Biomedical subjects

A J Hopfinger

Publications and source records attributed to A J Hopfinger.

At least 19 recordsLinked to original sources

PubMed2002

4D-QSAR analysis of a set of propofol analogues: mapping binding sites for an anesthetic phenol on the GABA(A) receptor.

A training set of 27 propofol (2,6-diisopropylphenol) analogues was used to construct four-dimensional (4D) quantitative structure-activity relationship (QSAR) models for three screens of biological activity: loss of righting reflex (LORR) in tadpoles, enhancement of agonist activity at the gamma-aminobutyric acid type A (GABA(A)) receptor, and direct (agonist-independent) activation of the receptor. The three resulting 4D-QSAR models are almost identical in form, and all suggest three key ligand-receptor interaction sites. The formation of an intermolecular hydrogen bond involving the proton of the ligand -OH group is the most important binding interaction. A hydrophobic pocket binding interaction involving the six-substituent is the second most significant binding site, and a similar hydrophobic pocket binding interaction near the two-substituent is the third postulated binding site from the 4D-QSAR models. A test set of eight compounds was used to evaluate the tadpole LORR 4D-QSAR model. Those compounds highly congeneric to the training set compounds were accurately predicted. However, compounds exploring substituent sites and/or electronic structures different from the training set were less well-predicted. Overall, the results show a striking similarity between the models of the sites responsible for anesthesia and those mediating effects of the training set of propofol analogues on the GABA(A) receptor; it follows that the GABA(A) receptor is therefore the likely site of propofol's anesthetic action.

Algorithms↗

PubMed2002

Predicting blood-brain barrier partitioning of organic molecules using membrane-interaction QSAR analysis.

PURPOSE: Membrane-interaction quantitative structure-activity relationship (OSAR) analysis (MI-QSAR) has been used to develop predictive models of blood-brain barrier partitioning of organic compounds by, in part, simulating the interaction of an organic compound with the phospholipid-rich regions of cellular membranes. METHOD: A training set of 56 structurally diverse compounds whose blood-brain barrier partition coefficients were measured was used to construct MI-QSAR models. Molecular dynamics simulations were used to determine the explicit interaction of each test compound (solute) with a model DMPC monolayer membrane model. An additional set of intramolecular solute descriptors were computed and considered in the trial pool of descriptors for building MI-QSAR models. The QSAR models were optimized using multidimensional linear regression fitting and a genetic algorithm. A test set of seven compounds was evaluated using the MI-QSAR models as part of a validation process. RESULTS: Significant MI-QSAR models (R2 = 0.845, Q2 = 0.795) of the blood-brain partitioning process were constructed. Blood-brain barrier partitioning is found to depend upon the polar surface area. the octanol/water partition coefficient, and the conformational flexibility of the compounds as well as the strength of their binding" to the model biologic membrane. The blood-brain barrier partitioning measures of the test set compounds were predicted with the same accuracy as the compounds of the training set. CONCLUSION: The MI-QSAR models indicate that the blood-brain barrier partitioning process can be reliably described for structurally diverse molecules provided interactions of the molecule with the phospholipids-rich regions of cellular membranes are explicitly considered.

Blood-Brain Barrier↗

PubMed2002

Prediction of skin irritation from organic chemicals using membrane-interaction QSAR analysis.

Membrane-interaction (MI) quantitative structure activity relationship (QSAR) analysis was carried out for a training set of 22 hydroxy organic compounds for which the Draize skin irritation scores, PII, had been determined. Significant MI-QSAR models were constructed in which skin irritation potency is predicted to increase with (1) increasing effective concentration of the compound available for uptake into phospholipid-rich regions of a cellular membrane, (2) increasing binding of the compound to the phospholipid-rich regions of a cellular membrane, and (3) the chemical reactivity of the compound as reflected by the highest occupied molecular orbital (HOMO) and/or lowest unoccupied molecular orbital (LUMO) of the molecule. Overall, the MI-QSAR models constructed for skin irritation are very similar, with respect to the types of descriptors, to those found for eye irritation. In turn, the skin irritation MI-QSAR models suggest a similar molecular mechanism of action to that postulated for eye irritation from MI-QSAR analysis. Significant and predictive QSAR models cannot be constructed unless test compound-membrane interaction descriptors are computed and used to build the QSAR models.

