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M J Sternberg

Publications and source records attributed to M J Sternberg.

At least 91 records · Page 5Linked to original sources
PubMed1992

Protein secondary structure prediction using logic-based machine learning.

Many attempts have been made to solve the problem of predicting protein secondary structure from the primary sequence but the best performance results are still disappointing. In this paper, the use of a machine learning algorithm which allows relational descriptions is shown to lead to improved performance. The Inductive Logic Programming computer program, Golem, was applied to learning secondary structure prediction rules for alpha/alpha domain type proteins. The input to the program consisted of 12 non-homologous proteins (1612 residues) of known structure, together with a background knowledge describing the chemical and physical properties of the residues. Golem learned a small set of rules that predict which residues are part of the alpha-helices--based on their positional relationships and chemical and physical properties. The rules were tested on four independent non-homologous proteins (416 residues) giving an accuracy of 81% (+/- 2%). This is an improvement, on identical data, over the previously reported result of 73% by King and Sternberg (1990, J. Mol. Biol., 216, 441-457) using the machine learning program PROMIS, and of 72% using the standard Garnier-Osguthorpe-Robson method. The best previously reported result in the literature for the alpha/alpha domain type is 76%, achieved using a neural net approach. Machine learning also has the advantage over neural network and statistical methods in producing more understandable results.

Amino Acid Sequence↗
PubMed1991

A simple method to generate non-trivial alternate alignments of protein sequences.

A major problem in sequence alignments based on the standard dynamic programming method is that the optimal path does not necessarily yield the best equivalencing of residues assessed by structural or functional criteria. An algorithm is presented that finds suboptimal alignments of protein sequences by a simple modification to the standard dynamic programming method. The standard pairwise weight matrix elements are modified in order to penalize, but not eliminate, the equivalencing of residues obtained from previous alignments. The algorithm thereby yields a limited set of alternate alignments that can differ considerably from the optimal. The approach is benchmarked on the alignments of immunoglobulin domains. Without a prior knowledge of the optimal choice of gap penalty, one of the suboptimal alignments is shown to be more accurate than the optimal.

Algorithms↗
PubMed1991

PROMOT: a FORTRAN program to scan protein sequences against a library of known motifs.

Information about the three-dimensional structure or function of a newly determined protein sequence can be obtained if the protein is found to contain a characterized motif or pattern of residues. Recently a database (PROSITE) has been established that contains 337 known motifs encoded as a list of allowed residue types at specific positions along the sequence. PROMOT is a FORTRAN computer program that takes a protein sequence and examines if it contains any of the motifs in PROSITE. The program also extends the definitions of patterns beyond those used in PROSITE to provide a simple, yet flexible, method to scan either a PROSITE or a user-defined pattern against a protein sequence database.

Amino Acid Sequence↗
PubMed1991

A three-dimensional molecular template for substrates of human cytochrome P450 involved in debrisoquine 4-hydroxylation.

A three-dimensional molecular template has been generated for substrates of human debrisoquine 4-hydroxylase cytochrome P450 (CYP2D6). This template defines the stereochemical requirements for CYP2D6 substrates in terms of the volume occupied and positions of key atoms. The modelling was based on the X-ray crystallographic coordinates of the location of the attacked C5 atom of camphor in relation to the haem in cytochrome P450 cam. Interactive molecular graphics combined with energy calculations were used to identify allowed conformers to superpose known CYP2D6 substrates to yield a molecular template. This model takes into account the site of attack of the known substrates and the requirement for a protonated nitrogen atom to interact with an anion site of the protein. A nitrogen-anion distance of between 2.5 and 4.5 A was allowed for the interaction. The substrates modelled were cardiovascular drugs (debrisoquine, sparteine, guanoxan and perhexiline), beta-adrenergic blocking agents (bufuralol and propranolol), tricyclic anti-depressants (desipramine, amitriptyline and nortriptyline) and other miscellaneous compounds (phenformin, methoxy-amphetamine, codeine and dextromethorphan). The template generated in this manner was then used to determine the likelihood that certain other compounds were substrates for CYP2D6. A carcinogenic protein pyrolysate product, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), did not fit the template and is therefore unlikely to be activated by this enzyme. A potent carcinogen in tobacco smoke, 4-(N-methyl-N-nitrosamino)-1-(3-pyridyl)-1-butanone (NNK), fitted the template but could not be modelled to form a favourable nitrogen-anion interaction. Experimental substrate competition studies also showed that NNK is unlikely to be a CYP2D6 substrate. It was also shown that the widely used drug for treatment of breast cancer, trans-1-(4-beta-dimethylaminoethoxyphenyl)-,2-diphenyl-1-ene (tamoxifen), did not fit the molecular template and is unlikely to be metabolized by CYP2D6. Coordinates of the template are available.

