Potent angiotensin-converting enzyme inhibitory tripeptides identified by a computer-based approach

Currently, peptides and peptidomimetics are the main focus in attempts to identify inhibitors of angiotensin-converting enzyme (ACE), the dipeptidyl carboxypeptidase that causes blood vessels to constrict and blood pressure to increase. This study was conducted to identify the most potent ACE-inhibitory tripeptides with a proline C-terminus, using a novel three-step (tautomerization-docking-ADME simulation) virtual screening process and in vitro assays. Sixteen candidates were identified, and their IC₅₀ values ranged from 5.6 to 274.4 μM. ACE inhibition activity for 14 of the 16 tripeptides was reported for the first time. We also found that changing from the L-form to the D-form of the amino acid at the amino and carboxyl termini resulted in a decrease of inhibition, but a greater decrease was observed for C-terminal changes. With low IC₅₀ values and high-predicted bioavailability, the peptides identified by our protocol are comparable in terms of ACE-inhibition to those derived from costly and time-consuming wet screening. Our in vitro and docking results showed that the configuration of the C-terminus is a critical parameter contributing to the inhibitory activity of tripeptides with proline at this position. These findings will contribute to the use of simulation tools for rational drug design, especially for ACE inhibitors.     

Stereoelectronic explanations for the mechanistic details of transimination and HF elimination reactions

The β-fluoroamines are commonly used as substrate analogs to determine the mechanistic details of enzymatic reactions. Presence of fluorine atom gives rise to the alterations in the electronic profile and the pK_a of molecules which results in mechanistic deviations. The fluorine-substituted mechanism-based substrate analogs are widely used in the inactivation of pyridoxal 5′-phosphate (PLP)-dependent enzymes. The presence of fluorine atom also alters the sequence of reactions taking place in PLP-dependent enzymes where the HF elimination reaction appears in between the transimination and inactivation reactions. Despite the amount of the works on β-fluoroamines, the effect of stereoelectronic differences on the transimination and HF elimination reactions taking place in PLP-dependent enzymes has not been investigated yet. A density functional theory study is conducted to elucidate mechanistic details of the reactions occurring in PLP-dependent enzymes. In order to understand the mechanistic insights of different isomers and the effect of the fluorine atom, 4-amino-3-fluorobutanoic acid (3-F-GABA) enantiomers are chosen to be investigated besides 4-aminobutanoic acid (GABA), which is the natural substrate for γ-aminobutyric acid aminotransferase (GABA-AT). The investigated β-fluoroamines are the experimentally proposed potential inhibitors of PLP-dependent enzyme GABA-AT.     

Homology modeling of human sialidase enzymes NEU1, NEU3 and NEU4 based on the crystal structure of NEU2: hints for the design of selective NEU3 inhibitors

Four types of human sialidases have been cloned and characterized at the molecular level. They are classified according to their major intracellular location as intralysomal (NEU1), cytosolic (NEU2), plasma membrane (NEU3) and lysosomal or mitochondrial membrane (NEU4) associated sialidases. These human isoforms are distinct from each other in their enzymatic properties as well as their substrate specificity. Altered expression of sialidases has been correlated with malignant transformation of cells and different sialidases have been known to behave differently during carcinogenesis. Particularly, increased expression of NEU3 has been implicated in the survival of various cancer cells and also in the development of insulin resistance. In the present study, we have modeled three-dimensional structures of NEU1, NEU3 and NEU4 based on the crystal structure of NEU2 using the homology modeling program MODELER. The best model in each enzyme case was chosen on the basis of various standard protein analysis programs. Predicted structures and the experimental protein-ligand complex of NEU2 were compared to identify similarities and differences among the active sites. The molecular electrostatic potential (MEP) was calculated for the predicted models to identify the differences in charge distribution around the active site and its vicinity. The primary objective of the present work is to identify the structural differences between the different isoforms of human sialidases, namely NEU1, NEU2, NEU3 and NEU4, thus providing a better insight into the differences in the active sites of these enzymes. This can in turn guide us in the better understanding and rationale of the differential substrate recognition and activity, thereby aiding in the structure-based design of selective NEU3 inhibitors.     

