Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches

In continuation of our recent studies on the quality of conformational models generated with CATALYST and OMEGA we present a large-scale survey focusing on the impact of conformational model quality and several screening parameters on pharmacophore-based and shape-based virtual high throughput screening (vHTS). Therefore, we collected known active compounds of CDK2, p38 MAPK, PPAR-gamma, and factor Xa and built a set of druglike decoys using ilib:diverse. Subsequently, we generated 3D structures using CORINA and also calculated conformational models for all compounds using CAESAR, CATALYST FAST, and OMEGA. A widespread set of 103 structure-based pharmacophore models was developed with LigandScout for virtual screening with CATALYST. The performance of both database search modes (FAST and BEST flexible database search) as well as the fit value calculation procedures (FAST and BEST fit) available in CATALYST were analyzed in terms of their ability to discriminate between active and inactive compounds and in terms of efficiency. Moreover, these results are put in direct comparison to the performance of the shape-based virtual screening platform ROCS. Our results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: In most of the experiments, we obtained the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used.     

eHiTS-to-VMD interface application. The search for tyrosine-tRNA ligase inhibitors

Owing to the recent development of virtual high-throughput screening (vHTS) and a vast number of compounds subjected to vHTS analyses, it has been essential to automate the processing of computational data required for the analysis and visualization of research results. Using the search for tyrosine-tRNA ligase inhibitors as an example, we present a computer application, an interface between eHiTS software for virtual high-throughput screening and VMD graphic software used to visualize calculation results.     

QSAR based virtual screening derived identification of a novel hit as a SARS CoV-229E 3CLpro Inhibitor: GA-MLR QSAR modeling supported by molecular Docking,molecular dynamics simulation and MMGBSA calculation approaches

Congruous coronavirus drug targets and analogous lead molecules must be identified as quickly as possible to produce antiviral therapeutics against human coronavirus (HCoV SARS 3CLpro) infections. In the present communication, we bear recognized a HIT candidate for HCoV SARS 3CLpro inhibition. Four Parametric GA-MLR primarily based QSAR model (R2:0.84, R2adj:0.82, Q2loo: 0.78) was once promoted using a dataset over 37 structurally diverse molecules along QSAR based virtual screening (QSAR-VS), molecular docking (MD) then molecular dynamic simulation (MDS) analysis and MMGBSA calculations. The QSAR-based virtual screening was utilized to find novel lead molecules from an in-house database of 100 molecules. The QSAR-vS successfully offered a hit molecule with an improved _PEC₅₀ value from 5.88 to 6.08. The benzene ring, phenyl ring, amide oxygen and nitrogen, and other important pharmacophoric sites are revealed via MD and MDS studies. Ile164, Pro188, Leu190, Thr25, His41, Asn46, Thr47, Ser49, Asn189, Gln191, Thr47, and Asn141 are among the key amino acid residues in the S1 and S2 pocket. A stable complex of a lead molecule with the HCoV SARS 3CLpro was discovered using MDS. MM-GBSA calculations resulted from MD simulation results well supported with the binding energies calculated from the docking results. The results of this study can be exploited to develop a novel antiviral target, such as an HCoV SARS 3CLpro Inhibitor.     

Accurate mass measurement using Fourier transform ion cyclotron resonance mass spectrometry for structure elucidation of designer drug analogs of tadalafil, vardenafil and sildenafil in herbal and pharmaceutical matrices

Phosphodiesterase type 5 (PDE-5) inhibitors are a class of drugs used primarily in the treatment of erectile dysfunction. The Food and Drug Administration (FDA) approved PDE-5 inhibitors include sildenafil citrate, vardenafil hydrochloride and tadalafil. In this study, accurate mass measurements were made by electrospray ionization (ESI) using Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) to elucidate the structures of sildenafil, tadalafil and vardenafil analogs that were found in products marketed as dietary supplements. Initial detection of these analogs was accomplished through routine screening of suspect samples by liquid chromatography/electrospray ionization multi-stage mass spectrometry (LC/ESI-MS(n)) on a low-resolution ion trap instrument. The chromatographic behavior and mass spectrometric fragmentation patterns observed were often similar to those observed for FDA approved PDE-5 inhibitors. The mass accuracy and resolving power associated with FTICRMS allows for the determination of elemental compositions. Elucidation of the product ion structures for the analogs was accomplished through the use of accurate mass measurements with the aid of Mass Frontier software (version 4.0). Using FTICRMS, accurate masses with measurement errors averaging <0.4 ppm were achieved, allowing assignment of one possible elemental formula to each fragment ion. The mass measurement errors associated with [M + H](+) for the analogs aminotadalafil, piperidino vardenafil, hydroxyacetildenafil and piperidino acetildenafil were 0.1, 0.0, 0.1 and 0.5 ppm, respectively. Based on the accuracy of the measurements, structural assignments could be made with a high degree of confidence.     

