Risk assessment of Soulatrolide and Mammea (A/BA+A/BB) coumarins from Calophyllum brasiliense by a toxicogenomic and toxicological approach.

Calophyllum brasiliense (Calophyllaceae) is a tropical rain forest tree distributed in Central and South America. It is an important source of tetracyclic dipyrano coumarins (Soulatrolide) and Mammea type coumarins. Soulatrolide is a potent inhibitor of HIV-1 reverse transcriptase and displays activity against Mycobacterium tuberculosis. Meanwhile, Mammea A/BA and A/BB, pure or as a mixture, are highly active against several human leukemia cell lines, Trypanosoma cruzi and Leishmania amazonensis. Nevertheless, there are few studies evaluating their safety profile. In the present work we performed toxicogenomic and toxicological analysis for both type of compounds. Soulatrolide, and the Mammea A/BA + A/BB mixture (2.1) were slightly toxic accordingly to Lorke assay classification (DL50 > 3000 mg/kg). After a short-term administration (100 mg/kg/daily, orally, 1 week) liver toxicogenomic analysis revealed 46 up and 72 downregulated genes for Mammea coumarins, and 665 up and 1077 downregulated genes for Soulatrolide. Gene enrichment analysis identified transcripts involved in drug metabolism for both compounds. In addition, network analysis through protein-protein interactions, tissue evaluation by TUNEL assay, and histological examination revealed no tissue damage on liver, kidney and spleen after treatments. Our results indicate that both type of coumarins displayed a safety profile, supporting their use in further preclinical studies to determine its therapeutic potential.

Structure of the FoxM1 DNA-recognition domain bound to a promoter sequence.

FoxM1 is a member of the Forkhead family of transcription factors and is implicated in inducing cell proliferation and some forms of tumorigenesis. It binds promoter regions with a preference for tandem repeats of a consensus 'TAAACA' recognition sequence. The affinity of the isolated FoxM1 DNA-binding domain for this site is in the micromolar range, lower than observed for other Forkhead proteins. To explain these FoxM1 features, we determined the crystal structure of its DNA-binding domain in complex with a tandem recognition sequence. FoxM1 adopts the winged-helix fold, typical of the Forkhead family. Neither 'wing' of the fold however, makes significant contacts with the DNA, while the second, C-terminal, wing adopts an unusual ordered conformation across the back of the molecule. The lack of standard DNA-'wing' interactions may be a reason for FoxM1's relatively low affinity. The role of the 'wings' is possibly undertaken by other FoxM1 regions outside the DBD, that could interact with the target DNA directly or mediate interactions with other binding partners. Finally, we were unable to show a clear preference for tandem consensus site recognition in DNA-binding, transcription activation or bioinformatics analysis; FoxM1's moniker, 'Trident', is not supported by our data.

Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking.

A major problem in genome annotation is whether it is valid to transfer the function from a characterised protein to a homologue of unknown activity. Here, we show that one can employ a strategy that uses a structure-based prediction of protein functional sites to assess the reliability of functional inheritance. We have automated and benchmarked a method based on the evolutionary trace approach. Using a multiple sequence alignment, we identified invariant polar residues, which were then mapped onto the protein structure. Spatial clusters of these invariant residues formed the predicted functional site. For 68 of 86 proteins examined, the method yielded information about the observed functional site. This algorithm for functional site prediction was then used to assess the validity of transferring the function between homologues. This procedure was tested on 18 pairs of homologous proteins with unrelated function and 70 pairs of proteins with related function, and was shown to be 94 % accurate. This automated method could be linked to schemes for genome annotation. Finally, we examined the use of functional site prediction in protein-protein and protein-DNA docking. The use of predicted functional sites was shown to filter putative docked complexes with a discrimination similar to that obtained by manually including biological information about active sites or DNA-binding residues.

Classification of protein disulphide-bridge topologies.