Animal Testing Alternatives↗

PubMed2001

A search for sources of drug resistance by the 4D-QSAR analysis of a set of antimalarial dihydrofolate reductase inhibitors.

A set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d pyrimidines were studied using four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis. The corresponding biological activities of these compounds include IC50 inhibition constants for both the wild type, and a specific mutant type of Plasmodium falciparum dihydrofolate reductase (DHFR). Two thousand conformations of each analog were sampled to generate a conformational ensemble profile (CEP) from a molecular dynamics simulation (MDS) of 100,000 conformer trajectory states. Each sampled conformation was placed in a 1 A cubic grid cell lattice for each of five trial alignments. The frequency of occupation of each grid cell was computed for each of six types of pharmacophore groups of atoms of each compound. These grid cell occupancy descriptors (GCODs) were then used as a descriptor pool to construct 4D-QSAR models. Models for inhibition of both the 'wild' type and the mutant enzyme were generated which provide detailed spatial pharmacophore requirements for inhibition in terms of atom types and their corresponding relative locations in space. The 4D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the Plasmodium falciparum DHFR to current antimalarials. One feature identified is a slightly different binding alignment of the ligands to the mutant form of the enzyme as compared to the wild type.

Animals↗

PubMed2001

Free energy force field (FEFF) 3D-QSAR analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors.

Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models for a set of 18 structurally diverse antifolates including pyrimethamine, cycloguanil, methotrexate, aminopterin and trimethoprim, and 13 pyrrolo[2,3-d]pyrimidines. The molecular target ('receptor') used was a 3D-homology model of a specific mutant type of Plasmodium falciparum (Pf) dihydrofolate reductase (DHFR). The dependent variable of the 3D-QSAR models is the IC50 inhibition constant for the specific mutant type of PfDHFR. The independent variables of the 3D-QSAR models (the descriptors) are scaled energy terms of a modified first-generation AMBER force field combined with a hydration shell aqueous solvation model and a collection of 2D-QSAR descriptors often used in QSAR studies. Multiple temperature molecular dynamics simulation (MDS) and the genetic function approximation (GFA) were employed using partial least square (PLS) and multidimensional linear regressions as the fitting functions to develop FEFF 3D-QSAR models for the binding process. The significant FEFF energy terms in the best 3D-QSAR models include energy contributions of the direct ligand-receptor interaction. Some changes in conformational energy terms of the ligand due to binding to the enzyme are also found to be important descriptors. The FEFF 3D-QSAR models indicate some structural features perhaps relevant to the mechanism of resistance of the PfDHFR to current antimalarials. The FEFF 3D-QSAR models are also compared to receptor-independent (RI) 4D-QSAR models developed in an earlier study and subsequently refined using recently developed generalized alignment rules.

Animals↗

PubMed2001

Prediction of eye irritation from organic chemicals using membrane-interaction QSAR analysis.

Eye irritation potency of a compound or mixture has traditionally been evaluated using the Draize rabbit-eye test (Draize et al., 1944). In order to aid predictions of eye irritation and to explore possible corresponding mechanisms of eye irritation, a methodology termed "membrane-interaction QSAR analysis" (MI-QSAR) has been developed (Kulkarni and Hopfinger 1999). A set of Draize eye-irritation data established by the European Center for Ecotoxicology and Toxicology of Chemicals (ECETOC) (Bagley et al., 1992) was used as a structurally diverse training set in an MI-QSAR analysis. Significant QSAR models were constructed based primarily upon aqueous solvation-free energy of the solute and the strength of solute binding to a model phospholipid (DMPC) monolayer. The results demonstrate that inclusion of parameters to model membrane interactions of potentially irritating chemicals provides significantly better predictions of eye irritation for structurally diverse compounds than does modeling based solely on physiochemical properties of chemicals. The specific MI-QSAR models reported here are, in fact, close to the upper limit in both significance and robustness that can be expected for the variability inherent to the eye-irritation scores of the ECETOC training set. The MI-QSAR models can be used with high reliability to classify compounds of low- and high-predicted eye irritation scores. Thus, the models offer the opportunity to reduce animal testing for compounds predicted to fall into these two extreme eye-irritation score sets. The MI-QSAR paradigm may also be applicable to other toxicological endpoints, such as skin irritation, where interactions with cellular membranes are likely.