Electrostatic screening and energy barriers of ions in low-dielectric membranes

We present exact solutions of the linear Poisson-Boltzmann equation for several problems relevant for ion translocation across low-dielectric membranes. Our results are obtained for a finite Debye screening length, and they generalize the classical results for pure Coulombic electrostatics (Parsegian, A. Nature (London) 1969, 221, 844). We calculate the electrostatic self-energy of an ion in the middle of a low-dielectric slab, its energy inside a cylindrical high-dielectric pore, and its energy inside a high-dielectric spherical jacket. We consider also the influence of negative charges distributed on the walls of the cylindrical pore. We show that ion self-energy barriers are considerably reduced due to screening of electrolyte. We compare our results with some numerical results for screened electrostatics of ion channels and wide pores.     

Simultaneous determination of norisoboldine and its major metabolite in rat plasma by ultra-performance liquid chromatography-mass spectrometry and its application in a pharmacokinetic study

Norisoboldine (NIB) is one of the main bioactive isoquinoline alkaloids in Linderae Radix. A rapid, selective and sensitive method using UPLC‐ESI/MS was first developed for simultaneous determination of NIB and norisoboldine‐9‐O‐α‐glucuronide (NIB‐Glu), its major metabolite in rat plasma. A one‐step protein precipitation with methanol was employed as sample preparation technique. Chromatographic separation was carried out on an Acquity UPLC BEH C₁₈ column (50 × 2.1 mm, i.d. 1.7 µm) with a gradient mobile phase consisting of acetonitrile and water containing 0.1% formic acid. Detection and quantification were performed using a quadrupole mass spectrometer by selective ion reaction‐monitoring mode. Good linearity was achieved using weighted (1/x²) least squares linear regression over the concentration ranges 0.01–2 µg/mL for NIB and 0.025–25 µg/mL for NIB‐Glu. The lower limit of quantification of NIB and NIB‐Glu was 0.01 and 0.025 µg/mL, respectively. The intra‐ and inter‐day precisions (relative standard deviations) of the assay at all three quality control levels were 4.6–14.1% for NIB, and 5.0–12.2% for NIB‐Glu. The accuracies (relative error) were −13.5–8.1% for NIB and −12.8–7.6% for NIB‐Glu, respectively. This developed method was successfully applied to an in vivo pharmacokinetic study in rats after a single intravenous dose of 10 mg/kg NIB. Copyright © 2010 John Wiley & Sons, Ltd.     

表面增强拉曼光谱对西地那非类药物的快速检测

采用表面增强拉曼光谱(SERS)技术并结合简单的前处理流程,对保健品样品中11种西地那非类药物进行了非定向快速筛查研究.结果表明,11种西地那非类药物可根据结构分为5类,类别之间SERS谱图差异显著;类别内SERS谱图具有共性特征,特征峰相对强度差异明显.实际样品的检测中,西地那非类药物的最低检出浓度约为0.05 mg/kg;前处理和测试的总时长约为3~5 min,且与检测目标物和样品无关.本方法高灵敏度、快速和非定向检测的设计理念为快速检测保健品中违禁添加药物提供了新思路和新方法.     

Novel approach to structure-based pharmacophore search using computational geometry and shape matching techniques

Computationally efficient structure-based virtual screening methods have recently been reported that seek to find effective means to utilize experimental structure information without employing detailed molecular docking calculations. These tools can be coupled with efficient experimental screening technologies to improve the probability of identifying hits and leads for drug discovery research. Commercial software ROCS (rapid overlay of chemical structures) from Open Eye Scientific is such an example, which is a shape-based virtual screening method using the 3D structure of a ligand, typically from a bound X-ray costructure, as the query. We report here the development of a new structure-based pharmacophore search method (called Shape4) for virtual screening. This method adopts a variant of the ROCS shape technology and expands its use to work with an empty crystal structure. It employs a rigorous computational geometry method and a deterministic geometric casting algorithm to derive the negative image (i.e., pseudoligand) of a target binding site. Once the negative image (or pseudoligand) is generated, an efficient shape comparison algorithm in the commercial OE SHAPE Toolkit is adopted to compare and match small organic molecules with the shape of the pseudoligand. We report the detailed computational protocol and its computational validation using known biologically active compounds extracted from the WOMBAT database. Models derived for five selected targets were used to perform the virtual screening experiments to obtain the enrichment data for various virtual screening methods. It was found that our approach afforded similar or better enrichment ratios than other related methods, often with better diversity among the top ranking computational hits.     

