuraminidase is a significant anti‐influenza target that plays crucial role in virus replication cycle. The discovery of 150‐cavity in Group‐1 neuraminidase provides us a novel mentality of designing inhibitor which can bind with both conserved site and 150‐cavity. In order to discover novel dual‐site‐binding inhibitors, a 3D chemical‐feature‐based pharmacophore model was established to cover dual‐site in neuraminidase. The dual‐site‐binding model was consistent in predicting the binding conformation of Group‐1 neuraminidase inhibitor and applied for virtual screening of Specs database. Compound 4 (ZINC05790048) that aligned well to the model was selected after multiple filtrations for molecular dynamics simulations, indicating improved binding energy with neuraminidase. It can sever as the lead compound for a novel series of inhibitors.     

Synthesis,Biological Evaluation,and Crystallographic Studies of Extended Guanine‐Based (lin‐Benzoguanine) Inhibitors for tRNA‐Guanine Transglycosylase (TGT)

This paper describes the rational design, synthesis, and biological evaluation of a new generation of inhibitors of the bacterial enzyme tRNA‐guanine transglycosylase (TGT), which has been identified as a new target in the fight against bacillary dysentery (Shigellosis). The enzyme catalyzes the exchange of guanine in the anticodon wobble position of tRNA by the modified base preQ₁, a guanine derivative, according to a ping‐pong mechanism involving a covalent TGT‐tRNA intermediate (Fig. 2). Based on computer modeling (Fig. 3), lin‐benzoguanine (6‐aminoimidazol[4,5‐g]quinazolin‐8(7H)‐one ( 2 )) was selected as an extended central scaffold, to form up to seven in‐plane intermolecular H‐bonds with the protein while sandwiching between Tyr106 and Met260. Versatile synthetic protocols were developed for the synthesis of 2 , and derivatives with phenyl, benzyl, and 2‐phenylethyl side chains (i.e., 16, 17a , and 12a, 12b, 13, 17 , resp.) to reach into the lipophilic pocket lined by Val282, Val45, and Leu68 (Schemes 1–3). To account for the limited solubility of the new ligands and in consequence of a recently developed detailed understanding of the mechanism of TGT catalysis (Fig. 2), the enzyme kinetic assay was completely redesigned, providing competitive (K_ic) and uncompetitive (K_iu) inhibition constants with respect to tRNA binding by TGT. The modifications of the various parameters in the new assay are described in detail. Binding affinities of the new inhibitors were found to be in the single‐digit micromolar range (K_ic values, Fig. 8). Decoration of the lin‐benzoguanine scaffold with lipophilic residues only gave a modest improvement in biological activity which was explained on structural grounds with the help of four crystal structures (Fig. 10) obtained by soaking the protein with inhibitors 2 and 12a – 12c . Both biochemical and biostructural analyses reported in this paper provide a fertile basis for the development of more potent future generations of TGT inhibitors.     

Virtual Screening of Natural Chemical Databases to Search for Potential ACE2 Inhibitors

The angiotensin-converting enzyme II (ACE2) is a multifunctional protein in both health and disease conditions, which serves as a counterregulatory component of RAS function in a cardioprotective role. ACE2 modulation may also have relevance to ovarian cancer, diabetes, acute lung injury, fibrotic diseases, etc. Furthermore, since the outbreak of the coronavirus disease in 2019 (COVID-19), ACE2 has been recognized as the host receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The receptor binding domain of the SARS-CoV-2 S-protein has a strong interaction with ACE2, so ACE2 may be a potent drug target to prevent the virus from invading host cells for anti-COVID-19 drug discovery. In this study, structure- and property-based virtual screening methods were combined to filter natural product databases from ChemDiv, TargetMol, and InterBioScreen to find potential ACE2 inhibitors. The binding affinity between protein and ligands was predicted using both Glide SP and XP scoring functions and the MM-GBSA method. ADME properties were also calculated to evaluate chemical drug-likeness. Then, molecular dynamics (MD) simulations were performed to further explore the binding modes between the highest-potential compounds and ACE2. Results showed that the compounds 154-23-4 and STOCK1N-07141 possess potential ACE2 inhibition activities and deserve further study.     

Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR—the quorum-sensing receptor from Chromobacterium violaceum—as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.     

