Topology Of Binding Sites Research Articles

Mapping the binding site topology of amyloid protein aggregates using multivalent ligands.

A key process in the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases is the aggregation of proteins to produce fibrillary aggregates with a cross β-sheet structure, amyloid. The development of reagents that can bind these aggregates with high affinity and selectivity has potential for early disease diagnosis. By linking two benzothiazole aniline (BTA) head groups with different length polyethylene glycol (PEG) spacers, fluorescent probes that bind amyloid fibrils with low nanomolar affinity have been obtained. Dissociation constants measured for interaction with Aβ, α-synuclein and tau fibrils show that the length of the linker determines binding affinity and selectivity. These compounds were successfully used to image α-synuclein aggregates in vitro and in the post-mortem brain tissue of patients with Parkinson's disease. The results demonstrate that multivalent ligands offer a powerful approach to obtain high affinity, selective reagents to bind the fibrillary aggregates that form in neurodegenerative disease.

Conformationally Unambiguous Spin Label for Exploring the Binding Site Topology of Multivalent Systems.

Multivalent carbohydrate-lectin interactions are a key concept in biological processes mediating, for example, signaling and adhesion. Binding affinities of multivalent ligands often increase by orders of magnitude compared to a monovalent binding situation. Thus, the design of multivalent ligands as potent inhibitors is a highly active field of research, where knowledge about the binding site topology is crucial. Here, we report a general strategy for precise distance measurements between the binding sites of multivalent target proteins using monovalent ligands. We designed and synthesized Monovalent, conformationally Unambiguously Spin-labeled LIgands (MUeSLI). Distances between the binding sites of the multivalent model lectin wheat germ agglutinin in complex with a GlcNAc-derived MUeSLI were determined using pulsed electron paramagnetic resonance spectroscopy. This approach is an efficient method for exploring multivalent systems with monovalent ligands, and it is readily transferable to other target proteins, allowing the targeted design of multivalent ligands without structural information available.

Anandamide Revisited: How Cholesterol and Ceramides Control Receptor-Dependent and Receptor-Independent Signal Transmission Pathways of a Lipid Neurotransmitter.

Anandamide is a lipid neurotransmitter derived from arachidonic acid, a polyunsaturated fatty acid. The chemical differences between anandamide and arachidonic acid result in a slightly enhanced solubility in water and absence of an ionisable group for the neurotransmitter compared with the fatty acid. In this review, we first analyze the conformational flexibility of anandamide in aqueous and membrane phases. We next study the interaction of the neurotransmitter with membrane lipids and discuss the molecular basis of the unexpected selectivity of anandamide for cholesterol and ceramide from among other membrane lipids. We show that cholesterol behaves as a binding partner for anandamide, and that following an initial interaction mediated by the establishment of a hydrogen bond, anandamide is attracted towards the membrane interior, where it forms a molecular complex with cholesterol after a functional conformation adaptation to the apolar membrane milieu. The complex is then directed to the anandamide cannabinoid receptor (CB1) which displays a high affinity binding pocket for anandamide. We propose that cholesterol may regulate the entry and exit of anandamide in and out of CB1 by interacting with low affinity cholesterol recognition sites (CARC and CRAC) located in transmembrane helices. The mirror topology of cholesterol binding sites in the seventh transmembrane domain is consistent with the delivery, extraction and flip-flop of anandamide through a coordinated cholesterol-dependent mechanism. The binding of anandamide to ceramide illustrates another key function of membrane lipids which may occur independently of protein receptors. Interestingly, ceramide forms a tight complex with anandamide which blocks the degradation pathway of both lipids and could be exploited for anti-cancer therapies.

