The Genetic Algorithm and the Conformational Search of Polypeptides and Proteins

Abstract

The genetic algorithm is a technique of function optimization derived from the principles of evolutionary theory. We have adapted it to perform conformational search on polypeptides and proteins. The algorithm was first tested on several small polypeptides and the 46 amino acid protein crambin under the AMBER potential energy function. The probable global minimum conformations of the polypeptides were located 90% of the time and a non-native conformation of crambin was located that was 150kcal/mol lower in potential energy than the minimized crystal structure conformation. Next, we used a knowledge-based potential function to predict the structures of melittin, pancreatic polypeptide, and crambin. A 2.31 Å ΔRMS conformation of melittin and a 5.33 Å ΔRMS conformation of pancreatic polypeptide were located by genetic algorithm-based conformational search under the knowledge-based potential function. Although the ΔRMS of pancreatic polypeptide was somewhat high, most of the secondary structure was correct. The secondary structure of crambin was predicted correctly, but the potential failed to promote packing interactions. Finally, we tested the packing aspects of our potential function by attempting to predict the tertiary structure of cytochrome b ₅₆₂ given correct secondary structure as a constraint. The final predicted conformation of cytochrome b ₅₆₂ was an almost completely extended continuous helix which indicated that the knowledge-based potential was useless for tertiary structure prediction. This work serves as a warning against testing potential functions designed for tertiary structure prediction on small proteins.     

Structure and energetics of ligand binding to proteins: Escherichia coli dihydrofolate reductase-trimethoprim, a drug-receptor system

A study of the binding of the antibacterial agent trimethoprim to Escherichia coli dihydrofolate reductase was carried out using energy minimization techniques with both a full, all-atom valence force field and a united atom force field. Convergence criteria ensured that no significant structural or energetic changes would occur with further minimization. Root-mean-square (RMS) deviations of both minimized structures with the experimental structure were calculated for selected regions of the protein. In the active site, the all-atom minimized structure fit the experimental structure much better than did the united atom structure. To ascertain what constitutes a good fit, the RMS deviations between crystal structures of the same enzyme either from different species or in different crystal environments were compared. The differences between the active site of the all-atom minimized structure and the experimental structure are similar to differences observed between crystal structures of the same protein. Finally, the energetics of ligand binding were analyzed for the all-atom minimized coordinates. Strain energy induced in the ligand, the corresponding entropy loss due to shifts in harmonic frequencies, and the role of specific residues in ligand binding were examined. Water molecules, even those not in direct contact with the ligand, were found to have significant interaction energies with the ligand. Thus, the inclusion of at least one shell of waters may be vital for accurate simulations of enzyme complexes.     

Molecular modeling of proteins: a strategy for energy minimization by molecular mechanics in the AMBER force field.

Energy minimization is an important step in molecular modeling of proteins. In this study, we sought to develop a minimization strategy which would give the best final structures with the shortest computer time in the AMBER force field. In the all-atom model, we performed energy minimization of the melittin (mostly alpha-helical) and cardiotoxin (mostly beta-sheet and beta-turns) crystal structures by both constrained and unconstrained pathways. In the constrained path, which has been recommended in the energy minimization of proteins, hydrogens were relaxed first, followed by the side chains of amino acid residues, and finally the whole molecule. Despite the logic of this approach, however, the structures minimized by the unconstrained path fit the experimental structures better than those minimized by constrained paths. Moreover, the unconstrained path saved considerable computer time. We also compared the effects of the steepest descents and conjugate gradients algorithms in energy minimization. Previously, steepest descents has been used in the initial stages of minimization and conjugate gradients in the final stages of minimization. We therefore studied the effect on the final structure of performing an initial minimization by steepest descents. The structures minimized by conjugate gradients alone resembled the structures minimized initially by the steepest descents and subsequently by the conjugate gradients algorithms. Thus an initial minimization using steepest descents is wasteful and unnecessary, especially when starting from the crystal structure. Based on these results, we propose the use of an unconstrained path and conjugate gradients for energy minimization of proteins. This procedure results in low energy structures closer to the experimental structures, and saves about 70-80% of computer time. This procedure was applied in building models of lysozyme mutants. The crystal structure of native T4 lysozyme was mutated to three different mutants and the structures were minimized. The minimized structures closely fit the crystal structures of the respective mutants (less than 0.3 A root-mean-square, RMS, deviation in the position of all heavy atoms). These results confirm the efficiency of the proposed minimization strategy in modeling closely related homologs. To determine the reliability of the united atom approximation, we also performed all of the above minimizations with united atom models. This approximation gave structures with similar but slightly higher RMS deviations than the all-atom model, but gave further savings of 60-70% in computer time. However, we feel further investigation is essential to determine the reliability of this approximation.(ABSTRACT TRUNCATED AT 400 WORDS)     