The preferential occurrence of certain disulphide-bridge topologies in proteins has prompted us to design a method and a program, KNOT-MATCH, for their classification. The program has been applied to a database of proteins with less than 65% homology and more than two disulphide bridges. We have investigated whether there are topological preferences that can be used to group proteins and if these can be applied to gain insight into the structural or functional relationships among them. The classification has been performed by Density Search and Hierarchical Clustering Techniques, yielding thirteen main protein classes from the superimposition and clustering process. It is noteworthy that besides the disulphide bridges, regular secondary structures and loops frequently become correctly aligned. Although the lack of significant sequence similarity among some clustered proteins precludes the easy establishment of evolutionary relationships, the program permits us to find out important structural or functional residues upon the superimposition of two protein structures apparently unrelated. The derived classification can be very useful for finding relationships among proteins which would escape detection by current sequence or topology-based analytical algorithms.

The crystal structure of the inhibitor-complexed carboxypeptidase D domain II and the modeling of regulatory carboxypeptidases.

The three-dimensional crystal structure of duck carboxypeptidase D domain II has been solved in a complex with the peptidomimetic inhibitor, guanidinoethylmercaptosuccinic acid, occupying the specificity pocket. This structure allows a clear definition of the substrate binding sites and the substrate funnel-like access. The structure of domain II is the only one available from the regulatory carboxypeptidase family and can be used as a general template for its members. Here, it has been used to model the structures of domains I and III from the former protein and of human carboxypeptidase E. The models obtained show that the overall topology is similar in all cases, the main differences being local and because of insertions in non-regular loops. In both carboxypeptidase D domain I and carboxypeptidase E slightly different shapes of the access to the active site are predicted, implying some kind of structural selection of protein or peptide substrates. Furthermore, emplacement of the inhibitor structure in the active site of the constructed models showed that the inhibitor fits very well in all of them and that the relevant interactions observed with domain II are conserved in domain I and carboxypeptidase E but not in the non-active domain III because of the absence of catalytically indispensable residues in the latter protein. However, in domain III some of the residues potentially involved in substrate binding are well preserved, together with others of unknown roles, which also are highly conserved among all carboxypeptidases. These observations, taken together with others, suggest that domain III might play a role in the binding and presentation of proteins or peptide substrates, such as the pre-S domain of the large envelope protein of duck hepatitis B virus.

Refinement of modelled structures by knowledge-based energy profiles and secondary structure prediction: application to the human procarboxypeptidase A2.

Knowledge-based energy profiles combined with secondary structure prediction have been applied to molecular modelling refinement. To check the procedure, three different models of human procarboxypeptidase A2 (hPCPA2) have been built using the 3D structures of procarboxypeptidase A1 (pPCPA1) and bovine procarboxypeptidase A (bPCPA) as templates. The results of the refinement can be tested against the X-ray structure of hPCPA2 which has been recently determined. Regions miss-modelled in the activation segment of hPCPA2 were detected by means of pseudo-energies using Prosa II and modified afterwards according to the secondary structure prediction. Moreover, models obtained by automated methods as COMPOSER, MODELLER and distance restraints have also been compared, where it was found possible to find out the best model by means of pseudo-energies. Two general conclusions can be elicited from this work: (1) on a given set of putative models it is possible to distinguish among them the one closest to the crystallographic structure, and (2) within a given structure it is possible to find by means of pseudo-energies those regions that have been defectively modelled.

Modelling repressor proteins docking to DNA.

The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/ DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA-protein recognition. Complexes were then ranked by an empirical score for the observed amino acid /nucleotide pairings (i.e., protein-DNA pair potentials) derived from a database of 20 protein/ DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three-dimensional models for protein/DNA complexes that do not involve gross conformational changes on association.

Protein similarities beyond disulphide bridge topology.

