Prediction of strong antigenic determinant of seminalplasmin and ribonuclease from the amino acid sequence

It has been reported earlier [Hopp, T.P. & Woods, K.R. (1981) Proc. Natl. Acad. Sci. US 78, 3824-3828] that the antigenic determinants of a protein can be delineated by examining the average local hydrophilicity values along the peptide chain. I have used this method to predict the strong antigenic determinants of two proteins, seminalplasmin and ribonuclease, of known sequence. In the former case, the N-terminal segment 1-14, and in the latter case the segments 27-38 and 80-86, are predicted to possess the antigenic determinants of the two proteins. Experimental verification already exists for the former case.     

Use of synthetic peptides to map the antigenic determinants of glycoprotein D of herpes simplex virus.

The predictive algorithm Surfaceplot (J.M.R. Parker, D. Guo, and R.S. Hodges, Biochemistry 25:5425-5432, 1986) was used to examine glycoprotein D of herpes simplex virus type 1 (HSV-1) for amino acid residues with a high probability of being exposed on the molecular surface. Based on these data, 11 different peptides corresponding to 10-residue segments in the primary sequence of glycoprotein D and one 20-residue segment were synthesized, conjugated to carrier proteins, and used to generate specific antisera in rabbits. Two synthetic peptides predicted not to be on the surface of glycoprotein D were included as negative controls. The polyclonal antisera against individual synthetic peptide conjugates were in turn evaluated for their ability to recognize both isolated glycoprotein D and intact HSV-1 virions in an enzyme-linked immunosorbent assay. Based on Surfaceplot predictions, eight linear antigenic sites on glycoprotein D were thereby defined from the 12 antipeptide antisera prepared. Four of these sites contained epitopes to which complement-independent neutralizing antibodies could be generated. The latter sites corresponded to sequences 12 to 21, 267 to 276, 288 to 297, and 314 to 323 of the mature protein. An additional peptide sequence, 2 to 21, was found to generate antisera which had potent virus-neutralizing capacity in the presence of complement. Identification of a neutralizing epitope in the sequence 314 to 323 makes it likely that the membrane-spanning region of glycoprotein D is within the subsequent sequence, 323 to 339. Antipeptide antisera prepared in this study from 12 synthetic peptides contained 13 surface sites predicted by Surfaceplot, of which 7 were not predicted by the parameters of Hopp and Woods (Proc. Natl. Acad. Sci. USA 78:3824-3828, 1981). Of these seven sites not predicted by the Hopp and Woods plot, all generated antipeptide antibodies that bound to HSV-1 virions and three of these seven sites generated neutralizing antibodies. In total, 8 of 12 synthetic peptides containing surface regions produced antipeptide antibodies that bound to HSV-1 virions and 5 of these generated neutralizing antibodies. These results suggest the advantages of Surfaceplot in mapping antigenic determinants in proteins.     

Complete amino acid sequence of a Lolium perenne (perennial rye grass) pollen allergen, Lol p II

The complete amino acid sequence of a Lolium perenne (rye grass) pollen allergen, Lol p II was determined by automated Edman degradation of the protein and selected fragments. Cleavage of the protein by enzymatic and chemical techniques established an unambiguous sequence for the protein. Lol p II contains 97 amino acid residues, with a calculated molecular weight of 10,882. The protein lacks cysteine and glutamine and shows no evidence of glycosylation. Theoretical predictions by Fraga's (Fraga, S. (1982) Can. J. Chem. 60, 2606-2610) and Hopp and Woods' (Hopp, T. P., and Woods, K. R. (1981) Proc. Natl. Acad. Sci. U.S.A. 78, 3824-3828) methods indicate the presence of four hydrophilic regions, which may contribute to sequential or parts of conformational B-cell epitopes. Analysis of amphipathic regions by Berzofsky's method indicates the presence of a highly amphipathic region, which may contain, or contribute to, an Ia/T-cell epitope. This latter segment of Lol p II was found to be highly homologous with an antibody-binding segment of the major rye allergen Lol p I and may explain why immune responsiveness to both the allergens is associated with HLA-DR3.     

Prediction of the subcellular location of prokaryotic proteins based on the hydrophobicity index of amino acids

An algorithm of predicting the subcellular location of prokaryotic proteins is proposed in this paper. In addition to the amino acid composition, the auto-correlation functions based on the hydrophobicity profile of amino acids along the primary sequence of the query protein have been used. Consequently, the best predictive accuracy to date has been achieved. Of the 997 prokaryotic proteins in the database used here, 688 cytoplasmic, 107 extracellular and 202 periplasmic proteins, the overall predictive accuracies are as high as 97.7 and 90.4% in the resubstitution and jackknife tests, respectively, using the hydrophilicity value of Hopp and Woods. The underlying mechanism of the improvement is also discussed. This work would be useful for a systematic analysis of the great amounts of prokaryotic genome sequences. The computer programs used in this paper are available on request via email.     