An iterative knowledge-based scoring function to predict protein-ligand interactions: II. Validation of the scoring function

We have developed an iterative knowledge-based scoring function (ITScore) to describe protein-ligand interactions. Here, we assess ITScore through extensive tests on native structure identification, binding affinity prediction, and virtual database screening. Specifically, ITScore was first applied to a test set of 100 protein-ligand complexes constructed by Wang et al. (J Med Chem 2003, 46, 2287), and compared with 14 other scoring functions. The results show that ITScore yielded a high success rate of 82% on identifying native-like binding modes under the criterion of rmsd < or = 2 A for each top-ranked ligand conformation. The success rate increased to 98% if the top five conformations were considered for each ligand. In the case of binding affinity prediction, ITScore also obtained a good correlation for this test set (R = 0.65). Next, ITScore was used to predict binding affinities of a second diverse test set of 77 protein-ligand complexes prepared by Muegge and Martin (J Med Chem 1999, 42, 791), and compared with four other widely used knowledge-based scoring functions. ITScore yielded a high correlation of R2 = 0.65 (or R = 0.81) in the affinity prediction. Finally, enrichment tests were performed with ITScore against four target proteins using the compound databases constructed by Jacobsson et al. (J Med Chem 2003, 46, 5781). The results were compared with those of eight other scoring functions. ITScore yielded high enrichments in all four database screening tests. ITScore can be easily combined with the existing docking programs for the use of structure-based drug design.     

A Bayesian statistical approach of improving knowledge‐based scoring functions for protein–ligand interactions

Knowledge‐based scoring functions are widely used for assessing putative complexes in protein–ligand and protein–protein docking and for structure prediction. Even with large training sets, knowledge‐based scoring functions face the inevitable problem of sparse data. Here, we have developed a novel approach for handling the sparse data problem that is based on estimating the inaccuracies in knowledge‐based scoring functions. This inaccuracy estimation is used to automatically weight the knowledge‐based scoring function with an alternative, force‐field‐based potential (FFP) that does not rely on training data and can, therefore, provide an improved approximation of the interactions between rare chemical groups. The current version of STScore, a protein–ligand scoring function using our method, achieves a binding mode prediction success rate of 91% on the set of 100 complexes by Wang et al., and a binding affinity correlation of 0.514 with the experimentally determined affinities in PDBbind. The method presented here may be used with other FFPs and other knowledge‐based scoring functions and can also be applied to protein–protein docking and protein structure prediction. © 2014 Wiley Periodicals, Inc.     

Molecular Dynamics Simulation of Ester‐Linked Hen Egg White Lysozyme Reveals the Effect of Missing Backbone Hydrogen Bond Donors on the Protein Structure

The three‐dimensional structure of a protein is stabilized by a number of different atomic interactions. One of these is hydrogen bonding. Its influence on the spatial structure of the hen egg white lysozyme is investigated by replacing peptide bonds (except those of the two proline residues) by ester bonds. Molecular dynamics simulations of native and ester‐linked lysozyme are compared with the native crystal structure and with NOE distance bounds derived from solution NMR experiments. The ester‐linked protein shows a slight compaction while losing its native structure. However, it does not unfold completely. The structure remains compact due to its hydrophobic core and a changed network of hydrogen bonds involving side chains.     

Coarse‐grained A‐graft‐B model of poly(lactic acid) for molecular dynamics simulations

A mesoscopic model of poly(lactic acid) is developed where the polymer is represented as an A‐graft‐B chain with monomer units consisting of two covalently connected beads. A coarse‐graining algorithm is proposed to convert an atomistic model of PLA into a coarse‐grained one. The developed model is based on atomistic simulations of oligolactides to take into account terminal groups correctly. It was used for coarse‐grained simulations of polylactide. Gyration radii and end to end distances of polymer chains as well as the density of the polymer melt are shown to be in a good agreement with those obtained from atomistic simulations. The thermal expansion coefficients of the OLA melts calculated using the coarse‐grained model are in reasonable agreement with those obtained from all‐atom molecular dynamics. The model provides a 17‐fold speedup compared with atomistic calculations. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2018 , 56, 604–612     

A Ferrocene‐Tagged Amyloid‐β Fragment for Rapid Screening of Aggregation Inhibitors from Natural Compounds by HPLC‐Electrochemical Detection