An allosteric binding site of the α7 nicotinic acetylcholine receptor revealed in a humanized acetylcholine-binding protein

Nicotinic acetylcholine receptors (nAChRs) belong to the family of pentameric ligand-gated ion channels and mediate fast excitatory transmission in the central and peripheral nervous systems. Among the different existing receptor subtypes, the homomeric α7 nAChR has attracted considerable attention because of its possible implication in several neurological and psychiatric disorders, including cognitive decline associated with Alzheimer's disease or schizophrenia. Allosteric modulators of ligand-gated ion channels are of particular interest as therapeutic agents, as they modulate receptor activity without affecting normal fluctuations of synaptic neurotransmitter release. Here, we used X-ray crystallography and surface plasmon resonance spectroscopy of α7-acetylcholine–binding protein (AChBP), a humanized chimera of a snail AChBP, which has 71% sequence similarity with the extracellular ligand-binding domain of the human α7 nAChR, to investigate the structural determinants of allosteric modulation. We extended previous observations that an allosteric site located in the vestibule of the receptor offers an attractive target for receptor modulation. We introduced seven additional humanizing mutations in the vestibule-located binding site of AChBP to improve its suitability as a model for studying allosteric binding. Using a fragment-based screening approach, we uncovered an allosteric binding site located near the β8–β9 loop, which critically contributes to coupling ligand binding to channel opening in human α7 nAChR. This work expands our understanding of the topology of allosteric binding sites in AChBP and, by extrapolation, in the human α7 nAChR as determined by electrophysiology measurements. Our insights pave the way for drug design strategies targeting nAChRs involved in ion channel–mediated disorders.

Diverse modes of galacto-specific carbohydrate recognition by a family 31 glycoside hydrolase from Clostridium perfringens.

Clostridium perfringens is a commensal member of the human gut microbiome and an opportunistic pathogen whose genome encodes a suite of putative large, multi-modular carbohydrate-active enzymes that appears to play a role in the interaction of the bacterium with mucin-based carbohydrates. Among the most complex of these is an enzyme that contains a presumed catalytic module belonging to glycoside hydrolase family 31 (GH31). This large enzyme, which based on its possession of a GH31 module is a predicted α-glucosidase, contains a variety of non-catalytic ancillary modules, including three CBM32 modules that to date have not been characterized. NMR-based experiments demonstrated a preference of each module for galacto-configured sugars, including the ability of all three CBM32s to recognize the common mucin monosaccharide GalNAc. X-ray crystal structures of the CpGH31 CBM32s, both in apo form and bound to GalNAc, revealed the finely-tuned molecular strategies employed by these sequentially variable CBM32s in coordinating a common ligand. The data highlight that sequence similarities to previously characterized CBMs alone are insufficient for identifying the molecular mechanism of ligand binding by individual CBMs. Furthermore, the overlapping ligand binding profiles of the three CBMs provide a fail-safe mechanism for the recognition of GalNAc among the dense eukaryotic carbohydrate networks of the colonic mucosa. These findings expand our understanding of ligand targeting by large, multi-modular carbohydrate-active enzymes, and offer unique insights into of the expanding ligand-binding preferences and binding site topologies observed in CBM32s.

Probability Distributions for Stochastic Gene Expression with Multiple Binding Sites

While regulation of intrinsic stochasticity in gene expression is essential for many cellular functions, there is considerable interest in understanding how different molecular mechanisms of gene expression impact variations in protein levels across a population of cells. Stochastic properties of the corresponding gene systems are usually examined by directly finding the probability distributions of mRNA or protein governed by chemical master equations. Here, we analyze four stochastic models of gene expression, each describing a representative topology of binding sites. The total mRNA or protein probability distributions are derived by the weight assignment method that we propose here. These distributions indicate that the total mRNA or protein number obeys a beta distribution or a linear superposition of two beta distributions in spite of differences in the local mRNA or protein numbers distributed in individual binding sites among the models. Our results reveal essential mechanisms of gene expression in terms of the probability distribution rather than finite-order moments, as was done in previous studies.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology.

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r(2) of 0.71 and root-mean-squared-error of 1.25 kcal/mol (N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

In silico molecular docking analysis of the human Argonaute 2 PAZ domain reveals insights into RNA interference

RNA interference (RNAi) is a critical cellular pathway activated by double stranded RNA and regulates the gene expression of target mRNA. During RNAi, the 3' end of siRNA binds with the PAZ domain, followed by release and rebinding in a cyclic manner, which deemed essential for proper gene silencing. Recently, we provided the forces underlying the recognition of small interfering RNA by PAZ in a computational study based on the structure of Drosophila Argonaute 2 (Ago2) PAZ domain. We have now reanalyzed these data within the view of the new available structures from human Argonauts. While the parameters of weak binding are correlated with higher (RNAi) in the Drosophila model, a different profile is predicted with the human Ago2 PAZ domain. On the basis of the human Ago2 PAZ models, the indicators of stronger binding as the total binding energy and the free energy were associated with better RNAi efficacy. This discrepancy might be attributable to differences in the binding site topology and the difference in the conformation of the bound nucleotides.