Epitope mapping of monoclonal antibodies against human immunodeficiency virus type 1 structural proteins by using peptides.

Murine monoclonal antibodies directed against the structural proteins p17 and p24 of human immunodeficiency virus type 1 were investigated in an epitope mapping system. Overlapping peptides consisting of 15 amino acids of the p17 and p24 protein, respectively, were used as competitors in an enzyme-linked immunosorbent assay. Three different immunogenic regions (A, B, and C) could be defined, one on p17 and two on p24. Twenty monoclonal antibodies reacted with the human immunodeficiency virus type 1 peptides of region B, although differences in the reactivity of these antibodies with human immunodeficiency virus type 2 and simian immunodeficiency virus strain mac were detectable. Recognized epitopes were characterized by computer analysis as described by T.P. Hopp and K.R. Woods (Proc. Natl. Acad. Sci. USA 78:3824-3828, 1981) and P.Y. Chou and G.D. Fasman (Biochemistry 13:222-245, 1974).     

Computer prediction of potential immunogenic determinants from protein amino acid sequence

In proteins, immunogenic determinants that can induce protein-reactive antipeptide antibodies reside mostly in those parts of the molecule that have a high tendency to form beta-turns. A program for an IBM personal computer which predicts protein immunogenic determinants is described. The program predicts potential immunogenic determinants from protein amino acid sequences according to a Chou-Fasman-based probability of a beta-turn occurrence, p greater than 1.5 X 10(-4)(P. Y. Chou and G. D. Fasman, 1978, Adv. Enzymol. 47, 46-148). Oncopeptides (whose efficacy in generating protein-reactive antipeptide antibodies has been described) with a beta-turn probability of p greater than 1.5 X 10(-4) elicited antipeptide antibodies that reacted with the parent oncoprotein at a rate of 96%, thus showing a surprisingly good correlation between the tendency to form a beta-turn and the protein reactivity of antipeptide antibodies. Potential immunogenic determinants were predicted on myohemerythrin and myoglobin.     

Computer-assisted analysis of envelope protein sequences of seven human immunodeficiency virus isolates: prediction of antigenic epitopes in conserved and variable regions.

Independent isolates of human immunodeficiency virus (HIV) exhibit a striking genomic diversity, most of which is located in the viral envelope gene. Since this property of the HIV group of viruses may play an important role in the pathobiology of the virus, we analyzed the predicted amino acid sequences of the envelope proteins of seven different HIV strains, three of which represent sequential isolates from a single patient. By using a computer program that predicts the secondary protein structure and superimposes values for hydrophilicity, surface probability, and flexibility, we identified several potential antigenic epitopes in the envelope proteins of the seven different viruses. Interestingly, the majority of the predicted epitopes in the exterior envelope protein (gp120) were found in regions of high sequence variability which are interspersed with highly conserved regions among the independent viral isolates. A comparison of the sequential viral isolates revealed that changes concerning the secondary structure of the protein occurred only in regions which were predicted to be antigenic, predominantly in highly variable regions. The membrane-associated protein gp41 contains no highly variable regions; about 80% of the amino acids were found to be conserved, and only one hydrophilic area was identified as likely to be accessible to antibody recognition. These findings give insight into the secondary and possible tertiary structure of variant HIV envelope proteins and should facilitate experimental approaches directed toward the identification and fine mapping of HIV envelope proteins.     

Consensus prediction of amyloidogenic determinants in amyloid fibril-forming proteins

We combine the results of three prediction algorithms on a test set of 21 amyloidogenic proteins to predict amyloidogenic determinants. Two prediction algorithms are recently developed prediction algorithms of amyloidogenic stretches in protein sequences, whereas the third is a secondary structure prediction algorithm capable of identifying 'conformational switches' (regions that have both the propensity for alpha-helix and beta-sheet). Surprisingly, the results of prediction agree well and also agree with experimentally investigated amyloidogenic regions. Furthermore, they suggest several previously not identified amino acid stretches as potential amyloidogenic determinants. Most predicted (and experimentally observed) amyloidogenic determinants reside on the protein surface of relevant solved crystal structures. It appears that a consensus prediction algorithm is more objective than individual prediction methods alone.     