The application of metabolic resistance theory to the selection of preferred target enzymes for therapeutic drugs

A number of drugs act by inhibition of a specific target enzyme, thereby interfering with the synthesis of a key metabolite. When a specific enzyme inhibitor is applied to a functioning metabolic pathway, the substrate will accumulate and the inhibition will be counteracted, a phenomenon known as metabolic resistance. The work described in this report delineates the circumstances which accentuate, and those which suppress, metabolic resistance. By computer simulation it is shown that the effect of an inhibitor is less pronounced when the target enzyme is remote from the reaction which produces the key metabolite, separated from it by a large pool of intermediates, or separated by an enzyme which is nearly saturated with its substrate. Further, it is shown that noncompetitive, uncompetitive, or irreversible inhibitors are more effective than competitive inhibitors. Finally, enzymes immediately following a branch point and those which form part of a cycle are the least likely to exhibit metabolic resistance. These considerations are encapsulated in six rules for the selection of preferred enzyme targets for drug action.     

Evaluation of the combination mode of azoles antifungal inhibitors with CACYP51 and the influence of Site-directed mutation

14α-demethylase (CYP51) is an essential metabolic enzyme for fungal survival and has been considered as an interesting target for the development of new antifungal inhibitors. Azoles antifungal inhibitors in the treatment of fungal diseases are good candidates via the interaction with the target enzyme CYP51 of fungus. In the study, we constructed the homology model for Candida albicans CYP51 (CACYP51) and analyzed the active site. In order to better understand the structural characteristics of azoles inhibitors and combination mode, the common feature pharmacophore model and the molecular docking were performed. The results suggest that the azoles inhibitors consist of three chemical features: the aromatic groups, phenyl groups and the azoles groups. The aromatic groups of inhibitors occupy the upper of active pocket, the phenyl groups and azoles groups occupy the bottom of active pocket. Further validation studies found these amino acid residues Tyr118, His310 and Ser378 play an important role in the substrate binding, and these amino acid residues with site-directed mutation will weaken the combining ability of the inhibitors.     

Modelling β-1,3-exoglucanase–saccharide interactions: Structure of the enzyme–substrate complex and enzyme binding to the cell wall

Glycoside hydrolases are a class of enzymes that break/form the bond between sugar monomers (monosaccharides). Candida albicans's β-1,3-exoglucanase (Exg), a family 5 glycosidase, belongs to this class of enzymes. This small protein is an ideal computational model for its family of enzymes and was used here to create several enzyme–substrate models starting from a crystallographic glucanase-inhibitor structure. A series of enzyme–substrate complexes were generated using molecular docking, ranging from Exg–glucose (Exg–1Glc) to Exg–laminarihexaose (Exg–6Glc). Structure optimizations followed by molecular dynamics provided a picture of the way the enzyme and substrates interact.Molecular dynamics was conducted for each complex to assess the flexibility of the substrate, of the enzyme as a whole, and of enzyme–substrate interactions. The enzyme overall conformation was found to be quite rigid, although most enzyme residues increase mobility upon substrate binding. However, two surface loops stand out by having large fluctuations and becoming less flexible when the substrates were bound. These data point to a possible biological role for the mentioned loops, corresponding to amino acids 36–47 and 101–106.We propose that these loops could bind the enzyme to a glucan chain in the cell wall. The polysaccharide and enzyme structures have very complementary shapes and form numerous interactions; so it appears likely that the flexible loops connect the enzyme to the cell wall and allow it to navigate the wall to shape glucan structure.     

Exploring the binding sites of Staphylococcus aureus phenylalanine tRNA synthetase: A homology model approach

Increased resistance of MRSA (multidrug resistance Staphylococcus aureus) to anti-infective drugs is a threat to global health necessitating the development of anti-infectives with novel mechanisms of action. Phenylalanine tRNA synthetase (PheRS) is a unique enzyme of the aminoacyl-tRNA synthetases (aaRSs), which are essential enzymes for protein biosynthesis. PheRS is an (αb)₂ tetrameric enzyme composed of two alpha subunits (PheS) and two larger beta subunits (PheT). Our potential target in the drug development for the treatment of MRSA infections is the phenylalanine tRNA synthetase alpha subunit that contains the binding site for the natural substrate. There is no crystal structure available for S. aureus PheRS, therefore comparative structure modeling is required to establish a putative 3D structure for the required enzyme enabling development of new inhibitors with greater selectivity. The S. aureus PheRS alpha subunit homology model was constructed using Molecular Operating Environment (MOE) software. Staphylococcus haemolyticus PheRS was the main template while Thermus thermophilus PheRS was utilised to predict the enzyme binding with tRNA^phe. The model has been evaluated and compared with the main template through Ramachandran plots, Verify 3D and Protein Statistical Analysis (ProSA). The query protein active site was predicted from its sequence using a conservation analysis tool. Docking suitable ligands using MOE into the constructed model were used to assess the predicted active sites. The docked ligands involved the PheRS natural substrate (phenylalanine), phenylalanyl-adenylate and several described S. aureus PheRS inhibitors.     

