Conversion of SB 203580-insensitive MAP kinase family members to drug-sensitive forms by a single amino-acid substitution

Background: Specific inhibitors of protein kinases have great therapeutic potential, but the molecular basis underlying their specificity is only poorly understood. We have investigated the drug SB 203580 which belongs to a class of pyridinyl imidazoles that inhibits the stress-activated protein (SAP) kinases SAPK2a/p38 and SAPK2b/p38β2 but not other mitogen-activated protein kinase family members. Like inhibitors of other protein kinases, SB 203580 binds in the ATP-binding pocket of SAPK2a/p38. Results: The SAP kinases SAPK1γ/JNK1, SAPK3 and SAPK4 are not inhibited by SB 203580, because they have methionine in the position equivalent to Thr106 in the ATP-binding region of SAPK2a/p38 and SAPK2b/p38β2. Using site-directed mutagenesis of five SAP kinases and the type I and type II TGFβ receptors, we have established that for a protein kinase to be inhibited by SB 203580, the sidechain of this residue must be no larger than that of threonine. Sensitivity to inhibition by SB 203580 is greatly enhanced when the sidechain is even smaller, as in serine, alanine or glycine. Thus, the type I TGFβ receptor, which has serine at the position equivalent to Thr106 of SAPK2a/p38 and SAPK2b/p38β2, is inhibited by SIB 203580. Conclusions: These findings explain how drugs that target the ATP-binding site can inhibit protein kinases specifically, and show that the presence of threonine or a smaller amino acid at the position equivalent to Thr106 of SAPK2a/p38 and SAPK2b/p38β2 is diagnostic of whether a protein kinase is sensitive to the pyridinyl imidazole class of inhibitor.     

反向传播人工神经网络用于薄层色谱中氨基酸的结构与保留关系的研究

在测定、收集和计算出一组氨基酸的拓扑指数和各种理化参数之后,再通过相关分析选择其中最有代表性的几个参数作为反向传播人工神经网络的输入参数,用于正相薄层色谱中氨基酸保留规律的研究。结果表明,氨基酸的色谱保留值与其结构之间呈现较强的非线性关系,采用人工神经网络方法比用多元线性回归方法能够更精确地描述这种关系。     

Elucidating the site of protein-ATP binding by top-down mass spectrometry

A Fourier-transform ion cyclotron resonance (FT-ICR) top-down mass spectrometry strategy for determining the adenosine triphosphate (ATP)-binding site on chicken adenylate kinase is described. Noncovalent protein-ligand complexes are readily detected by electrospray ionization mass spectrometry (ESI-MS), but the ability to detect protein-ligand complexes depends on their stability in the gas phase. Previously, we showed that collisionally activated dissociation (CAD) of protein-nucleotide triphosphate complexes yield products from the dissociation of a covalent phosphate bond of the nucleotide with subsequent release of the nucleotide monophosphate (Yin, S. et al., J. Am. Soc. Mass Spectrom. 2008, 19, 1199–1208). The intrinsic stability of electrostatic interactions in the gas phase allows the diphosphate group to remain noncovalently bound to the protein. This feature is exploited to yield positional information on the site of ATP-binding on adenylate kinase. CAD and electron capture dissociation (ECD) of the adenylate kinase-ATP complex generate product ions bearing monoand diphosphate groups from regions previously suggested as the ATP-binding pocket by NMR and crystallographic techniques. Top-down MS may be a viable tool to determine the ATP-binding sites on protein kinases and identify previously unknown protein kinases in a functional proteomics study.     

活性导向的化学探针在氨基酸反应活性表征中的应用进展

原创药物的研制得益于蛋白质新靶标的发现,而新靶标的发现依赖于高可信度、高通量的药物-蛋白质相互作用分析方法。蛋白质作为生命功能的执行者,其表达量、空间定位与结构差异直接影响药效的发挥。目前,超过85%的蛋白质尚被认为是无法成药的,主要原因是缺少药物分子靶向的空腔以及相应的反应活性位点。因此,基于蛋白质组学层次实现对氨基酸反应活性位点的表征成为原创共价靶向药物设计的关键,也是克服难以成药靶标蛋白问题的关键。近年来,质谱技术的飞速发展极大地推动了基于蛋白质组学技术的药物-靶蛋白相互作用研究。其中基于活性的蛋白质组分析(ABPP)策略是利用活性位点导向的化学探针分子在复杂样品中实现功能状态酶和药物靶标等蛋白质的检测。基于化学探针的开发和质谱定量技术的发展,ABPP技术在氨基酸反应活性表征研究中展现出重要的应用潜力,将助力于药物新靶标的发现和药物先导化合物的开发。ABPP策略主要基于蛋白质的活性特征进行富集,活性探针作为ABPP策略的核心,近年来取得了飞速进展。该文回顾了ABPP策略的发展历程,重点介绍基于广谱活性探针的ABPP技术在多种氨基酸反应活性筛选领域的研究进展,并对其在药物靶点发现中...     