Molecular Modeling of Proteins: A Strategy for Energy Minimization by Molecular Mechanics in the AMBER Force Field

Abstract

Energy minimization is an important step in molecular modeling of proteins. In this study, we sought to develop a minimization strategy which would give the best final structures with the shortest computer time in the AMBER force field. In the all-atom model, we performed energy minimization of the melittin (mostly α-helical) and cardiotoxin (mostly β-sheet and β-turns) crystal structures by both constrained and unconstrained pathways. In the constrained path, which has been recommended in the energy minimization of proteins, hydrogens were relaxed first, followed by the side chains of amino acid residues, and finally the whole molecule. Despite the logic of this approach, however, the structures minimized by the unconstrained path fit the experimental structures better than those minimized by constrained paths. Moreover, the unconstrained path saved considerable computer time. We also compared the effects of the steepest descents and conjugate gradients algorithms in energy minimization. Previously, steepest descents has been used in the initial stages of minimization and conjugate gradients in the final stages of minimization. We therefore studied the effect on the final structure of performing an initial minimization by steepest descents. The structures minimized by conjugate gradients alone resembled the structures minimized initially by the steepest descents and subsequently by the conjugate gradients algorithms. Thus an initial minimization using steepest descents is wasteful and unnecessary, especially when starting from the crystal structure. Based on these results, we propose the use of an unconstrained path and conjugate gradients for energy minimization of proteins. This procedure results in low energy structures closer to the experimental structures, and saves about 70–80% of computer time. This procedure was applied in building models of lysozyme mutants. The crystal structure of native T₄ lysozyme was mutated to three different mutants and the structures were minimized. The minimized structures closely fit the crystal structures of the respective mutants (< 0.3 Å root-mean-square, RMS, deviation in the position of all heavy atoms). These results confirm the efficiency of the proposed minimization strategy in modeling closely related homologs. To determine the reliability of the united atom approximation, we also performed all of the above minimizations with united atom models. This approximation gave structures with similar but slightly higher RMS deviations than the all-atom model, but gave further savings of60-70% in computer time. However, we feel further investigation is essential to determine the reliability of this approximation. Finally, to determine the limitation of the procedure, we built the melittin molecule interactively in an α-helical conformation and this model showed an RMS deviation greater than 2.8 Å when compared to the melittin crystal structure. This model was minimized by various strategies. None of the minimized structures converged towards the crystal structure. Thus, although the proposed method seems to give valid structures starting from closely related crystal structures, it cannot predict the native structure when the starting structure is far from the native structure. From these results, we recommend the use of the proposed strategy of minimizing by an unconstrained path using the conjugate gradients algorithm, but only for modeling of closely related structural homologs of proteins.     