A CoMFA study of COX-2 inhibitors with receptor based alignment

A diverse set of 53 cyclooxygenase-2 (COX-2) inhibitors which were aligned in two different ways were subjected to CoMFA analysis. The first method of alignment of the molecules was based on the binding information sourced from the crystallographic study, from which CoMFA Model 1 was derived. The second mode of alignment was generated by docking the inhibitors in the binding pocket using the DOCK and AFFINITY suite of programs; this gave a second model. The CoMFA Model 2 was slightly better than Model 1 in terms of the statistical parameters r(2) and q(2). The two models could predict very well the activity of a test set of diverse molecules, with a predictive r(2) of 0.593 and 0.768, respectively. Besides the QSAR results, the docking studies give a deep insight into the H-bonding interactions between the inhibitors and residues in the active site of the enzyme, which can be exploited in designing better inhibitors. Useful ideas on activity improvement could be gleaned from these models.     

Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation

With growing interest in extending GIS to support multi-criteria decision-making (MCDM) methods, enhancing GIS-based MCDM with sensitivity analysis (SA) procedures is crucial to understand the model behavior and its limitations. This paper presents a novel approach of examining multi-criteria weight sensitivity of a GIS-based MCDM model. It explores the dependency of model output on the weights of input parameters, identifying criteria that are especially sensitive to weight changes and to show the impacts of changing criteria weights on the model outcomes in spatial dimension. A methodology was developed to perform simulations where the weights associated with all criteria used for suitability modelling were varied one-at-a-time (OAT) to investigate their relative impacts on the final evaluation results. A tool which incorporates the OAT method with the Analytical Hierarchy Process (AHP) within the ArcGIS environment was implemented. It permits a range of user defined simulations to be performed to quantitatively evaluate model dynamic changes, measures the stability of results with respect to the variation of different parameter weights, and displays spatial change dynamics. A case study of irrigated cropland suitability assessment addressing the application of the new GIS-based AHP-SA tool is described. It demonstrates that the tool is spatial, simple and flexible.     

芳香/杂环磺胺类碳酸酐酶Ⅱ抑制剂的活性定量预测(英文)

对125个磺胺类碳酸酐酶Ⅱ抑制剂的生物活性进行了预测研究。利用ADRIANA.Code软件计算得到了化合物的一系列2D和3D结构描述符,从中选用了12个描述符进行建模。分别用数学随机划分的方法和Kohonen自组织神经网络的方法把数据集划分成两组不同的训练集和测试集。对于这两组不同的训练集和测试集,分别利用多元线性回归(MLR)和支持向量机(SVM)的方法进行建模,共得到4个模型。其中SVM得到的2个模型,训练集的相关系数在0.92以上,测试集预测的相关系数都在0.90以上。所有模型可进一步用于碳酸酐酶Ⅱ抑制剂的虚拟筛选。     

From screening to quantitative sensitivity analysis. A unified approach

The present work is a sequel to a recent one published on this journal where the superiority of ‘radial design’ to compute the ‘total sensitivity index’ was ascertained. Both concepts belong to sensitivity analysis of model output. A radial design is the one whereby starting from a random point in the hyperspace of the input factors one step in turn is taken for each factor. The procedure is iterated a number of times with a different starting random point as to collect a sample of elementary shifts for each factor. The total sensitivity index is a powerful sensitivity measure which can be estimated based on such a sample. Given the similarity between the total sensitivity index and a screening test known as method of the elementary effects (or method of Morris), we test the radial design on this method. Both methods are best practices: the total sensitivity index in the class of the quantitative measures and the elementary effects in that of the screening methods. We find that the radial design is indeed superior even for the computation of the elementary effects method. This opens the door to a sensitivity analysis strategy whereby the analyst can start with a small number of points (screening-wise) and then – depending on the results – possibly increase the numeral of points up to compute a fully quantitative measure. Also of interest to practitioners is that a radial design is nothing else than an iterated ‘One factor At a Time’ (OAT) approach. OAT is a radial design of size one. While OAT is not a good practice, modelers in all domains keep using it for sensitivity analysis for reasons discussed elsewhere (Saltelli and Annoni, 2010) [23]. With the present approach modelers are offered a straightforward and economic upgrade of their OAT which maintain OAT's appeal of having just one factor moved at each step.     