Characterization of the Ligand Receptor Encounter Complex and Its Potential for in Silico Kinetics-Based Drug Development.

The study of drug-receptor interactions has largely been framed in terms of the equilibrium thermodynamic binding affinity, an in vitro measure of the stability of the drug-receptor complex that is commonly used as a proxy measure of in vivo biological activity. In response to the growing realization of the importance of binding kinetics to in vivo drug activity we present a computational methodology for the kinetic characterization of drug-receptor interactions in terms of the encounter complex. Using trajectory data from multiple Brownian dynamics simulations of ligand diffusion, we derive the spatial density of the ligand around the receptor and show how it can be quantitatively partitioned into different basins of attraction. Numerical integration of the ligand densities within the basins can be used to estimate the residence time of the ligand within these diffusive binding sites. Simulations of two structurally similar inhibitors of Hsp90 exhibit diffusive binding sites with similar spatial structure but with different ligand residence times. In contrast, a pair of structurally dissimilar inhibitors of MDM2, a peptide and a small molecule, exhibit spatially distinct basins of attraction around the receptor, which in turn reveal differences in ligand orientational order. Thus, our kinetic approach provides microscopic details of drug-receptor dynamics that provide novel insight into the observed differences in the thermodynamic binding affinities for the two inhibitors, such as the differences in the entropic contributions to binding. The characterization of the encounter complex, in terms of the structure, topology, and dynamics of diffusive binding sites, offers a new perspective on ligand-receptor interactions and the potential for greater insight into drug action. The method, which requires no prior knowledge of the bound state, is a first step toward the incorporation of ligand kinetics into in silico drug development protocols.

Evolutionarily Conserved TCR Binding Sites, Identification of T Cells in Primary Lymphoid Tissues, and Surprising Trans-Rearrangements in Nurse Shark

Cartilaginous fish are the oldest animals that generate RAG-based Ag receptor diversity. We have analyzed the genes and expressed transcripts of the four TCR chains for the first time in a cartilaginous fish, the nurse shark (Ginglymostoma cirratum). Northern blotting found TCR mRNA expression predominantly in lymphoid and mucosal tissues. Southern blotting suggested translocon-type loci encoding all four chains. Based on diversity of V and J segments, the expressed combinatorial diversity for gamma is similar to that of human, alpha and beta may be slightly lower, and delta diversity is the highest of any organism studied to date. Nurse shark TCRdelta have long CDR3 loops compared with the other three chains, creating binding site topologies comparable to those of mammalian TCR in basic paratope structure; additionally, nurse shark TCRdelta CDR3 are more similar to IgH CDR3 in length and heterogeneity than to other TCR chains. Most interestingly, several cDNAs were isolated that contained IgM or IgW V segments rearranged to other gene segments of TCRdelta and alpha. Finally, in situ hybridization experiments demonstrate a conservation of both alpha/beta and gamma/delta T cell localization in the thymus across 450 million years of vertebrate evolution, with gamma/delta TCR expression especially high in the subcapsular region. Collectively, these data make the first cellular identification of TCR-expressing lymphocytes in a cartilaginous fish.

Architectural Repertoire of Ligand‐Binding Pockets on Protein Surfaces

Knowledge of the three-dimensional structure of ligand binding sites in proteins provides valuable information for computer-assisted drug design. We present a method for the automated extraction and classification of ligand binding site topologies, in which protein surface cavities are represented as branched frameworks. The procedure employs a growing neural gas approach for pocket topology assignment and pocket framework generation. We assessed the structural diversity of 623 known ligand binding site topologies based on framework cluster analysis. At a resolution of 5 A only 23 structurally distinct topology groups were formed; this suggests an overall limited structural diversity of ligand-accommodating protein cavities. Higher resolution allowed for identification of protein-family specific pocket features. Pocket frameworks highlight potentially preferred modes of ligand-receptor interactions and will help facilitate the identification of druggable subpockets suitable for ligand affinity and selectivity optimization.