Camphor↗
PubMed1991

A predicted three-dimensional structure of human cytochrome P450: implications for substrate specificity.

A three-dimensional structure for human cytochrome P450IA1 was predicted based on the crystal coordinates of cytochrome P450cam from Pseudomonas putida. As there was only 15% residue identity between the two enzymes, additional information was used to establish an accurate sequence alignment that is a prerequisite for model building. Twelve representative eukaryotic sequences were aligned and a net prediction of secondary structure was matched against the known alpha-helices and beta-sheets of P450cam. The cam secondary structure provided a fixed main-chain framework onto which loops of appropriate length from the human P450IA1 structure were added. The model-built structure of the human cytochrome conformed to the requirements for the segregation of polar and nonpolar residues between the core and the surface. The first 44 residues of human cytochrome P450 could not be built into the model and sequence analysis suggested that residues 1-26 formed a single membrane-spanning segment. Examination of the sequences of cytochrome P450s from distinct gene families suggested specific residues that could account for the differences in substrate specificity. A major substrate for P450IA1, 3-methyl-cholanthrene, was fitted into the proposed active site and this planar aromatic molecule could be accommodated into the available cavity. Residues that are likely to interact with the haem were identified. The sequence similarity between 59 eukaryotic enzymes was represented as a dendrogram that in general clustered according to gene family. Until a crystallographic structure is available, this model-building study identifies potential residues in cytochrome P450s important in the function of these enzymes and these residues are candidates for site-directed mutagenesis.

Amino Acid Sequence↗
PubMed1991

Prediction of ATP/GTP-binding motif: a comparison of a perceptron type neural network and a consensus sequence method [corrected].

Neural networks have been applied to a number of protein structure problems. In some applications their success has not been substantiated by a comparison with the performance of a suitable alternative statistical method on the same data. In this paper, a two-layer feed-forward neural network has been trained to recognize ATP/GTP-binding [corrected] local sequence motifs. The neural network correctly classified 78% of the 349 sequences used. This was much better than a simple motif-searching program. A more sophisticated statistical method was developed, however, which performed marginally better (80% correct classification) than the neural network. The neural network and the statistical method performed similarly on sequences of varying degrees of homology. These results do not imply that neural networks, especially those with hidden layers, are not useful tools, but they do suggest that two-layer networks in particular should be carefully tested against other statistical methods.

Adenosine Triphosphate↗
PubMed1990

Machine learning approach for the prediction of protein secondary structure.

PROMIS (protein machine induction system), a program for machine learning, was used to generalize rules that characterize the relationship between primary and secondary structure in globular proteins. These rules can be used to predict an unknown secondary structure from a known primary structure. The symbolic induction method used by PROMIS was specifically designed to produce rules that are meaningful in terms of chemical properties of the residues. The rules found were compared with existing knowledge of protein structure: some features of the rules were already recognized (e.g. amphipathic nature of alpha-helices). Other features are not understood, and are under investigation. The rules produced a prediction accuracy for three states (alpha-helix, beta-strand and coil) of 60% for all proteins, 73% for proteins of known alpha domain type, 62% for proteins of known beta domain type and 59% for proteins of known alpha/beta domain type. We conclude that machine learning is a useful tool in the examination of the large databases generated in molecular biology.

Amino Acid Sequence↗
PubMed1990

A molecular model for the enzyme cytochrome P450(17 alpha), a major target for the chemotherapy of prostatic cancer.

The enzyme cytochrome P450(17 alpha) catalyses two key steps in the biosynthesis of the androgens from pregnanes: the 17 alpha hydroxylation step and the subsequent 17-20 lyase reaction. Using a variety of techniques, including sequence alignment, secondary structure prediction, molecular mechanics and molecular dynamics, we have constructed a model for the three-dimensional structure of P450(17 alpha) based on that of P450cam, the only cytochrome P450 enzyme for which the crystal structure is known. The model suggests the possibility of two modes of binding of steroid substrates at the active site, perhaps reflecting the dual functionality of the enzyme.

Amino Acid Sequence↗
PubMed1990

Flexible protein sequence patterns. A sensitive method to detect weak structural similarities.