Structural superimposition is an important procedure to analyse the relationships between proteins. A new approach and program, KNOT-MATCH, has been developed for automated structural superimposition of proteins by means of their disulphide bridge topology. As a result of the superimposition, regular secondary structures, loops and clusters of residues become correctly aligned. This fact allows us to find out important structural overlaps of residues, sometimes with functional significance, not only among proteins belonging to the same family but also between apparently non-related proteins. Different disulphide-rich protein families, such as EGF-like, defensin-like and plant protease inhibitors, have been self or cross analysed with this approach. Some amino acids that have been experimentally determined to be structural and/or functional key residues for these proteins are conserved in the three-dimensional space after superimposition by KNOT-MATCH. The program can be very useful for finding relationships among proteins that would be hidden to the current alignment methods based on sequence and on main-chain topology.

A computational system for modelling flexible protein-protein and protein-DNA docking.

A computational system is described that predicts the structure of protein/protein and protein/DNA complexes starting from unbound coordinate sets. The approach is (i) a global search with rigid-body docking for complexes with shape complementarity and favourable electrostatics; (ii) use of distance constraints from experimental (or predicted) knowledge of critical residues; (iii) use of pair potential to screen docked complexes and (iv) refinement and further screening by protein-side chain optimisation and interfacial energy minimisation. The system has been applied to model ten protein/protein and eight protein-repressor/DNA (steps i to iii only) complexes. In general a few complexes, one of which is close to the true structure, can be generated.

Comparative analysis of the sequences and three-dimensional models of human procarboxypeptidases A1, A2 and B.

A full-length cDNA clone for preprocarboxypeptidase B from human pancreas has been isolated and sequenced. The open reading frame is 1254 bp in length, encoding a protein of 417 amino acids that includes a leader signal peptide of 15 amino acids and a 95-amino acid-long pro-segment. It contains two differences when compared to the sequence reported for pancreas-specific protein, a human serum marker for acute pancreatitis identified as procarboxypeptidase B. The main difference is a previously unreported Cys at position 138, which is needed for the formation of one of the three disulphide bridges. Sequence alignments between human procarboxypeptidases A1, A2 and B and other known forms show that the most conserved region is the enzyme moiety followed by the globular domain of the pro-segment. The maximum variability is found in the connecting region between moieties. The known three-dimensional structures of procarboxypeptidases from bovine and porcine species have been used to model all three human procarboxypeptidases and also to estimatethe interaction energies between the different parts of the molecules, in an attempt to gain insight into the structural features responsible for the differences observed in the functionality of the proenzymes, particularly in their proteolytic activation pathways. Taken together, the results obtained confirm that the main determinant for the rate and mode of activation of procarboxypeptidases is the strength of the interaction between the enzyme and the globular domain of the pro-segment, the connecting segment playing a complementary role.

'TransMem': a neural network implemented in Excel spreadsheets for predicting transmembrane domains of proteins.

MOTIVATION: Genomic sequences from different organisms, even prokaryotic, have plenty of orphan ORFs, making necessary methods for the prediction of protein structure and function. The prediction of the presence of hydrophobic transmembrane (HTM) stretches is a valuable clue for this. RESULTS: The program. TransMem, based on a neural network and running on personal computers (either Apple Macintosh or PC, using Excel worksheets), for the prediction and distribution of amino acid residues in transmembrane segments of integral membrane proteins is reported. The percentage of residue predictive accuracy obtained for the set of proteins tested is 93%, ranging from 99.9% for the best to 71.7% for the worst prediction. The segment-based accuracy is 93.6%; 63.6% of the protein set match any of the predicted and observed segment locations. AVAILABILITY: TransMem is available upon request or by anonymous up: IP address: luz.uab.es, directory/pub/ TransMem. It is also placed on the EMBL file server (ftp:/(/)ftp.ebi.ac.uk/pub/software/mac/TransMem ).

Relation between amino acid composition and cellular location of proteins.

A correlation analysis of the amino acid composition and the cellular location of a protein is presented. The statistical analysis discriminates among the following five protein classes: integral membrane proteins, anchored membrane proteins, extracellular proteins, intracellular proteins and nuclear proteins. This segregation into protein classes related to their location can help researchers to design experimental work for testing hypotheses in order to find out the functionality of a reading frame in search of function. A program (ProtLock) to predict the cellular location of a protein has been designed.