NF-κB Activation in Breast Cancer Occurs Via Different Mechanisms in Triple Negative and HER2+ Tumors with Lymphocytic Infiltrate

NF-κB transcription factors regulate expression of genes involved in immune response, inflammation, apoptosis and cancer. NF-κB is known to be regulated via two main mechanisms: (i) through the IκB kinase complex (via the canonical pathway), and (ii) through the IKKα and NIK kinases (via the alternative pathway). Recently, NF-κB has also been shown to be activated by the IKBKE kinase. In breast cancer the level of NF-κB was found elevated only in triple negative (basal) and in HER2+ tumors. Inhibition of NF-κB has been shown to block cell proliferation and tumor formation, and therefore, genes that activate NF-κB might be potential drug targets in the treatment of cancer. Our study aims to identify the mechanisms of activation of NF-κB in various breast cancer subtypes.We analyzed several breast cancer gene expression microarray datasets from public repositories (GSE 2034, 4922, 7390) and used our molecular classification of breast cancer proposed in (Can Res 2007 67: 10669-76) to identify the subtypes of breast cancer in which the NF-κB pathway is altered. The NF-κB activity was evaluated based on upstream and downstream events for the canonical and the alternative pathways, and quantified through a consensus of geneset enrichment scores. We found that the NF-κB downstream genes are upregulated only in triple negative (subtype basal BA) and Her2+ tumors having an immune signature provided by the presence of a lymphocytic infiltrate (subtype Her2I).In order to identify the pathways involved in NF-κB activation, we analyzed the expression of the upstream genes in the canonical, alternative, IKBKE and PI3K/AKT pathways. We found that AKT1 -- an AKT isoform that activates IKKα -- is overexpressed in Her2I, while other AKT isoforms, AKT2 and AKT3, are overexpressed in BA. PI3K is overexpressed in BA, but not in Her2I. We also found that PDK1, which phosphorylates and activates AKT, is overexpressed in Her2I but not in BA. TNFα -- an activator of the NF-κB canonical pathway -- was found overexpressed in BA. However, in BA the components of the IKK complex have low expression apart from IKKγ. IKBKE was found upregulated in both BA and Her2I subtypes.In Her2I, the absence of high expression of TRAF2/5, which recruits the IKK complex, and also the low expression of IKKβ, indicates that NF-κB is not activated by the canonical pathway. Combined with the overexpression of the NIK gene in Her2I, this leads to the hypothesis that in Her2I, NF-κB is being activated by IKBKE and the alternative pathway.In BA, the overexpression of TRAF3 -- an inhibitor of the alternative pathway, suggests that the activation of NF-κB may also occur via the canonical pathway.In summary, we hypothesize that the activation of NF-κB in Her2I tumors is initiated by the IKBKE oncogene and the alternative pathway, while the activation of NF-κB in BA tumors is initiated by IKBKE and the canonical pathway. Boehm et al (Cell, 2007) shown that NF-κB can be inhibited by simultaneously targeting AKT and IKBKE. Combined with our findings, this raises the interesting possibility of developing a targeted therapy for the BA and Her2I breast tumors.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1164.

Applications of optical resonance to biological imaging and label-free protein microarrays

We present biological imaging and sensing methods based on optical resonance and interference. In fluorescence microscopy, our nanoscale imaging capability sheds light onto conformational changes of DNA, DNA-protein complexes and polymer coatings on a solid surface. Interference measurements on a layered substrate yield a label-free sensing platform for protein binding in a high-throughput micro-array format.

Data perturbation independent diagnosis and validation of breast cancer subtypes using clustering and patterns

Molecular stratification of disease based on expression levels of sets of genes can help guide therapeutic decisions if such classifications can be shown to be stable against variations in sample source and data perturbation. Classifications inferred from one set of samples in one lab should be able to consistently stratify a different set of samples in another lab. We present a method for assessing such stability and apply it to the breast cancer (BCA) datasets of Sorlie et al. 2003 and Ma et al. 2003. We find that within the now commonly accepted BCA categories identified by Sorlie et al. Luminal A and Basal are robust, but Luminal B and ERBB2+ are not. In particular, 36% of the samples identified as Luminal B and 55% identified as ERBB2+ cannot be assigned an accurate category because the classification is sensitive to data perturbation. We identify a "core cluster" of samples for each category, and from these we determine "patterns" of gene expression that distinguish the core clusters from each other. We find that the best markers for Luminal A and Basal are (ESR1, LIV1, GATA-3) and (CCNE1, LAD1, KRT5), respectively. Pathways enriched in the patterns regulate apoptosis, tissue remodeling and the immune response. We use a different dataset (Ma et al. 2003) to test the accuracy with which samples can be allocated to the four disease subtypes. We find, as expected, that the classification of samples identified as Luminal A and Basal is robust but classification into the other two subtypes is not.

Genes linked by fusion events are generally of the same functional category: a systematic analysis of 30 microbial genomes

Recent work in computational genomics has shown that a functional association between two genes can be derived from the existence of a fusion of the two as one continuous sequence in another genome. For each of 30 completely sequenced microbial genomes, we established all such fusion links among its genes and determined the distribution of links within and among 15 broad functional categories. We found that 72% of all fusion links related genes of the same functional category. A comparison of the distribution of links to simulations on the basis of a random model further confirmed the significance of intracategory fusion links. Where a gene of annotated function is linked to an unclassified gene, the fusion link suggests that the two genes belong to the same functional category. The predictions based on fusion links are shown here for Methanobacterium thermoautotrophicum, and another 661 predictions are available at http://fusion.bu.edu.

Protein folds: molecular systematics in three dimensions

Advances in methods of structure determination have led to the accumulation of large amounts of protein structural data. Some 500 distinct protein folds have now been characterized, representing one-third of all globular folds that exist. The range of known structural types and the relatively large fraction of the protein universe that has already been sampled have greatly facilitated the discovery of some unifying principles governing protein structure and evolutionary relationships. These include a highly skewed distribution of topological arrangements of secondary-structure elements that favors a few very common connectivities and a highly skewed distribution in the capacity of folds to accommodate unrelated sequences. These and other observations suggest that the number of folds is far fewer than the number of genes, and that the fold universe is dominated by a small number of giant attractors that accommodate large numbers of unrelated sequences. Thus all basic protein folds will likely be determined in the near future, laying the foundation for a comprehensive understanding of the biochemical and cellular functions of whole organisms.

Predictions of gene family distributions in microbial genomes: evolution by gene duplication and modification

A universal property of microbial genomes is the considerable fraction of genes that are homologous to other genes within the same genome. The process by which these homologues are generated is not well understood, but sequence analysis of 20 microbial genomes unveils a recurrent distribution of gene family sizes. We show that a simple evolutionary model based on random gene duplication and point mutations fully accounts for these distributions and permits predictions for the number of gene families in genomes not yet complete. Our findings are consistent with the notion that a genome evolves from a set of precursor genes to a mature size by gene duplications and increasing modifications.

