Parameter relation rows: a query system for protein structure function relationships

In the course of molecular modeling or mutant prediction oneoften wants quick answers to questions such as: ‘Are thereany residues in a beta-strand that point into an internal cavity,and are highly mutable?;’ ‘Are there large polarresidues in a helix that make a contact with a hydrophobic residuein a sheet, and don't make the maximal number of hydrogen bonds?’or ‘Which hydrophobic residues are in a helix with a largehydrophobic moment, and make a contact with a co-factor, butat the same time still have a large accessible surface?’.I describe here a method to get answers to these kinds of questionsin a very quick and easy manner. The method described is partlybased on the principles used in the design of relational databases,and its mode of operation is similar to the query methods usedin a relational database environment. Although designed foraiding in molecular modeling, its applicability is much moregeneral. The method has been implemented as part of a largemolecular modeling package which copes with the numerous problemsin systematic handling of protein structures, e.g. residue numbering.This also implies that many normal tools such as graphical analyses,I/O facilities, etc. are available on-line.     

A study of simulated annealing protocols for use with molecular dynamics in protein structure prediction

The method of simulated annealing can be of use in protein structureprediction by homology modelling where side chain conformationsmust be predicted. In this study an attempt has been made tooptimize a molecular dynamics method for this purpose. Heatingand cooling protocols to maximize the accuracy of the predictionshave been developed. The optimized protocol involves coolingfrom 3000 to 0 K over 20 ps while simultaneously introducingthe non-bonded energy term. The use of a 'soft' non-bonded interactionenergy term in place of a standard 6–12 potential is foundto be important. The reliability of the predictions has beenanalysed in terms of the environment of the residues (solventaccessibility) and the degree of uncertainty in the structure(number of unknown torsion angles). Depending on these factorsthe percentage of unknown side chain torsion angles that arecorrectly predicted within 30° ranges from –50 to75%. Potential problems and limitations of the method are discussed.     

A neural network based predictor of residue contacts in proteins

We describe a method based on neural networks for predictingcontact maps of proteins using as input chemico-physical andevolutionary information. Neural networks are trained on a dataset comprising the contact maps of 200 non-homologous proteinsof well resolved three-dimensional structures. The systems learnthe association rules between the covalent structure of eachprotein and its correspondent contact map by means of a standardback propagation algorithm. Validation of the predictor on thetraining set and on 408 proteins of known structure which arenot homologous to those contained in the training set indicatethat this method scores higher than statistical approaches previouslydescribed and based on correlated mutations and sequence information.     

Computational analysis of alpha-helical membrane protein structure: implications for the prediction of 3D structural models

Relatively little has been known about the structure of alpha-helical membrane proteins, since until recently few structures had been crystallized. These limited data have restricted structural analyses to the prediction of secondary structure, rather than tertiary folds. In order to address this, this paper describes an analysis of the 23 available membrane protein structures. A number of findings are made that are of particular relevance to transmembrane helix packing: (1) on average lipid-tail-accessible transmembrane residues are significantly more hydrophobic, less conserved and contain different residue types to buried residues; (2) charged residues are not always buried and, when accessible to membrane lipid tails, few are paired with another charge and instead they often interact with phospholipid head-groups or with other residue types; (3) a significant proportion of lipid-tail-accessible charged and polar residues form hydrogen bonds only with residues one turn away in the same helix (intra-helix); (4) pore-lining residues are usually hydrophobic and it is difficult to distinguish them from buried residues in terms of either residue type or conservation; and (5) information was gained about the proportion of helices that tend to contribute to lining a pore and the resulting pore diameter. These findings are discussed with relevance to the prediction of membrane protein 3D structure.     

Quantification of secondary structure prediction improvement using multiple alignments

The use of multiple sequence alignments for secondary structurepredictions is analysed. Seven different protein families, containingonly sequences of known structure, were considered to providea range of alignment and prediction conditions. Using alignmentsobtained by spatial superposition of main chain atoms in knowntertiary protein structures allowed a mean of 8% in secondarystructure prediction accuracy, when compared to those obtainedfrom the individual sequences. Substitution of these alignmentsby those determined directly from an automated sequence alignmentalgorithm showed variations in the prediction accuracy whichcorrelated with the quality of the multiple alignments and distanceof the primary sequence. Secondary structure predictions canbe reliably improved using alignments from an automatic alignmentprocedure with a mean increase of 6.87percnt;, giving an overallprediction accuracy of 68.5%, if there is a minimum of 25% sequenceidentity between all sequences in a family.     

Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction

De novo protein structure prediction plays an important role in studies of helical membrane proteins as well as structure-based drug design efforts. Developing an accurate scoring function for protein structure discrimination and validation remains a current challenge. Network approaches based on overall network patterns of residue packing have proven useful in soluble protein structure discrimination. It is thus of interest to apply similar approaches to the studies of residue packing in membrane proteins. In this work, we first carried out such analysis on a set of diverse, non-redundant and high-resolution membrane protein structures. Next, we applied the same approach to three test sets. The first set includes nine structures of membrane proteins with the resolution worse than 2.5 A; the other two sets include a total of 101 G-protein coupled receptor models, constructed using either de novo or homology modeling techniques. Results of analyses indicate the two criteria derived from studying high-resolution membrane protein structures are good indicators of a high-quality native fold and the approach is very effective for discriminating native membrane protein folds from less-native ones. These findings should be of help for the investigation of the fundamental problem of membrane protein structure prediction.     

Secondary structure prediction for modelling by homology

An improved method of secondary structure prediction has beendeveloped to aid the modelling of proteins by homology. Selecteddata from four published algorithms are scaled and combinedas a weighted mean to produce consensus algorithms. Each consensusalgorithm is used to predict the secondary structure of a proteinhomologous to the target protein and of known structure. Bycomparison of the predictions to the known structure, accuracyvalues are calculated and a consensus algorithm chosen as theoptimum combination of the composite data for prediction ofthe homologous protein. This customized algorithm is then usedto predict the secondary structure of the unknown protein. Inthis manner the secondary structure prediction is initiallytuned to the required protein family before prediction of thetarget protein. The method improves statistical secondary structureprediction and can be incorporated into more comprehensive systemssuch as those involving consensus prediction from multiple sequencealignments. Thirty one proteins from five families were usedto compare the new method to that of Garnier, Osguthorpe andRobson (GOR) and sequence alignment. The improvement over GORis naturally dependent on the similarity of the homologous protein,varying from a mean of 3% to 7% with increasing alignment significancescore.     

Search for the most stable folds of protein chains: I. Application of a self-consistent molecular field theory to a problem of protein three-dimensional structure prediction

We present a general approach to the prediction of 3-D foldsof protein chains from their amino acid sequences. The approachis based on the use of the self-consistent molecular field theoryfor long-range interactions, the use of 1-D statistical mechanicsfor short-range interactions and on the discovery that thereis and should only be a relatively small discrete set of foldingpatterns. This makes it possible to examine the full varietyof ‘potentially stable’ folds and to determine thethermodynamically stable structure. In this paper, we give thegeneral theoretical background of the approach. The encouragingresults of the application of this approach to ß-domainsare described in another paper.     

Potassium channels: a computer prediction of structure and selectivity

Model structures for the pore of the potassium channels Shakerand ROMK1 are predicted. The models arise from computer simulationsand suggest reasons for the striking selectivity of these channelsfor K+ and the blocking of ROMK1 by internal Mg²⁺. The modelledstructure of the Shaker pore is supported by mutagenesis data.The mutagenesis experiments indicate the side chains responsiblefor binding to blocking agents [tetraethylammonium (TEA) andcharybdotoxin (CTX)] and the model has these side chains suitablyoriented for binding. An aromatic K+ binding site part way downthe pore is also predicted by the Shaker pore model.     

Secondary structure prediction: combination of three different methods

A combination of three complementary secondary structure predictionmethods is presented. The methods used are the GOR III method,the Homologue method and a new method, the bit pattern method,which is based on hydrophilic/hydrophobic residue patterns.For this purpose a hydropathy scale was developed and is presentedhere. The combination algorithm (Combine method) was designedto take the best results of each method and use their differencesin order to improve the prediction. The combination yields 65.5%correctly predicted residues in three states: -helix (H), ß-strand(E) and aperiodic structure (C) which is an improvement rangingfrom 2.5 to 6.5% compared with the individual methods when testedwith a 67-polypeptide chain database. Seventy-five per centof the regular secondary structure (H and E) runs are correctlylocated and ß-sheet runs are much better located bythe Combine method in comparison to the other methods.     