Animal Testing Alternatives↗

PubMed2001

General anesthetic potencies of a series of propofol analogs correlate with potency for potentiation of gamma-aminobutyric acid (GABA) current at the GABA(A) receptor but not with lipid solubility.

A series of 27 analogs of the general anesthetic propofol (2,6-diisopropylphenol) were examined for general anesthetic activity in Xenopus laevis tadpoles and for the ability to produce enhancement of submaximal GABA responses and/or direct activation at recombinant GABA(A) receptors. Fourteen of the propofol analogs produced loss of righting reflex in the tadpoles, whereas 13 were inactive as anesthetics. The same pattern of activity was noted with the actions of the compounds at the GABA(A) alpha(1)beta(2)gamma(2s) receptor. The potencies of the analogs as general anesthetics in tadpoles correlated better with potentiation of GABA responses than direct activation at the GABA(A) alpha(1)beta(2)gamma(2s) receptor. The calculated octanol/water partition coefficients for the analogs did not explain the lack of activity exhibited by the 13 nonanesthetic analogs, although this physicochemical parameter did correlate modestly with in vivo anesthetic potency. The actions of one nonanesthetic analog, 2,6-di-tert-butylphenol, were examined in detail. 2,6-Di-tert-butylphenol was inactive at GABA(A) receptors, did not function as an anesthetic in the tadpoles, and did not antagonize any of the actions of propofol at GABA(A) receptors or in tadpoles. A key influence on the potency of propofol analogs appears to be the size and shape of the alkyl groups at positions 2 and 6 of the aromatic ring relative to the substituent at position 1. These data suggest steric constraints for the binding site for propofol on the GABA(A) receptor.

Allosteric Regulation↗

PubMed2000

Extraction of pharmacophore information from high-throughput screens.

Two major advances have been made in the computational perception and utilization of pharmacophores in compound libraries, both real and virtual. Firstly, a hierarchical set of filtering calculations has emerged that can be used to efficiently partition a library into a trial set of pharmacophores. This sequential filtering permits large libraries to be efficiently processed, as well as compounds judged as 'hits' to be analyzed in great detail. Secondly, new and extended methods of QSAR (quantitative structure-activity relationship) analysis have evolved to translate pharmacophore information into QSAR models that, in turn, can be used as virtual high-throughput screens for activity profiling of a library.

Combinatorial Chemistry Techniques↗

PubMed1999

Synthesis, pharmacological and biophysical characterization, and membrane-interaction QSAR analysis of cationic amphiphilic model compounds.

Cationic amphiphilic drugs have a propensity to interact with biological interphases. This study was designed to gain more insight into the molecular properties of catamphiphilic drugs which govern this type of interaction. A series of phenylpropylamine model compounds were synthesized in which modifications were incorporated at the aromatic part of the molecule. The replacement of (45)Ca(2+) from phosphatidylserine monolayers served to monitor drug binding to the phospholipid. The influence on the phase-transition temperature of liposomes of dipalmitoylphosphatidic acid was measured to assess the perturbing action of the drugs on the structural organization of phospholipid assemblies. The antiarrhythmic activity of the compounds was determined in Langendorff preparations of guinea pig hearts to assess the membrane-stabilizing action. Quantitative structure-activity relationship (QSAR) models for these endpoints were developed using both intra- and intermolecular QSAR descriptors. Intermolecular membrane-interaction descriptors were derived from molecular dynamics simulations of the compounds in a model phospholipid monolayer. QSAR models were derived for all endpoints using partial least-squares regression (PLS) and a genetic algorithm tool, the genetic function approximation (GFA). Membrane-interaction descriptors appear to be of a particular importance in explaining the influence of the compounds on the phase-transition temperature of DPPA liposomes, while the other endpoints can be adequately modeled by intramolecular descriptors. The calcium-displacing activity at phosphatidylserine monolayers is governed by the electrostatic properties of the compounds. Measures of lipophilicity and molecular size are of particular importance for antiarrhythmic activity. Possible improvements to both the molecular modeling and the applied computational protocol of membrane-solute systems are identified and discussed.