Prediction of quaternary structure by analysis of hot spot residues in protein-protein interfaces: the case of anthranilate phosphoribosyltransferases

It is an important goal of computational biology to correctly predict the association state of a protein based on its amino acid sequence and the structures of known homologues. We have pursued this goal on the example of anthranilate phosphoribosyltransferase (AnPRT), an enzyme that is involved in the biosynthesis of the amino acid tryptophan. Firstly, known crystal structures of naturally occurring homodimeric AnPRTs were analyzed using the Protein Interfaces, Surfaces, and Assemblies (PISA) service of the European Bioinformatics Institute (EBI). This led to the identification of two hydrophobic “hot spot” amino acids in the protein-protein interface that were predicted to be essential for self-association. Next, in a comprehensive multiple sequence alignment (MSA), naturally occurring AnPRT variants with hydrophilic or charged amino acids in place of hydrophobic residues in the two hot spot positions were identified. Representative variants were characterized in terms of thermal stability, enzymatic activity, and quaternary structure. We found that AnPRT variants with charged residues in both hot spot positions exist exclusively as monomers in solution. Variants with hydrophilic amino acids in one hot spot position occur in both forms, monomer and dimer. The results of the present study provide a detailed characterization of the determinants of the AnPRT monomer-dimer equilibrium and show that analysis of hot spots in combination with MSAs can be a valuable tool in prediction of protein quaternary structures.     

The antigenic index: a novel algorithm for predicting antigenic determinants

In this paper, we introduce a computer algorithm which can beused to predict the topological features of a protein directlyfrom its primary amino acid sequence. The computer program generatesvalues for surface accessibility parameters and combines thesevalues with those obtained for regional backbone flexibilityand predicted secondary structure. The output of this algorithm,the antigenic index, is used to create a linear surface contourprofile of the protein. Because most, if not all, antigenicsites are located within surface exposed regions of a protein,the program offers a reliable means of predicting potentialantigenic determinants. We have tested the ability of this programto generate accurate surface contour profiles and predict antigenicsites from the linear amino acid sequences of well-characterizedproteins and found a strong correlation between the predictionsof the antigenic index and known structural and biological data. Received on August 17, 1987; accepted on December 31, 1987     

The importance of soil and air temperature in spring phenoclimatic modelling

Mathematical models utilizing average Calendar date, geographic parameters, and accumulated soil and/or air heat units were tested for predicting the date of leaf emergence ofSyringa chinensis, CV Red Rothamagensis, lilac. Forty five sets of data, from 7 locations in New York state, were used. A model accumulating daily heat units above a base temperature of 5.5°C, gave the best prediction, with a standard error of ± 6.0 days.Regional research projects NE-35 and NE-69 have collected dates of first leaf and three stages of bloom for the Red Rothomagensis lilac since 1965. Data from approximately 300 sites were reported by Hopp, Blair and Hickin (1973). Hopp and Blair (1973) developed models to predict the average date of the lilac phenological events based on latitude, longitude and elevation. Models using only geographic input do not have the capability to predict the year to year variations that occur in spring development of perennial plants. Early and late biological springs are associated with variations in the weather. Such factors as air temperature, solar radiation, precipitation, soil temperature and wind all have an effect on the environment sensed by the plant, and thus may influence the rate of development.A common method of predicting a spring phenological event is by accumulating heat units above a given base temperature. This proved to be useful for predicting maturity of seeded crops when accumulations are started on either the day of planting or the date of seedling emergence. There is no seeding date from which to start heat unit accumulations for perennial plants emerging from winter dormancy. Thus, the problem of evaluating the base temperature is compounded by variability introduced when different start dates are used. The first phenological event to be observed in the spring is the main one to present the problem of start date variation. This event can be used as a base line for predicted subsequent events from heat unit accumulations.This study is concerned with the emergence of the first leaf of the Red Rothomagensis lilac. This event, as defined by Hopp, Vittum and Canfield (1969) is "the date when the widest part of the newly emerging leaf has grown beyond the ends of its opening winter bud scales". We evaluated mathematical models utilizing soil and air temperature for predicting the first leaf phenophase.Presented at the Seventh International Biometeorological Congress, 17–23 August 1975, College Park, Maryland, USA.     