Structure prediction of the EcoRV DNA methyltransferase based on mutant profiling, secondary structure analysis, comparison with known structures of methyltransferases and isolation of catalytically inactive single mutants

The EcoRV DNA methyltransferase (M·EcoRV) is an -adeninemethyltransferase. We have used two different programs to predictthe secondary structure of M·EcoRV. The resulting consensusprediction was tested by a mutant profiling analysis. 29 neutralmutations of M·EcoRV were generated by five cycles ofrandom mutagenesis and selection for active variants to increasethe reliability of the prediction and to get a secondary structureprediction for some ambiguously predicted regions. The predictedconsensus secondary structure elements could be aligned to thecommon topology of the structures of the catalytic domains ofM·HhaI and M·TaqI. In a complementary approachwe have isolated nine catalytically inactive single mutants.Five of these mutants contain an amino acid exchange withinthe catalytic domain of M·EcoRV (Val20-Ala, Lys81Arg,Cys192Arg, Asp193Gly, Trp231Arg). The Trp231Arg mutant bindsDNA similarly to wild-type M·EcoRV, but is catalyticallyinactive. Hence this mutant behaves like a bona fide activesite mutant. According to the structure prediction, Trp231 islocated in a loop at the putative active site of M·EcoRV.The other inactive mutants were insoluble. They contain aminoacid exchanges within the conserved amino acid motifs X, IIIor IV in M·EcoRV confirming the importance of these regions.     

Adaptability of restrained molecular dynamics for tertiary structure prediction: application to Crotalus atrox venom phospholipase A2

In order to assess the adaptability and/or applicability ofthe restrained molecular dynamics (RMD) simulation for buildinga possible tertiary structure of a protein from the X-ray crystalstructure of a family reference protein, the tertiary structureprediction of Crotalus atrox venom phospholipase A₂ (PLA₂) wasattempted based on the X-ray crystal structure of bovine pancreaticPLA₂. For the formation of secondary and tertiary structuresfrom the fully extended starting structure, the RMD simulationwith interatomic distance restraints and torsion angle restraints,which were derived from homologous amino acid sequence regionsin the reference protein, was carried out until the molecularsystem was fully equilibrated. The predicted tertiary structureof C.atrox venom PLA₂ was compared with its X-ray crystal structure,and furthermore the utility of this method was discussed byreference to the similar tertiary structure prediction of ß-trypsinfrom the X-ray crystal structure of an elastase.     

A simple approach for protein structure discrimination based on the network pattern of conserved hydrophobic residues

Evolutionarily conserved hydrophobic residues at the core of protein structures are generally assumed to play a structural role in protein folding and stability. Recent studies have implicated that their importance to protein structures is uneven, with a few of them being crucial and the rest of them being secondary. In this work, we explored the possibility of employing this feature of native structures for discriminating non-native structures from native ones. First, we developed a network tool to quantitatively measure the structural contributions of individual amino acid residues. We systematically applied this method to diverse fold-type sets of native proteins. It was confirmed that this method could grasp the essential structural features of native proteins. Next, we applied it to a number of decoy sets of proteins. The results indicate that such an approach indeed identified non-native structures in most test cases. This finding should be of help for the investigation of the fundamental problem of protein structure prediction.     

Predicted secondary structure and membrane topology of the scrapie prion protein

The integral membrane sialoglycoprotein PrP^Sc is the only identifiablecomponent of the scrapie prion. Scrapie in animals and Creutzfeldt-Jakobdisease in humans are transmissible, degenerative neurologicaldiseases caused by prions. Standard predictive strategies havebeen used to analyze the secondary structure of the prion proteinin conjunction with Fourier analysis of the primary sequencehydrophobicities to detect potential amphipathic regions. Severalhydrophobic segments, a proline- and glycine-rich repeat regionand putative glycosylation sites are incorporated into a modelfor the integral membrane topology of PrP. The complete aminoacid sequences of the hamster, human and mouse prion proteinsare compared and the effects of residue substitutions upon thepredicted conformation of the polypeptide chain are discussed.While PrP has a unique primary structure, its predicted secondarystructure shares some interesting features with the serum amyloidA proteins. These proteins undergo a post-translational modificationto yield amyloid A, molecules that share with PrP the abilityto polymerize into birefringent filaments. Our analyses mayexplain some experimental observations on PrP, and suggest furtherstudies on the properties of the scrapie and cellular PrP isoforms.     