Animals↗

PubMed1999

Prediction of ligand-receptor binding thermodynamics by free energy force field three-dimensional quantitative structure-activity relationship analysis: applications to a set of glucose analogue inhibitors of glycogen phosphorylase.

Glucose analogue inhibitors of glycogen phosphorylase, GP, may be of clinical interest in the regulation of glycogen metabolism in diabetes. The receptor geometry of glycogen phosphorylase b, GPb, is available for structure-based design and also for the evaluation of the thermodynamics of ligand-receptor binding. Free energy force field (FEFF) 3D-QSAR analysis was used to construct ligand-receptor binding models. FEFF terms involved in binding are represented by a modified first-generation AMBER force field combined with a hydration shell solvation model. The FEFF terms are then treated as independent variables in the development of 3D-QSAR models by correlating these energy terms with experimental binding energies for a training set of inhibitors. The genetic function approximation, employing both multiple linear regression and partial least squares regression data fitting, was used to develop the FEFF 3D-QSAR models for the binding process and to scale the free energy force field for this particular ligand-receptor system. The significant FEFF energy terms in the resulting 3D-QSAR models include the intramolecular vacuum energy of the unbound ligand, the intermolecular ligand-receptor van der Waals interaction energy, and the van der Waals energy of the bound ligand. Other terms, such as the change in the stretching energy of the receptor on binding, change in the solvation energy of the system on binding, and the change in the solvation energy of the ligand on binding are also found in the set of significant FEFF 3D-QSAR models. Overall, the binding of this class of ligands to GPb is largely characterized by how well the ligand can sterically fit into the active site of the enzyme. The FEFF 3D-QSAR models can be used to estimate the binding free energy of any new analogue in substituted glucose series prior to synthesis and testing.

Binding Sites↗

PubMed1999

Quantitative component analysis of mixtures for risk assessment: application to eye irritation.

A methodology called quantitative component analysis of mixtures (QCAM) was used to analyze an existing set of product formulation data to determine if the irritating ingredients in the mixtures could be identified. Eye irritation scores, based on a rat model, for 18 mixtures having a composite total of 37 components, were analyzed by QCAM. QCAM relates a net toxicity measure of a mixture to the toxicities of the individual components of the mixture through linear, quadratic, and pairwise cross-component concentration-dependent interactions. A correlation model is established using a particular genetic algorithm employing either multidimensional linear regression or partial least-squares regression fitting. Cornea eye irritation and average eye irritation are well-explained in terms of a linear model of, at most, three components over the set of mixtures. Moreover, extensive cornea and average eye irritations are due to only one of these three components of the mixtures. Also, one of the three significant components was predicted to decrease the extent of eye irritation, and subsequently identified as an "anti-irritant" in contact lens solutions. A reasonable linear correlation model could also be developed for conjunctiva irritation, but no significant iris irritation model could be constructed. The addition of quadratic and/or cross-component concentration terms to a linear correlation model did not statistically improve the overall resultant model. The QCAM models permit estimation of the intrinsic (self) toxicity of each of the components of a mixture, and may aid in the reduction, and ultimate elimination, of the need for animal eye irritation studies.

Algorithms↗

PubMed1999

Membrane-interaction QSAR analysis: application to the estimation of eye irritation by organic compounds.

PURPOSE: The purpose of this study was to explore a potential mechanism of eye irritation, and to construct a corresponding general quantitative structure-activity relationship (QSAR) model, in terms of diversity of irritant chemical structure, based on the Draize eye irritation ECETOC data set. METHODS: Molecular dynamic simulation (MDS) was used to generate intermolecular membrane-solute interaction properties. These intermolecular properties were combined with intramolecular physicochemical properties and features of the solute (irritant) to construct QSAR models using multi-dimensional linear regression and the Genetic Function Approximation (GFA) algorithm. RESULTS: Significant QSAR models for estimating eye irritation potential were constructed in which solute aqueous solvation free energy and solute-membrane interaction energies are the principle correlation descriptors. These physicochemical descriptors were selected from a trial set of 95 descriptors for 18 structurally diverse compounds fully representative of the ECETOC set of 38 compounds. CONCLUSIONS: Combining intermolecular solute-membrane interaction descriptors with intramolecular solute descriptors yields statistically significant eye irritation QSAR models. The resultant QSAR models support an eye irritation mechanism of the action in which increased aqueous solubility of the irritant and its strength of binding to the membrane both increase eye irritation.