Kinetics of desolvation-mediated protein-protein binding

The role of desolvation in protein binding kinetics is investigated using Brownian dynamics simulations in complexes in which the electrostatic interactions are relatively weak. We find that partial desolvation, modeled by a short-range atomic contact potential, is not only a major contributor to the binding free energy but also substantially increases the diffusion-limited rate for complexes in which long-range electrostatics is weak. This rate enhancement is mostly due to weakly specific pathways leading to a low free-energy attractor, i.e., a precursor state before docking. For alpha-chymotrypsin and human leukocyte elastase, both interacting with turkey ovomucoid third domain, we find that the forward rate constant associated with a collision within a solid angle phi around their corresponding attractor approaches 10(7) and 10(6) M(-1)s(-1), respectively, in the limit phi approximately 2 degrees. Because these estimates agree well with experiments, we conclude that the final bound conformation must be preceded by a small set of well-defined diffusion-accessible precursor states. The inclusion of the otherwise repulsive desolvation interaction also explains the lack of aggregation in proteins by restricting nonspecific association times to approximately 4 ns. Under the same reaction conditions but without short range forces, the association rate would be only approximately 10(3) M(-1)s(-1). Although desolvation increases these rates by three orders of magnitude, desolvation-mediated association is still at least 100-fold slower than the electrostatically assisted binding in complexes such as barnase and barstar.

Free energy landscapes of encounter complexes in protein-protein association

We report the computer generation of a high-density map of the thermodynamic properties of the diffusion-accessible encounter conformations of four receptor-ligand protein pairs, and use it to study the electrostatic and desolvation components of the free energy of association. Encounter complex conformations are generated by sampling the translational/rotational space of the ligand around the receptor, both at 5-A and zero surface-to-surface separations. We find that partial desolvation is always an important effect, and it becomes dominant for complexes in which one of the reactants is neutral or weakly charged. The interaction provides a slowly varying attractive force over a small but significant region of the molecular surface. In complexes with no strong charge complementarity this region surrounds the binding site, and the orientation of the ligand in the encounter conformation with the lowest desolvation free energy is similar to the one observed in the fully formed complex. Complexes with strong opposite charges exhibit two types of behavior. In the first group, represented by barnase/barstar, electrostatics exerts strong orientational steering toward the binding site, and desolvation provides some added adhesion within the local region of low electrostatic energy. In the second group, represented by the complex of kallikrein and pancreatic trypsin inhibitor, the overall stability results from the rather nonspecific electrostatic attraction, whereas the affinity toward the binding region is determined by desolvation interactions.

Protein-protein recognition: exploring the energy funnels near the binding sites

We present a rapidly executable minimal binding energy model for molecular docking and use it to explore the energy landscape in the vicinity of the binding sites of four different enzyme inhibitor complexes. The structures of the complexes are calculated starting with the crystal structures of the free monomers, using DOCK 4.0 to generate a large number of potential configurations, and screening with the binding energy target function. In order to investigate possible correlations between energy and variation from the native structure, we introduce a new measure of similarity, which removes many of the difficulties associated with root mean square deviation. The analysis uncovers energy gradients, or funnels, near the binding site, with decreasing energy as the degree of similarity between the native and docked structures increases. Such energy funnels can increase the number of random collisions that may evolve into productive stable complex, and indicate that short-range interactions in the precomplexes can contribute to the association rate. The finding could provide an explanation for the relatively rapid association rates that are observed even in the absence of long-range electrostatic steering.

Estimating the number of protein folds

A number of fundamental questions in structural biology concern the diversity of protein architectures (or folds). Here, we address two of them, the size of the universe of folds, and the distribution of sequence families among them, using an analysis based on a new and rigorous statistical sampling method. In particular we show that the number of known non-transmembrane protein folds is approximately one half of the total that exist, and that certain superfolds should exist, which accommodate dozens of non-homologous sequence families.

Computational determination of the structure of rat Fc bound to the neonatal Fc receptor

The available crystal structure for the complex between the Fc fragment of immunoglobulin G (IgG) and the neonatal Fc receptor (FcRn) was determined at low resolution and has no electron density for a large portion of the CH2 domain of the Fc. Here, we use a well validated computational docking algorithm in conjunction with known crystallographic data to predict the orientation of CH2 when bound to FcRn, and validate the predicted structure with data from site-specific mutagenesis experiments. The predicted Fc structure indicates that the CH2 domain moves upon binding FcRn , such that the end-to-end distance of the bound Fc fragment is greater than it is in the crystal structure of isolated Fc. The calculated orientation of the bound CH2 domain is displaced by an average of 6 A from the CH2 orientation in the structure of Fc alone, and shows improved charge complementarity with FcRn. The predicted effects of 11 specific mutations in Fc and FcRn are calculated and the results are compared with experimental measurements. The predicted structure is consistent with all reported mutagenesis data, some of which are explicable only on the basis of our model. The current study predicts that FcRn-bound Fc is asymmetric due to reorientation of the CH2 domain upon FcRn binding, a rearrangement that would be likely to interfere with optimal binding of FcRn at the second binding site of the Fc homodimer.

Structural principles that govern the peptide-binding motifs of class I MHC molecules

The peptides that bind class I MHC molecules are restricted in length and often contain key amino acids, anchor residues, at particular positions. The side-chains of peptide anchor residues interact with the polymorphic complementary pockets in MHC peptide-binding grooves and provide the molecular basis for allele-specific recognition of antigenic peptides. We establish correlations between class I MHC specificities for anchor residues and class I MHC sequence markers that occur at the polymorphic positions lining the structural pockets. By analyzing the pocket structures of nine crystallized class I MHC molecules and the modeled structures of another 39 class I MHC molecules, we show that class I pockets can be classified into families that are distinguishable by their common physico-chemical properties and peptide side-chain selectivities. The identification of recurrent structural principles among class I pockets makes it possible to greatly expand the repertoire of known peptide-binding motifs of class I MHC molecules. The evolutionary strategies underlying the emergence of pocket families is briefly discussed.

