Model For Ligand Binding Research Articles

Single Molecule FRET Studies of Protein Conformational Landscapes: 3 Prototypic Examples for the Relation Between Conformational Dynamics and Function

Since the major structural biology method, X-ray crystallography, is limited to resolving fixed homogeneous conformations, techniques like single molecule FRET are becoming more important to determine dynamic behaviour of proteins. In comparing three different single molecule FRET studies of prototypic proteins we show that their structural aspects and dynamic behaviour are closely related to function. Initiation factor 3 (IF3) plays an important role in protein synthesis since it is an activating ligand for the correct assembly of a ribosome. It could be shown, that free IF3 is a highly flexible molecule. However this flexibility is lost completely after binding to the 30s subunit of the ribosome where it functions as a structural stabiliser, supporting the conformer selection model for ligand binding. Human guanylate binding protein 1 (hGBP1) is a member of the dynamin superfamily which is known for mediating membrane fusion in endocytosis. We show fast dynamic processes in solution between two distinct conformations. After binding its substrate GTP, hGBP1 becomes more rigid, working as a conformational switch where the GTP-bound conformation allows dimerisation leading to a functional dimer. DNA polymerases, such as the Klenow fragment of DNA polymerase I, are highly processive enzymes synthesizing double stranded DNA with a rate constant, kpol, of ∼40 s-1. We could show fast dynamics between different conformations of the enzyme in the absence of substrate. After binding of DNA and the “correct” dNTP, a closure of the protein is expected but however was not seen, rather the equilibria is shifted towards a closed conformation. This flexibility reflects the balance between specificity and velocity for this polymerase.

Plasticity of Cytochrome P450 2B4 as Investigated by Hydrogen-Deuterium Exchange Mass Spectrometry and X-ray Crystallography

Crystal structures of the xenobiotic metabolizing cytochrome P450 2B4 have demonstrated markedly different conformations in the presence of imidazole inhibitors or in the absence of ligand. However, knowledge of the plasticity of the enzyme in solution has remained scant. Thus, hydrogen-deuterium exchange mass spectrometry (DXMS) was utilized to probe the conformations of ligand-free P450 2B4 and the complex with 4-(4-chlorophenyl)imidazole (4-CPI) or 1-biphenyl-4-methyl-1H-imidazole (1-PBI). The results of DXMS indicate that the binding of 4-CPI slowed the hydrogen-deuterium exchange rate over the B'- and C-helices and portions of the F-G-helix cassette compared with P450 2B4 in the absence of ligands. In contrast, there was little difference between the ligand-free and 1-PBI-bound exchange sets. In addition, DXMS suggests that the ligand-free P450 2B4 is predominantly open in solution. Interestingly, a new high resolution structure of ligand-free P450 2B4 was obtained in a closed conformation very similar to the 4-CPI complex. Molecular dynamics simulations performed with the closed ligand-free structure as the starting point were used to probe the energetically accessible conformations of P450 2B4. The simulations were found to equilibrate to a conformation resembling the 1-PBI-bound P450 2B4 crystal structure. The results indicate that conformational changes observed in available crystal structures of the promiscuous xenobiotic metabolizing cytochrome P450 2B4 are consistent with its solution structural behavior.

Complexation of arsenite with dissolved organic matter: Conditional distribution coefficients and apparent stability constants

