Toward high‐resolution homology modeling of antibody Fv regions and application to antibody–antigen docking

High‐resolution homology models are useful in structure‐based protein engineering applications, especially when a crystallographic structure is unavailable. Here, we report the development and implementation of RosettaAntibody, a protocol for homology modeling of antibody variable regions. The protocol combines comparative modeling of canonical complementarity determining region (CDR) loop conformations and de novo loop modeling of CDR H3 conformation with simultaneous optimization of V_L‐V_H rigid‐body orientation and CDR backbone and side‐chain conformations. The protocol was tested on a benchmark of 54 antibody crystal structures. The median root mean square deviation (rmsd) of the antigen binding pocket comprised of all the CDR residues was 1.5 Å with 80% of the targets having an rmsd lower than 2.0 Å. The median backbone heavy atom global rmsd of the CDR H3 loop prediction was 1.6, 1.9, 2.4, 3.1, and 6.0 Å for very short (4–6 residues), short (7–9), medium (10–11), long (12–14) and very long (17–22) loops, respectively. When the set of ten top‐scoring antibody homology models are used in local ensemble docking to antigen, a moderate‐to‐high accuracy docking prediction was achieved in seven of fifteen targets. This success in computational docking with high‐resolution homology models is encouraging, but challenges still remain in modeling antibody structures for sequences with long H3 loops. This first large‐scale antibody–antigen docking study using homology models reveals the level of “functional accuracy” of these structural models toward protein engineering applications. Proteins 2009; 74:497–514. © 2008 Wiley‐Liss, Inc.     

Modeling of protein loops by simulated annealing.

A method is presented to model loops of protein to be used in homology modeling of proteins. This method employs the ESAP program of Higo et al. (Higo, J., Collura, V., & Garnier, J., 1992, Biopolymers 32, 33-43) and is based on a fast Monte Carlo simulation and a simulated annealing algorithm. The method is tested on different loops or peptide segments from immunoglobulin, bovine pancreatic trypsin inhibitor, and bovine trypsin. The predicted structure is obtained from the ensemble average of the coordinates of the Monte Carlo simulation at 300 K, which exhibits the lowest internal energy. The starting conformation of the loop prior to modeling is chosen to be completely extended, and a closing harmonic potential is applied to N, CA, C, and O atoms of the terminal residues. A rigid geometry potential of Robson and Platt (1986, J. Mol. Biol. 188, 259-281) with a united atom representation is used. This we demonstrate to yield a loop structure with good hydrogen bonding and torsion angles in the allowed regions of the Ramachandran map. The average accuracy of the modeling evaluated on the eight modeled loops is 1 A root mean square deviation (rmsd) for the backbone atoms and 2.3 A rmsd for all heavy atoms.     

The loop problem in proteins: A monte carlo simulated annealing approach

A Monte Carlo simulated annealing (MCSA) algorithm was used to generate the conformations of local regions in bovine pancreatic trypsin inhibitor (BPTI) starting from random initial conformations. In the approach explored, only the conformation of the segment is computed; the rest of the protein is fixed in the known native conformation. Rather than follow a single simulation exhaustively, computer time is better used by performing multiple independent MCSA simulations in which different starting temperatures are employed and the number of conformations sampled is varied. The best computed conformation is chosen on the basis of lowest total energy and refined further. The total energy used in the annealing is the sum of the intrasegment energy, the interaction energy of the segment with the local surrounding region, and a distance constraint to generate a smooth connection of the initially randomized segment with the rest of the protein. The rms deviations between the main-chain conformations of the computed segments in BPTI and those of the native x-ray structure are 0.94 Å for a 5-residue α-helical segment, 1.11 Å for a 5-residue β-strand segment, and 1.03, 1.61, and 1.87 Ã for 5-, 7-, and 9-residue loop segments. Side-chain deviations are comparable to the main-chain deviations for those side chains that interact strongly with the fixed part of the protein. A detailed view of the deviations at an atom-resolved level is obtained by comparing the predicted segments with their known conformations in the crystal structure of BPTI. These results emphasize the value of predetermined fixed structure against which the computed segment can nest. © 1993 John Wiley & Sons, Inc.     