Toward a predictive understanding of molecular recognition

T cells circulate in blood and the lymphatic system, continually engaging cells through transient non-specific adhesion. In a normally functioning immune system, these interactions permit sufficient time for T-cell receptors (TCRs) to sample major histocompatibility complex (MHC)-peptide complexes for the presence of foreign antigen, with detection of the latter to some extent being triggered by a longer dwell time of the receptor on the complex. Precisely how this incremental stability, which may be relatively small, leads to activation is unclear, but it appears to be related to diffusion-mediated formation of ternary complex dimers. The formation of stable dimers can explain the high sensitivity of the response, but leaves a number of questions unaddressed, including the following: i) How can high sensitivity be reconciled with high specificity, and how can a short TCR dwell time be reconciled with a comparably short time for ternary complex pair formation? ii) What is the nature of the early signals on the plasma membrane that determine alternative responses e.g. proliferation at one extreme and apoptosis at the other? iii) What are the cell-surface correlates of biphasic dose response functions i.e. of responses that peak as a function of dose and then descend? This paper has two loosely coupled goals. One is to review and assess the mathematical and computational methods available for analyzing reactions with and between mobile membrane-bound receptors. These methods range from phenomenological to mechanistic, the latter being based on the details of atomic structure. The other is to apply these methods to address biological questions, such as those raised above, part of whose answer may lie in the kinetic competition between alternative reaction paths.

The organization of human leucocyte antigen class I epitopes in HIV genome products: implications for HIV evolution and vaccine design

Knowledge of human leucocyte antigen (HLA) peptide binding motifs permits rapid selection of candidate viral protein fragments for induction of T cell-mediated immunity. A search for HLA class I peptide binding motifs in structural proteins of human immunodeficiency virus (HIV) of different genetic lineages provides a map of the genetic organization of potential T cell antigenic sites, and at the same time identifies all motifs in highly conserved regions of HIV-1 env, gag and pol. The density of motifs is anomalous at both the high and low end of the spectrum: local organization is characterized by clustering in relatively short regions, while large scale organization is characterized by anomalously long runs between motifs. The former is expected simply due to the fact that motifs often have overlapping anchor residue sets. A detailed statistical analysis of the latter, however, shows that the length of the runs cannot be accounted for by chance alone. Although motif clusters show no preference to be in either conserved or variable regions, low motif density stretches occur preferentially in variable portions of the protein sequence, which suggests that the virus may be mutating to evade the cellular arm of the immune system.

Two complementary methods for predicting peptides binding major histocompatibility complex molecules

Peptides that bind to major histocompatibility complex products (MHC) are known to exhibit certain sequence motifs which, though common, are neither necessary nor sufficient for binding: MHCs bind certain peptides that do not have the characteristic motifs and only about 30% of the peptides having the required motif, bind. In order to develop and test more accurate methods we measured the binding affinity of 463 nonamer peptides to HLA-A2.1. We describe two methods for predicting whether a given peptide will bind to an MHC and apply them to these peptides. One method is based on simulating a neural network and another, called the polynomial method, is based on statistical parameter estimation assuming independent binding of the side-chains of residues. We compare these methods with each other and with standard motif-based methods. The two methods are complementary, and both are superior to sequence motifs. The neural net is superior to simple motif searches in eliminating false positives. Its behavior can be coarsely tuned to the strength of binding desired and it is extendable in a straightforward fashion to other alleles. The polynomial method, on the other hand, has high sensitivity and is a superior method for eliminating false negatives. We discuss the validity of the independent binding assumption in such predictions.

Determination of atomic desolvation energies from the structures of crystallized proteins

We estimated effective atomic contact energies (ACE), the desolvation free energies required to transfer atoms from water to a protein's interior, using an adaptation of a method introduced by S. Miyazawa and R. L. Jernigan. The energies were obtained for 18 different atom types, which were resolved on the basis of the way their properties cluster in the 20 common amino acids. In addition to providing information on atoms at the highest resolution compatible with the amount and quality of data currently available, the method itself has several new features, including its reference state, the random crystal structure, which removes compositional bias, and a scaling factor that makes contact energies quantitatively comparable with experimentally measured energies. The high level of resolution, the explicit accounting of the local properties of protein interiors during determination of the energies, and the very high computational efficiency with which they can be assigned during any computation, should make the results presented here widely applicable. First we used ACE to calculate the free energies of transferring side-chains from protein interior into water. A comparison of the results thus obtained with the measured free energies of transferring side-chains from n-octanol to water, indicates that the magnitude of protein to water transfer free energies for hydrophobic side-chains is larger than that of n-octanol to water transfer free energies. The difference is consistent with observations made by D. Shortle and co-workers, who measured differential free energies of protein unfolding for site-specific mutants in which Ala or Gly was substituted for various hydrophobic side-chains. A direct comparison (calculated versus observed free energy differences) with those experiments finds slopes of 1.15 and 1.13 for Gly and Ala substitutions, respectively. Finally we compared calculated and observed binding free energies of nine protease-inhibitor complexes. This requires a full free energy function, which is created by adding direct electrostatic interactions and an appropriate entropic component to the solvation free energy term. The calculated free energies are typically within 10% of the observed values. Taken collectively, these results suggest that ACE should provide a reasonably accurate and rapidly evaluatable solvation component of free energy, and should thus make accessible a range of docking, design and protein folding calculations that would otherwise be difficult to perform.

Computational determination of side chain specificity for pockets in class I MHC molecules

We show that a rapidly executable computational procedure provides the basis for a predictive understanding of antigenic peptide side chain specificity, for binding to class I major histocompatibility complex (MHC) molecules. The procedure consists of a combined search to identify the joint conformations of peptide side chains and side chains comprising the MHC pocket, followed by conformational selection, using a target function, based on solvation energies and modified electrostatic energies. The method was applied to the B pocket region of five MHC molecules, which were chosen to encompass the full range of specificities displayed by anchors at peptide position 2. These were a medium hydrophobic residue (Leu or Met) for HLA-A*0201, a basic residue (Arg or Lys) for HLA-B*2705; a small hydrophobic residue (Val) for HLA-A*6801, an acidic residue (Glu) for HLA-B*4001 and a bulky residue (Tyr) for H-2K(d). The observed anchors are correctly predicted in each case. The agreement for HLA-B40 and H-2K(d) is especially promising, since their structures have not yet been determined experimentally. Because the experimental determination of motifs by elution is difficult and these calculations take only hours on a high speed workstation, the results open the possibility of routine determination of motifs computationally.

HLA allele selection for designing peptide vaccines

A central problem in developing vaccines against rapidly evolving viruses such as HIV and Influenza is the mutability of their antigens. In principle, the problem can be mitigated by using peptides from conserved portions of viral proteins. However, because cytotoxic T lymphocytes (CTLs), which such vaccines would stimulate, recognize pathogenic peptides only in association with class I products of the Major Histocompatibility Complex (MHC), and because human leukocyte antigen genes (HLA; the human MHC) are highly polymorphic, a peptide vaccine would have to bind a number of different HLA products. A natural question then, which is pertinent to the safety of the vaccine is, which HLA molecules should be targeted to achieve a prespecified coverage (say 90%) of a population. Taking account of disequilibrium between linked HLA loci, we identify 3-6 class I HLA alleles, depending on ethnic group, which cover about 90% of the population. While this leaves large numbers of individuals uncovered, a high level of herd immunity, and hence eradication of the virus, can be achieved through such a vaccine.