Theoretical study of the hydrolysis mechanism of 2-pyrone-4,6-dicarboxylate (PDC) catalyzed by LigI

2-Pyrone-4,6-dicarboxylate lactonase (LigI) is the first identified enzyme from amidohydrolase superfamily that does not require a divalent metal ion for catalytic activity. It catalyzes the reversible hydrolysis of 2-pyrone-4,6-dicarboxylate (PDC) to 4-oxalomesaconate (OMA) and 4-carboxy-2-hydroxymuconate (CHM) in the degradation of lignin. In this paper, a combined quantum mechanics and molecule mechanics (QM/MM) approach was employed to study the reaction mechanism of LigI from Sphingomonas paucimobilis. According to the results of our calculations, the whole catalytic reaction contains three elementary steps, including the nucleophilic attack, the cleavage of CO of lactone (substrate) and the intramolecular proton transfer. The intermediate has two intramolecular proton transfer pathways, due to which, two final hydrolysis products can be obtained. The energy profile indicates that 4-carboxy-2-hydroxymuconate (CHM) is the main hydrolysis product, therefore, the isomerization between 4-carboxy-2-hydroxymuconate (CHM) and 4-oxalomesaconate (OMA) is suggested to occur in solvent. During the catalytic reaction, residue Asp248 acts as a general base to activate the hydrolytic water molecule. Although His31, His33 and His180 do not directly participate in the chemical process, they play assistant roles by forming electrostatic interactions with the substrate and its involved species in activating the carbonyl group of the substrate and stabilizing the intermediates and transition states.     

How to avoid a perfunctory sensitivity analysis

Mathematical modelers from different disciplines and regulatory agencies worldwide agree on the importance of a careful sensitivity analysis (SA) of model-based inference. The most popular SA practice seen in the literature is that of ’one-factor-at-a-time’ (OAT). This consists of analyzing the effect of varying one model input factor at a time while keeping all other fixed. While the shortcomings of OAT are known from the statistical literature, its widespread use among modelers raises concern on the quality of the associated sensitivity analyses. The present paper introduces a novel geometric proof of the inefficiency of OAT, with the purpose of providing the modeling community with a convincing and possibly definitive argument against OAT. Alternatives to OAT are indicated which are based on statistical theory, drawing from experimental design, regression analysis and sensitivity analysis proper.     

User perception of adapting video quality

In general, video quality adaptation and video quality evaluation are distinct activities. Most adaptive delivery mechanisms for streaming multimedia content do not explicitly consider user-perceived quality when making adaptation decisions. Equally, video quality evaluation techniques are not designed to evaluate instantaneous quality where the quality is changing over time. We propose that an Optimal Adaptation Trajectory (OAT) through the set of possible encoding exists, and that it indicates how to adapt encoding quality in response to changes in network conditions in order to maximize user-perceived quality. The subjective and objective tests carried out to find such trajectories for a number of different MPEG-4 video clips are described. Experimental subjective testing results are presented that demonstrate the dynamic nature of user perception with adapting multimedia. The results demonstrate that adaptation using the OAT out-performs conventional adaptation strategies in which only a single aspect of the video quality is adapted. In contrast, the OAT provides a mechanism to adapt multiple aspects of the video quality thereby giving better user-perceived quality in both the short and long term.     

Modelling β-1,3-exoglucanase–saccharide interactions: Structure of the enzyme–substrate complex and enzyme binding to the cell wall

Glycoside hydrolases are a class of enzymes that break/form the bond between sugar monomers (monosaccharides). Candida albicans's β-1,3-exoglucanase (Exg), a family 5 glycosidase, belongs to this class of enzymes. This small protein is an ideal computational model for its family of enzymes and was used here to create several enzyme–substrate models starting from a crystallographic glucanase-inhibitor structure. A series of enzyme–substrate complexes were generated using molecular docking, ranging from Exg–glucose (Exg–1Glc) to Exg–laminarihexaose (Exg–6Glc). Structure optimizations followed by molecular dynamics provided a picture of the way the enzyme and substrates interact.Molecular dynamics was conducted for each complex to assess the flexibility of the substrate, of the enzyme as a whole, and of enzyme–substrate interactions. The enzyme overall conformation was found to be quite rigid, although most enzyme residues increase mobility upon substrate binding. However, two surface loops stand out by having large fluctuations and becoming less flexible when the substrates were bound. These data point to a possible biological role for the mentioned loops, corresponding to amino acids 36–47 and 101–106.We propose that these loops could bind the enzyme to a glucan chain in the cell wall. The polysaccharide and enzyme structures have very complementary shapes and form numerous interactions; so it appears likely that the flexible loops connect the enzyme to the cell wall and allow it to navigate the wall to shape glucan structure.     