Study on Binding of Drug to Serum Protein

After being distributed in the circulating blood, drugs bind to serum proteins varying degrees. In general, such binding is reversible, and a dynamic equilibrium exists between the bound and unbound molecular species. It is believed that unless there is a specific transport system (e.g. receptor-mediated endocytosis, protein-mediated transport), only unbound drugs are able to penetrate through biomembranes, are distributed to tissues, and undergo metabolism and glomerular filtration. It is also believed that only unbound molecules present in target tissues can exert their pharmacological effects, and that the concentration of unbound molecules in tissues is in proportion to the drug serum concentration. Therefore, drug-serum protein binding is critically involved in the manifestation of the pharmacological effects of a drug as well as its pharmacokinetics. Among serum proteins, human serum albumin (HSA) and alpha(1)-acid glycoprotein (AGP) play important roles in protein binding for many drugs, which is of key importance to drug distribution in the body. In addition, they are widely used in clinical settings as blood preparations and drug delivery system carriers. It is thus of great importance from the viewpoint of pharmaceutical science to clarify the structure, function, and pharmaceutical properties of HSA and AGP. Accordingly, since starting my laboratory, the focus of my research has involved molecular pharmaceutical studies on the interactions of drugs and HSA and AGP for the purpose of applying these findings to clinical fields, such as drug treatment, diagnosis and drug discovery. In this review, the molecular properties of HSA and AGP will be briefly outlined. The static and dynamic topology of drug binding sites on these proteins, investigated by various spectroscopic techniques, X-ray crystallography, quantitative structure-activity relationships, molecular modeling, photo affinity labeling, site-directed mutagenesis etc., changes in the serum protein binding of drugs in pathological conditions, such as liver and kidney failure and various inflammation diseases and factors contributing to the changes will then be summarized. Finally, cases in which protein binding displacement can be applied to medical fields will also be introduced.

Computational analysis of R and S isoforms of 12-Lipoxygenases: Homology modeling and docking studies

The present study is aimed at predicting human 12R-LOX structure by constructing a homology model. Based upon Blast results, rabbit reticulocyte 15-Lipoxygenase 1LOX (protein data bank) was considered as a template for homology modeling. The 3D model was generated with Modeler in InsightII and further refined using AMBER. Further to understand the relationship of protein structure with stereo specificity, a comparative analysis of 12R-LOX model was done with that of 12S-LOX homology model to identify differences in the binding site topology and interacting residues. The large insertion of 31-aa seen in 12R-LOX is located beyond the N-terminal barrel and is accommodated on the outside of the protein without disruption of the overall tertiary structure. The 31-aa region includes SH3 domain binding PXXP motif, seven prolines and five arginines. The docking of the substrate, arachidonic acid was also performed. Our results show that the Gly441 and substrate orientation within the active site play an important role in stereo specificity of 12R-LOX.

Structure of coronavirus hemagglutinin-esterase offers insight into corona and influenza virus evolution.

The hemagglutinin-esterases (HEs) are a family of viral envelope glycoproteins that mediate reversible attachment to O-acetylated sialic acids by acting both as lectins and as receptor-destroying enzymes (RDEs). Related HEs occur in influenza C, toro-, and coronaviruses, apparently as a result of relatively recent lateral gene transfer events. Here, we report the crystal structure of a coronavirus (CoV) HE in complex with its receptor. We show that CoV HE arose from an influenza C-like HE fusion protein (HEF). In the process, HE was transformed from a trimer into a dimer, whereas remnants of the fusion domain were adapted to establish novel monomer-monomer contacts. Whereas the structural design of the RDE-acetylesterase domain remained unaltered, the HE receptor-binding domain underwent remodeling to such extent that the ligand is now bound in opposite orientation. This is surprising, because the architecture of the HEF site was preserved in influenza A HA over a much larger evolutionary distance, a switch in receptor specificity and extensive antigenic variation notwithstanding. Apparently, HA and HEF are under more stringent selective constraints than HE, limiting their exploration of alternative binding-site topologies. We attribute the plasticity of the CoV HE receptor-binding site to evolutionary flexibility conferred by functional redundancy between HE and its companion spike protein S. Our findings offer unique insights into the structural and functional consequences of independent protein evolution after interviral gene exchange and open potential avenues to broad-spectrum antiviral drug design.