TcR recognition of the MHC-peptide dimer: structural properties of a ternary complex

We have developed a method that utilizes site-specific mutation data, sequence analysis, immunological data and free-energy minimization, to determine structural features of the ternary complex formed by the T-cell receptor (TcR) and the class I major histocompatibility complex (MHC) molecule bound by peptide. The analysis focuses on the mouse Kd MHC system, for which a large set of clones with sequenced T-cell receptors is available for specific peptides. The general philosophy is to reduce the uncertainties and computation time in a free-energy minimization procedure by identifying and imposing experimental constraints. In addition to assessing compatibility with various kinds of immunological data, we are particularly interested in differentiating the structural features peculiar to this particular system from generic features, and in ascertaining the robustness of the structure; i.e. determining, in so far as possible, the variations in the structure that leave its compatibility with experiment unaltered from those that do not. This last is equivalent to recognizing that certain features of the model are presented with a reasonable degree of confidence, while others remain highly tentative. The central conclusion in the former category is a placement of the TcR on the Kd peptide complex, which has its beta 2, beta 3 and alpha 3 loops (i.e. the second and third complementarity-determining region of the TcR beta chain, and the third complementarity-determining region of the alpha chain) covering the peptide; the alpha 1 and alpha 2 loops covering the MHC alpha 1 helix; the alpha 2 loop interacting with residues on the MHC beta sheet; and the beta 1 and (part of) the beta 2 loops covering the alpha 2 MHC helix. More specifically, our findings include the following. (1) A highly conserved histidine residue in the first complementarity-determining region of the TcR beta chain (beta:CDR1) points outward and interacts with highly conserved side-chains on the MHC alpha 2 helix. (2) The amino-terminal portion of the beta 2 loop interacts with the carboxyl portion of the peptide. A particularly important interaction is K4 of the loop interacting with E8 of the peptide. (3) Charged side-chains of the 11-residue TcR alpha 2 loop interact with conserved charged side-chains at positions 44, 58, 61 and 68 on the MHC. (4) The TcR beta 3 loop interacts with the amino-terminal part of the peptide, up through position 4. (5) the TcR alpha 3 loop interacts with the central portion of the peptide and stacks against the beta 2 loop. (6) Because of the interaction between the beta 2 loop and the peptide, and stacking of beta 2 on alpha 3, alpha 3 gene and V beta gene selection can be correlated. (7) Using the topology of the recently solved TcR alpha chain we predict that the alpha 2 loop interacts with the loop on the MHC beta sheet floor, which encompasses residues 42 to 44.

Free energy mapping of class I MHC molecules and structural determination of bound peptides

Free energy maps of the binding site are constructed for class I major histocompatibility complex (MHC) proteins, by rotating and translating amino acid probes along the cleft, and performing a side-chain conformational search at each position. The free energy maps are used to determine favorable residue positions that are then combined to form docked peptide conformations. Because the generic backbone structural motif of peptides bound to class I MHC is known, the mapping is restricted to appropriate regions of the site, but allows for the sometimes substantial variations in backbone and side-chain conformations. In a test demonstrating the quality of predictions for a known MHC site using only a rotational and conformational search, we started from the crystal structure of the HIV-1 gp120/HLA-A2 complex, and predicted the HLA-A2 bound structures of peptides from the influenza matrix protein, the HIV-1 reverse transcriptase, and the human T cell leukemia virus. The calculated peptides are at 1.6, 1.3, and 1.4 A all-atom RMSDs from their respective crystal structures (Madden DR, Garboczi DN, Wiley DC, 1993). A further test, which also included a local translational search, predicted structures across MHCs. In particular, we obtained the Kb/SEV-9 complex (Fremont DH et al., 1992, Science 257:919-927) starting with the complex between HLA-B27 and a generic peptide (Madden DR, Gorga JC, Strominger JL, Wiley DC, 1991, Nature (Lond) 353:321-325), with an all-atom RMSD of 1.2 A, indicating that the docking procedure is essentially as effective for predictions across MHCs as it is for determinations within the same MHC, although at substantially greater computational cost. The requirements for further improvement in accuracy are identified and discussed briefly.

RNA loop structure prediction via bond scaling and relaxation

We have developed a method for predicting the structure of small RNA loops that can be used to augment already existing RNA modeling techniques. The method requires no input constraints on loop configuration other than end-to-end distance. Initial loop structures are generated by randomizing the torsion angles, beginning at one end of the polynucleotide chain and correlating each successive angle with the previous. The bond lengths of these structures are then scaled to fit within the known end constraints and the equilibrium bond lengths of the potential energy function are scaled accordingly. Through a series of rescaling and minimization steps the structures are allowed to relax to lower energy configurations with standard bond lengths and reduced van der Waals clashes. This algorithm has been tested on the variable loops of yeast tRNA-Asp and yeast tRNA-Phe, as well as the sarcin-ricin tetraloop and the anticodon loop of yeast tRNA-Phe. The results indicate good correlation between potential energy and the loop structure predictions that are closest to the variable loop crystal structures, but poorer correlation for the more isolated stem loops. The number of stacking interactions has proven to be a good objective measure of the best loop predictions. Selecting on the basis of energy and stacking, we obtain two structures with 0.65 and 0.75 A all-atom rms deviations (RMSD) from the crystal structure for the tRNA-Asp variable loop. The best structure prediction for the tRNA-Phe variable loop has an all-atom RMSD of 2.2 A and a backbone RMSD of 1.6 A, with a single base responsible for most of the deviation. For the sarcin-ricin loop from 28S ribosomal RNA, the predicted structure's all-atom RMSD from the nmr structure is 1.0 A. We obtain a 1.8 A RMSD structure for the tRNA-Phe anticodon loop.

Empirical free energy as a target function in docking and design: application to HIV-1 protease inhibitors

Structure-based drug design requires the development of efficient computer programs for exploring the structural compatibility of various flexible ligands with a given receptor. While various algorithms are available for finding docked conformations, selecting a target function that can reliably score the conformations remains a serious problem. We show that the use of an empirical free energy evaluation method, originally developed to characterize protein-protein interactions, can substantially improve the efficacy of search algorithms. In addition to the molecular mechanics interaction energy, the function takes account of solvation and side chain conformational entropy, while remaining simple enough to replace the incomplete target functions used in many drug docking and design procedures. The free energy function is used here in conjunction with a simple site mapping-fragment assembly algorithm, for docking the MVT-101 non-peptide inhibitor to HIV-1 protease. In particular, we predict the bound structure with an all atom RMSD of 1.21 A, compared to 1.69 A using an energy target function, and also accurately predict the free energy shifts obtained with a series of five trimeric hydroxyethylene isostere analogs.