Free energy landscape of protein folding in water: explicit vs. implicit solvent

The Generalized Born (GB) continuum solvent model is arguably the most widely used implicit solvent model in protein folding and protein structure prediction simulations; however, it still remains an open question on how well the model behaves in these large-scale simulations. The current study uses the beta-hairpin from C-terminus of protein G as an example to explore the folding free energy landscape with various GB models, and the results are compared to the explicit solvent simulations and experiments. All free energy landscapes are obtained from extensive conformation space sampling with a highly parallel replica exchange method. Because solvation model parameters are strongly coupled with force fields, five different force field/solvation model combinations are examined and compared in this study, namely the explicit solvent model: OPLSAA/SPC model, and the implicit solvent models: OPLSAA/SGB (Surface GB), AMBER94/GBSA (GB with Solvent Accessible Surface Area), AMBER96/GBSA, and AMBER99/GBSA. Surprisingly, we find that the free energy landscapes from implicit solvent models are quite different from that of the explicit solvent model. Except for AMBER96/GBSA, all other implicit solvent models find the lowest free energy state not the native state. All implicit solvent models show erroneous salt-bridge effects between charged residues, particularly in OPLSAA/SGB model, where the overly strong salt-bridge effect results in an overweighting of a non-native structure with one hydrophobic residue F52 expelled from the hydrophobic core in order to make better salt bridges. On the other hand, both AMBER94/GBSA and AMBER99/GBSA models turn the beta-hairpin in to an alpha-helix, and the alpha-helical content is much higher than the previously reported alpha-helices in an explicit solvent simulation with AMBER94 (AMBER94/TIP3P). Only AMBER96/GBSA shows a reasonable free energy landscape with the lowest free energy structure the native one despite an erroneous salt-bridge between D47 and K50. Detailed results on free energy contour maps, lowest free energy structures, distribution of native contacts, alpha-helical content during the folding process, NOE comparison with NMR, and temperature dependences are reported and discussed for all five models.     

Packed protein bilayers in the 0.90 A resolution structure of a designed alpha helical bundle.

A 12-residue peptide designed to form an alpha-helix and self-associate into an antiparallel 4-alpha-helical bundle yields a 0.9 A crystal structure revealing unanticipated features. The structure was determined by direct phasing with the "Shake-and-Bake" program, and contains four crystallographically distinct 12-mer peptide molecules plus solvent for a total of 479 atoms. The crystal is formed from nearly ideal alpha-helices hydrogen bonded head-to-tail into columns, which in turn pack side-by-side into sheets spanning the width of the crystal. Within each sheet, the alpha-helices run antiparallel and are closely spaced (9-10 A center-to-center). The sheets are more loosely packed against each other (13-14 A between helix centers). Each sheet is amphiphilic: apolar leucine side chains project from one face, charged lysine and glutamate side chains from the other face. The sheets are stacked with two polar faces opposing and two apolar faces opposing. The result is a periodic biomaterial composed of packed protein bilayers, with alternating polar and apolar interfaces. All of the 30 water molecules in the unit cell lie in the polar interface or between the stacked termini of helices. A section through the sheet reveals that the helices packed at the apolar interface resemble the four-alpha-helical bundle of the design, but the helices overhang parts of the adjacent bundles, and the helix crossing angles are less steep than intended (7-11 degrees rather than 18 degrees).     

Molecular dynamics simulation of a leucine zipper motif predicted for the integrase of human immunodeficiency virus type I

We have used the molecular dynamics (MD) simulation package AMBER4 to search the conformation of a peptide predicted as a leucine zipper motif for the human immunodeficiency virus type I integrase protein (HIV IN-LZM). The peptide is composed of 22 amino acid residues and its location is from Val 151 to Leu 172. The searching procedure also includes two known α-helices that served as positive controls—namely, a 22-residue GCN4-p1 (LZM) and a 20-residue poly(L -alanine) (PLA). A 21-residue peptide extracted from a cytochrome C crystal (CCC-t) with determined conformation as a β-turn is also included as a negative control. At the beginning of the search, two starting conformations—namely, the standard right-handed α-helix and the fully stretched conformations—are generated for each peptide. Structures generated as standard α-helix are equilibrated at room temperature for 90 ps while structures generated as a fully stretched one are equilibrated at 600 K for 120 ps. The CCC-t and PLA helices are nearly destroyed from the beginning of equilibration. However, for both the HIV IN-LZM and the GCN4-p1 LZM structures, there is substantial helicity being retained throughout the entire course of equilibration. Although helix propagation profiles calculated indicate that both peptides possess about the same propensity to form an α-helix, the HIV IN-LZM helix appears to be more stable than the GCN4-p1 one as judged by a variety of analyses on both structures generated during the equilibration course. The fact that predicted HIV IN-LZM can exist as an α-helix is also supported by the results of high temperature equilibration run on the fully stretched structures generated. In this run, the RMS deviations between the backbone atoms of the structures with the lowest potential energy (PE) identified within every 2 ps and the structure with the lowest PE searched in the same course of simulation are calculated. For both the HIV IN-LZM and the GCN4-p1 LZM, these rms values decrease with the decrease of PE, which indicates that both structures are closer in conformations as their PEs are moved deeper into the PE well. © 1994 John Wiley & Sons, Inc.     

