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.

Analysis of breast cancer progression using principal component analysis and clustering.

We develop a new technique to analyse microarray data which uses a combination of principal components analysis and consensus ensemble k-clustering to find robust clusters and gene markers in the data. We apply our method to a public microarray breast cancer dataset which has expression levels of genes in normal samples as well as in three pathological stages of disease; namely, atypical ductal hyperplasia or ADH, ductal carcinoma in situ or DCIS and invasive ductal carcinoma or IDC. Our method averages over clustering techniques and data perturbation to find stable, robust clusters and gene markers. We identify the clusters and their pathways with distinct subtypes of breast cancer (Luminal,Basal and Her2+). We confirm that the cancer phenotype develops early (in early hyperplasia or ADH stage) and find from our analysis that each subtype progresses from ADH to DCIS to IDC along its own specific pathway, as if each was a distinct disease.

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.

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.

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.

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.

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.

Empirical free energy calculation: comparison to calorimetric data.

An effective free energy potential, developed originally for binding free energy calculation, is compared to calorimetric data on protein unfolding, described by a linear combination of changes in polar and nonpolar surface areas. The potential consists of a molecular mechanics energy term calculated for a reference medium (vapor or nonpolar liquid), and empirical terms representing solvation and entropic effects. It is shown that, under suitable conditions, the free energy function agrees well with the calorimetric expression. An additional result of the comparison is an independent estimate of the side-chain entropy loss, which is shown to agree with a structure-based entropy scale. These findings confirm that simple functions can be used to estimate the free energy change in complex systems, and that a binding free energy evaluation model can describe the thermodynamics of protein unfolding correctly. Furthermore, it is shown that folding and binding leave the sum of solute-solute and solute-solvent van der Waals interactions nearly invariant and, due to this invariance, it may be advantageous to use a nonpolar liquid rather than vacuum as the reference medium.

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.

Consistency in structural energetics of protein folding and peptide recognition.

We report a new free energy decomposition that includes structure-derived atomic contact energies for the desolvation component, and show that it applies equally well to the analysis of single-domain protein folding and to the binding of flexible peptides to proteins. Specifically, we selected the 17 single-domain proteins for which the three-dimensional structures and thermodynamic unfolding free energies are available. By calculating all terms except the backbone conformational entropy change and comparing the result to the experimentally measured free energy, we estimated that the mean entropy gain by the backbone chain upon unfolding (delta Sbb) is 5.3 cal/K per mole of residue, and that the average backbone entropy for glycine is 6.7 cal/K. Both numbers are in close agreement with recent estimates made by entirely different methods, suggesting a promising degree of consistency between data obtained from disparate sources. In addition, a quantitative analysis of the folding free energy indicates that the unfavorable backbone entropy for each of the proteins is balanced predominantly by favorable backbone interactions. Finally, because the binding of flexible peptides to receptors is physically similar to folding, the free energy function should, in principle, be equally applicable to flexible docking. By combining atomic contact energies, electrostatics, and sequence-dependent backbone entropy, we calculated a priori the free energy changes associated with the binding of four different peptides to HLA-A2, 1 MHC molecule and found agreement with experiment to within 10% without parameter adjustment.

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.

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.