Extracting hydrophobicity parameters from solute partition and protein mutation/unfolding experiments

Hydrophobicity values for amino acids obtained from protein unfolding experiments are about twice as large as those obtained from data on the partitioning of amino acids between water and octanol. Quantitative analyses of several data sets, presented here, indicate that the difference is best explained by the most direct hypothesis, i.e. that the environment of hydrophobic groups in the interior of a protein is poorly modeled by octanol. Instead, we propose--and provide supporting evidence--that hydrocarbons are a more suitable model. First, we reanalyze data from both solute partitioning and protein unfolding experiments, taking account of the effects that were omitted previously, by introducing a volume dependence in the former and a full free energy analysis in the latter. Both changes in evaluation methodology decrease the discrepancy, but the differences remain substantial. The hydrophobicity parameter obtained from side-chain transfers between octanol and water increases from 16.7 to 22 cal/mol/Angstrom2, while that obtained from protein unfolding decreases from 34.9 to 31.2 cal/mol/Angstrom2. On the other hand, our analysis of the solubilities of pure hydrocarbons in water provides a hydrophobicity parameter of 30.8 cal/mol/Angstrom2. This apparent hydrocarbon-like environment of a protein's interior is also suggested more directly by an analysis of the contact environment of hydrophobic side chains in mutation/unfolding experiments, which have polar contact areas that are <2% of the total.

Periodic variation in side-chain polarities of T-cell antigenic peptides correlates with their structure and activity

We present an analysis that synthesizes information on the sequence, structure, and motifs of antigenic peptides, which previously appeared to be in conflict. Fourier analysis of T-cell antigenic peptides indicates a periodic variation in amino acid polarities of 3-3.6 residues per period, suggesting an amphipathic alpha-helical structure. However, the diffraction patterns of major histocompatibility complex (MHC) molecules indicate that their ligands are in an extended non-alpha-helical conformation. We present two mutually consistent structural explanations for the source of the alpha-helical periodicity, based on an observation that the side chains of MHC-bound peptides generally partition with hydrophobic (hydrophilic) side chains pointing into (out of) the cleft. First, an analysis of haplotype-dependent peptide motifs indicates that the locations of their defining residues tend to force a period 3-4 variation in hydrophobicity along the peptide sequence, in a manner consistent with the spacing of pockets in the MHC. Second, recent crystallographic determination of the structure of a peptide bound to a class II MHC molecule reveals an extended but regularly twisted peptide with a rotation angle of about 130 degrees. We show that similar structures with rotation angles of 100-130 degrees are energetically acceptable and also span the length of the MHC cleft. These results provide a sound physical chemical and structural basis for the existence of a haplotype-independent antigenic motif which can be particularly important in limiting the search time for antigenic peptides.

Flexible docking and design

Docking and design are the major computational steps toward understanding and affecting receptor-ligand interactions. The flexibility of many ligands makes these calculations difficult and requires the development and use of special methods. The need for such tools is illustrated by two examples: the design of protease inhibitors and the analysis and design of peptide antigens binding to specific MHC receptors. We review the computational concepts that have been extended from rigid-body to flexible docking, as well as the following important strategies for flexible docking and design: (a) Monte Carlo/molecular dynamics docking, (b) in-site combinatorial search, (c) ligand build-up, and (d) site mapping and fragment assembly. The use of empirical free energy as a target function is discussed. Due to the rapid development of the methodology, most new methods have been tested on only a limited number of applications and are likely to improve results obtained by more traditional computational or graphic tools.

Flexible docking of peptides to class I major-histocompatibility-complex receptors

We present a new method for docking flexible peptides to class I Major-Histocompatibility-Complex (MHC) receptors. Docking is performed in two steps: (a) The charged terminal peptide residues are located by randomly distributing multiple copies of each in volumes of approximately 150 A at either end of the binding groove, and then minimizing the system energy using a modified multiple-copy search algorithm. This is followed by (b) construction of the intervening chain using the multiple-copy bond-scaling-relaxation loop closure algorithm. In both steps, the copies tend to cluster and the size of the resulting clusters is proportional to the basin of attraction of the corresponding energy well. We show that native MHC-bound peptides have broad minima and, consequently, that misfolded, low-energy peptide conformations can be eliminated by restricting consideration to groups of peptides which cluster into broad minima. The accuracy of the method is assessed by comparing the predictions with crystallographic data for three different MHC peptide systems, at various degrees of stringency: (a) the extent to which we can determine side chain function (anchor vs. T-cell epitopes); (b) the extent to which we can determine the peptide-receptor orientation; and (c) the accuracy with which we can predict atomic coordinates. We find the method correct on (a) for 19 of the 22 non-Gly positions; the failures appearing to be a consequence of omitting solvation. Predictions related to (b) are also very encouraging, with the overall orientation of the predicted peptides being very similar to the crystal conformation, when measured by the hydrogen bonding pattern between the two. The degree of success in predicting atomic coordinates varied considerably, however, from 1.4 A for the HLA-A2 peptide to 2.7 A for the Kb peptide. The inaccuracy of the latter appears to reflect an incomplete target function, most likely the ommission of solvation. The calculations thus define the current limits of accuracy in docking flexible peptides to Class I receptors and identify the methodological improvements that must be made for the next advance in accuracy.

Effect of conformational flexibility and solvation on receptor-ligand binding free energies

A coherent framework is presented for determining the free energy change accompanying ligand binding to protein receptors. The most important new feature of the method is the contribution of the flexibility of the free ligand, and hence its conformational change on binding, to the free energy. Flexibility introduces two additional terms in the free energy difference: the internal energy difference between the ligand in the bound and free states and the backbone entropy loss. The former requires taking explicit account of the difference in solvation of the various forms of the free ligand. The solvation free energy change is estimated using an atomic solvation parameter model [Eisenberg & Mclachlan (1986) Nature 319, 199-203], with an improved parameter set. In order to evaluate the method, we applied it to three data sets for which increasingly general methods are required. The set to which the most restrictive theory can be applied consists of eight crystallized endopeptidase--protein inhibitor complexes which do not change conformation on binding and for which the major contribution to the solvation free energy is entropic. The results are in good agreement with the measured values and somewhat better than those previously reported in the literature. The second data set compares the relative binding free energies of biotin and its analogs for streptavidin. In this case the structures are also rigid, but solvation free energy must include both enthalpic and entropic components. We find that differential free energy predictions are approximately the same as those obtained by free energy perturbation techniques. The final application is an analysis of the measured stabilities of 13 different MHC receptor-peptide complexes. In this case we show that flexibility contributes 30-50% of the free energy change and find a correlation of 0.88 between our predicted free energies and peptide dissociation times.