The concept of a flexible protein sequence pattern is defined. In contrast to conventional pattern matching, template or sequence alignment methods, flexible patterns allow residue patterns typical of a complete protein fold to be developed in terms of residue positions (elements), separated by gaps of defined range. An efficient dynamic programming algorithm is presented to enable the best alignment(s) of a pattern with a sequence to be identified. The flexible pattern method is evaluated in detail by reference to the globin protein family, and by comparison to alignment techniques that exploit single sequence, multiple sequence and secondary structural information. A flexible pattern derived from seven globins aligned on structural criteria successfully discriminates all 345 globins from non-globins in the Protein Identification Resource database. Furthermore, a pattern that uses helical regions from just human alpha-haemoglobin identified 337 globins compared to 318 for the best non-pattern global alignment method. Patterns derived from successively fewer, yet more highly conserved positions in a structural alignment of seven globins show that as few as 38 residue positions (25 buried hydrophobic, 4 exposed and 9 others) may be used to uniquely identify the globin fold. The study suggests that flexible patterns gain discriminating power both by discarding regions known to vary within the protein family, and by defining gaps within specific ranges. Flexible patterns therefore provide a convenient and powerful bridge between regular expression pattern matching techniques and more conventional local and global sequence comparison algorithms.

Amino Acid Sequence↗
PubMed1990

Prediction of protein structure from sequence.

Methods to predict the three-dimensional structure of a protein from its sequence are reviewed. The approaches to derive information about the local conformation from the local sequence include hydrophobicity plots, secondary structure prediction and the identification of short, functional sequence motifs. The most reliable method of tertiary structure prediction is model building from the experimentally determined coordinates of a protein with an homologous sequence. This approach is illustrated by a prediction of the three-dimensional structure of human cytochrome P450-IA1. If no known homologous structure is available, then the only approach is to suggest models for the tertiary fold of proteins by packing together predicted secondary structures. A three-dimensional model for the dimerisation of the transmembrane alpha-helices of neu, a tyrosine kinase growth factor receptor, is described. In general, structure prediction can suggest approaches for regulating protein activity that may lead to new pharmaceutical therapies for cancer.

Amino Acid Sequence↗
PubMed1990

A sequence motif in the transmembrane region of growth factor receptors with tyrosine kinase activity mediates dimerization.

A mechanism by which ligand binding to the extracellular domain of a growth factor receptor causes activation of its cytoplasmic tyrosine kinase domain is that binding promotes receptor dimerization. Recently we proposed a model in which dimerization of the transmembrane alpha-helices in one member of this family, rat neu, is mediated by the presence of three specific residues. This paper shows that a similar sequence motif is observed in 18 of the 20 transmembrane alpha-helices of the tyrosine kinase family of growth factor receptors. The motif encompasses a five residue segment in which position 0 (P0) requires a small side chain (Gly, Ala, Ser, Thr or Pro), P3 an aliphatic side chain (Ala, Val, Leu or Ile) and P4 only the smallest side chains (Gly or Ala). In addition other features of the transmembrane sequences are reported. It is concluded that the dimerization of transmembrane alpha-helices may be a general mechanism of tyrosine kinase activation in this family of growth factor receptors.

Amino Acid Sequence↗
PubMed1990

Inter-species sequence conservation of single-spanning transmembrane regions.

The extent of inter-species sequence identity in single-spanning transmembrane regions of integral membrane proteins was evaluated. The sequences of the 32 human transmembrane regions were compared with the respective rodent homologues. The identity between homologous transmembrane regions ranged from 32 to 100%, compared with a mean value of 14% identity between unrelated transmembrane sections. On average the identity between homologous transmembrane regions is slightly higher than for the rest of the chain. These values suggest that, in general, there are structural and/or functional constraints on the transmembrane regions beyond the simple requirement to act as a passive, nonpolar, connecting region across the cell membrane. Although there is limited experimental evidence available, the three transmembrane regions (CD2 antigen, MHC class I and ICAM-1) with particularly low values of inter-species identity (less than 50%) are probably not involved in an interaction with another transmembrane section in the same cell.

Amino Acid Sequence↗
PubMed1990

Local protein sequence similarity does not imply a structural relationship.

A database search often will find a seemingly strong sequence similarity between two fragments of proteins that are not expected to have an evolutionary or functional relationship. It is tempting to suggest that the two fragments will adopt a similar conformation due to a common pattern of residues that dictate a particular substructure. To investigate the likelihood of such a structural similarity, local sequence similarities between proteins of known conformation were identified by a standard database search algorithm. Significant sequence similarity was identified as when the chance probability of obtaining the relatedness score from a scan of the entire database was less than 1%. In this region both true homologies and false homologies are detected. A total of 69 false homologies was located of length between 20 and 262 aligned positions. Many of these alignments had approximately 25% sequence identity and a further 25% of conservative changes. However, the results show in general these aligned fragments did not have a significant similarity in secondary or tertiary structure. Thus local sequence does not indicate a structural similarity when there is neither an evolutionary nor functional explanation to support this. Accordingly structure predictions based on finding a local sequence similarity with an evolutionary unrelated protein of known conformation are unlikely to be valid.

Algorithms↗