38 resultados para quantitative structure activity relation
Resumo:
Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.
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The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.
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Calcitonin gene-related peptide (CGRP) is a member of the calcitonin (CT) family of peptides. It is a widely distributed neuropeptide implicated in conditions such as neurogenic inflammation. With other members of the CT family, it shares an N-terminal disulphide-bonded ring which is essential for biological activity, an area of potential α-helix, and a C-terminal amide. CGRP binds to the calcitonin receptor-like receptor (CLR) in complex with receptor activity-modifying protein 1 (RAMP1), a member of the family B (or secretin-like) GPCRs. It can also activate other CLR or calcitonin-receptor/RAMP complexes. This 37 amino acid peptide comprises the N-terminal ring that is required for receptor activation (residues 1-7); an α-helix (residues 8-18), a region incorporating a β-bend (residues 19-26) and the C-terminal portion (residues 27-37), that is characterized by bends between residues 28-30 and 33-34. A few residues have been identified that seem to make major contributions to receptor binding and activation, with a larger number contributing either to minor interactions (which collectively may be significant), or to maintaining the conformation of the bound peptide. It is not clear if CGRP follows the pattern of other family B GPCRs in binding largely as an α-helix. Linked Articles This article is part of a themed section on Neuropeptides. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2013.170.issue-7 © 2012 The Authors. British Journal of Pharmacology © 2012 The British Pharmacological Society.
Resumo:
Background and purpose - The N-terminus of calcitonin gene-related peptide (CGRP) is important for receptor activation, especially the disulphide-bonded ring (residues 1-7). However, the roles of individual amino acids within this region have not been examined and so the molecular determinants of agonism are unknown. This study has examined the role of residues 1, 3-6 and 8-9, excluding Cys-2 and Cys-7. Experimental approach - CGRP derivatives were substituted with either cysteine or alanine; further residues were introduced at position 6. Their affinity was measured by radioligand binding and their efficacy by measuring cAMP production in SK-N-MC cells and ß-arrestin 2 translocation in CHO-K1 cells at the CGRP receptor. Key results - Substitution of Ala-5 by cysteine reduced affinity 270-fold and reduced efficacy for production of cAMP in SK-N-MCs. Potency at ß-arrestin translocation was reduced by 9-fold. Substitution of Thr-6 by cysteine destroyed all measurable efficacy of both cAMP and ß-arrestin responses; substitution with either alanine or serine impaired potency. Substitutions at positions 1, 4, 8 and 9 resulted in approximately 10-fold reductions in potency at both responses. Similar observations were made at a second CGRP-activated receptor, the AMY1(a) receptor. Conclusions and implications - Ala-5 and Thr-6 are key determinants of agonist activity for CGRP. Ala-5 is also very important for receptor binding. Residues outside of the 1-7 ring also contribute to agonist activity.
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A series of insoluble heteropolytungstate (H3PW12O40 HPW) salts, CsxH3−xPW12O40 (x=0.9–3x=0.9–3), were synthesized and characterized using a range of bulk and surface sensitive probes including N2 porosimetry, powder XRD, FTIR, XPS, 31P MAS NMR, and NH3 calorimetry. Materials with Cs content in the range x=2.0–2.7x=2.0–2.7 were composed of dispersed crystallites with surface areas ∼100 m2 g−1 and high Brönsted acid strengths [ΔH0ads(NH3)=−150 kJmol−1], similar to the parent heteropolyacid. The number of accessible surface acid sites probed by α -pinene isomerization correlated well with those determined by NH3 adsorption calorimetry and surface area measurements. CsxH3−xPW12O40 were active toward the esterification of palmitic acid and transesterification of tributyrin, important steps in fatty acid and ester processing for biodiesel synthesis. Optimum performance occurs for Cs loadings of x=2.0–2.3x=2.0–2.3, correlating with the accessible surface acid site density. These catalysts were recoverable with no leaching of soluble HPW.
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Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient P (commonly expressed in logarithm form: logP), is useful for screening out unsuitable molecules and also for the development of predictive Quantitative Structure-Activity Relationships (QSARs). In this paper we develop a new approach to the prediction of LogP values for peptides based on an empirical relationship between global molecular properties and measured physical properties. Our method was successful in terms of peptide prediction (total r2 = 0.641). The final model consisted of 5 physicochemical descriptors (molecular weight, number of single bonds, 2D-VDW volume, 2D-VSA hydrophobic and 2D-VSA polar). The approach is peptide specific and its predictive accuracy was high. Overall, 67% of the peptides were able to be predicted within +/-0.5 log units from the experimental values. Our method thus represents a novel prediction method with proven predictive ability.