Scaffold mining of kinase hinge binders in crystal structure database

Protein kinases are the second most prominent group of drug targets, after G-protein-coupled receptors. Despite their distinct inhibition mechanisms, the majority of kinase inhibitors engage the conserved hydrogen bond interactions with the backbone of hinge residues. We mined Pfizer internal crystal structure database (CSDb) comprising of several thousand of public as well as internal X-ray binary complexes to compile an inclusive list of hinge binding scaffolds. The minimum ring scaffolds with directly attached hetero-atoms and functional groups were extracted from the full compounds by applying a rule-based filtering procedure employing a comprehensive annotation of ATP-binding site of the human kinase complements. The results indicated large number of kinase inhibitors of diverse chemical structures are derived from a relatively small number of common scaffolds, which serve as the critical recognition elements for protein kinase interaction. Out of the nearly 4,000 kinase-inhibitor complexes in the CSDb we identified approximately 600 unique scaffolds. Hinge scaffolds are overwhelmingly flat with very little sp3 characteristics, and are less lipophilic than their corresponding parent compounds. Examples of the most common as well as the uncommon hinge scaffolds are presented. Although the most common scaffolds are found in complex with multiple kinase targets, a large number of them are uniquely bound to a specific kinase, suggesting certain scaffolds could be more promiscuous than the others. The compiled collection of hinge scaffolds along with their three-dimensional binding coordinates could serve as basis set for hinge hopping, a practice frequently employed to generate novel invention as well as to optimize existing leads in medicinal chemistry.     

Structural basis for selective inhibition of Src family kinases by PP1.

BACKGROUND: Small-molecule inhibitors that can target individual kinases are powerful tools for use in signal transduction research. It is difficult to find such compounds because of the enormous number of protein kinases and the highly conserved nature of their catalytic domains. Recently, a novel, potent, Src family selective tyrosine kinase inhibitor was reported (PP1). Here, we study the structural basis for this inhibitor's specificity for Src family kinases. RESULTS: A single residue corresponding to Ile338 (v-Src numbering; Thr338 in c-Src) in Src family tyrosine kinases largely controls PP1's ability to inhibit protein kinases. Mutation of Ile338 to a larger residue such as methionine or phenylalanine in v-Src makes this inhibitor less potent. Conversely, mutation of Ile338 to alanine or glycine increases PP1's potency. PP1 can inhibit Ser/Thr kinases if the residue corresponding to Ile338 in v-Src is mutated to glycine. We have accurately predicted several non-Src family kinases that are moderately (IC(50) approximately 1 microM) inhibited by PP1, including c-Abl and the MAP kinase p38. CONCLUSIONS: Our mutagenesis studies of the ATP-binding site in both tyrosine kinases and Ser/Thr kinases explain why PP1 is a specific inhibitor of Src family tyrosine kinases. Determination of the structural basis of inhibitor specificity will aid in the design of more potent and more selective protein kinase inhibitors. The ability to desensitize a particular kinase to PP1 inhibition of residue 338 or conversely to sensitize a kinase to PP1 inhibition by mutation should provide a useful basis for chemical genetic studies of kinase signal transduction.     