A critical assessment of the secondary structure alpha-helices and their termini in proteins

Secondary structure prediction from amino acid sequence is a key component of protein structure prediction, with current accuracy at approximately 75%. We analysed two state-of-the-art secondary structure prediction methods, PHD and JPRED, comparing predictions with secondary structure assigned by the algorithms DSSP and STRIDE. The specific focus of our study was alpha-helix N-termini, as empirical free energy scales are available for residue preferences at N-terminal positions. Although these prediction methods perform well in general at predicting the alpha-helical locations and length distributions in proteins, they perform less well at predicting the correct helical termini. For example, although most predicted alpha-helices overlap a real alpha-helix (with relatively few completely missed or extra predicted helices), only one-third of JPRED and PHD predictions correctly identify the N-terminus. Analysis of neighbouring N-terminal sequences to predicted helical N-termini shows that the correct N-terminus is often within one or two residues. More importantly, the true N-terminal motif is, on average, more favourable as judged by our experimentally measured free energies. This suggests a simple, but powerful, strategy to improve secondary structure prediction using empirically derived energies to adjust the predicted output to a more favourable N-terminal sequence.     

Energy of stabilization of the right-handed beta alpha beta crossover in proteins

An explanation in terms of conformational energies is provided for the observed nearly exclusive preference of the beta alpha beta structure for forming a right-handed, rather than a left-handed, crossover connection. Conformational energy computations have been carried out on a model beta alpha beta structure, consisting of two six-residue Val beta-strands and of a 12-residue Ala alpha-helix, connected by two flexible four-residue Ala links to the strands. The energy of the most favorable right-handed crossover is 15.51 kcal/mol lower than that of the corresponding left-handed cross-over. The right-handed crossover is a strain-free structure. Its energy of stabilization arises largely from the interactions of the two beta-strands with one another and with the alpha-helix. On the other hand, the left-handed crossover is either disrupted after energy minimization or it remains conformationally strained, as indicated by an energetically unfavorable left twisting of the beta-sheet and by the presence of high-energy local residue conformations. In the energetically most favorable right-handed crossover, the right twisting of the beta-sheet and its manner of interacting with the alpha-helix are identical with those computed earlier for isolated beta-sheets and for packed alpha/beta structures. This result supports a proposed principle that it is possible to account for the main features of frequently occurring structural arrangements in globular proteins in terms of the properties of their component structural elements.     

Prediction of protein conformation on the basis of a search for compact structures: test on avian pancreatic polypeptide.

Based on the concept that hydrophobic interactions cause a polypeptide chain to adopt a compact structure, a method is proposed to predict the structure of a protein. The procedure is carried out in four stages: (1) use of a virtual-bond united-residue approximation with the side chains represented by spheres to search conformational space extensively using specially designed interactions to lead to a collapsed structure, (2) conversion of the lowest-energy virtual-bond united-residue chain to one with a real polypeptide backbone, with optimization of the hydrogen-bond network among the backbone groups, (3) perturbation of the latter structure by the electrostatically driven Monte Carlo (EDMC) procedure, and (4) conversion of the spherical representation of the side chains to real groups and perturbation of the whole molecule by the EDMC procedure using the empirical conformational energy program for peptides (ECEPP/2) energy function plus hydration. Application of this procedure to the 36-residue avian pancreatic polypeptide led to a structure that resembled the one determined by X-ray crystallography; it had an alpha-helix starting at residue 13, with the N-terminal portion of the chain in an extended conformation packed against the alpha-helix. Similar structures with slightly higher energies, but looser packing, were also obtained.     