Antibodies as a model system for comparative model refinement

Predicting the conformations of loops is a critical aspect of protein comparative (homology) modeling. Despite considerable advances in developing loop prediction algorithms, refining loops in homology models remains challenging. In this work, we use antibodies as a model system to investigate strategies for more robustly predicting loop conformations when the protein model contains errors in the conformations of side chains and protein backbone surrounding the loop in question. Specifically, our test system consists of partial models of antibodies in which the “scaffold” (i.e., the portion other than the complementarity determining region, CDR, loops) retains native backbone conformation, whereas the CDR loops are predicted using a combination of knowledge‐based modeling (H1, H2, L1, L2, and L3) and ab initio loop prediction (H3). H3 is the most variable of the CDRs. Using a previously published method, a test set of 10 shorter H3 loops (5–7 residues) are predicted to an average backbone (N? Cα? C? O) RMSD of 2.7 Å while 11 longer loops (8–9 residues) are predicted to 5.1 Å, thus recapitulating the difficulties in refining loops in models. By contrast, in control calculations predicting the same loops in crystal structures, the same method reconstructs the loops to an average of 0.5 and 1.4 Å for the shorter and longer loops, respectively. We modify the loop prediction method to improve the ability to sample near‐native loop conformations in the models, primarily by reducing the sensitivity of the sampling to the loop surroundings, and allowing the other CDR loops to optimize with the H3 loop. The new method improves the average accuracy significantly to 1.3 Å RMSD and 3.1 Å RMSD for the shorter and longer loops, respectively. Finally, we present results predicting 8–10 residue loops within complete comparative models of five nonantibody proteins. While anecdotal, these mixed, full‐model results suggest our approach is a promising step toward more accurately predicting loops in homology models. Furthermore, while significant challenges remain, our method is a potentially useful tool for predicting antibody structures based on a known Fv scaffold. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

The diversity of H3 loops determines the antigen‐binding tendencies of antibody CDR loops

Of the complementarity‐determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen‐binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen‐binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen‐binding tendencies of all the CDR loops.     

Conformational analysis and clustering of short and medium size loops connecting regular secondary structures: a database for modeling and prediction.

Loops are regions of nonrepetitive conformation connecting regular secondary structures. We identified 2,024 loops of one to eight residues in length, with acceptable main-chain bond lengths and peptide bond angles, from a database of 223 protein and protein-domain structures. Each loop is characterized by its sequence, main-chain conformation, and relative disposition of its bounding secondary structures as described by the separation between the tips of their axes and the angle between them. Loops, grouped according to their length and type of their bounding secondary structures, were superposed and clustered into 161 conformational classes, corresponding to 63% of all loops. Of these, 109 (51% of the loops) were populated by at least four nonhomologous loops or four loops sharing a low sequence identity. Another 52 classes, including 12% of the loops, were populated by at least three loops of low sequence similarity from three or fewer nonhomologous groups. Loop class suprafamilies resulting from variations in the termini of secondary structures are discussed in this article. Most previously described loop conformations were found among the classes. New classes included a 2:4 type IV hairpin, a helix-capping loop, and a loop that mediates dinucleotide-binding. The relative disposition of bounding secondary structures varies among loop classes, with some classes such as beta-hairpins being very restrictive. For each class, sequence preferences as key residues were identified; those most frequently at these conserved positions than in proteins were Gly, Asp, Pro, Phe, and Cys. Most of these residues are involved in stabilizing loop conformation, often through a positive phi conformation or secondary structure capping. Identification of helix-capping residues and beta-breakers among the highly conserved positions supported our decision to group loops according to their bounding secondary structures. Several of the identified loop classes were associated with specific functions, and all of the member loops had the same function; key residues were conserved for this purpose, as is the case for the parvalbumin-like calcium-binding loops. A significant number, but not all, of the member loops of other loop classes had the same function, as is the case for the helix-turn-helix DNA-binding loops. This article provides a systematic and coherent conformational classification of loops, covering a broad range of lengths and all four combinations of bounding secondary structure types, and supplies a useful basis for modelling of loop conformations where the bounding secondary structures are known or reliably predicted.     

