Structure-activity relationships for α-calcitonin gene-related peptide

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.

Structure-activity relationships of the N-terminus of calcitonin gene-related peptide:key roles of alanine-5 and threonine-6 in receptor activation

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.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

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.

Quantitative structure-activity relationships and the prediction of MHC supermotifs

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.

Anti-AIDS agents 81. Design, synthesis, and structure-activity relationship study of betulinic acid and moronic acid derivatives as potent HIV maturation inhibitors.

In our continuing study of triterpene derivatives as potent anti-HIV agents, different C-3 conformationally restricted betulinic acid (BA, 1) derivatives were designed and synthesized in order to explore the conformational space of the C-3 pharmacophore. 3-O-Monomethylsuccinyl-betulinic acid (MSB) analogues were also designed to better understand the contribution of the C-3' dimethyl group of bevirimat (2), the first-in-class HIV maturation inhibitor, which is currently in phase IIb clinical trials. In addition, another triterpene skeleton, moronic acid (MA, 3), was also employed to study the influence of the backbone and the C-3 modification toward the anti-HIV activity of this compound class. This study enabled us to better understand the structure-activity relationships (SAR) of triterpene-derived anti-HIV agents and led to the design and synthesis of compound 12 (EC(50): 0.0006 microM), which displayed slightly better activity than 2 as a HIV-1 maturation inhibitor.

Structure-function relationships of the peptide Paulistine: A novel toxin from the venom of the social wasp Polybia paulista

Background: The peptide Paulistine was isolated from the venom of wasp Polybia paulista. This peptide exists under a natural equilibrium between the forms: oxidised - with an intra-molecular disulphide bridge; and reduced - in which the thiol groups of the cysteine residues do not form the disulphide bridge. The biological activities of both forms of the peptide are unknown up to now. Methods: Both forms of Paulistine were synthesised and the thiol groups of the reduced form were protected with the acetamidemethyl group [Acm-Paulistine] to prevent re-oxidation. The structure/activity relationships of the two forms were investigated, taking into account the importance of the disulphide bridge. Results: Paulistine has a more compact structure, while Acm-Paulistine has a more expanded conformation. Bioassays reported that Paulistine caused hyperalgesia by interacting with the receptors of lipid mediators involved in the cyclooxygenase type II pathway, while Acm-Paullistine also caused hyperalgesia, but mediated by receptors involved in the participation of prostanoids in the cyclooxygenase type II pathway. Conclusion: The acetamidemethylation of the thiol groups of cysteine residues caused small structural changes, which in turn may have affected some physicochemical properties of the Paulistine. Thus, the dissociation of the hyperalgesy from the edematogenic effect when the actions of Paulistine and Acm-Paulistine are compared to each other may be resulting from the influence of the introduction of Acm-group in the structure of Paulistine. General significance: The peptides Paulistine and Acm-Paulistine may be used as interesting tools to investigate the mechanisms of pain and inflammation in future studies. © 2013 Elsevier B.V.

High yield conversion of doxorubicin to 2-pyrrolinodoxorubicin, an analog 500-1000 times more potent: structure-activity relationship of daunosamine-modified derivatives of doxorubicin.

A convenient, high yield conversion of doxorubicin to 3'-deamino-3'-(2''-pyrroline-1''-yl)doxorubicin is described. This daunosamine-modified analog of doxorubicin is 500-1000 times more active in vitro than doxorubicin. The conversion is effected by using a 30-fold excess of 4-iodobutyraldehyde in anhydrous dimethylformamide. The yield is higher than 85%. A homolog of this compound, 3'-deamino-3'-(1'',3''-tetrahydropyridine-1''-yl)doxorubicin, was also synthesized by using 5-iodovaleraldehyde. In this homolog, the daunosamine nitrogen is incorporated into a six- instead of a five-membered ring. This analog was 30-50 times less active than its counterpart with a five-membered ring. A similar structure-activity relationship was found when 3'-deamino-3'-(3''-pyrrolidone-1''-yl)doxorubicin (containing a five-membered ring) and 3'-deamino-3'-(3''-piperidone-1''-yl)doxorubicin (with a six-membered ring) were tested in vitro, the former being 5 times more potent than the latter. To further elucidate structure-activity relationships, 3'-deamino-3'-(pyrrolidine-1''-yl)doxorubicin, 3'-deamino-3'-(isoindoline-2''-yl)doxorubicin, 3'-deamino-3'-(2''-methyl-2''-pyrroline-1''-yl)doxorubicin, and 3'-deamino-3'-(3''-pyrroline-1''-yl)doxorubicin were also synthesized and tested. All the analogs were prepared by using reactive halogen compounds for incorporating the daunosamine nitrogen of doxorubicin into a five- or six-membered ring. These highly active antineoplastic agents can be used for incorporation into targeted cytotoxic analogs of luteinizing hormone-releasing hormone intended for cancer therapy.