Sequence-specific 1H NMR assignments and solution structure of bovine pancreatic polypeptide.

Sequence-specific 1H NMR assignments for the 36 residue bovine pancreatic polypeptide (bPP) have been completed. The secondary and tertiary structure of bPP in solution has been determined from experimental NMR data. It is shown that bPP has a very well-defined C-terminal alpha-helix involving residues 15-32. Although regular secondary structure cannot be clearly defined in the N-terminal region, residues 4-8 maintain a rather ordered conformation in solution. This is attributed primarily to the hydrophobic interactions between this region and the C-terminal helix. The two segments of the structure are joined by a turn which is poorly defined. The four end residues both at the N-terminus and the C-terminus are highly disordered in solution. The overall fold of the bPP molecule is very closely similar to that found in the crystal structure of avian pancreatic polypeptide (aPP). The RMS deviation for backbone atoms of residues 4-8 and 15-32 between the bPP mean structure and the aPP crystal structure is 0.65 A, although there is only 39% identity of the residues. Furthermore, the average conformations of some (mostly from the alpha-helix) side chains of bPP in solution are closely similar to those of aPP in the crystal structure. A large number of side chains of bPP, however, show significant conformational averaging in solution.     

Rationale for Bcl-xL/Bad peptide complex formation from structure, mutagenesis, and biophysical studies

The three-dimensional structure of the anti-apoptotic protein Bcl-xL complexed to a 25-residue peptide from the death promoting region of Bad was determined using NMR spectroscopy. Although the overall structure is similar to Bcl-xL bound to a 16-residue peptide from the Bak protein (Sattler et al., 1997), the Bad peptide forms additional interactions with Bcl-xL. However, based upon site-directed mutagenesis experiments, these additional contacts do not account for the increased affinity of the Bad 25-mer for Bcl-xL compared to the Bad 16-mer. Rather, the increased helix propensity of the Bad 25-mer is primarily responsible for its greater affinity for Bcl-xL. Based on this observation, a pair of 16-residue peptides were designed and synthesized that were predicted to have a high helix propensity while maintaining the interactions important for complexation with Bcl-xL. Both peptides showed an increase in helix propensity compared to the wild-type and exhibited an enhanced affinity for Bcl-xL.     

Study and prediction of secondary structure for membrane proteins

In this paper we present a novel approach to membrane protein secondary structure prediction based on the statistical stepwise discriminant analysis method. A new aspect of our approach is the possibility to derive physical-chemical properties that may affect the formation of membrane protein secondary structure. The certain physical-chemical properties of protein chains can be used to clarify the formation of the secondary structure types under consideration. Another aspect of our approach is that the results of multiple sequence alignment, or the other kinds of sequence alignment, are not used in the frame of the method. Using our approach, we predicted the formation of three main secondary structure types (alpha-helix, beta-structure and coil) with high accuracy, that is Q(3) = 76%. Predicting the formation of alpha-helix and non-alpha-helix states we reached the accuracy which was measured as Q(2) = 86%. Also we have identified certain protein chain properties that affect the formation of membrane protein secondary structure. These protein properties include hydrophobic properties of amino acid residues, presence of Gly, Ala and Val amino acids, and the location of protein chain end.     