Canonical antigen-binding loop structures in immunoglobulins: more structures, more canonical classes?

Grafting the antigen-binding loops onto a human antibody scaffold is a widely used technique to humanise murine antibodies. The success of this approach depends largely on the observation that the antigen-binding loops adopt only a limited number of canonical structures. Identification of the correct canonical structure is therefore essential. Algorithms that predict the main-chain conformation of the hypervariable loops using only the amino acid sequence often provide this information. Here, we describe new canonical loop conformations for the hypervariable regions H1 and H2 as found in single-domain antibody fragments of dromedaries or llama. Although the occurrence of these new loop conformations was not predicted by the algorithms used, it seems that they could occur in human or mouse antigen-binding loops. Their discovery indicates that the currently used set of canonical structures is incomplete and that the prediction algorithms should be extended to include these new structures.     

Ab initio structure prediction of the antibody hypervariable H3 loop

Antibodies have the capability of binding a wide range of antigens due to the diversity of the six loops constituting the complementarity determining region (CDR). Among the six loops, the H3 loop is the most diverse in structure, length, and sequence identity. Prediction of the three‐dimensional structures of antibodies, especially the CDR loops, is an important step in the computational design and engineering of novel antibodies for improved affinity and specificity. Although it has been demonstrated that the conformation of the five non‐H3 loops can be accurately predicted by comparing their sequences against databases of canonical loop conformations, no such connection has been established for H3 loops. In this work, we present the results for ab initio structure prediction of the H3 loop using conformational sampling and energy calculations with the program Prime on a dataset of 53 loops ranging in length from 4 to 22 residues. When the prediction is performed in the crystal environment and including symmetry mates, the median backbone root mean square deviation (RMSD) is 0.5 Å to the crystal structure, with 91% of cases having an RMSD of less than 2.0 Å. When the prediction is performed in a noncrystallographic environment, where the scaffold is constructed by swapping the H3 loops between homologous antibodies, 70% of cases have an RMSD below 2.0 Å. These results show promise for ab initio loop predictions applied to modeling of antibodies. © 2012 Wiley Periodicals, Inc.     

Does conformational free energy distinguish loop conformations in proteins?

Limitations in protein homology modeling often arise from the inability to adequately model loops. In this paper we focus on the selection of loop conformations. We present a complete computational treatment that allows the screening of loop conformations to identify those that best fit a molecular model. The stability of a loop in a protein is evaluated via computations of conformational free energies in solution, i.e., the free energy difference between the reference structure and the modeled one. A thermodynamic cycle is used for calculation of the conformational free energy, in which the total free energy of the reference state (i.e., gas phase) is the CHARMm potential energy. The electrostatic contribution of the solvation free energy is obtained from solving the finite-difference Poisson-Boltzmann equation. The nonpolar contribution is based on a surface area-based expression. We applied this computational scheme to a simple but well-characterized system, the antibody hypervariable loop (complementarity-determining region, CDR). Instead of creating loop conformations, we generated a database of loops extracted from high-resolution crystal structures of proteins, which display geometrical similarities with antibody CDRs. We inserted loops from our database into a framework of an antibody; then we calculated the conformational free energies of each loop. Results show that we successfully identified loops with a "reference-like" CDR geometry, with the lowest conformational free energy in gas phase only. Surprisingly, the solvation energy term plays a confusing role, sometimes discriminating "reference-like" CDR geometry and many times allowing "non-reference-like" conformations to have the lowest conformational free energies (for short loops). Most "reference-like" loop conformations are separated from others by a gap in the gas phase conformational free energy scale. Naturally, loops from antibody molecules are found to be the best models for long CDRs (> or = 6 residues), mainly because of a better packing of backbone atoms into the framework of the antibody model.     

New efficient statistical sequence-dependent structure prediction of short to medium-sized protein loops based on an exhaustive loop classification.