Preliminary structure-activity relationship studies on some novel s-substituted aliphatic analogues of 5-{1-[(4- chlorophenyl) sulfonyl]-3-piperidinyl}-1, 3, 4-oxadiazol-2-yl sulfide

Purpose: To study the structure-activity relationships of synthetic multifunctional sulfides through evaluation of lipoxygenase and anti-bacterial activities. Methods: S-substituted derivatives of the parent compound 5-(1-(4-chlorophenylsulfonyl) piperidin-3- yl)-1, 3, 4-oxadiazole-2-thiol were synthesized through reaction with different saturated and unsaturated alkyl halides in DMF medium, with NaH catalyst. Spectral characterization of each derivative was carried out with respect to IR, 1H - NMR, 13C - NMR and EI - MS. The lipoxygenase inhibitory and antibacterial activities of the derivatives were determined using standard procedures. Results: Compound 5e exhibited higher lipoxygenase inhibitory potential than the standard (Baicalein®), with % inhibition of 94.71 ± 0.45 and IC50 of 20.72 ± 0.34 μmoles/L. Compound 5b showed significant antibacterial potential against all the bacterial strains with % inhibition ranging from 62.04 ± 2.78, 69.49 ± 0.41, 63.38 ± 1.97 and 59.70 ± 3.70 to 78.32 ± 0.41, while MIC ranged from 8.18 ± 2.00, 10.60 ± 1.83, 10.84 ± 3.00, 9.81 ± 1.86 and 11.73 ± 5.00 μmoles/L for S. typhi, E. coli, P. aeruginosa, B. subtilis and S. aureus, respectively. Compounds 5d, 5e and 5g showed good antibacterial activity against S. typhi and B. subtilis bacterial strains. Conclusion: The results suggest that compound 5e bearing n-pentyl group is a potent lipoxygenase inhibitor, while compound 5b with n-propyl substitution is a strong antibacterial agent. In addition, compounds 5d, 5e and 5g bearing n-butyl, n-pentyl and n-octyl groups, respectively, are good antibacterial agents against S. typhi and B. subtilis.