Structural insights into the Plasmodium falciparum histone deacetylase 1 ( PfHDAC-1): A novel target for the development of antimalarial therapy

The histone deacetylase (HDAC) enzyme from Plasmodium falciparum has been identified as a novel target for the development of antimalarial therapy. A ligand-refined homology model of PfHDAC-1 was generated from the crystal structures of human HDAC8 and HDLP using a restraint guided optimization procedure involving the OPLS/GBSA potential setup. The model was extensively validated using protein structure checking tools. A predictive docking study was carried out using a set of known human HDAC inhibitors, which were shown to have in vitro antimalarial activity against the chloroquine sensitive D6 and resistant W2 strains of P. falciparum. Pose validation and score-based active/inactive separation studies provided independent validation of the geometric accuracy and the predictive ability of the generated model. Comparative analysis was carried out with the human HDACs to identify differences in the binding site topology and interacting residues, which might be utilized to develop selective PfHDAC-1 inhibitors.

Identification and Characterization of a Novel Periplasmic Polygalacturonic Acid Binding Protein from Yersinia enterolitica

A number of bacteria in the family Enterobacteriaceae harbor the genes comprising well-developed pectinolytic pathways (e.g. Erwinia sp.) or abridged versions of this pathway (e.g. Yersinia sp.). One of the most enigmatic components present in some of these pathways is a small gene that encodes a predicted secreted protein of ∼160 amino acid residues with unknown function. This protein shows distant amino acid sequence similarity over its entire length to galactose-specific family 32 carbohydrate-binding modules (CBMs). Here we demonstrate the ability of the Yersinia enterocolitica example, here called YeCBM32, to bind polygalacturonic acid containing components of pectin. This binding is selective for highly polymerized galacturonic acid and shows a complex mode of polysaccharide recognition. The high resolution X-ray crystal structure (1.35 Å) shows YeCBM32s overall structural similarity to galactose specific CBMs and conserved binding site location but reveals a substantially different binding site topology, which likely reflects its unique polymeric and acidic ligand. The results suggest the possibility of a unique role for YeCBM32 in polygalacturonic acid transport.

Interaction of daunomycin antibiotic with human α 1-acid glycoprotein: Spectroscopy and modeling

Daunomycin (DM) is a clinically used antitumor anthracycline antibiotic. Understanding the interaction of DM with plasma proteins such as human α 1-acid glycoprotein (AGP) is essential to understanding their pharmacokinetics and pharmacodynamics. The interaction between DM and AGP was investigated using fluorescence quenching technique, circular dichroism (CD) spectroscopy and molecular modeling methods. The binding constants of DM with AGP were determined at different temperatures based on the fluorescence quenching results. In addition, the thermodynamic functions standard enthalpy (Δ H) and standard entropy (Δ S) for the binding reaction were calculated to be −14.23 kJ mol −1 and 37.80 J mol −1 K −1, according to the van't Hoff equation, which indicated that hydrophobic, hydrogen bond, electrostatic interactions are important driving forces for protein-DM association. Furthermore, the spectra data suggested that the association between DM and AGP did not change molecular conformation of AGP and a docking model of DM and AGP around Trp160 provided further details of the binding site topology.

Structural Requirements for Factor Xa Inhibition by 3-Oxybenzamides with Neutral P1 Substituents: Combining X-ray Crystallography, 3D-QSAR, and Tailored Scoring Functions