The complexation of arsenic (As) with dissolved organic matter (DOM), although playing an important role in regulating As mobility and transformation, is poorly characterized, as evidenced by scarce reporting of fundamental parameters of As–DOM complexes. The complexation of arsenite (As III) with Aldrich humic acid (HA) at different pHs was characterized using a recently developed analytical technique to measure both free and DOM-bound As. Conditional distribution coefficient ( K D ), describing capacity of DOM in binding As III from the mass perspective, and apparent stability constant ( K s ), describing stability of resulting As III–DOM complexes, were calculated to characterize As III–DOM complexation. Log K D of As III ranged from 3.7 to 2.2 (decreasing with increase of As/DOM ratio) at pH 5.2, from 3.6 to 2.6 at pH 7, and from 4.3 to 3.2 at pH = 9.3, respectively. Two-site ligand binding models can capture the heterogeneity of binding sites and be used to calculate K s by classifying the binding sites into strong (S1) and weak (S2) groups. Log K s for S1 sites are 7.0, 6.5, and 5.9 for pH 5.2, 7, and 9.3, respectively, which are approximately 1–2 orders of magnitude higher than for weak S2 sites. The results suggest that As III complexation with DOM increases with pH, as evidenced by significant spikes in concentrations of DOM-bound As III and in K D values at pH 9.3. In contrary to K D , log K s decreased with pH, in particular for S1 sites, probably due to the presence of negatively charged H 2 AsO 3 - and the involvement of metal-bridged As III–DOM complexation at pH 9.3.

ChemInform Abstract: Development of Pharmacophore Alignment Models as Input for Comparative Molecular Field Analysis of a Diverse Set of Azole Antifungal Agents.

Molecular modeling studies were performed on a diverse set of 24 cytochrome P-45014αDM inhibiting azole antifungals that demonstrate different degrees of biological activity. The studied compounds, which have been reported to be active in vitro against Candida albicans, were divided into a training set of 20 compounds and a test set of 4 compounds. In an effort to develop a ligand-binding model for the cytochrome P-45014αDM receptor, a pharmacophore mapping program (Apex-3D) was used to search structural features that are common to ligands that exhibit moderate to high antifungal activity. Apex-3D then was utilized to propose a common biophoric region that included one low-energy conformation of each compound in the training set. These aligned structures suggested a three-point pharmacophore map (two atom-centered descriptors and one aromatic ring centroid) for the azole antifungals. The resulting alignment was used in a comparative molecular field analysis (CoMFA) study in an attempt to correlate the ste...

Temporal transformations in olfactory encoding promote rapid detection of natural odor fluctuations

Event Abstract Back to Event Temporal transformations in olfactory encoding promote rapid detection of natural odor fluctuations Katherine Nagel1* and Rachel Wilson1 1 Harvard Medical School, United States Natural olfactory stimuli form turbulent plumes that fluctuate rapidly in time and may provide information about the location of an odor source. However, olfactory neurons respond to odor with complex and prolonged spike dynamics that would seem unsuitable for encoding such stimuli. We used Drosophila as a model system for understanding how complex response dynamics arise in the first layer of an olfactory system and what function they might serve. Using pharmacological and genetic tools, we showed that we could obtain separate measures of transduction currents and spikes from olfactory receptor neurons (ORNs) in vivo. This revealed that ORN response dynamics arise from two non-trivial temporal transformations: one imposed by odor transduction, and one by spike generation. Odor transduction dynamics were fast, and were well-described by a model of ligand binding and receptor activation. This model was sufficient to account for differences in response dynamics across odors and receptors, asymmetries between onset and offset dynamics, and receptor-specific adaptation and recovery. Spiking dynamics were captured by a differentiating linear filter that was similar across odors and ORNs. Spike dynamics could be altered by genetic knockdown of sodium channel expression levels, suggesting that they are tightly regulated. This is consistent with Hodgkin Huxley models showing that the temporal selectivity of a neuron depends on its balance of sodium and potassium conductances and suggests that the differentiating transformation arises from known models of spike generation. In the context of rapid and intermittent natural stimuli, the transduction and spiking transformations lead to fast and highly sensitive reporting of plume encounters, while in response to longer synthetic pulses they produce more complex dynamics. Our analysis suggest that complex spike patterns in olfaction are an unavoidable consequence of the biophysics of odor transduction, coupled to adaptations for rapid encoding of transient plume encounters. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Oral Presentation Topic: Oral presentations Citation: Nagel K and Wilson R (2010). Temporal transformations in olfactory encoding promote rapid detection of natural odor fluctuations. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00062 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Feb 2010; Published Online: 19 Feb 2010. * Correspondence: Katherine Nagel, Harvard Medical School, Boston, United States, katherine_nagel@hms.harvard.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Katherine Nagel Rachel Wilson Google Katherine Nagel Rachel Wilson Google Scholar Katherine Nagel Rachel Wilson PubMed Katherine Nagel Rachel Wilson Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