Chemometrical classification of ephrin ligands and Eph kinases using GRID/CPCA approach

Eph receptor tyrosine kinases are divided on two subfamilies based on their affinity for ephrin ligands and play a crucial role in the intercellular processes such as angiogenesis, neurogenesis, and carcinogenesis. As such, Eph kinases represent potential targets for drug design, which requires the knowledge of structural features responsible for their specific interactions. To overcome the existing gap between available sequence and structure information we have built 3D models of eight ephrins and 13 Eph kinase ligand-binding domains using homology modeling techniques. The interaction energies for several molecular probes with binding sites of these models were calculated using GRID and subjected to chemometrical classification based on consensus principal component analysis (CPCA). Despite inherent limitations of the homology models, CPCA was able to successfully distinguish between ephrins and Eph kinases, between Eph kinase subfamilies, and between ephrin subfamilies. As a result we have identified several amino acids that may account for selectivity in ephrin-Eph kinase interactions. In general, although the difference in charge between ephrin and Eph kinase binding domains creates an attractive long-range electrostatic force, the hydrophobic and steric interactions are highly important for the short-range interactions between two proteins. The chemometrical analysis also provides the pharmacophore model, which could be used for virtual screening and de novo ligand design.     

Characterization of a conserved structural determinant controlling protein kinase sensitivity to selective inhibitors

Some protein kinases are known to acquire resistance to selective small molecule inhibitors upon mutation of a conserved threonine at the ATP binding site to a larger residue. Here, we performed a comprehensive mutational analysis of this structural element and determined the cellular sensitivities of several disease-relevant tyrosine kinases against various inhibitors. Mutant kinases possessing a larger side chain at the critical site showed resistance to most compounds tested, such as ZD1839, PP1, AG1296, STI571, and a pyrido[2,3-d]pyrimidine inhibitor. In contrast, indolinones affected both wild-type and mutant kinases with similar potencies. Resistant mutants were established for pharmacological analysis of betaPDGF receptor-mediated signaling and allowed the generation of a drug-inducible system of cellular Src kinase activity. Our data establish a conserved structural determinant of protein kinase sensitivity relevant for both signal transduction research and drug development.     

Repositioning of Ligands That Target the Spike Glycoprotein as Potential Drugs for SARS-CoV-2 in an In Silico Study

The worldwide health emergency of the SARS-CoV-2 pandemic and the absence of a specific treatment for this new coronavirus have led to the use of computational strategies (drug repositioning) to search for treatments. The aim of this work is to identify FDA (Food and Drug Administration)-approved drugs with the potential for binding to the spike structural glycoprotein at the hinge site, receptor binding motif (RBM), and fusion peptide (FP) using molecular docking simulations. Drugs that bind to amino acids are crucial for conformational changes, receptor recognition, and fusion of the viral membrane with the cell membrane. The results revealed some drugs that bind to hinge site amino acids (varenicline, or steroids such as betamethasone while other drugs bind to crucial amino acids in the RBM (naldemedine, atovaquone, cefotetan) or FP (azilsartan, maraviroc, and difluprednate); saquinavir binds both the RBM and the FP. Therefore, these drugs could inhibit spike glycoprotein and prevent viral entry as possible anti-COVID-19 drugs. Several drugs are in clinical studies; by focusing on other pharmacological agents (candesartan, atovaquone, losartan, maviroc and ritonavir) in this work we propose an additional target: the spike glycoprotein. These results can impact the proposed use of treatments that inhibit the first steps of the virus replication cycle.     

Enzyme active sites: bioinformatics,architecture, and mechanisms of action

A comparative analysis of the amino acid sequences of some enzymes which comprise superfamilies of enzymes belonging to different classes was carried out. Based on the amino acid sequence alignment for enzymes belonging to different classes with the use of the information entropy as a criterion, the amino acid residues involved in the catalytic portion of the active site are demonstrated to be most conservative. The rating scale for conservativeness of amino acids in enzymes is created. Glycine and aspartic acid are the most commonly occurring conservative amino acids essential for the catalysis. The role of aspartic acid and histidine in the mechanism of molecule activation in the catalytic site is considered using hydrolases as examples. The role of glycine, proline, and cysteine in the structural organization of the active sites is discussed.     