Aggregates of amyloid beta (Aβ) peptides are believed to be responsible for the neuropathology of Alzheimer’s disease. In this work, ferrocene (Fc) is attached to the aggregating core of the Aβ peptides, KLVFFAE. Inhibition of Fc‐KLVFFAE aggregation by curcumin, a natural compound, was monitored by HPLC‐electrochemical detection (HPLC‐EC). The Fc oxidation current is dependent on the incubation condition and curcumin can retain Fc‐KLVFFAE in its monomeric form. We demonstrate that tagging Fc to KLVFFAE affords a cost‐effective and electroactive mimicry of Aβ(1? 42) and HPLC‐EC is suitable for sensitive, reproducible, and facile screening of drugs for inhibiting the aggregation of Aβ peptides.     

The Effect of Fluoro Substitution upon the β‐Hairpin Fold of a β‐Tetrapeptide in Methanol

The importance of β‐peptides lies in their ability to mimic the conformational behavior of α‐peptides, even with a much shorter chain length, and in their resistance to proteases. To investigate the effect of substitution of β‐peptides on their dominant fold, we have carried out a molecular‐dynamics (MD) simulation study of two tetrapeptides, Ac‐(2R,3S)‐β^2,3hVal(αMe)‐(2S)‐β²hPhe‐(R)‐β³hLys‐(2R,3S)‐β^2,3‐Ala(αMe)‐NH₂, differing in the substitution at the C_α of Phe2 (pepF with F, and pepH with H). Three simulations, unrestrained (UNRES), using ³J‐coupling biasing with local elevation in combination with either instantaneous (INS) or time‐averaging (AVE) NOE distance restraining, were carried out for each peptide. In the unrestrained simulations, we find three (pepF) and two (pepH) NOE distance bound violations of maximally 0.22 nm that involve the terminal residues. The restrained simulations match both the NOE distance bounds and ³J‐values derived from experiment. The fluorinated peptide shows a slightly larger conformational variability than the non‐fluorinated one.     

Identification of Flavonoids as Putative ROS-1 Kinase Inhibitors Using Pharmacophore Modeling for NSCLC Therapeutics

Non-small cell lung cancer (NSCLC) is a lethal non-immunogenic malignancy and proto-oncogene ROS-1 tyrosine kinase is one of its clinically relevant oncogenic markers. The ROS-1 inhibitor, crizotinib, demonstrated resistance due to the Gly2032Arg mutation. To curtail this resistance, researchers developed lorlatinib against the mutated kinase. In the present study, a receptor-ligand pharmacophore model exploiting the key features of lorlatinib binding with ROS-1 was exploited to identify inhibitors against the wild-type (WT) and the mutant (MT) kinase domain. The developed model was utilized to virtually screen the TimTec flavonoids database and the retrieved drug-like hits were subjected for docking with the WT and MT ROS-1 kinase. A total of 10 flavonoids displayed higher docking scores than lorlatinib. Subsequent molecular dynamics simulations of the acquired flavonoids with WT and MT ROS-1 revealed no steric clashes with the Arg2032 (MT ROS-1). The binding free energy calculations computed via molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) demonstrated one flavonoid (Hit) with better energy than lorlatinib in binding with WT and MT ROS-1. The Hit compound was observed to bind in the ROS-1 selectivity pocket comprised of residues from the β-3 sheet and DFG-motif. The identified Hit from this investigation could act as a potent WT and MT ROS-1 inhibitor.     

Use of Molecular‐Dynamics Simulation for Optimizing Protein Stability: Consensus‐Designed Ankyrin Repeat Proteins

In earlier work, two highly homologous (87% sequence identity) ankyrin repeat (AR) proteins, E3_5 and E3_19, were studied using molecular‐dynamics (MD) simulation. Their stabilities were compared, and it was found that the C‐terminal capping unit is unstable in the protein E3_19, in agreement with CD experiments. The different stabilities of these two very similar proteins could be explained by the different charge distributions among the AR units of the two proteins. Here, another AR protein, N3C, with yet another charge distribution has been simulated using MD, and its stability was analyzed. In agreement with the experimental data, the structure of N3C was found to be less stable than that of E3_5, but, in contrast to E3_19, secondary structure was only slightly lost, while structurally N3C is closer to E3_19 than to E3_5. The results suggest that a homogeneous charge distribution over the repeat units does enhance the stability of design AR proteins in aqueous solution, which, however, may be modulated by the bulkiness of amino‐acid side chains involved in the mutations.     