The design, synthesis, and structure-activity relationship of 3-oxybenzamides as potent inhibitors of the coagulation protease factor Xa are described on the basis of X-ray structures, privileged structure motifs, and SAR information. A total of six X-ray structures of fXa/inhibitor complexes led us to identify the major protein-ligand interactions. The binding mode is characterized by a lipophilic dichlorophenyl substituent interacting with Tyr228 in the protease S1 pocket, while polar parts are accommodated in S4. This alignment in combination with docking allowed derivation of 3D-QSAR models and tailored scoring functions to rationalize biological affinity and provide guidelines for optimization. The resulting models showed good correlation coefficients and predictions of external test sets. Furthermore, they correspond to binding site topologies in terms of steric, electrostatic, and hydrophobic complementarity. Two approaches to derive tailored scoring functions combining binding site and ligand information led to predictive models with acceptable predictions of the external set. Good correlations to experimental affinities were obtained for both AFMoC (adaptation of fields for molecular comparison) and the novel TScore function. The SAR information from 3D-QSAR and tailored scoring functions agrees with all experimental data and provides guidelines and reasonable activity estimations for novel fXa inhibitors.

Use of Photoaffinity Labeling and Site-directed Mutagenesis for Identification of the Key Residue Responsible for Extraordinarily High Affinity Binding of UCN-01 in Human α1-Acid Glycoprotein

7-Hydroxystaurosporine (UCN-01) is a protein kinase inhibitor anticancer drug currently undergoing a phase II clinical trial. The low distribution volumes and systemic clearance of UCN-01 in human patients have been found to be caused in part by its extraordinarily high affinity binding to human alpha1-acid glycoprotein (hAGP). In the present study, we photolabeled hAGP with [3H]UCN-01 without further chemical modification. The photolabeling specificity of [3H]UCN-01 was confirmed by findings in which other hAGP binding ligands inhibited formation of covalent bonds between hAGP and [3H]UCN-01. The amino acid sequence of the photolabeled peptide was concluded to be SDVVYTDXK, corresponding to residues Ser-153 to Lys-161 of hAGP. No PTH derivatives were detected at the 8th cycle, which corresponded to the 160th Trp residue. This strongly implies that Trp-160 was photolabeled by [3H]UCN-01. Three recombinant hAGP mutants (W25A, W122A, and W160A) and wild-type recombinant hAGP were photolabeled by [3H]UCN-01. Only mutant W160A showed a marked decrease in the extent of photoincorporation. These results strongly suggest that Trp-160 plays a prominent role in the high affinity binding of [3H]UCN-01 to hAGP. A docking model of UCN-01 and hAGP around Trp-160 provided further details of the binding site topology.

Structural requirements for inhibition of the neuronal nitric oxide synthase (NOS-I): 3D-QSAR analysis of 4-oxo- and 4-amino-pteridine-based inhibitors.

The family of homodimeric nitric oxide synthases (NOS I-III) catalyzes the generation of the cellular messenger nitric oxide (NO) by oxidation of the substrate L-arginine. The rational design of specific NOS inhibitors is of therapeutic interest in regulating pathological NO levels associated with sepsis, inflammatory, and neurodegenerative diseases. The cofactor (6R)-5,6,7,8-tetrahydrobiopterin (H(4)Bip) maximally activates all NOSs and stabilizes enzyme quaternary structure by promoting and stabilizing dimerization. Here, we describe the synthesis and three-dimensional (3D) quantitative structure-activity relationship (QSAR) analysis of 65 novel 4-amino- and 4-oxo-pteridines (antipterins) as inhibitors targeting the H(4)Bip binding site of the neuronal NOS isoform (NOS-I). The experimental binding modes for two inhibitors complexed with the related endothelial NO synthase (NOS-III) reveal requirements of biological affinity and form the basis for ligand alignment. Different alignment rules were derived by building other compounds accordingly using manual superposition or a genetic algorithm for flexible superposition. Those alignments led to 3D-QSAR models (comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)), which were validated using leave-one-out cross-validation, multiple analyses with two and five randomly chosen cross-validation groups, perturbation of biological activities by randomization or progressive scrambling, and external prediction. An iterative realignment procedure based on rigid field fit was used to improve the consistency of the resulting partial least squares models. This led to consistent and highly predictive 3D-QSAR models with good correlation coefficients for both CoMFA and CoMSIA, which correspond to experimentally determined NOS-II and -III H(4)Bip binding site topologies as well as to the NOS-I homology model binding site in terms of steric, electrostatic, and hydrophobic complementarity. These models provide clear guidelines and accurate activity predictions for novel NOS-I inhibitors.