A bank of 13,563 loops from three to eight amino acid residues long, representing motifs between two consecutive regular secondary structures, has been derived from protein structures presenting less than 95 % sequence identity. Statistical analyses of occurrences of conformations and residues revealed length-dependent over-representations of particular amino acids (glycine, proline, asparagine, serine, and aspartate) and conformations (alphaL, epsilon, betaPregions of the Ramachandran plot). A position-dependent distribution of these occurrences was observed for N and C-terminal residues, which are correlated to the nature of the flanking regions. Loops of the same length were clustered into statistically meaningful families on the basis of their backbone structures when placed in a common reference frame, independent of the flanks. These clusters present significantly different distributions of sequence, conformations, and endpoint residue Calphadistances. On the basis of the sequence-structure correlation of this clustering, an automatic loop modeling algorithm was developed. Based on the knowledge of its sequence and of its flank backbone structures each query loop is assigned to a family and target loop supports are selected in this family. The support backbones of these target loops are then adjusted on flanking structures by partial exploration of the conformational space. Loop closure is performed by energy minimization for each support and the final model is chosen among connected supports based upon energy criteria. The quality of the prediction is evaluated by the root-mean-square deviation (rmsd) between the final model and the native loops when the whole bank is re-attributed on itself with a Jackknife test. This average rmsd ranges from 1.1 A for three-residue loops to 3.8 A for eight-residue loops. A few poorly predicted loops are inescapable, considering the high level of diversity in loops and the lack of environment data. To overcome such modeling problems, a statistical reliability score was assigned for each prediction. This score is correlated to the quality of the prediction, in terms of rmsd, and thus improves the selection accuracy of the model. The algorithm efficiency was compared to CASP3 target loop predictions. Moreover, when tested on a test loop bank, this algorithm was shown to be robust when the loops are not precisely delimited, therefore proving to be a useful tool in practice for protein modeling.     

Ab initio construction of all-atom loop conformations

In this study, a new ab initio method named CLOOP has been developed to build all-atom loop conformations. In this method, a loop main-chain conformation is generated by sampling main-chain dihedral angles from a restrained varphi/psi set, and the side-chain conformations are built randomly. The CHARMM all-atom force field was used to evaluate the loop conformations. Soft core potentials were used to treat the non-bond interactions, and a designed energy-minimization technique was used to close and optimize the loop conformations. It is shown that the two strategies improve the computational efficiency and the loop-closure rate substantially compared to normal minimization methods. CLOOP was used to construct the conformations of 4-, 8-, and 12-residue loops in Fiser's test set. The average main-chain root-mean-square deviations obtained in 1,000 trials for the 10 different loops of each size are 0.33, 1.27, and 2.77 A, respectively. CLOOP can build all-atom loop conformations with a sampling accuracy comparable with previous loop main-chain construction algorithms. [Figure: see text].     

Modeling of loops in protein structures

Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4-, 8-, and 12-residue loop predictions, respectively, had <2 A RMSD error for the mainchain N, C(alpha), C, and O atoms; the average accuracies were 0.59 +/- 0.05, 1.16 +/- 0.10, and 2.61 +/- 0.16 A, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 A, the average loop prediction error increased by 180, 25, and 3% for 4-, 8-, and 12-residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling.     

Anti-insulin antibody structure and conformation. II. Molecular dynamics with explicit solvent.

Molecular dynamics at 300 K was used as a conformation searching tool to analyze a knowledge-based structure prediction of an anti-insulin antibody. Solvation effects were modeled by packing water molecules around the antigen binding loops. Some loops underwent backbone and side-chain conformational changes during the 95-ps equilibration, and most of these new, lower potential energy conformations were stable during the subsequent 200-ps simulation. Alterations to the model include changes in the intraloop, main-chain hydrogen bonding network of loop H3, and adjustments of Tyr and Lys side chains of H3 induced by hydrogen bonding to water molecules. The structures observed during molecular dynamics support the conclusion of the previous paper that hydrogen bonding will play the dominant role in antibody-insulin recognition. Determination of the structure of the antibody by x-ray crystallography is currently being pursued to provide an experimental test of these results. The simulation appears to improve the model, but longer simulations at higher temperatures should be performed.     

Crystal structure of a chimeric Fab' fragment of an antibody binding tumour cells.