Adsorption of zwitterionic drugs onto oxidized cellulose

Adsorption of zwitterionic drugs (beta-lactam antibiotics and amino acids) onto samples of oxidized cellulose (OC) with various carboxyl contents and structural characteristics from aqueous and water/alcohol solutions was investigated. The adsorption process can be described according to the theory of localized stoichiometric adsorption and represented by Langmuir isotherms. It was established that the constants of interfacial distribution mainly increase with increased relative sorbate hydrophobicity. The dependencies of adsorption on pH of equilibrium drug solution have a maximum at pH 3-3.5, which is caused by peculiarities of dissociation of OC and sorbates. The drug uptake is shown to increase with an increase of alcohol mole fraction in the solution and transfer to the binary water/isopropanol from water/ethanol solutions. The dominant contribution to the increase of uptake is the desolvation of ionic groups of zwitterions in the solution, which increases with increased alcohol content. The degree of crystallinity of the sorbent has no considerable effect on drug adsorption from aqueous solutions. In water/alcohol solutions the adsorption of drugs by OC samples with similar exchange capacity increases with reducted uniformity of carboxylic group distribution in the volume of the polymer, which is connected with increased accessibility of carboxylic groups for sorbate molecules.     

Identification of common inhibitors of wild-type and T315I mutant of BCR-ABL through the parallel structure-based virtual screening

Although the constitutively activated break-point cluster region-Abelson (BCR-ABL) tyrosine kinase was well known to be responsible for chronic myelogenous leukemia (CML), the existence of drug-resistant mutants of BCR-ABL has made it difficult to develop effective anti-CML drugs. Here, we report the first example for a successful application of the structure-based virtual screening to identify two common inhibitors equipotent for the wild type and the most drug-resistant T315I mutant of BCR-ABL. Because both inhibitors were screened for having desirable physicochemical properties as a drug candidate and revealed micromolar inhibitory activities, they deserve consideration for further development by structure-activity relationship (SAR) studies to optimize the anti-CML activity. We also address the structural features relevant to the stabilizations of the identified inhibitors in the ATP-binding sites. The results indicate that the inhibitors should be less stabilized by the hydrogen-bond interactions with the change of the receptor from the wild type to T315I mutant due to the replacement of the hydroxy group with the ethyl moiety in the ATP-binding site. Nonetheless, the inhibitors are found to be capable of maintaining the potency for the mutant through the strengthening of hydrophobic interactions to the extent sufficient to compensate for the loss of some hydrogen bonds. This differential binding mode may serve as key information for designing new common inhibitors of the wild type and T315I mutant of BCR-ABL.     

Mycobacterium tuberculosis serine/threonine protein kinases: structural information for the design of their specific ATP-competitive inhibitors

In the last decades, human protein kinases (PKs) have been relevant as targets in the development of novel therapies against many diseases, but the study of Mycobacterium tuberculosis PKs (MTPKs) involved in tuberculosis pathogenesis began much later and has not yet reached an advanced stage of development. To increase knowledge of these enzymes, in this work we studied the structural features of MTPKs, with focus on their ATP-binding sites and their interactions with inhibitors. PknA, PknB, and PknG are the most studied MTPKs, which were previously crystallized; ATP-competitive inhibitors have been designed against them in the last decade. In the current work, reported PknA, PknB, and PknG inhibitors were extracted from literature and their orientations inside the ATP-binding site were proposed by using docking method. With this information, interaction fingerprints were elaborated, which reveal the more relevant residues for establishing chemical interactions with inhibitors. The non-crystallized MTPKs PknD, PknF, PknH, PknJ, PknK, and PknL were also studied; their three-dimensional structural models were developed by using homology modeling. The main characteristics of MTPK ATP-binding sites (the non-crystallized and crystallized MTPKs, including PknE and PknI) were accounted; schemes of the main polar and nonpolar groups inside their ATP-binding sites were constructed, which are suitable for a major understanding of these proteins as antituberculotic targets. These schemes could be used for establishing comparisons between MTPKs and human PKs in order to increase selectivity of MTPK inhibitors. As a key tool for guiding medicinal chemists interested in the design of novel MTPK inhibitors, our work provides a map of the structural elements relevant for the design of more selective ATP-competitive MTPK inhibitors.     

Identification of novel inhibitors of tropomyosin-related kinase A through the structure-based virtual screening with homology-modeled protein structure

Tropomyosin-related kinase A (TrkA) is a promising target for the development of cancer and pain therapeutics. Here, we report the first successful example of the use of a structure-based virtual screening to identify novel TrkA inhibitors. The accuracy of the virtual screening was improved by introducing an accurate solvation free energy term into the original AutoDock scoring function. We applied a drug design protocol involving homology modeling, docking analysis of a large chemical library, and enzyme inhibition assays to identify six structurally diverse TrkA inhibitors with K(d) values ranging from 3 to 40 μM. The significant potencies and good physicochemical properties of these drug candidates strongly support their consideration in a development effort that would involve structure-activity relationship (SAR) studies to optimize the inhibitory activities. We also addressed the structural and energetic features associated with binding of the newly identified inhibitors in the ATP-binding site of TrkA. The results indicate that any structural modifications introduced for the purpose of enhancing the activity of TrkA inhibitors should maximize the attractive interactions within the ATP-binding site and simultaneously minimize the desolvation cost for complexation.     