Monte Carlo study of the effect of beta 2-microglobulin on the binding cleft of the HLA-A2 complex

Peptide recognition by class I products of the major histocompatibility complex requires association of the class I heavy chain with beta 2-microglobulin. We present results of Monte Carlo simulations of the beta-pleated sheet floor of the human class I MHC molecule, HLA-A2, with and without beta 2-microglobulin. We find a significant effect of beta 2-microglobulin on the side chains of residues near a region that would accommodate the C-terminus of a bound peptide. By modeling simultaneously each loop and its neighboring strand at either end of the class I cleft, we find that beta 2-microglobulin restricts the conformational space of residues that are central to binding peptides. The effect is most pronounced for R97 and H114 and somewhat less important for Y99 and Y116, the latter forming strong hydrogen bonds with neighboring residues in the heavy chain itself.

Multiple copy sampling in protein loop modeling: computational efficiency and sensitivity to dihedral angle perturbations

Multiple copy sampling and the bond scaling-relaxation technique are combined to generate 3-dimensional conformations of protein loop segments. The computational efficiency and sensitivity to initial loop copy dispersion are analyzed. The multicopy loop modeling method requires approximately 20-50% of the computational time required by the single-copy method for the various protein segments tested. An analytical formula is proposed to estimate the computational gain prior to carrying out a multicopy simulation. When 7-residue loops within flexible proteins are modeled, each multicopy simulation can sample a set of loop conformations with initial dispersions up to +/- 15 degrees for backbone and +/- 30 degrees for side-chain rotatable dihedral angles. The dispersions are larger for shorter and smaller for longer and/or surface loops. The degree of convergence of loop copies during a simulation can be used to complement commonly used target functions (such as potential energy) for distinguishing between native and misfolded conformations. Furthermore, this convergence also reflects the conformational flexibility of the modeled protein segment. Application to simultaneously building all 6 hypervariable loops of an antibody is discussed.

Computing the structure of bound peptides. Application to antigen recognition by class I major histocompatibility complex receptors

The ability to accurately compute the atomic positions of substrate-bound ligands is central to understanding biological recognition. Although substantial progress has been made in docking small, relatively rigid ligands, the problem of docking flexible peptides remains open. In this communication we present a new method that allows configurational flexibility of peptides, and apply it to predict the conformation of peptides bound to two class-I major histocompatibility complex receptors: human HLA-A2, and murine H-2Kb. Using only the approximate locations of the amino and carboxyl-terminal residues of the bound peptide, our calculations yield structures with backbone conformations that are similar to structures reported crystallographically.

Toward computational determination of peptide-receptor structure

We introduce a method for docking small flexible ligands of the size of dipeptides and phosphocholine and test it against crystallographic complexes. We then show how the method can be used as the basis for a strategy for solving the much more difficult problem of docking fully flexible peptides in the 8-10-residue size range. After developing the method we apply it to peptide-MHC class I systems and find that the predictions are in accord with biological and crystallographic data.

Graphical representations of the class I MHC cleft

We describe computer graphics and computer aided manufacture of three-dimensional models designed specifically to elucidate the cleft in the class I human leukocyte antigen. The models evolve from computer graphical representations and provide a geometrically and chemically concise and detailed view of the antigen binding site. The techniques provide a new approach to representations of binding sites. The model provides sufficient detail to support binding specificities analysis of active sites involved in protein and DNA binding.

Role of conserved regions of class I MHC molecules in the activation of CD8+ cytotoxic T lymphocytes by peptide and purified cell-free class I molecules

To analyze the molecular interactions involved in CD8+ cytotoxic T lymphocyte (CTL) recognition quantitatively, we developed a cell-free antigen presenting system. Genetically engineered soluble H-2Dd molecules coated on plastic microtiter plates could present HIV envelope peptide to an antigen-specific CTL clone, inducing it to produce IFN-gamma in the absence of accessory cells and their accessory or co-stimulatory molecules. The peptide-MHC complexes were functionally stable for over 24 h. The magnitude of T cell activation was dependent on the concentrations of both class I MHC molecule and the peptide, but was more sensitive to the concentration of the MHC molecule than to that of peptide. This result suggests that one MHC molecule can play more than one role in activating the CTL. One such role is the interaction between CD8 and a conserved region of class I MHC, as suggested by the finding that holding the total MHC concentration constant with an irrelevant class I MHC molecule (H-2Kb engineered to have the same alpha 3 domain as H-2Dd) made the T cell response less sensitive to the change in concentration of the relevant MHC molecule (H-2Dd). The irrelevant class I MHC molecule (H-2Kb), unable to present this peptide by itself, augmented the T cell response at lower concentrations of peptide. These results suggest that the conserved alpha 3 domain of the class I MHC heavy chain as well as polymorphic regions play an important role in T cell activation and that T cell interaction with MHC molecules not presenting peptide can still augment the response.

Determining protein loop conformation using scaling-relaxation techniques

We recently developed a rapid loop closure algorithm in which bond lengths are scaled to constrain the ends of a segment to match a known distance and then gradually relaxed to their standard values, with boundary constraints maintained. Although the algorithm predicted the Zif286 zinc-finger loop to within approximately 2 A, it had a serious limitation that made its more general use tentative: it omitted the atomic environment of the loop. Here we report an extension of the algorithm to take into account the protein environment surrounding a given loop from the outset of the conformational search and show that it predicts structure with an efficiency and accuracy that could not be achieved without continuous environmental inclusion. The algorithm should be widely applicable to structure determination when complete experimental information is unavailable.

Necessary conditions for avoiding incorrect polypeptide folds in conformational search by energy minimization

Low energy conformations have been generated for melittin, pancreatic polypeptide, and ribonuclease S-peptide, both in the vicinity of x-ray structures by energy refinement and by an unconstrained search over the entire conformational space. Since the structural polymorphism of these medium-sized peptides in crystal and solution is moderate, comparing the calculated conformation to x-ray and nmr data provides information on local and global behavior of potential functions. Local analysis includes standardization calculations, which show that models with standard geometry can approximate good resolution x-ray data with less than 0.5 A rms deviation (RMSD). However, the atomic coordinates are shifted up to 2 A RMSD by local energy minimization, and thus 2 A is generally the smallest RMSD value one can target in a conformational search using the same energy evaluation models. The unconstrained search was performed by a buildup-type method based on dynamic programming. To accelerate the generation of structures in the conformational search, we used the ECEPP potential, defined in terms of standard polypeptide geometry. A number of low energy conformations were further refined by relaxing the assumption of standard bond lengths and bond angles through the use of the CHARMM potential, and the hydrophobic folding energies of Eisenberg and McLachlan were calculated. Each conformation is described in terms of the RMSD from the native, hydrogen-bonding structure, solvent-accessible surface area, and the ratio of surfaces corresponding to nonpolar and polar residues. The unconstrained search finds conformations that are different from the native, sometimes substantially, and in addition, have lower conformational energies than the native. The origin of deviations is different for each of the three peptides, but in all examples the refined x-ray structures have lower energies than the calculated incorrect folds when (1) the assumption of standard bond lengths and bond angles is relaxed; (2) a small and constant effective dielectric permittivity (epsilon < 10) is used; and (3) the hydrophobic folding energy is incorporated into the potential.