Predicting absolute ligand binding free energies to a simple model site

A central challenge in structure-based ligand design is the accurate prediction of binding free energies. Here we apply alchemical free energy calculations in explicit solvent to predict ligand binding in a model cavity in T4 lysozyme. Even in this simple site, there are challenges. We made systematic improvements, beginning with single poses from docking, then including multiple poses, additional protein conformational changes, and using an improved charge model. Computed absolute binding free energies had an RMS error of 1.9 kcal/mol relative to previously determined experimental values. In blind prospective tests, the methods correctly discriminated between several true ligands and decoys in a set of putative binders identified by docking. In these prospective tests, the RMS error in predicted binding free energies relative to those subsequently determined experimentally was only 0.6 kcal/mol. X-ray crystal structures of the new ligands bound in the cavity corresponded closely to predictions from the free energy calculations, but sometimes differed from those predicted by docking. Finally, we examined the impact of holding the protein rigid, as in docking, with a view to learning how approximations made in docking affect accuracy and how they may be improved.     

Conversion of a beta-strand to an alpha-helix induced by a single-site mutation observed in the crystal structure of Fis mutant Pro26Ala.

The conversion from an alpha-helix to a beta-strand has received extensive attention since this structural change may induce many amyloidogenic proteins to self-assemble into fibrils and cause fatal diseases. Here we report the conversion of a peptide segment from a beta-strand to an alpha-helix by a single-site mutation as observed in the crystal structure of Fis mutant Pro26Ala determined at 2.0 A resolution. Pro26 in Fis occurs at the point where a flexible extended beta-hairpin arm leaves the core structure. Thus it can be classified as a "hinge proline" located at the C-terminal end of the beta2-strand and the N-terminal cap of the A alpha-helix. The replacement of Pro26 to alanine extends the A alpha-helix for two additional turns in one of the dimeric subunits; therefore, the structure of the peptide from residues 22 to 26 is converted from a beta-strand to an alpha-helix. This result confirms the structural importance of the proline residue located at the hinge region and may explain the mutant''s reduced ability to activate Hin-catalyzed DNA inversion. The peptide (residues 20 to 26) in the second monomer subunit presumably retains its beta-strand conformation in the crystal; therefore, this peptide shows a "chameleon-like" character since it can adopt either an alpha-helix or a beta-strand structure in different environments. The structure of Pro26Ala provides an additional example where not only the protein sequence, but also non-local interactions determine the secondary structure of proteins.     

Tackling Force-Field Bias in Protein Folding Simulations: Folding of Villin HP35 and Pin WW Domains in Explicit Water

The ability to fold proteins on a computer has highlighted the fact that existing force fields tend to be biased toward a particular type of secondary structure. Consequently, force fields for folding simulations are often chosen according to the native structure, implying that they are not truly “transferable.” Here we show that, while the AMBER ff03 potential is known to favor helical structures, a simple correction to the backbone potential (ff03^∗) results in an unbiased energy function. We take as examples the 35-residue α-helical Villin HP35 and 37 residue β-sheet Pin WW domains, which had not previously been folded with the same force field. Starting from unfolded configurations, simulations of both proteins in Amber ff03^∗ in explicit solvent fold to within 2.0 Å RMSD of the experimental structures. This demonstrates that a simple backbone correction results in a more transferable force field, an important requirement if simulations are to be used to interpret folding mechanism.     

Secondary structure of the murine histocompatibility alloantigen H-2Kb: relationship between heavy chain, beta 2-microglobulin, and antigenic reactivity

The far-ultraviolet circular dichroism (CD) spectra of the extracellular portion (papain-cleaved fragment) of the histocompatibility antigen H-2Kb and its noncovalently associated components, heavy chain and beta 2-microglobulin (beta 2m), indicate that the antigen is highly structured, containing about 30% alpha-helix, 41% beta-sheet, and 29% random coil. Separation of beta 2m from the heavy chain produced a decrease in heavy chain alpha-helix and beta-sheet structure which correlated with a loss of alloantigenic reactivity. Reconstitution of the heavy chain-beta 2m complex resulted in an increase in secondary structure which was greater than the sum of the free chains and the recovery of considerable alloantigenic reactivity. This suggests that some of the secondary structure and much of the alloantigenic reactivity may depend on conformation associated with the binding of beta 2m to heavy chain. A prediction of heavy chain secondary structure based on Chou-Fasman analysis of the primary amino acid sequence agreed with results from CD measurements and suggested that the segments of alpha-helix and beta-sheet structure are distributed throughout the molecule.     