On the Relative Merits of Equilibrium and Non‐Equilibrium Simulations for the Estimation of Free‐Energy Differences

The possibility of estimating equilibrium free‐energy profiles from multiple non‐equilibrium simulations using the fluctuation–dissipation theory or the relation proposed by Jarzynski has attracted much attention. Although the Jarzynski estimator has poor convergence properties for simulations far from equilibrium, corrections have been derived for cases in which the work is Gaussian distributed. Here, we examine the utility of corrections proposed by Gore and collaborators using a simple dissipative system as a test case. The system consists of a single methane‐like particle in explicit water. The Jarzynski equality is used to estimate the change in free energy associated with pulling the methane particle a distance of 3.9 nm at rates ranging from ～0.1 to 100 m s^?1. It is shown that although the corrections proposed by Gore and collaborators have excellent numerical performance, the profiles still converge slowly. Even when the corrections are applied in an ideal case where the work distribution is necessarily Gaussian, performing simulations under quasi‐equilibrium conditions is still most efficient. Furthermore, it is shown that even for a single methane molecule in water, pulling rates as low as 1 m s^?1 can be problematic. The implications of this finding for studies in which small molecules or even large biomolecules are pulled through inhomogeneous environments at similar pulling rates are discussed.     

The Propensity of α‐Aminoisobutyric Acid (=2‐Methylalanine; Aib) to Induce Helical Secondary Structure in an α‐Heptapeptide: A Computational Study

We present a molecular‐dynamics simulation study of an α‐heptapeptide containing an α‐aminoisobutyric acid (=2‐methylalanine; Aib) residue, Val¹‐Ala²‐Leu³‐Aib⁴‐Ile⁵‐Met⁶‐Phe⁷, and a quantum‐mechanical (QM) study of simplified models to investigate the propensity of the Aib residue to induce 3₁₀/α‐helical conformation. For comparison, we have also performed simulations of three analogues of the peptide with the Aib residue being replaced by L ‐Ala, D ‐Ala, and Gly, respectively, which provide information on the subtitution effect at C(α) (two Me groups for Aib, one for L ‐Ala and D ‐Ala, and zero for Gly). Our simulations suggest that, in MeOH, the heptapeptide hardly folds into canonical helical conformations, but appears to populate multiple conformations, i.e., C₇ and 3₁₀‐helical ones, which is in agreement with results from the QM calculations and NMR experiments. The populations of these conformations depend on the polarity of the solvent. Our study confirms that a short peptide, though with the presence of an Aib residue in the middle of the chain, does not have to fold to an α‐helical secondary structure. To generate a helical conformation for a linear peptide, several Aib residues should be present in the peptide, either sequentially or alternatively, to enhance the propensity of Aib‐containing peptides towards the helical conformation. A correction of a few of the published NMR data is reported.     

Potential of atmospheric pressure chemical ionization source in GC‐QTOF MS for pesticide residue analysis

The potential applications of a new atmospheric pressure source for GC‐MS analysis have been investigated in this work. A list of around 100 GC‐amenable pesticides, which includes organochlorine, organophosphorus and organonitrogenated compounds, has been used to evaluate their behavior in the new source. Favoring the major formation of the molecular ion in the source has been the main goal due to the wide‐scope screening possibilities that this fact brings in comparison with the traditional, highly fragmented electron ionization spectra. Thus, the addition of water as modifier has been tested as a way to promote the generation of protonated molecules. Pesticides investigated have been classified into six groups according to their ionization/fragmentation behavior. Four of them are characterized by the abundant formation of the protonated molecule in the atmospheric pressure source, mostly being the base peak of the spectrum. These results show that wide‐scope screening could be easily performed with this source by investigating the presence of the protonated molecule ion, MH+. The developed procedure has been applied to pesticide screening in different food samples (nectarine, orange and spinach) and it has allowed the presence of several pesticides to be confirmed such as chlorpyriphos ethyl, deltamethrin and endosulfan sulfate. The availability of a quadrupole time‐of‐flight instrument made it feasible to perform additional MS/MS experiments for both standards and samples to go further in the confirmation of the identity of the detected compounds. Results shown in this paper have been obtained using a prototype source which exhibits promising features that could be applied to other analytical problems apart from those illustrated in this work. Copyright © 2010 John Wiley & Sons, Ltd.