一个组织型纤溶性溶解酶原激活剂(T-pa)非共价类抑制剂的药效模型

为了研究组织型纤溶性溶解酶原激活剂（T－pa)的非共价类抑制剂的三维定量构效关系，本文采用分子模拟软件Catalyst4.0(molecular simulation company)构建T-pa的非共价类抑制剂的三维药效模型。14个非共价类的抑制剂及其体外活性数据被用于构建此药效模型。此药效模型有3个疏水区特性，一个正离子化区特性和氢键供体区特性，且结构与活性相关系数为r=0.962。与T－pa的晶体结构比较，此药物模型在化学状态和疏水性上与其能很好的相匹配。且利用此是找到的抑制剂（bbzi14)的活性构象，与晶体结构中此抑制剂的结合构象基本一致。通过此药效集团模型反映的抑制剂与受体的相互作用模式，能为发现新型亲和配基和抑制剂提供有用的启示。     

一个组织型纤溶性溶解酶原激活剂(T-pa)非共价类抑制剂的药效模型

为了研究组织型纤溶性溶解酶原激活剂(T-pa)的非共价类抑制剂的三维定量构效关系,本文采用分子模拟软件Catalyst 4.0(molecular simulation company)构建T-pa的非共价类抑制剂的三维药效模型。14个非共价类的抑制剂及其体外活性数据被用于构建此药效模型。此药效模型有3个疏水区特性,一个正离子化区特性和氢键供体区特性,且结构与活性相关系数为r=0.962。与T-pa的晶体结构比较,此药物模型在化学状态和疏水性上与其能很好的相匹配。且利用此模型查找到的抑制剂(bbzi14)的活性构象,与晶体结构中此抑制剂的结合构象基本一致。通过此药效集团模型反映的抑制剂与受体的相互作用模式,能为发现新型亲和配基和抑制剂提供有用的启示。     

流感病毒神经氨酸酶抑制剂的理性筛选

介绍了理性筛选流感病毒神经氨酸酶抑制剂的全过程，共分4个阶段：1)化合物数据库类药性处理；2)建立神经氨酸酶抑制剂三维药效团并对目标数据库进行构象搜索；3)分子对接及对接后分析；4)神经氨酸酶抑制模型的建立及待测化合物的活性检测。活性检测后发现4个活性化合物，其中Ic。为10。M的化合物1个．Ic，。为10^-6M的化合物2个，IC50为10^-7M的化合物1个。应用理性筛选方法，从化合物数据库中挑选出部分化合物进行神经氨酸酶抑制活性的筛选，减少了药物筛选的盲目性，提高了药物发现的机率。     

Dbtop: topomer similarity searching of conventional structure databases

A new topomer-based method for 3D searching of conventional structural databases is described, according to which 3D molecular structures are compared as sets of fragments or topomers, in single rule-generated conformations oriented by superposition of their fragmentation bonds. A topomer is characterized by its CoMFA-like steric shape and now also by its pharmacophoric features, in some novel ways that are detailed and discussed.

To illustrate the behavior of topomer similarity searching, a new dbtop program was used to generate a topomer distance matrix for a diverse set of 26 PDE4 inhibitors and 15 serotonin receptor modulators. With the best of three parameter settings tried, within the 210 shortest topomer distances (of 1460), 94.7% involved pairs of compounds having the same biological activity, and the nearest neighbor to every compound also shared its activity. The standard similarity metric, Tanimoto coefficients of “2D fingerprints”, could achieve a similar selectivity performance only for the 108 shortest distances, and three Tanimoto nearest neighbors had a different biological activity. Topomer similarity also allowed “lead-hopping” among 22 of the 26 PDE4 inhibitors, notably between rolipram and cipamfylline, while “2D fingerprints” Tanimotos recognized similarity only within generally recognized structural classes.

In 370 searches of authentic high-throughput screening (HTS) data sets, the typical topomer similarity search rate was about 200 structures per s.