Animals↗

PubMed1998

Pharmacological activity and membrane interactions of antiarrhythmics: 4D-QSAR/QSPR analysis.

PURPOSE: This study was done to explore the relationships of both macroscopic and molecular level physicochemical properties to in-vivo antiarrhythmic activity and interactions with phospholipid membranes for a set of cationic-amphiphilic analogs. METHODS: The 4D-QSAR method, recently developed by Hopfinger and co-workers (1), was employed to establish 3D-QSAR/QSPR models. Molecular dynamics simulations provided the set of conformational ensembles which were analyzed using partial least squares regression in combination with the Genetic Function Approximation algorithm to construct QSAR and QSPR models. RESULTS: Significant QSAR models for in-vivo antiarrhythmic activity were constructed in which logP (the partition coefficient), and specific grid cell occupancy (spatial) descriptors are the main activity correlates. LogP is the most significant QSAR descriptor. 4D-QSPR models were also developed for two analog-membrane interaction properties, the change in a membrane transition temperature and the ability of the analogs to displace adsorbed Ca(2+)-ions from phosphatidylserine monolayers. CONCLUSIONS: Spatial features, represented by grid cell occupancy descriptors, supplement partition coefficient, which is the most important determinant of in-vivo antiarrhythmic activity, to provide a comprehensive model for drug action. The QSPR models are less significant in statistical measures, and limited to interpretation of possible molecular mechanisms of action.

Animals↗

PubMed1997

Characterization of lipid membrane dynamics by simulation: I. Torsion angle motions of the linear chains.

The torsion angle motions, generated from molecular dynamics (MD) simulations, of the two aliphatic chains of 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine (DMPC) in its lipid monolayer were evaluated by comparing these motions to those of an equivalent isolated (free) n-alkane chain, and the same n-alkane chain in its crystal lattice. The time-dependent autocorrelation and (1,2)-, (1,3)-, (1,4)-, and (1,5)-cross-correlation functions were constructed to analyze the torsion angle motions. It was found that the torsion angle motions of the DMPC lipid monolayer aliphatic chains are intermediate to those of the free n-alkane chain and the same n-alkane chain in its crystal lattice, particularly for short correlation times. The torsion angle motions of the aliphatic chains of DMPC are also found to be essentially independent of the charge state on the head group. The linear aliphatic chains of a DMPC lipid monolayer behave most like the isolated n-alkane chains with respect to torsion angle flexibility, even though the pairs of aliphatic chains of each DMPC are part of an ordered monolayer assembly. The aliphatic chains of the DMPC molecules in their monolayer exhibit at least two types of wave motions. One of the wave motions is the same in form, though somewhat more diffuse, as a traveling wave found in n-alkane crystals. The other wave motion involves major torsion angle transitions, and has some characteristics of the soliton properties observed in n-alkane crystals near their respective melt transition temperatures.

Computer Simulation↗

PubMed1997

Molecular modeling of polymers 16. Gaseous diffusion in polymers: a quantitative structure-property relationship (QSPR) analysis.

PURPOSE: The purpose of this study was to identify the key physicochemical molecular properties of polymeric materials responsible for gaseous diffusion in the polymers. METHODS: Quantitative structure-property relationships, QSPRs were constructed using a genetic algorithm on a training set of 16 polymers for which CO2, N2, O2 diffusion constants were measured. Nine physicochemical properties of each of the polymers were used in the trial basis set for QSPR model construction. The linear cross-correlation matrices were constructed and investigated for colinearity among the members of the training sets. Common water diffusion measures for a limited training set of six polymers was used to construct a "semi-QSPR" model. RESULTS: The bulk modulus of the polymer was overwhelmingly found to be the dominant physicochemical polymer property that governs CO2, N2 and O2 diffusion. Some secondary physicochemical properties controlling diffusion, including conformational entropy, were also identified as correlation descriptors. Very significant QSPR diffusion models were constructed for all three gases. Cohesive energy was identified as the main correlation physicochemical property with aqueous diffusion measures. CONCLUSIONS: The dominant role of polymer bulk modulus on gaseous diffusion makes it difficult to develop criteria for selective transport of gases through polymers. Moreover, high bulk moduli are predicted to be necessary for effective gas barrier materials. This property requirement may limit the processing and packaging features of the material. Aqueous diffusion in polymers may occur by a different mechanism than gaseous diffusion since bulk modulus does not correlate with aqueous diffusion, but rather cohesive energy of the polymer.