T1R receptors mediate mammalian sweet and umami taste

The T1R family of taste receptors mediates 2 taste qualities: T1R2/T1R3 for sweet taste and T1R1/T1R3 for umami taste. Functional expression in heterologous system and gene knockout studies has shown their functions as taste receptors. Structure-function relation studies on T1R2/T1R3 showed multiple ligand binding sites on both subunits. The umami taste of l-glutamate can be drastically enhanced by 5′ ribonucleotides, and the synergy is a hallmark of this taste quality. On the basis of chimeric T1R receptors, site-directed mutagenesis, and molecular modeling data, we recently proposed a cooperative ligand binding model that involved the Venus flytrap domain of T1R1 in which l-glutamate binds close to the hinge region and 5′ ribonucleotides bind to an adjacent site close to the opening of the flytrap to further stabilize the closed conformation. This novel mechanism may apply to other class C, G protein–coupled receptors.

Molecular mechanism for the umami taste synergism

Umami is one of the 5 basic taste qualities. The umami taste of L-glutamate can be drastically enhanced by 5' ribonucleotides and the synergy is a hallmark of this taste quality. The umami taste receptor is a heteromeric complex of 2 class C G-protein-coupled receptors, T1R1 and T1R3. Here we elucidate the molecular mechanism of the synergy using chimeric T1R receptors, site-directed mutagenesis, and molecular modeling. We propose a cooperative ligand-binding model involving the Venus flytrap domain of T1R1, where L-glutamate binds close to the hinge region, and 5' ribonucleotides bind to an adjacent site close to the opening of the flytrap to further stabilize the closed conformation. This unique mechanism may apply to other class C G-protein-coupled receptors.

A repulsive field: advances in the electrostatics of the ion atmosphere

The large electrostatic repulsion arising from the negatively charged backbone of RNA molecules presents a large barrier to folding. Solution counterions assist in the folding process by screening this electrostatic repulsion. While early research interpreted the effect of these counterions in terms of an empirical ligand-binding model, theories based on physical models have supplanted them and revised our view of the roles that ions play in folding. Instead of specific ion-binding sites, most ions in solution interact inside an 'ion atmosphere'--a fluctuating cloud of nonspecifically associated ions surrounding any charged molecule. Recent advances in experiments have begun the task of characterizing the ion atmosphere, yielding valuable data that have revealed deficiencies in Poisson-Boltzmann theory, the most widely used theory of the ion atmosphere. The continued development of experiments will help guide the development of improved theories, with the ultimate goal of understanding RNA folding and function and nucleic acid/protein interactions from a quantitative perspective.

Dynamic energy landscape view of coupled binding and protein conformational change: Induced-fit versus population-shift mechanisms

Allostery, the coupling between ligand binding and protein conformational change, is the heart of biological network and it has often been explained by two representative models, the induced-fit and the population-shift models. Here, we clarified for what systems one model fits better than the other by performing molecular simulations of coupled binding and conformational change. Based on the dynamic energy landscape view, we developed an implicit ligand-binding model combined with the double-basin Hamiltonian that describes conformational change. From model simulations performed for a broad range of parameters, we uncovered that each of the two models has its own range of applicability, stronger and longer-ranged interaction between ligand and protein favors the induced-fit model, and weaker and shorter-ranged interaction leads to the population-shift model. We further postulate that the protein binding to small ligand tends to proceed via the population-shift model, whereas the protein docking to macromolecules such as DNA tends to fit the induced-fit model.