Constrained optimization and protein structure determination

Energy minimization is one of the main approaches to the computational determination of macromolecular structure. Due to the approximations in the empirical free-energy functions and due to the computational difficulties in locating their global minima, the problem is at present intractable when the only information available is the sequence of subunits forming the molecule. A less-demanding problem in terms of both physics and mathematics is constrained optimization, which uses additional but incomplete experimental information such as distances between certain atoms. This paper reviews methods for generating molecular structure using bond lengths and angles as variables and shows how the structure can be fully specified in terms of local geometry. The analysis permits precise statements to be made about the minimum set of distances that specify a unique structure without recourse to energy minimization. We then discuss the complementary situation, i.e., structure prediction with energy minimization based only on sequence information. Finally, we show how distance constraints can be incorporated into energy minimization methods.

Characterization of a helper T cell epitope recognized by mice of a low responder major histocompatibility type

Most known helper T cell (Th) epitopes studied have naturally been immunodominant epitopes recognized by T cells from animals of high responder major histocompatibility complex (MHC) haplotype. We have previously found that most such immunodominant Th epitopes tend to be amphipathic alpha helices, that is, helices with hydrophobic residues on one side and hydrophilic residues on the other, and the corresponding peptide can usually elicit a response to the native protein. However, very few epitopes seen by MHC low responder T cells have been identified. Within the CNBr fragment of residues 1-55 of sperm whale myoglobin (SwMb), a Th epitope is known to exist that stimulates T cells from low responder H-2k mice, but it has not yet been localized to a length of 8-12 residues, the usual length of a Th epitope. To determine whether this low responder epitope would have similar properties, we located it using 10 evenly overlapping 15-residue peptides that span the region. Analysis of this region by the computer program predicted the site covered by two peptides (residues 26-40 and 31-45 which overlap by 10 residues) to be the most likely site for a Th epitope. Of the 10 peptides tested experimentally, only one peptide (residues 26-40) was able to stimulate two low responder Th clones that are specific for the 1-55 region. The peptide was able to prime T cells of low responder B10.BR mice in vivo for in vitro response to the native SwMb as well as to the peptide fragment of residues 1-55. Immunization of low responder mice with SwMb showed that, of the 10 overlapping peptides, the major site of response within the 1-55 region is to the identified peptide. Finally, an extended peptide of residues 24-42 was made to increase the amphipathic score. This extended peptide induced greater proliferation of the clones. Thus, this low responder epitope has properties similar to those of immunodominant epitopes recognized by high responders.

Identifying weak signals in the presence of noise: a new method of locating potential ligand contact residues in immunoglobulin-related molecules

We develop and apply a new method for estimating the locations of hypervariable residues in immunoglobulin-related molecules. The method differs from the standard introduced by Wu and Kabat in two essential ways: (1) we take explicit account of the type of substitution at a given position, rather than just the total number of substitutions, and (2) we use an explicit statistical decision criterion for classifying a site into either the complementarity determining or framework category. Simulations indicate that the method is reliable with relatively little data, approximately 5% of the sites being misclassified when 10 sequences are aligned. The method is applied to immunoglobulin light chains and to class 1 and class 2 products of the major histocompatibility complex.

Identification of T-cell epitopes and use in construction of synthetic vaccines

The T cell is central to the immune system response to foreign antigens, and understanding the mechanism of T cell response to antigen is crucial for vaccine development. Short subpeptides of foreign antigen can prime the T cells to respond to the whole antigen, in some cases as well as or better than immunization with the whole antigen itself. Antigenic sites located first in the murine model are also antigenic in the human, suggesting that the structural features of antigenic sites are species-independent. The amphipathic helix hypothesis has proven useful in developing an algorithm that has successfully located immunodominant sites in important proteins, thus reducing substantially the experimental time and effort required to locate those sites. Other algorithms have also been used successfully, but in all cases there are proven T-cell sites not accounted for by the algorithm. A data base showing T-cell response to collections of peptides uniformly distributed along protein antigens would be very useful in subsequent efforts to characterize the physical and chemical properties of T-cell antigenic sites.

T cell multideterminant regions in the human immunodeficiency virus envelope: toward overcoming the problem of major histocompatibility complex restriction

Helper T cell determinants should be an important component of an anti-human immunodeficiency virus (HIV) vaccine aimed at either antibody or cytotoxic T cell immunity. However, model protein studies have raised concern about the usefulness of any single determinant, because a given determinant is likely to be seen by only a small subset of major histocompatibility complex (MHC) types within the population. Here, we use 44 peptides, including ones predicted and not predicted on the basis of amphipathicity to be potential T cell sites, to locate T cell antigenic determinants recognized by mice of four MHC haplotypes immunized with the whole gp 160 envelope protein. Although the preselection of peptides necessitates caution in a statistical analysis, alpha-amphipathic peptides predominated among sites eliciting the strongest response. Although we have not tested the entire sequence, we have identified six multideterminant regions, in which overlapping peptides are recognized by mice of either three or all four MHC types. Four of the six regions have sequences relatively conserved among HIV-1 isolates. The existence of such multideterminant regions recognized by multiple MHC haplotypes suggests the possibility that use of peptides longer than a minimal determinant and containing several overlapping determinants may be a possible approach to circumvent the serious problem of MHC restriction in peptide vaccines aimed at eliciting T cell immunity.

An immunodominant epitope of the human immunodeficiency virus envelope glycoprotein gp160 recognized by class I major histocompatibility complex molecule-restricted murine cytotoxic T lymphocytes

Because cytotoxic T lymphocytes (CTL) may be important for preventing direct cell-to-cell transmission of human immunodeficiency virus (HIV), the agent responsible for acquired immunodeficiency syndrome, we have begun to investigate the epitope specificity and immune response (Ir) gene control of anti-HIV CTL responses in experimental animals. Mice were infected with a recombinant vaccinia virus expressing the HIV gp160 envelope gene, and the primed lymphocytes were restimulated in vitro with a transfected histocompatible cell line expressing the same gene. Our results show that H-2d mice are CTL high responders and H-2k mice are low responders to the HIV gp160 envelope protein under these conditions. Moreover, the H-2d mice respond predominantly to a single immunodominant site represented by a 15-residue synthetic peptide conforming to the amphipathic alpha-helix model of T-cell epitopes and seen by CD4- CD8+ CTL in association with the Dd class I major histocompatibility complex (MHC) molecules. The facts that CTL responses were detected in the context of only one of four class I MHC molecules tested and that the response was limited predominantly to a single epitope indicate that the CTL repertoire elicited by the HIV envelope protein in association with murine class I MHC molecules may be very limited. In addition, this epitope occurs in a highly variable segment of the envelope protein. This puts constraints on the use of a single peptide sequence from this region in a vaccine, as such a vaccine would have to be polyvalent. Nevertheless, this same variability suggests that this region may be under selective pressure from human CTL, and therefore that this site may be immunodominant in humans as well as mice and so of clinical importance in vaccine development.