The crystal structure of a chimeric Fab' fragment of a monoclonal antibody is presented. The Fab' comprises the murine light chain and heavy chain variable domains of the carcinoma-binding antibody B72.3 fused to the constant domain of human kappa, and the first constant domain and hinge domain of human gamma 4, respectively. A model for the Fab' has been determined by molecular replacement and refined to a resolution of 3.1 A with an R-factor of 17.6%. The additional residues that distinguish a Fab' from a Fab fragment are seen to be disordered in the crystals. The H3 hypervariable loop is short and adopts a sharp hairpin turn in a conformation that results from an interaction between the lysine side-chain of H93 and the main-chain carbonyl group of H96. The remaining hypervariable loops display conformations similar to those predicted from the canonical structures approach, although loop H2 is apparently displaced by a salt-bridge formed between H55 Asp and the neighbouring H73 Lys. These and other features of the structure likely to be important in grafting the hypervariable loops to an otherwise human framework are discussed.     

Predicting antibody hypervariable loop conformations. II: Minimization and molecular dynamics studies of MCPC603 from many randomly generated loop conformations

We describe a method for predicting the conformations of loops in proteins and its application to four of the complementarity determining regions [CDRs] in the crystallographically determined structure of MCPC603. The method is based on the generation of a large number of randomly generated conformations for the backbone of the loop being studied, followed by either minimization or molecular dynamics followed by minimization starting from these random structures. The details of the algorithm for the generation of the loops are presented in the first paper in this series (Shenkin et al. [submitted]). The results of minimization and molecular dynamics applied to these loops is presented here. For the two shortest CDRs studied (H1 and L2, which are five and seven amino acids long), minimizations and dynamics simulations which ignore interactions of the loop amino acids beyond the carbon beta replicate the conformation of the crystal structure closely. This suggests that these loops fold independently of sequence variation. For the third CDR (L3, which is nine amino acids), those portions of the CDR near its base which are hydrogen bonded to framework are well replicated by our procedures, but the top of the loop shows significant conformational variability. This variability persists when side chain interactions for the MCPC603 sequence are included. For a fourth CDR (H3, which is 11 amino acids long), new low-energy backbone conformations are found; however, only those which are close to the crystal are compatible with the sequence when side chain interactions are taken into account. Results from minimization and dynamics on single CDRs with all other CDRs removed are presented. These allow us to explore the extent to which individual CDR conformations are determined by interactions with framework only.     

Modeling the anti-CEA antibody combining site by homology and conformational search.

A model for an antibody specific for the carcinoembryonic antigen (CEA) has been constructed using a method which combines the concept of canonical structures with conformational search. A conformational search technique is introduced which couples random generation of backbone loop conformations to a simulated annealing method for assigning side chain conformations. This technique was used both to verify conformations selected from the set of known canonical structures and to explore conformations available to the H3 loop in CEA ab initio. Canonical structures are not available for H3 due to its variability in length, sequence, and observed conformation in known antibody structures. Analysis of the results of conformational search resulted in three equally probable conformations for H3 loop in CEA. Force field energies, solvation free energies, exposure of charged residues and burial of hydrophobic residues, and packing of hydrophobic residues at the base of the loop were used as selection criteria. The existence of three equally plausible structures may reflect the high degree of flexibility expected for an exposed loop of this length. The nature of the combining site and features which could be important to interaction with antigen are discussed.     

The energy of formation of internal loops in triple-helical collagen polypeptides