Resumo:
Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient logP, is useful for the development of predictive Quantitative Structure-Activity Relationships (QSARs). We have investigated the accuracy of available programs for the prediction of logP values for peptides with known experimental values obtained from the literature. Eight prediction programs were tested, of which seven programs were fragment-based methods: XLogP, LogKow, PLogP, ACDLogP, AlogP, Interactive Analysis's LogP and MlogP; and one program used a whole molecule approach: QikProp. The predictive accuracy of the programs was assessed using r(2) values, with ALogP being the most effective (r( 2) = 0.822) and MLogP the least (r(2) = 0.090). We also examined three distinct types of peptide structure: blocked, unblocked, and cyclic. For each study (all peptides, blocked, unblocked and cyclic peptides) the performance of programs rated from best to worse is as follows: all peptides - ALogP, QikProp, PLogP, XLogP, IALogP, LogKow, ACDLogP, and MlogP; blocked peptides - PLogP, XLogP, ACDLogP, IALogP, LogKow, QikProp, ALogP, and MLogP; unblocked peptides - QikProp, IALogP, ALogP, ACDLogP, MLogP, XLogP, LogKow and PLogP; cyclic peptides - LogKow, ALogP, XLogP, MLogP, QikProp, ACDLogP, IALogP. In summary, all programs gave better predictions for blocked peptides, while, in general, logP values for cyclic peptides were under-predicted and those of unblocked peptides were over-predicted.
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A series of N1-benzylidene pyridine-2-carboxamidrazone anti-tuberculosis compounds has been evaluated for their cytotoxicity using human mononuclear leucocytes (MNL) as target cells. All eight compounds were significantly more toxic than dimethyl sulphoxide control and isoniazid (INH) with the exception of a 4-methoxy-3-(2-phenylethyloxy) derivative, which was not significantly different in toxicity compared with INH. The most toxic agent was an ethoxy derivative, followed by 3-nitro, 4-methoxy, dimethylpropyl, 4-methylbenzyloxy, 3-methoxy-4-(-2-phenylethyloxy) and 4-benzyloxy in rank order. In comparison with the effect of selected carboxamidrazone agents on cells alone, the presence of either N-acetyl cysteine (NAC) or glutathione caused a significant reduction in the toxicity of INH, as well as on the 4-benzyloxy derivative, although both increased the toxicity of a 4-N,N-dimethylamino-1-naphthylidene and a 2-t-butylthio derivative. The derivatives from this and three previous studies were subjected to computational analysis in order to derive equations designed to establish quantitative structure activity relationships for these agents. Twenty-five compounds were thus resolved into two groups (1 and 2), which on analysis yielded equations with r2 values in the range 0.65-0.92. Group 1 shares a common mode of toxicity related to hydrophobicity, where cytotoxicity peaked at logP of 3.2, while Group 2 toxicity was strongly related to ionisation potential. The presence of thiols such as NAC and GSH both promoted and attenuated toxicity in selected compounds from Group 1, suggesting that secondary mechanisms of toxicity were operating. These studies will facilitate the design of future low toxicity high activity anti-tubercular carboxamidrazone agents. © 2003 Elsevier Science B.V. All rights reserved.
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Structure–activity relationships are indispensable to identify the most optimal antioxidants. The advantages of in vitro over in vivo experiments for obtaining these relationships are, that the structure is better defined in vitro, since less metabolism takes place. It is also the case that the concentration, a parameter that is directly linked to activity, is more accurately controlled. Moreover, the reactions that occur in vivo, including feed-back mechanisms, are often too multi-faceted and diverse to be compensated for during the assessment of a single structure–activity relationship. Pitfalls of in vitro antioxidant research include: (i) by definition, antioxidants are not stable and substantial amounts of oxidation products are formed and (ii) during the scavenging of reactive species, reaction products of the antioxidants accumulate. Another problem is that the maintenance of a defined concentration of antioxidants is subject to processes such as oxidation and the formation of reaction products during the actual antioxidant reaction, as well as the compartmentalization of the antioxidant and the reactive species in the in vitro test system. So determinations of in vitro structure-activity relationships are subject to many competing variables and they should always be evaluated critically. (c) 2005 Published by Elsevier B.V.