Computers in molecular biology: current applications and emerging trends

The rate of generation of molecular sequence data is forcing the use of computers as a central tool in molecular biology. Current use of computers is limited largely to data management and sequence comparisons, but rapid growth in the volume of data is generating pressure for the development of high-speed analytical methods for deciphering the codes connecting nucleotide sequence with protein structure and function.

Some mathematical aspects of mapping DNA cosmids

A number of experimental and mathematical problems must be solved before high resolution physical maps of mammalian chromosomes can be reliably determined. Such a map might consist of an ordered set of nonsequenced, overlapping DNA fragments 20,000-40,000 bases long, produced by digestion of a chromosome, using two restriction enzymes. Map construction requires assigning a signature to each fragment that differentiates it unambiguously from every other fragment, and then devising a computationally efficient algorithm that will provide a unique ordering of the fragments. In the first part of this paper we present a polynomial time algorithm that yields a unique map, and is largely independent of the method for assigning signatures. In the next section we analyze the distribution of lengths of restriction digest fragments and discuss the implications for the algorithm, including the expected number of map gaps. Finally, we discuss a specific method for assigning signatures proposed by Hans Lehrach, based on which of a panel of probes binds to a given fragment. In particular we examine the effects of fragment length heterogeneity on the theoretical optimum length and number of probes, and the extent to which false signatures might be obtained by nonspecific binding. We conclude that the Lehrach strategy is effective provided the number of probes is greater than or equal to 150, but that each fragment will need testing with at most 25 probes.

Protein antigenic structures recognized by T cells: potential applications to vaccine design

In summary, our results using the model protein antigen myoglobin indicated, in concordance with others, that helper T lymphocytes recognize a limited number of immunodominant antigenic sites of any given protein. Such immunodominant sites are the focus of a polyclonal response of a number of different T cells specific for distinct but overlapping epitopes. Therefore, the immunodominance does not depend on the fine specificity of any given clone of T cells, but rather on other factors, either intrinsic or extrinsic to the structure of the antigen. A major extrinsic factor is the MHC of the responding individual, probably due to a requirement for the immunodominant peptides to bind to the MHC of presenting cells in that individual. In looking for intrinsic factors, we noted that both immunodominant sites of myoglobin were amphipathic helices, i.e., helices having hydrophilic and hydrophobic residues on opposite sides. Studies with synthetic peptides indicated that residues on the hydrophilic side were necessary for T-cell recognition. However, unfolding of the native protein was shown to be the apparent goal of processing of antigen, presumably to expose something not already exposed on the native molecule, such as the hydrophobic sides of these helices. We propose that such exposure is necessary to interact with something on the presenting cell, such as MHC or membrane, where we have demonstrated the presence of antigenic peptides by blocking of presentation of biotinylated peptide with avidin. The membrane may serve as a short-term memory of peptides from antigens encountered by the presenting cell, for dynamic sampling by MHC molecules to be available for presentation to T cells. These ideas, together with the knowledge that T-cell recognition required only short peptides and therefore had to be based only on primary or secondary structure, not tertiary folding of the native protein, led us to propose that T-cell immunodominant epitopes may tend to be amphipathic structures. An algorithm to search for potential amphipathic helices from sequence information identified 18 of 23 known immunodominant T-cell epitopes from 12 proteins (p less than 0.001). Another statistical approach confirmed the importance of amphipathicity and also supported the importance of helical structure that had been proposed by others. It suggested that peptides able to form a stable secondary structure, especially a helix, more commonly formed immunodominant epitopes. We used this approach to predict potential immunodominant epitopes for induction of T-cell immunity in proteins of clinical relevance, such as the malarial circumsporozoite protein and the AIDS viral envelope.(ABSTRACT TRUNCATED AT 400 WORDS)

Hydrophobicity scales and computational techniques for detecting amphipathic structures in proteins

Protein segments that form amphipathic alpha-helices in their native state have periodic variation in the hydrophobicity values of the residues along the segment, with a 3.6 residue per cycle period characteristic of the alpha-helix. The assignment of hydrophobicity values to amino acids (hydrophobicity scale) affects the display of periodicity. Thirty-eight published hydrophobicity scales are compared for their ability to identify the characteristic period of alpha-helices, and an optimum scale for this purpose is computed using a new eigenvector method. Two of the published scales are also characterized by eigenvectors. We compare the usual method for detecting periodicity based on the discrete Fourier transform with a method based on a least-squares fit of a harmonic sequence to a sequence of hydrophobicity values. The two become equivalent for very long sequences, but, for shorter sequences with lengths commonly found in alpha-helices, the least-squares procedure gives a more reliable estimate of the period. The analog to the usual Fourier transform power spectrum is the "least-squares power spectrum", the sum of squares accounted for in fitting a sinusoid of given frequency to a sequence of hydrophobicity values. The sum of the spectra of the alpha-helices in our data base peaks at 97.5 degrees, and approximately 50% of the helices can account for this peak. Thus, approximately 50% of the alpha-helices appear to be amphipathic, and, of those that are, the dominant frequency at 97.5 degrees rather than 100 degrees indicates that the helix is slightly more open than previously thought, with the number of residues per turn closer to 3.7 than 3.6. The extra openness is examined in crystallographic data, and is shown to be associated with the C terminus of the helix. The alpha amphipathic index, the key quantity in our analysis, measures the fraction of the total spectral area that is under the 97.5 degrees peak, and is a characteristic of hydrophobicity scales that is consistent for different sets of helices. Our optimized scale maximizes the amphipathic index and has a correlation of 0.85 or higher with nine previously published scales. The most surprising feature of the optimized scale is that arginine tends to behave as if it were hydrophobic; i.e. in the crystallographic data base it has a tendency to be on the hydrophobic face of teh amphipathic helix. Although the scale is optimal only for predicting alpha-amphipathicity, it also ranks high in identifying beta-amphipathicity and in distinguishing interior from exterior residues in a protein.(ABSTRACT TRUNCATED AT 400 WORDS)