The sequence-dependent local destabilization in the interior of the collagen triple helix has been evaluated by means of conformational energy computations. Using a model poly(Gly-Pro-Pro) triple helix as the reference state, a method was developed for generating local loops, i.e., internal deformations, and analyzing their conformations. A seven-residue Gly-Pro-Pro-Gly-Pro-Pro-Gly fragment was replaced by the Gly-Pro-Ala-Gly-Ala-Ala-Gly sequence in one, two, or all three of the strands of the loop region. A set of loop conformations was generated in which the ends of the loop were initially fixed in the triple-helical structure. The potential energy of the entire deformed triple helix was then minimized, resulting in a variety of structures that contained deformed loops. The conformations of the triple helices at the two ends of the loops remained essentially unchanged in many of the low-energy conformations. In numerous high-energy conformations, however, the triple-helical segments were also partially or totally disrupted. The minimum-energy conformations of the whole structures were compared in terms of rms deviations of atomic coordinates with respect to the original triple helix, and of the shapes of the loops (using a distance function derived from differential geometry). Three new geometrical parameters—stretch S, kink K, and unwinding U—were defined to describe the changes in the overall orientation of the triple helices at the two ends of the loop. It is shown that, when the number of Pro residues in a short fragment is reduced, the triple helical structure can accomodate internal loops (i.e., distortions) within a 5 kcal/mol cutoff from the essentially unperturbed triple helical structure. For structures with a Gly-Pro-Ala-Gly-Ala-Ala-Gly sequence in all three strands, the probability of finding conformations with internal loops is small, i.e., 0.06. Internal loops affect the overall orientation of these structures, as measured by the helix-distortion parameters S, K, and U. © 1995 John Wiley & Sons, Inc.     

Structure of a shark IgNAR antibody variable domain and modeling of an early-developmental isotype

The new antigen receptor (IgNAR) antibodies from sharks are disulphide bonded dimers of two protein chains, each containing one variable and five constant domains. Three types of IgNAR variable domains have been discovered, with Type 3 appearing early in shark development and being overtaken by the antigen-driven affinity-matured Type 1 and 2 response. Here, we have determined the first structure of a naturally occurring Type 2 IgNAR variable domain, and identified the disulphide bond that links and stabilizes the CDR1 and CDR3 loops. This disulphide bridge locks the CDR3 loop in an "upright" conformation in contrast to other shark antibody structures, where a more lateral configuration is observed. Further, we sought to model the Type 3 isotype based on the crystallographic structure reported here. This modeling indicates (1) that internal Type 3-specific residues combine to pack into a compact immunoglobulin core that supports the CDR loop regions, and (2) that despite apparent low-sequence variability, there is sufficient plasticity in the CDR3 loop to form a conformationally diverse antigen-binding surface.     

Molecular recognition. Conformational analysis of limited proteolytic sites and serine proteinase protein inhibitors

The conformations of known tryptic limited proteolytic sites have been analysed and compared to the structures of the binding regions of serine proteinase inhibitors, as they are found when complexed to a serine proteinase. Conformational parameters studied include main-chain torsion angles, root-mean-square fits, accessibility, mobility and protrusion indices. As observed before, the inhibitors share a common main-chain conformation at the binding loop from P3-P'3 (Schechter & Berger notation), which is maintained throughout all the serine proteinase inhibitor families for which X-ray data is available, despite lack of similarity in the rest of the protein. This canonical structure is not found amongst the limited proteolytic sites (or nicksites), which differ markedly from the inhibitor binding loop conformation, and also amongst themselves. The experimentally determined nicksites are in general both accessible and protruding; as are the inhibitor binding loops, as well as being typically flexible regions of structure, as denoted by elevated temperature factors from crystallographic determinations. For cleavage by serine proteinases these loops must radically alter their local conformations and a large motion of the loop relative to the structure, in some cases, would be required to orientate these sites for cleavage.     

Structural determinants of the conformations of medium-sized loops in proteins

Loops are integral components of protein structures, providing links between elements of secondary structure, and in many cases contributing to catalytic and binding sites. The conformations of short loops are now understood to depend primarily on their amino acid sequences. In contrast, the structural determinants of longer loops involve hydrogen-bonding and packing interactions within the loop and with other parts of the protein. By searching solved protein structures for regions similar in main chain conformation to the antigen-binding loops in immunoglobulins, we identified medium-sized loops of similar structure in unrelated proteins, and compared the determinants of their conformations. For loops that form compact substructures the major determinant of the conformation is the formation of hydrogen bonds to inward-pointing main chain atoms. For loops that have more extended conformations, the major determinant of their structure is the packing of a particular residue or residues against the rest of the protein. The following picture emerges: Medium-sized loops of similar conformation are stabilized by similar interactions. The groups that interact with the loop have very similar spatial dispositions with respect to the loop. However, the residues that provide these interactions may arise from dissimilar parts of the protein: The conformation of the loop requires certain interactions that the protein may provide in a variety of ways.