Docking of calcium ions in proteins with flexible side chains and deformable backbones

A method of docking Ca²⁺ ions in proteins with flexible side chains and deformable backbones is proposed. The energy was calculated with the AMBER force field, implicit solvent, and solvent exposure-dependent and distance-dependent dielectric function. Starting structures were generated with Ca²⁺ coordinates and side-chain torsions sampled in 1000 Å³ cubes centered at the experimental Ca²⁺ positions. The energy was Monte Carlo-minimized. The method was tested on fourteen Ca²⁺-binding sites. For twelve Ca²⁺-binding sites the root mean square (RMS) deviation of the apparent global minimum from the experimental structure was below 1.3 and 1.7 Å for Ca²⁺ ions and side-chain heavy atoms, respectively. Energies of multiple local minima correlate with the RMS deviations from the X-ray structures. Two Ca²⁺-binding sites at the surface of proteinase K were not predicted, because of underestimation of Ca²⁺ hydration energy by the implicit-solvent method.     

Isolation, amino acid sequence, and synthesis of dermaseptin, a novel antimicrobial peptide of amphibian skin

A 34-residue antimicrobial peptide named dermaseptin was purified to homogeneity from amphibian skin by a 3-step protocol involving molecular sieve filtration, ion-exchange chromatography, and reversed-phase high-performance liquid chromatography. The complete amino acid sequence of dermaseptin, ALWKTMLKKLGTMALHAGKAALGAAADTISQGTQ, was determined by automated Edman degradation of the peptide and of fragments generated by trypsin. Fast atom bombardment mass spectra of dermaseptin gave a protonated molecular ion m/z 3455.4 which matched the theoretical molecular weight predicted from the amino acid sequence. Dermaseptin was synthesized by the solid-phase method. The synthetic replicate was shown to be indistinguishable from natural dermaseptin with respect to chromatographic properties, amino acid sequence determination, and mass spectrometry analysis. Dermaseptin is a water-soluble, thermostable, and nonhemolytic peptide endowed with highly potent antimicrobial activity against pathogenic fungi at micromolar concentration. Circular dichroism spectra of dermaseptin in hydrophobic media indicated 80% alpha-helical conformation, and predictions of secondary structure suggested that dermaseptin can be configured as an amphiphatic alpha-helix spanning over residues 1-27, a structure that perturbs membrane functions regulating water flux.     

Homology modeling by the ICM method

Five models have been built by the ICM method for the Comparative Modeling section of the Meeting on the Critical Assessment of Techniques for Protein Structure Prediction. The targets have homologous proteins with known three-dimensional structure with sequence identity ranging from 25 to 77%. After alignment of the target sequence with the related three-dimensional structure, the modeling procedure consists of two subproblems: side-chain prediction and loop prediction. The ICM method approaches these problems with the following steps: (1) a starting model is created based on the homologous structure with the conserved portion fixed and the noncon-served portion having standard covalent geometry and free torsion angles; (2) the Biased Probability Monte Carlo (BPMC) procedure is applied to search the subspaces of either all the nonconservative side-chain torsion angles or torsion angles in a loop backbone and surrounding side chains. A special algorithm was designed to generate low-energy loop deformations. The BPMC procedure globally optimizes the energy function consisting of ECEPP/3 and solvation energy terms. Comparison of the predictions with the NMR or crystallographic solutions reveals a high proportion of correctly predicted side chains. The loops were not correctly predicted because imprinted distortions of the backbone increased the energy of the near-native conformation and thus made the solution unrecognizable. Interestingly, the energy terms were found to be reliable and the sampling of conformational space sufficient. The implications of this finding for the strategies of future comparative modeling are discussed. © 1995 Wiley-Liss, Inc.