Carbon Dioxide↗

PubMed1996

Solution of the conformation and alignment tensors for the binding of trimethoprim and its analogs to dihydrofolate reductase: 3D-quantitative structure-activity relationship study using molecular shape analysis, 3-way partial least-squares regression, and 3-way factor analysis.

Molecular recognition is the basis of rational drug design, and for this reason it has been extensively studied. However, the process by which a ligand recognizes and binds to its receptor is complex and not well understood. For the case in which the geometries (conformation and alignment) of the ligand and receptor are known from X-ray crystal structure data, the problem is simplified. The receptor-bound conformation and alignment of the ligand is assumed, and those of additional ligands are inferred. For the general case in which the geometries of the ligand(s) and receptor are unknown, no general treatment or solution is available and receptor-ligand geometries must be obtained indirectly from structure-activity studies or synthesis and evaluation of rigid analogs. A general treatment for solving for the receptor-bound geometry of a series of ligands is presented here. Using molecular shape analysis, for ligand description, tensor analysis of N-way arrays by partial least-squares (PLS) regression, and 3-way factor analysis, the receptor-bound geometries of trimethoprim and a series of trimethoprim-like dihydrofolate reductase inhibitors are correctly predicted.

Chemical Phenomena↗

PubMed1996

Nonspecific protease-catalyzed hydrolysis/synthesis of a mixture of peptides: product diversity and ligand amplification by a molecular trap.

We sought to develop a peptide library in solution and dynamically screen this library for peptides that would bind to macromolecules of interest. Peptide diversity was achieved in an initial stock solution of peptides by using proteases under conditions in which both hydrolysis and synthesis occurred. As an example, a simple reaction containing YGG, FL and thermolysin resulted in the synthesis of YGGFL as well as many other undefined products. When low molecular weight products of a reaction containing VA, AL, and thermolysin were subsequently exposed to dipeptidase, 7 out of 9 potential dipeptides were observed. Incubation of protease with an hydrolysate of albumin and a radiolabeled peptide resulted in the radiolabel participating in reactions other than simple hydrolysis and, after 24 h, the specific activity of radiolabel was shown by high performance liquid chromatography to disperse to a level that would be necessary in the event of maximum theoretical diversity. When a binding macromolecule was exposed to this system, ligand production was amplified relative to reactions run in the absence of binding macromolecule. This protease-based peptide scrambling and binding system was utilized for the discovery of novel peptides that bind to fibrinogen.

Chromatography, High Pressure Liquid↗

PubMed1996

The rationale for E2020 as a potent acetylcholinesterase inhibitor.

The phase III drug-candidate, E2020, developed for treatment of Alzheimer's disease, and possibly other demenitas, and its analogues have been the focus of extensive molecular pharmacological and structural studies. The potency and selectivity of E2020 as an inhibitor of acetylcholinesterase, AChE, in the brain is established. A combination of molecular modeling and QSAR studies have been used throughout the evolution of the AChE inhibitor program leading to the benzylpiperidine series, and, ultimately, E2020. QSAR studies have identified requirements of optimize inhibition activity as a function of substituent choice on both the indanone and benzyl rings in the E2020 class of inhibitors. A combination of X-ray crystal structure studies of E2020 isomers and the molecular shape analysis, MSA, of E2020 and its analogues has led to a postulated active conformation, and molecular shape, for these AChE inhibitors. The active molecular shape corresponds to a high degree of shape similarity between the two E2020 isomers which, in turn, is consistent with the observed high inhibition potencies of both of these compounds. Intermolecular docking studies were carried out for E2020 and some analogues with the crystal structure of AChE when it became available. The docking simulations involving E2020 analogues suggest these inhibitors do not bind at the acetylcholine, ACh, active site, but rather at the most narrow location of the long channel leading to the active site. Intermolecular binding geometries are consistent with the postulated active conformations derived from structure-activity (receptor geometry independent) information.

Acetylcholinesterase↗