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A series of N1-benzylideneheteroarylcarboxamidrazones was prepared in an automated fashion, and tested against Mycobacterium fortuitum in a rapid screen for antimycobacterial activity. Many of the compounds from this series were also tested against Mycobacterium tuberculosis, and the usefulness as M.fortuitum as a rapid, initial screen for anti-tubercular activity evaluated. Various deletions were made to the N1-benzylideneheteroarylcarboxamidrazone structure in order to establish the minimum structural requirements for activity. The N1-benzylideneheteroarylcarbox-amidrazones were then subjected to molecular modelling studies and their activities against M.fortuitum and M.tuberculosis were analysed using quantitative structure-analysis relationship (QSAR) techniques in the computational package TSAR (Oxford Molecular Ltd.). A set of equations predictive of antimycobacterial activity was hereby obtained. The series of N1-benzylidenehetero-arylcarboxamidrazones was also tested against a multidrug-resistant strain of Staphylococcus aureus (MRSA), followed by a panel of Gram-positive and Gram-negative bacteria, if activity was observed for MRSA. A set of antimycobacterial N1-benzylideneheteroarylcarboxamidrazones was hereby discovered, the best of which had MICs against m. fortuitum in the range 4-8μgml-1 and displayed 94% inhibition of M.tuberculosis at a concentration of 6.25μgml-1. The antimycobacterial activity of these compounds appeared to be specific, since the same compounds were shown to be inactive against other classes of organisms. Compounds which were found to be sufficiently active in any screen were also tested for their toxicity against human mononuclear leucocytes. Polyethylene glycol (PEG) was used as a soluble polymeric support for the synthesis of some fatty acid derivatives, containing an isoxazoline group, which may inhibit mycolic acid synthesis in mycobacteria. Both the PEG-bound products and the cleaved, isolated products themselves were tested against M.fortuitum and some low levels of antimycobacterial activity were observed, which may serve as lead compounds for further studies.
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Human adrenomedullin (AM) is a 52-amino acid peptide belonging to the calcitonin peptide family, which also includes calcitonin gene-related peptide (CGRP) and AM2. The two AM receptors, AM(1) and AM(2), are calcitonin receptor-like receptor (CL)/receptor activity-modifying protein (RAMP) (RAMP2 and RAMP3, respectively) heterodimers. CGRP receptors comprise CL/RAMP1. The only human AM receptor antagonist (AM(22-52)) is a truncated form of AM; it has low affinity and is only weakly selective for AM(1) over AM(2) receptors. To develop novel AM receptor antagonists, we explored the importance of different regions of AM in interactions with AM(1), AM(2), and CGRP receptors. AM(22-52) was the framework for generating further AM fragments (AM(26-52) and AM(30-52)), novel AM/alphaCGRP chimeras (C1-C5 and C9), and AM/AM(2) chimeras (C6-C8). cAMP assays were used to screen the antagonists at all receptors to determine their affinity and selectivity. Circular dichroism spectroscopy was used to investigate the secondary structures of AM and its related peptides. The data indicate that the structures of AM, AM2, and alphaCGRP differ from one another. Our chimeric approach enabled the identification of two nonselective high-affinity antagonists of AM(1), AM(2), and CGRP receptors (C2 and C6), one high-affinity antagonist of AM(2) receptors (C7), and a weak antagonist selective for the CGRP receptor (C5). By use of receptor mutagenesis, we also determined that the C-terminal nine amino acids of AM seem to be responsible for its interaction with Glu74 of RAMP3. We provide new information on the structure-activity relationship of AM, alphaCGRP, and AM2 and how AM interacts with CGRP and AM(2) receptors.
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A novel synthetic approach towards N1-alkylated 3-propyl-1,4-benzodiazepines was developed in five synthetic steps from 2-amino-4-chlorobenzophenone, in which the N-oxide 4 served as a key intermediate. The structure-activity relationship optimization of this 3-prophyl-1,4-benzodiazepine template was carried out on the N1-position by selective alkylation reactions and resulted in a ligand with an improved affinity on the cholecystokinin (CCK2) receptor. The N-allyl-3-propyl-benzodiazepine 6d displayed an affinity towards the CCK2 (CCK-B) receptor of 170 nM in a radiolabelled receptor-binding assay. The anxiolytic activity of this allyl-3-propyl-1,4-benzodiazepine 6d was subsequently determined in in-vivo psychotropic assays. This novel ligand had ED50 values of 4.7 and 5.2 mg kg-1 in the black and white box test and the x-maze, respectively, and no significant sedation/muscle relaxation was observed.