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C DeLisi

Publications and source records attributed to C DeLisi.

At least 19 recordsLinked to original sources
PubMed1999

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.

Algorithms↗
PubMed1999

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.

Animals↗
PubMed1998

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.

Databases, Factual↗
PubMed1998

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.

Animals↗
PubMed1998

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.

Alleles↗
PubMed1998

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.

Animals↗
PubMed1997

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.

Artificial Intelligence↗
PubMed1997

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.

1-Octanol↗
PubMed1996

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.

Amino Acid Sequence↗
PubMed1996

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.

Algorithms↗
PubMed1996

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.

Algorithms↗
PubMed1996

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.

Histocompatibility Antigens Class I↗
PubMed1996

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.

Alleles↗
PubMed1996

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.

Amino Acid Sequence↗
PubMed1995

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.

Antigens↗
PubMed1995

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.

Algorithms↗
PubMed1995

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.

Amino Acids↗