Testing the Coulomb/Accessible Surface Area solvent model for protein stability, ligand binding, and protein design

BackgroundProtein structure prediction and computational protein design require efficient yet sufficiently accurate descriptions of aqueous solvent. We continue to evaluate the performance of the Coulomb/Accessible Surface Area (CASA) implicit solvent model, in combination with the Charmm19 molecular mechanics force field. We test a set of model parameters optimized earlier, and we also carry out a new optimization in this work, using as a target a set of experimental stability changes for single point mutations of various proteins and peptides. The optimization procedure is general, and could be used with other force fields. The computation of stability changes requires a model for the unfolded state of the protein. In our approach, this state is represented by tripeptide structures of the sequence Ala-X-Ala for each amino acid type X. We followed an iterative optimization scheme which, at each cycle, optimizes the solvation parameters and a set of tripeptide structures for the unfolded state. This protocol uses a set of 140 experimental stability mutations and a large set of tripeptide conformations to find the best tripeptide structures and solvation parameters.ResultsUsing the optimized parameters, we obtain a mean unsigned error of 2.28 kcal/mol for the stability mutations. The performance of the CASA model is assessed by two further applications: (i) calculation of protein-ligand binding affinities and (ii) computational protein design. For these two applications, the previous parameters and the ones optimized here give a similar performance. For ligand binding, we obtain reasonable agreement with a set of 55 experimental mutation data, with a mean unsigned error of 1.76 kcal/mol with the new parameters and 1.47 kcal/mol with the earlier ones. We show that the optimized CASA model is not inferior to the Generalized Born/Surface Area (GB/SA) model for the prediction of these binding affinities. Likewise, the new parameters perform well for the design of 8 SH3 domain proteins where an average of 32.8% sequence identity relative to the native sequences was achieved. Further, it was shown that the computed sequences have the character of naturally-occuring homologues of the native sequences.ConclusionOverall, the two CASA variants explored here perform very well for a wide variety of applications. Both variants provide an efficient solvent treatment for the computational engineering of ligands and proteins.

Structural studies of neuropilin/antibody complexes provide insights into semaphorin and VEGF binding

Neuropilins (Nrps) are co-receptors for class 3 semaphorins and vascular endothelial growth factors and important for the development of the nervous system and the vasculature. The extracellular portion of Nrp is composed of two domains that are essential for semaphorin binding (a1a2), two domains necessary for VEGF binding (b1b2), and one domain critical for receptor dimerization (c). We report several crystal structures of Nrp1 and Nrp2 fragments alone and in complex with antibodies that selectively block either semaphorin or vascular endothelial growth factor (VEGF) binding. In these structures, Nrps adopt an unexpected domain arrangement in which the a2, b1, and b2 domains form a tightly packed core that is only loosely connected to the a1 domain. The locations of the antibody epitopes together with in vitro experiments indicate that VEGF and semaphorin do not directly compete for Nrp binding. Based upon our structural and functional data, we propose possible models for ligand binding to neuropilins.

Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches.

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2–S2′ pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays (∼20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity.

Copper complexation by fulvic acid affects copper toxicity to the larvae of the polychaete Hydroides elegans

Copper toxicity is influenced by a variety of environmental factors including dissolved organic matter (DOM). We examined the complexation of copper by fulvic acid (FA), one of the major components of DOM, by measuring the decline in labile copper by anodic stripping voltammetrically (ASV). The data were described using a one-site ligand binding model, with a ligand concentration of 0.19micromol site mg(-1) C, and a logK' of 6.2. The model was used to predict labile copper concentration in a bioassay designed to quantify the extent to which Cu-FA complexation affected copper toxicity to the larvae of marine polychaete Hydroides elegans. The toxicity data, when expressed as labile copper concentration causing abnormal development, were independent of FA concentration and could be modeled as a logistic function, with a 48-h EC(50) of 58.9microgl(-1). However, when the data were expressed as a function of total copper concentration, the toxicity was dependent on FA concentration, with a 48-h EC(50) ranging from 55.6microgl(-1) in the no-FA control to 137.4microgl(-1) in the 20mgl(-1) FA treatment. Thus, FA was protective against copper toxicity to the larvae, and such an effect was caused by the reduction in labile copper due to Cu-FA complexation. Our results demonstrate the potential of ASV as a useful tool for predicting metal toxicity to the larvae in coastal environment where DOM plays an important role in complexing metal ions.