Common structural basis for central nervous system drug design

The main theme of this thesis is that there is a common structural basis for drugs acting on the central nervous system (CNS), and that this concept may be used to design new CNS-active drugs which have greater specificity and hence less side-effects. To develop these ideas, the biological basis of how drugs modify CMS neurotransmission is described, and illustrated using dopaminergic pathways. An account is then given of the use of physicochemical concepts in contemporary drug design. The complete conformational analysis of several antipsychotic drugs is used to illustrate some of these techniques in the development of a model for antipsychotic drug action. After reviewing current structure-activity studies in several classes of CNS drugs (antipsychotics, anti-depressants, stimulants, hal1ucinogens, anticonvulsants and analgesics), a hypothesis for a common structural basis of CNS drug action is proposed- This is based on a topographical comparison of the X-ray structures of eight representative CNS-active drugs, and consists of three parts: 1.there is a common structural basis for the activity of many different CNS-active drug classes; 2. an aromatic ring and a nitrogen atom are the primary binding groups whose topographical arrangement is fundamental to the activity of these drug classes; 3. the nature and placement of secondary binding determines different classes of CNS drug activity. A four-Point model for this common structural basis is then defined using 14- CNS-active drug structures that include the original eight used in proposing the hypothesis. The coordinates of this model are: R1 (0. 3.5, 0), R2 (0, -3.5, O), N (4.8. -0.3, 1.4), and R3 (6.3, 1.3, 0), where R1 and R2 represent the point locations of a hydrophobic interaction of the common aromatic ring with a receptor, and R3 locates the receptor point for a hydrogen bond involving the common nitrogen, N. Extended structures were used to define the receptor points R1, R2 and R3, and the complete conformational space of each of the 14 molecules was considered. It is then shoun that the model may be used to predict whether a given structure is likely to show CNS activity: a search over 1,000 entries in the current Merck Index shows a high probability (82%) of CNS activity in compounds fitting the structural model. Analysis of CNS neurotransmitters and neuropeptides shows that these fit the common model well. Based on the available evidence supporting chemical evolution, protein evolution, and the evolution of neurotransmitter functions, it is surmised that the aromatic ring/nitrogen atom pharmacophore proposed in the common model supports the idea of the evolution of CNS receptors and their neurotransmitters, possibly from an aromatic amine or acety1cho1ine acting as a primaeval communicating molecule. The third point in the hypothesis trilogy is then addressed. The extensive conformation-activity analyses that have resulted in well-defined models for five separate CNS drug classes are used to map out the locations of secondary binding groups relative to the common model for anti-psychotics, antidepressants, analgesics, anticholinergics, and anticonvulsants. With this information, and knowledge derived from receptor-binding data, it is postulated that drugs having specified activity could be designed. In order to generate novel structures having a high probability of CNS-activity, a process of drug design is described in which known CNS structures are superimposed topographically using the common model as a template. Atoms regarded as superfluous may be selectively deleted and the required secondary binding groups added in predicted locations to give novel structures. It is concluded that this process provides the basis for the rational design of new lead compounds which could further be optimized for potent and specific CNS activity.

Quantitative structure-property relationships for colour reagents and their colour reactions with cerium using computational neural networks

Quantitative structure-activity/property relationships (QSAR/QSPR) studies have been exploited extensively in the designs of drugs and pesticides, but few such studies have been applied to the design of colour reagents. In this work, the topological indices A(x1)-A(x3) suggested in this laboratory were applied to multivariate analysis in structure-property studies. The topological indices of 43 phosphone bisazo derivatives of chromotropic acid were calculated. The structure-property relationships between colour reagents and their colour reactions with cerium were studied using A(x1-Ax3) indices with satisfactory results. The purpose of this work was to establish whether QSAR can be used to predict the contrasts of colour reactions and in the longer term to be a helpful tool in colour reagent design.

Immobilized artificial membrane chromatography : quantitative structure-retention relationships of structurally diverse drugs

The chromatographic capacity factors (log k‘) for 32 structurally diverse drugs were determined by high performance liquid chromatography (HPLC) on a stationary phase composed of phospholipids, the so-called immobilized artificial membrane (IAM). In addition, quantitative structure-retention relationships (QSRR) were developed in order to explain the dependence of retention on the chemical structure of the neutral, acidic, and basic drugs considered in this study. The obtained retention data were modeled by means of multiple regression analysis (MLR) and partial least squares (PLS) techniques. The structures of the compounds under study were characterized by means of calculated physicochemical properties and several nonempirical descriptors. For the carboxylic compounds included in the analysis, the obtained results suggest that the IAM-retention is governed by hydrophobicity factors followed by electronic effects due to polarizability in second place. Further, from the analysis of the results obtained of two developed quantitative structure-permeability studies for 20 miscellaneous carboxylic compounds, it may be concluded that the balance between polarizability and hydrophobic effects is not the same toward IAM phases and biological membranes. These results suggest that the IAM phases could not be a suitable model in assessing the acid-membrane interactions. However, it is not possible to generalize this observation, and further work in this area needs to be done to obtain a full understanding of the partitioning of carboxylic compounds in biological membranes. For the non-carboxylic compounds included in the analysis, this work shows that the hydrophobic factors are of prime importance for the IAM-retention of these compounds, while the specific polar interactions, such as electron pair donor−acceptor interactions and electrostatic interactions, are also involved, but they are not dominant.