TM-align: a protein structure alignment algorithm based on the TM-score

We have developed TM-align, a new algorithm to identify the best structural alignment between protein pairs that combines the TM-score rotation matrix and Dynamic Programming (DP). The algorithm is approximately 4 times faster than CE and 20 times faster than DALI and SAL. On average, the resulting structure alignments have higher accuracy and coverage than those provided by these most often-used methods. TM-align is applied to an all-against-all structure comparison of 10 515 representative protein chains from the Protein Data Bank (PDB) with a sequence identity cutoff <95%: 1996 distinct folds are found when a TM-score threshold of 0.5 is used. We also use TM-align to match the models predicted by TASSER for solved non-homologous proteins in PDB. For both folded and misfolded models, TM-align can almost always find close structural analogs, with an average root mean square deviation, RMSD, of 3 A and 87% alignment coverage. Nevertheless, there exists a significant correlation between the correctness of the predicted structure and the structural similarity of the model to the other proteins in the PDB. This correlation could be used to assist in model selection in blind protein structure predictions. The TM-align program is freely downloadable at http://bioinformatics.buffalo.edu/TM-align.     

Data-sieving hydrophobicity plots

Hydrophobicity plots provide clues to the tertiary structure of proteins (J. Kyte and R. F. Doolittle, 1982, J. Mol. Biol. 157, 105; C. Chothia, 1984, Annu. Rev. Biochem. 53, 537; T. P. Hopp and K. R. Woods, 1982, Proc. Natl. Acad. Sci. USA 78, 3824). To render domains more visible, the raw data are usually smoothed using a running mean of between 5 and 19 amino acids. This type of smoothing still incorporates two disadvantages. First, peculiar residues that do not share the properties of most of the amino acids in the domain may prevent its identification. Second, as a low-pass frequency filter the running mean smoothes sudden transitions from one domain, or phase, to another. Data-sieving is described here as an alternative method for identifying domains within amino acid sequences. The data-sieve is based on a running median and is characterized by a single parameter, the mesh size, which controls its resolution. It is a technique that could be applied to other series data and, in multidimensions, to images in the same way as a median filter.     

CARd: Carbon distribution analysis program for protein sequences

Carbon distribution is responsible for stability and structure of proteins. Arrangement of carbon along the protein sequence is depends on how the amino acids are organized and is guided by mRNAs. An atomic level revision is important for understanding these codes. This will ultimately help in identification of disorders and suggest mutations. For this purpose a carbon distribution analysis program has been developed. This program captures the hydrophobic / hydrophilic / disordered regions in a protein. The program gives accurate results. The calculations are precise and sensitive to single amino acid resolution. This program is to help in mutational studies leading to protein stabilisation.     

The structural characteristics of human preprotein translocase of the inner mitochondrial membrane Tim23: implications for its physiological activities

The preprotein translocase of the inner mitochondrial membrane (TIM23 complex) is the main entry gate for proteins of the matrix and the inner membrane. Tim23 forms a pore for preprotein transportation in TIM23 complex, which spans the inner membrane with transmembrane segments and exposes a hydrophilic domain in the intermembrane space. In this study, we expressed and purified the intermembrane space (IMS) domain of human Tim23 (Tim23(IMS)). The far-UV CD spectra of Tim23(IMS) in native and denatured states revealed that the protein has a limited secondary structure and a not well-defined tertiary packing. Its Stokes radius was larger than both its expected size as a folded globular protein and the size determined by size exclusion chromatography. A large increase in 8-anilino-1-naphthalene-sulfonate (ANS) fluorescence (>50-fold) was observed, indicating that hydrophobic clusters are exposed at its surface. And GlobPlot/DisEMBL program predicted that the protein is in a loose folding state. We therefore conclude that, the non-bound hydrophilic domain of the human Tim23 is in a molten globule configuration with marginal stability. Furthermore, size exclusion chromatography and sedimentation equilibrium analysis showed that Tim23(IMS) exists as a dimer. And the results, showed by ANS binding and fluorescence quenching, indicated that a pH-dependent conformational change of Tim23(IMS) occurs, and at pH 4 and 3, it forms a compact structure.     

Prediction of 3-dimensional structure of salivary odorant-binding protein-2 of the mosquito Culex quinquefasciatus, the vector of human lymphatic filariasis

Olfaction of insects is currently recognized as the major area of research for developing novel control strategies to prevent mosquito-borne infections. A 3-dimensional model (3D) was developed for the salivary gland odorant-binding protein-2 of the mosquito Culex quinquefasciatus, a major vector of human lymphatic filariasis. A homology modeling method was used for the prediction of the structure. For the modeling, two template proteins were obtained by mGenTHERADER, namely the high-resolution X-ray crystallography structure of a pheromone-binding protein (ASP1) of Apis mellifera L., [1R5R:A] and the aristolochene synthase from Penicillium roqueforti [1DI1:B]. By comparing the template protein a rough model was constructed for the target protein using MODELLER, a program for comparative modelling. The structure of OBP of the mosquito Culex quinquefasciatus resembles the structure of pheromone-binding protein ASP1 of Apis mellifera L., [1R5R:A]. From Ramachandran plot analysis it was found that the portion of residues falling into the most favoured regions was 86.0%. The predicted 3-D model may be further used in characterizing the protein in wet laboratory.     

Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment‐based local and energy‐based nonlocal profiles

Locating sequences compatible with a protein structural fold is the well‐known inverse protein‐folding problem. While significant progress has been made, the success rate of protein design remains low. As a result, a library of designed sequences or profile of sequences is currently employed for guiding experimental screening or directed evolution. Sequence profiles can be computationally predicted by iterative mutations of a random sequence to produce energy‐optimized sequences, or by combining sequences of structurally similar fragments in a template library. The latter approach is computationally more efficient but yields less accurate profiles than the former because of lacking tertiary structural information. Here we present a method called SPIN that predicts Sequence Profiles by Integrated Neural network based on fragment‐derived sequence profiles and structure‐derived energy profiles. SPIN improves over the fragment‐derived profile by 6.7% (from 23.6 to 30.3%) in sequence identity between predicted and wild‐type sequences. The method also reduces the number of residues in low complex regions by 15.7% and has a significantly better balance of hydrophilic and hydrophobic residues at protein surface. The accuracy of sequence profiles obtained is comparable to those generated from the protein design program RosettaDesign 3.5. This highly efficient method for predicting sequence profiles from structures will be useful as a single‐body scoring term for improving scoring functions used in protein design and fold recognition. It also complements protein design programs in guiding experimental design of the sequence library for screening and directed evolution of designed sequences. The SPIN server is available at http://sparks‐lab.org . Proteins 2014; 82:2565–2573. © 2014 Wiley Periodicals, Inc.     

Role of the coronavirus E viroporin protein transmembrane domain in virus assembly

Coronavirus envelope (E) proteins are small (approximately 75- to 110-amino-acid) membrane proteins that have a short hydrophilic amino terminus, a relatively long hydrophobic membrane domain, and a long hydrophilic carboxy-terminal domain. The protein is a minor virion structural component that plays an important, not fully understood role in virus production. It was recently demonstrated that the protein forms ion channels. We investigated the importance of the hydrophobic domain of the mouse hepatitis coronavirus (MHV) A59 E protein. Alanine scanning insertion mutagenesis was used to examine the effect of disruption of the domain on virus production in the context of the virus genome by using a MHV A59 infectious clone. Mutant viruses exhibited smaller plaque phenotypes, and virus production was significantly crippled. Analysis of recovered viruses suggested that the structure of the presumed alpha-helical structure and positioning of polar hydrophilic residues within the predicted transmembrane domain are important for virus production. Generation of viruses with restored wild-type helical pitch resulted in increased virus production, but some exhibited decreased virus release. Viruses with the restored helical pitch were more sensitive to treatment with the ion channel inhibitor hexamethylene amiloride than were the more crippled parental viruses with the single alanine insertions, suggesting that disruption of the transmembrane domain affects the functional activity of the protein. Overall the results indicate that the transmembrane domain plays a crucial role during biogenesis of virions.     

Homology modeling of an antifungal metabolite plipastatin synthase from the Bacillus subtilis 168

Lipopeptides have a widespread role in different pathways of Bacillus subtilis; they can act as antagonists, spreader and immunostimulators. Plipastatin, an antifungal antibiotic, is one of the most important lipopeptide nonribosomly produced by Bacillus subtilis. Plipastatin has strong fungitoxic activity and involve in inhibition of phospholipase A2 and biofilm formation. For better understanding of the molecule and pathway by which lipopeptide plipastatin is synthesized, we present a computationally predicted structure of plipastatin using homology modeling. Primary and secondary structure analysis suggested that ppsD is a hydrophilic protein containing a significant proportion of alpha helices, and subcellular localization predictions suggested it is a cytoplasmic protein. The tertiary structure of protein (plipastatin synthase subunit D) was predicted by homology modeling. The results suggest a flexible structure which is also an important characteristic of active enzymes enabling them to bind various cofactors and substrates for proper functioning. Validation of 3D structure was done using Ramachandran plot ProsA-web and QMEAN score.This predicted information will help in better understanding of mechanisms underlying plipastatin synthase subunit D synthesis. Plipastatin can be used as an inhibitor of various fungal diseases in plants.