Receptor‐Ligand Docking Simulation for Membrane Proteins

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.

Receptor-ligand Docking Simulation for Membrane Proteins

Protein structure-based molecular design using the computational techniques of protein structure prediction, ligand docking, and virtual screening is an integral part of drug discovery for limiting the application of the structure-based approach to target proteins such as G-protein-coupled receptors (GPCRs). GPCRs play an important role in living organisms and are of major interest to the pharmaceutical industry. However, structural data on ligand-binding forms for GPCRs from experiments to elucidate structural templates for docking simulations are lacking due to the difficulties associated with crystallization and crystallography. Therefore structural prediction of GPCRs in the ligand-bound state using computational methods has been introduced, but the prediction of ligand conformation onto target GPCRs is still constructed manually by human experts. We developed a molecular modeling technique for the prediction of ligand-receptor binding using comparative ligand-binding analysis (CoLBA) that not only considers interaction energy but also the similarity of interaction profiles among ligands. The advantage of CoLBA is that it can facilitate intuitive and flexible screening based on docking results when protein structures with low resolution (or theoretical models) are targeted. We applied CoLBA to ligand-binding prediction in several GPCRs. The predicted ligand-binding models were evaluated in site-directed mutagenesis experiments in collaborative research, and the enrichment rate of activated ligands was compared with random compounds in virtual screening simulations. We propose that CoLBA can be applied in large-scale modeling of ligand-receptor complexes and virtual screening for GPCRs.

Mechanism of Interaction of the Double-Stranded RNA (dsRNA) Binding Domain of Protein Kinase R with Short dsRNA Sequences

The dsRNA-activated protein kinase (PKR) plays a major role in the cellular response to viral infection. PKR contains an N-terminal dsRNA binding domain (dsRBD) and a C-terminal kinase domain. The dsRBD consists of two tandem copies of a conserved double-stranded RNA binding motif, dsRBM1 and dsRBM2. dsRNA binding is believed to activate PKR by inducing dimerization and subsequent autophosphorylation reactions. We have characterized the function of the dsRBD by assessing the binding of dsRBM1 and dsRBD to a series of dsRNA sequences ranging from 15 to 45 bp. For dsRBM1, the binding stoichiometries agree with an overlapping ligand binding model where the motif binds to multiple faces of the dsRNA duplex and overlaps along the helical axis. Similar behavior is observed for a dsRBD containing both dsRBM1 and dsRBM2 for sequences up to 30 bp; however, the binding affinity is enhanced 30-fold. Longer dsRNA sequences exhibit lower-than-expected stoichiometries, indicating a change in binding mode. NMR spectroscopy was used to define the regions of the dsRBD that interact with dsRNA. dsRNA binding induces exchange broadening of cross-peaks in 1H-15N HSQC spectra. For a 20 bp dsRNA, the resonances most affected map to the known dsRNA binding regions of dsRBM1 as well as the N-terminus of dsRBM2. For a longer 40 bp sequence, additional regions of dsRBM2 exhibit enhanced broadening. These data support a model in which dsRBM1 plays the dominant role in binding short dsRNA sequences and dsRBM2 makes additional interactions with the longer sequences capable of activating PKR.