Potent cyclic antagonists of the complement C5a receptor on human polymorphonulcear leukocytes. Relationships between structures and activity

Human C5a is a plasma protein with potent chemoattractant and pro-inflammatory properties, and its overexpression correlates with severity of inflammatory diseases. C5a binds to its G protein-coupled receptor (C5aR) on polymorphonuclear leukocytes (PMNLs) through a high-affinity helical bundle and a low-affinity C terminus, the latter being solely responsible for receptor activation. Potent and selective C5a antagonists are predicted to be effective anti-inflammatory drugs, but no pharmacophore for small molecule antagonists has yet been developed, and it would significantly aid drug design. We have hypothesized that a turn conformation is important for activity of the C terminus of C5a and herein report small cyclic peptides that are stable turn mimics with potent antagonism at C5aR on human PMNLs. A comparison of solution structures for the C terminus of C5a, small acyclic peptide ligands, and cyclic antagonists supports the importance of a turn for receptor binding. Competition between a cyclic antagonist and either C5a or an acyclic agonist for C5aR on PMNLs supports a common or overlapping binding site on the C5aR. Structure-activity relationships for 60 cyclic analogs were evaluated by competitive radioligand binding with C5a (affinity) and myeloperoxidase release (antagonist potency) from human PMNLs, with 20 compounds having high antagonist potencies (IC50, 20 nM(-1) muM). Computer modeling comparisons reveal that potent antagonists share a common cyclic backbone shape, with affinity-determining side chains of defined volume projecting from the cyclic scaffold. These results define a new pharmacophore for C5a antagonist development and advance our understanding of ligand recognition and receptor activation of this G protein-coupled receptor.

Molecular modeling on some human interleukins sharing gamma c of interleukin-2 receptor, and structure-function relationships

Five models for human interleukin-7 (HIL-7), HIL-9, HIL-13, HIL-15 and HIL-17 have been generated by SYBYL software package. The primary models were optimized using molecular dynamics and molecular mechanics methods. The final models were optimized using a steepest descent algorithm and a subsequent conjugate gradient method. The complexes with these interleukins and the common gamma chain of interleukin-2 receptor (IL-2R) were constructed and subjected to energy minimization. We found residues, such as Gln127 and Tyr103, of the common gamma chain of IL-2R are very important. Other residues, e.g. Lys70, Asn128 and Glu162, are also significant. Four hydrophobic grooves and two hydrophilic sites converge at the active site triad of the gamma chain. The binding sites of these interleukins interaction with the common gamma chain exist in the first helical and/or the fourth helical domains. Therefore, we conclude that these interleukins binds to the common gamma chain of IL-2R by the first and the fourth helix domain. Especially at the binding sites of some residues (lysine, arginine, asparagine, glutamic acid and aspartic acid), with a discontinuous region of the common gamma chain of IL-2R, termed the interleukins binding sites (103-210). The study of these sites can be important for the development of new drugs. (C) 2000 Elsevier Science B.V. All rights reserved.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Addressing Selective Polypharmacology of Antipsychotic Drugs Targeting the Bioaminergic Receptors through the Receptor Dynamic Conformational Ensembles

Selective polypharmacology, where a drug acts on multiple rather than single molecular targets involved in a disease, emerges to develop a structure-based system biology approach to design drugs selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that belong to the group of integral membrane signalling proteins coupled to the G protein and represent targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown that the serotonin (5-HT2A and 5-HT6), dopamine (D2 and D3) receptors induce a cognition-enhancing effect (group 1), while the histamine (H1) and serotonin (5-HT2C) receptors lead to metabolic side effects and the 5-HT2B serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem arises to develop an approach that allows identifying drugs targeting only the disease-active receptors, i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving the D3 and H1 receptors provides the possibility to model the structures of all receptors and initiate a study of the structural and dynamic context of selective polypharmacology. In this work, we use molecular dynamics simulations to generate a conformational space of the receptors and subsequently characterize its binding properties applying molecular probe mapping. All-against-all comparison of the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto similarity coefficient (Tc) enable to separate the receptors of group 1 from group 2. The pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps discovers structural features that can be used to design molecules selective towards the receptors of group 1. The importance of several predicted residues to ligand selectivity is supported by the available mutagenesis and ligand structure-activity relationships studies. In addition, the Tc-selected conformations of the receptors for group 1 show good performance in isolation of known ligands from a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as oncologic and infectious disorders.