Nanoscale molecular traps and dams for ultrafast protein enrichment in high-conductivity buffers

We report a new approach, molecular dam, to enhance mass transport for protein enrichment in nanofluidic channels by nanoscale electrodeless dielectrophoresis under physiological buffer conditions. Dielectric nanoconstrictions down to 30 nm embedded in nanofluidic devices serve as field-focusing lenses capable of magnifying the applied field to 10(5)-fold when combined with a micro- to nanofluidic step interface. With this strong field and the associated field gradient at the nanoconstrictions, proteins are enriched by the molecular damming effect faster than the trapping effect, to >10(5)-fold in 20 s, orders of magnitude faster than most reported methods. Our study opens further possibilities of using nanoscale molecular dams in miniaturized sensing platforms for rapid and sensitive protein analysis and biomarker discovery, with potential applications in precipitation studies and protein crystallization and possible extensions to small-molecules enrichment or screening.     

Molecular dynamics and continuum electrostatics studies of inactivation in the HERG potassium channel

Fast inactivation of the HERG potassium channel plays a critical role in normal cardiac function. Malfunction of these channels due to either genetic mutations or blockade by drugs leads to cardiac arrhythmias. An unusually long S5-P linker in the outer mouth of HERG is implicated in the fast inactivation mechanism. To examine the role of the S5-P linker in this inactivation mechanism, we study the permeation properties of the open and inactive states of a recent homology model of HERG. This model was constructed using the KcsA potassium channel as a template and contains specific conformations of the S5-P linker in the open and inactive states. We perform molecular dynamics simulations on the HERG model, followed by free energy, structural, and continuum electrostatics calculations. Our free energy calculations lead to selectivity results of the model channel (K+ over Na+) that are different in some respects from those of other potassium channels but consistent with experimental observations. Our structural results show that, in the inactive state, the S5-P linkers move closer to the channel axis, possibly causing a steric hindrance to permeating K+ ions. Our electrostatics calculations reveal, in the inactive state, an electrostatic potential energy barrier of approximately 14 kT at the extracellular pore entrance, again sufficient to stop K+ ion permeation through the pore. These results suggest that a steric and/or electrostatic plug mechanism contributes to inactivation in the HERG homology model.     

Challenges in the determination of the binding modes of non-standard ligands in X-ray crystal complexes

Despite its central role in structure based drug design the determination of the binding mode (position, orientation and conformation in addition to protonation and tautomeric states) of small heteromolecular ligands in protein:ligand complexes based on medium resolution X-ray diffraction data is highly challenging. In this perspective we demonstrate how a combination of molecular dynamics simulations and free energy (FE) calculations can be used to correct and identify thermodynamically stable binding modes of ligands in X-ray crystal complexes. The consequences of inappropriate ligand structure, force field and the absence of electrostatics during X-ray refinement are highlighted. The implications of such uncertainties and errors for the validation of virtual screening and fragment-based drug design based on high throughput X-ray crystallography are discussed with possible solutions and guidelines.     

Universal solvation model based on conductor‐like screening model

Atomic surface tensions are parameterized for use with solvation models in which the electrostatic part of the calculation is based on the conductor‐like screening model (COSMO) and the semiempirical molecular orbital methods AM1, PM3, and MNDO/d. The convergence of the calculated polarization free energies with respect to the numerical parameters of the electrostatic calculations is first examined. The accuracy and precision of the calculated values are improved significantly by adjusting two parameters that control the segmentation of the solvent‐accessible surface that is used for the calculations. The accuracy of COSMO calculations is further improved by adopting an optimized set of empirical electrostatic atomic radii. Finally, the electrostatic calculation is combined with SM5‐type atomic surface tension functionals that are used to compute the nonelectrostatic portions of the solvation free energy. All parameterizations are carried out using rigid (R) gas‐phase geometries; this combination (SM5‐type surface tensions, COSMO electrostatics, and rigid geometries) is called SM5CR. Six air–water and 76 water–solvent partition coefficients are added to the training set of air–solvent data points previously used to parameterize the SM5 suite of solvation models, thereby bringing the total number of data points in the training set to 2266. The model yields free energies of solvation and transfer with mean unsigned errors of 0.63, 0.59, and 0.61 kcal/mol for AM1, PM3, and MNDO/d, respectively, over all 2217 data points for neutral solutes in the training set and mean unsigned errors of 3.0, 2.7, and 3.1 kcal/mol, respectively, for 49 data points for the ions. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 340–366, 2000     

Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide

Fragment-based drug discovery approaches allow for a greater coverage of chemical space and generally produce high efficiency ligands. As such, virtual and experimental fragment screening are increasingly being coupled in an effort to identify new leads for specific therapeutic targets. Fragment docking is employed to create target-focussed subset of compounds for testing along side generic fragment libraries. The utility of the program Glide with various scoring schemes for fragment docking is discussed. Fragment docking results for two test cases, prostaglandin D2 synthase and DNA ligase, are presented and compared to experimental screening data. Self-docking, cross-docking, and enrichment studies are performed. For the enrichment runs, experimental data exists indicating that the docking decoys in fact do not inhibit the corresponding enzyme being examined. Results indicate that even for difficult test cases fragment docking can yield enrichments significantly better than random. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A_1腺苷受体的同源模建及其结构验证

采用同源模建的方法构建了A1腺苷受体的三维结构,并与拮抗剂分子DPCPX对接,将得到的复合物结构进行5 ns的分子动力学模拟,以最后2 ns的平均结构和平衡后抽取的11帧构象共12个蛋白结构为研究对象,用包含52个活性分子和1000个诱饵分子的测试库,分别通过DOCK、VINA和GOLD三种对接软件进行评价,最终得出合理的蛋白质模型.根据top10%的富集因子(EF)和ROC曲线下面积(AU-ROC)的计算结果,我们认为GOLD是最适合A1腺苷受体的对接软件,而12个蛋白质结构中F5和Favg的三维结构模型比较合理,可以作为进一步大规模虚拟筛选的模型.     

Chemical space sampling by different scoring functions and crystal structures

Virtual screening has become a popular tool to identify novel leads in the early phases of drug discovery. A variety of docking and scoring methods used in virtual screening have been the subject of active research in an effort to gauge limitations and articulate best practices. However, how to best utilize different scoring functions and various crystal structures, when available, is not yet well understood. In this work we use multiple crystal structures of PI3 K-γ in both prospective and retrospective virtual screening experiments. Both Glide SP scoring and Prime MM-GBSA rescoring are utilized in the prospective and retrospective virtual screens, and consensus scoring is investigated in the retrospective virtual screening experiments. The results show that each of the different crystal structures that was used, samples a different chemical space, i.e. different chemotypes are prioritized by each structure. In addition, the different (re)scoring functions prioritize different chemotypes as well. Somewhat surprisingly, the Prime MM-GBSA scoring function generally gives lower enrichments than Glide SP. Finally we investigate the impact of different ligand preparation protocols on virtual screening enrichment factors. In summary, different crystal structures and different scoring functions are complementary to each other and allow for a wider variety of chemotypes to be considered for experimental follow-up.     

Direct measurements of electric fields in weak OH···π hydrogen bonds

Hydrogen bonds and aromatic interactions are of widespread importance in chemistry, biology, and materials science. Electrostatics play a fundamental role in these interactions, but the magnitude of the electric fields that support them has not been quantified experimentally. Phenol forms a weak hydrogen bond complex with the π-cloud of benzene, and we used this as a model system to study the role of electric fields in weak OH···π hydrogen bonds. The effects of complex formation on the vibrational frequency of the phenol OH or OD stretches were measured in a series of benzene-based aromatic solvents. Large shifts are observed and these can be converted into electric fields via the measured vibrational Stark effect. A comparison of the measured fields with quantum chemical calculations demonstrates that calculations performed in the gas phase are surprisingly effective at capturing the electrostatics observed in solution. The results provide quantitative measurements of the magnitude of electric fields and electrostatic binding energies in these interactions and suggest that electrostatics dominate them. The combination of vibrational Stark effect (VSE) measurements of electric fields and high-level quantum chemistry calculations is a general strategy for quantifying and characterizing the origins of intermolecular interactions.     

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein–ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.     

In-silico guided discovery of novel CCR9 antagonists

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn’s disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.