Binding of the Universal Minicircle Sequence Binding Protein at the Kinetoplast DNA Replication Origin

Kinetoplast DNA, the mitochondrial DNA of trypanosomatids, is a remarkable DNA structure that contains, in the species Crithidia fasciculata, 5000 topologically linked duplex DNA minicircles. Their replication initiates at two conserved sequences, a dodecamer, known as the universal minicircle sequence (UMS), and a hexamer, which are located at the replication origins of the minicircle L and H strands, respectively. A UMS-binding protein (UMSBP) binds specifically the 12-mer UMS sequence and a 14-mer sequence that contains the conserved hexamer in their single-stranded DNA conformation. In vivo cross-linking analyses reveal the binding of UMSBP to kinetoplast DNA networks in the cell. Furthermore, UMSBP binds in vitro to native minicircle origin fragments, carrying the UMSBP recognition sequences. UMSBP binding at the replication origin induces conformational changes in the bound DNA through its folding, aggregation and condensation.

Linear Interaction Energy (LIE) Models for Ligand Binding in Implicit Solvent: Theory and Application to the Binding of NNRTIs to HIV-1 Reverse Transcriptase.

Expressions for Linear Interaction Energy (LIE) estimators for the binding of ligands to a protein receptor in implicit solvent are derived based on linear response theory and the cumulant expansion expression for the free energy. Using physical arguments, values of the LIE linear response proportionality coefficients are predicted for the explicit and implicit solvent electrostatic and van der Waals terms. Motivated by the fact that the receptor and solution media may respond differently to the introduction of the ligand, a novel form of the LIE regression equation is proposed to model independently the processes of insertion of the ligand in the receptor and in solution. We apply these models to the problem of estimating the binding free energy of two non-nucleoside classes of inhibitors of HIV-1 RT (HEPT and TIBO analogues). We develop novel regression models with greater predictive ability than more standard LIE formulations. The values of the regression coefficients generally conform to linear response predictions, and we use this fact to develop a LIE regression equation with only one adjustable parameter (excluding the intercept parameter) which is superior to the other models we tested and to previous results in terms of predictive accuracy for the HEPT and TIBO compounds individually. The new models indicate that, due to the different effects of induced steric strain of the receptor, an increase of ligand size alone opposes binding for ligands of the HEPT class, whereas it favors binding for ligands of the TIBO class.

Unactivated PKR Exists in an Open Conformation Capable of Binding Nucleotides

The dsRNA-activated protein kinase, PKR, plays a pivotal role in the cellular antiviral response. PKR contains an N-terminal dsRNA binding domain (dsRBD) and a C-terminal kinase domain. An autoinhibition model has been proposed in which latent PKR exists in a closed conformation where the substrate binding cleft of the kinase is blocked by the dsRBD. Binding to dsRNA activates the enzyme by inducing an open conformation and enhancing dimerization. We have tested this model by characterizing the affinity and kinetics of binding of a nucleotide substrate to PKR. The fluorescent nucleotide mant-AMPPNP binds to unactivated PKR with a Kd of approximately 30 microM, and the affinity is not strongly affected by autophosphorylation or binding to dsRNA. We observe biphasic binding kinetics in which the fast phase depends on ligand concentration but the slow phase is ligand-independent. The kinetic data fit to a two-step model of ligand binding followed by a slow conformation change. The kinetics are also not strongly affected by phosphorylation state or dsRNA binding. Thus, the equilibrium and kinetic data indicate that the substrate accessibility of the kinase is not modulated by PKR activation state as predicted by the autoinhibition model. In atomic force microscopy images, monomers of the latent protein are resolved with three separate regions linked by flexible, bridgelike structures. The resolution of the individual domains in the images supports a model in which unactivated PKR exists in an open conformation where the kinase domain is accessible and capable of binding substrate.

Interaction of arylpiperazine ligands with the hydrophobic part of the 5-HT 1A receptor binding site

A flexible docking of a series of arylpiperazine derivatives with structurally different aryl part to the binding site of a model of human 5-HT 1A receptor was exercised. The influence of structure and hydrophobic properties of aryl moiety on binding affinities was discussed and a model for ligand binding in the hydrophobic part of the binding site was proposed.