When awaiting 'Bio' Champollion: dynamic programming regularization of the protein secondary structure predictions

Predictions of protein secondary structure using current methodsare often unrealistic, i.e. the predicted -helices or ß-strandsare too short. To improve the realism, various heuristic ‘filtering’or ‘smoothing’ methods are used. They are more orless intuitive and are based on ad hoc corrections. We presenta regularization method to obtain a realistic secondary structurefrom predicted propensities. It is based on the known dynamicprogramming algorithm and is quite objective. It can be usedwith any prediction method which yields propensities. The regularizedpredictions conserve well the overall prediction accuracy andimprove the ‘protein-likeness’ of the prediction.     

Predicted structure for the calcium-dependent membrane-binding proteins p35, p36 and p32

A new family of proteins (annexins) that bind to membranes atmicromolar free Ca²⁺ has been recognized. Its members includean EGF-receptor kinase substrate (p35) a retroviral tyrosinekinase substrate (p36), the liver protein endonexin (p32) andan electric ray protein, calelectrin. Each protein containsfour sequence repeats with a further 2-fold Internal homology.Using the predicted secondary structure and pat tern of conservedhydrophobic residues in each repeat, we have built a three-dimensionalmodel that is largely isostruc tural with the known molecularconformation of bovine In testinal calcium-binding protein.The final (energy-refined) model had a core formed from theconserved hydrophobic residues. It differed from ICaBP principallyin the length of the two Ca²⁺ loops with only one loop beingable to bind. The model suuggest a mechanism for interactionof these new Ca²⁺ proteins with phospholipid bilayers.     

Optimal protein library design using recombination or point mutations based on sequence-based scoring functions

In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.     

A predicted three-dimensional structure for the human immunodeficiency virus binding domains of CD4 antigen

A predicted three-dimensional structure of the two N-terminalextracellular domains of human CD4 antigen, a cell surface glycoprotein,is reported. This region of CD4, particularly the first domain,has been identified as containing the binding region for theenvelope gp120 protein of the human immuno-deficiency virus.The model was predicted based on the sequence homology of eachdomain with the variable light chain of immunoglobulins. Theframework ß-sheet regions were taken from the crystalcoordinates of REI. For one region in the first domain of CD4there was an ambiguity in the alignment with REI and two alternatemodels are presented. Loops connecting the framework were modeledfrom fragments selected from a database of main chain coordinatesfrom all known protein structures. Residues identified as involvedin binding gp120 have been located in several other studieswithin the first domain of CD4. Epitopes from eight monoclonalantibodies have been mapped onto residues in both domains. Competitionof these antibodies with each other and with gp120 can be interpretedfrom the structural model.     

The protein threading problem with sequence amino acid interaction preferences is NP-complete

In recent protein structure prediction research there has beena great deal of interest in using amino acid interaction preferences(e.g. contact potentials or potentials of mean force) to align(‘thread’) a protein sequence to a known structuralmotif. An important open question is whether a polynomial timealgorithm for finding the globally optimal threading is possible.We identify the two critical conditions governing this question:(i) variable-length gaps are admitted into the alignment, and(ii) interactions between amino acids from the sequence areadmitted into the score function. We prove that if both theseconditions are allowed then the protein threading decision problem(does there exist a threading with a score K?) is NP-complete(in the strong sense, i.e. is not merely a number problem) andthe related problem of finding the globally optimal proteinthreading is NP-hard. Therefore, no polynomial time algorithmis possible (unless P = NP). This result augments existing proofsthat the direct protein folding problem is NP-complete by providingthe corresponding proof for the ‘inverse’ proteinfolding problem. It provides a theoretical basis for understandingalgorithms currently in use and indicates that computationalstrategies from other NP-complete problems may be useful forpredictive algorithms.