Reduced bio basis function neural network for identification of protein phosphorylation sites: comparison with pattern recognition algorithms

Protein phosphorylation is a post-translational modification performed by a group of enzymes known as the protein kinases or phosphotransferases (Enzyme Commission classification 2.7). It is essential to the correct functioning of both proteins and cells, being involved with enzyme control, cell signalling and apoptosis. The major problem when attempting prediction of these sites is the broad substrate specificity of the enzymes. This study employs back-propagation neural networks (BPNNs), the decision tree algorithm C4.5 and the reduced bio-basis function neural network (rBBFNN) to predict phosphorylation sites. The aim is to compare prediction efficiency of the three algorithms for this problem, and examine knowledge extraction capability. All three algorithms are effective for phosphorylation site prediction. Results indicate that rBBFNN is the fastest and most sensitive of the algorithms. BPNN has the highest area under the ROC curve and is therefore the most robust, and C4.5 has the highest prediction accuracy. C4.5 also reveals the amino acid 2 residues upstream from the phosporylation site is important for serine/threonine phosphorylation, whilst the amino acid 3 residues upstream is important for tyrosine phosphorylation.     

Total synthesis and biological evaluation of the nakijiquinones.

The Her-2/Neu receptor tyrosine kinase is vastly overexpressed in about 30% of primary breast, ovary, and gastric carcinomas. The nakijiquinones are the only naturally occurring inhibitors of this important oncogene, and structural analogues of the nakijiquinones may display inhibitory properties toward other receptor tyrosine kinases involved in cell signaling and proliferation. Here, we describe the first enantioselective synthesis of the nakijiquinones. Key elements of the synthesis are (i) the reductive alkylation of a Wieland-Miescher-type enone with a tetramethoxyaryl bromide, (ii) the oxidative conversion of the aryl ring into a p-quinoid system, (iii) the regioselective saponification of one of the two vinylogous esters incorporated therein, and (iv) the selective introduction of different amino acids via nucleophilic conversion of the remaining vinylogous ester into the corresponding vinylogous amide. The correct stereochemistry and substitution patterns are completed by conversion of two keto groups into a methyl group and an endocyclic olefin via olefination/reduction and olefination/isomerization sequences, respectively. This synthesis route also gave access to analogues of nakijiquinone C with inverted configuration at C-2 or with an exocyclic instead of an endocyclic double bond. Investigation of the kinase-inhibiting properties of the synthesized derivatives revealed that the C-2 epimer 30 of nakijiquinone C is a potent and selective inhibitor of the KDR receptor, a receptor tyrosine kinase involved in tumor angiogenesis. Molecular modeling studies based on the crystal structure of KDR and a model of the ATP binding site built from a crystal structure of FGF-R revealed an insight into the structural basis for the difference in activity between the natural product nakijiquinone C and the C-2 epimer 30.     

Prediction of Molecular Properties Using Molecular Topographic Map

Prediction of molecular properties plays a critical role towards rational drug design. In this study, the Molecular Topographic Map (MTM) is proposed, which is a two-dimensional (2D) map that can be used to represent a molecule. An MTM is generated from the atomic features set of a molecule using generative topographic mapping and is then used as input data for analyzing structure-property/activity relationships. In the visualization and classification of 20 amino acids, differences of the amino acids can be visually confirmed from and revealed by hierarchical clustering with a similarity matrix of their MTMs. The prediction of molecular properties was performed on the basis of convolutional neural networks using MTMs as input data. The performance of the predictive models using MTM was found to be equal to or better than that using Morgan fingerprint or MACCS keys. Furthermore, data augmentation of MTMs using mixup has improved the prediction performance. Since molecules converted to MTMs can be treated like 2D images, they can be easily used with existing neural networks for image recognition and related technologies. MTM can be effectively utilized to predict molecular properties of small molecules to aid drug discovery research.