Biomedical subjects

Marco Punta

Publications and source records attributed to Marco Punta.

8 recordsLinked to original sources

PubMed2006

Identifying cysteines and histidines in transition-metal-binding sites using support vector machines and neural networks.

Accurate predictions of metal-binding sites in proteins by using sequence as the only source of information can significantly help in the prediction of protein structure and function, genome annotation, and in the experimental determination of protein structure. Here, we introduce a method for identifying histidines and cysteines that participate in binding of several transition metals and iron complexes. The method predicts histidines as being in either of two states (free or metal bound) and cysteines in either of three states (free, metal bound, or in disulfide bridges). The method uses only sequence information by utilizing position-specific evolutionary profiles as well as more global descriptors such as protein length and amino acid composition. Our solution is based on a two-stage machine-learning approach. The first stage consists of a support vector machine trained to locally classify the binding state of single histidines and cysteines. The second stage consists of a bidirectional recurrent neural network trained to refine local predictions by taking into account dependencies among residues within the same protein. A simple finite state automaton is employed as a postprocessing in the second stage in order to enforce an even number of disulfide-bonded cysteines. We predict histidines and cysteines in transition-metal-binding sites at 73% precision and 61% recall. We observe significant differences in performance depending on the ligand (histidine or cysteine) and on the metal bound. We also predict cysteines participating in disulfide bridges at 86% precision and 87% recall. Results are compared to those that would be obtained by using expert information as represented by PROSITE motifs and, for disulfide bonds, to state-of-the-art methods.

Amino Acid Sequence↗

PubMed2005

Beyond annotation transfer by homology: novel protein-function prediction methods to assist drug discovery.

Every entirely sequenced genome reveals 100 s to 1000 s of protein sequences for which the only annotation available is 'hypothetical protein'. Thus, in the human genome and in the genomes of pathogenic agents there could be 1000 s of potential, unexplored drug targets. Computational prediction of protein function can play a role in studying these targets. We shall review the challenges, research approaches and recently developed tools in the field of computational function-prediction and we will discuss the ways these issues can change the process of drug discovery.

Computational Biology↗

PubMed2005

PROFcon: novel prediction of long-range contacts.

MOTIVATION: Despite the continuing advance in the experimental determination of protein structures, the gap between the number of known protein sequences and structures continues to increase. Prediction methods can bridge this sequence-structure gap only partially. Better predictions of non-local contacts between residues could improve comparative modeling, fold recognition and could assist in the experimental structure determination. RESULTS: Here, we introduced PROFcon, a novel contact prediction method that combines information from alignments, from predictions of secondary structure and solvent accessibility, from the region between two residues and from the average properties of the entire protein. In contrast to some other methods, PROFcon predicted short and long proteins at similar levels of accuracy. As expected, PROFcon was clearly less accurate when tested on sparse evolutionary profiles, that is, on families with few homologs. Prediction accuracy was highest for proteins belonging to the SCOP alpha/beta class. PROFcon compared favorably with state-of-the-art prediction methods at the CASP6 meeting. While the performance may still be perceived as low, our method clearly pushed the mark higher. Furthermore, predictions are already accurate enough to seed predictions of global features of protein structure.

Algorithms↗

PubMed2005

Protein folding rates estimated from contact predictions.

Folding rates of small single-domain proteins that fold through simple two-state kinetics can be estimated from details of the three-dimensional protein structure. Previously, predictions of secondary structure had been exploited to predict folding rates from sequence. Here, we estimate two-state folding rates from predictions of internal residue-residue contacts in proteins of unknown structure. Our estimate is based on the correlation between the folding rate and the number of predicted long-range contacts normalized by the square of the protein length. It is well known that long-range order derived from known structures correlates with folding rates. The surprise was that estimates based on very noisy contact predictions were almost as accurate as the estimates based on known contacts. On average, our estimates were similar to those previously published from secondary structure predictions. The combination of these methods that exploit different sources of information improved performance. It appeared that the combined method reliably distinguished fast from slow two-state folders.

Amino Acid Sequence↗

PubMed2005

CASP6 assessment of contact prediction.

Here we present the evaluation results of the Critical Assessment of Protein Structure Prediction (CASP6) contact prediction category. Contact prediction was assessed with standard measures well known in the field and the performance of specialist groups was evaluated alongside groups that submitted models with 3D coordinates. The evaluation was mainly focused on long range contact predictions for the set of new fold targets, although we analyzed predictions for all targets. Three groups with similar levels of accuracy and coverage performed a little better than the others. Comparisons of the predictions of the three best methods with those of CASP5/CAFASP3 suggested some improvement, although there were not enough targets in the comparisons to make this statistically significant.

Algorithms↗

PubMed2003

Molecular modeling studies on CNG channel from bovine retinal rod: a structural model of the cyclic nucleotide-binding domain.

A dimeric model of the cyclic nucleotide-binding domain of the all-alpha homomeric cyclic nucleotide-gated channel from bovine retinal rod is constructed. The model, based on the structure of the fairly homologous catabolite gene activator protein (Weber and Steitz, J Mol Biol 1987;198:311-326), is obtained by use of comparative modeling and molecular dynamics simulations. Our model provides a structural basis for the experimentally measured difference in activity between cAMP and cGMP, as well as the different solvent accessibilities of GLY597 in the complex with cGMP, with cAMP and in the protein in free state. In addition, it provides support for the rearrangement of the domain C helix on ligand binding and releasing proposed by Matulef et al. (Neuron 1999;24:443-452).

Animals↗

PubMed2003

A knowledge-based scale for amino acid membrane propensity.

In this article, a membrane-propensity scale for amino acids is derived using only two ingredients: (i) a set of transmembrane helices segments from membrane protein crystal structures and (ii) the request that each component of the set has a free energy lower than that of a typical soluble protein sequence of the same length. Although the most widely used hydropathy scales satisfy this request, we use an optimization procedure that allows for extraction of an optimal scale, which correlates equally well with those scales. We show that, if the choice of the sequence database is accurate, significant knowledge-based scales, which are robust with respect to changes in the learning set, can be easily derived. The obtained scales can be used for transmembrane helices prediction. The predictive power of one of these scales is tested on membrane proteins, soluble proteins, and signal peptides databases, finding that its performances is comparable with those of the hydropathy scales.

Algorithms↗

PubMed2002

Movement of the C-helix during the gating of cyclic nucleotide-gated channels.

Movements within the cyclic nucleotide-binding domain of cyclic nucleotide-gated channels are thought to underlie the initial phase of channel gating (Tibbs, G. R., D. T. Liu, B. G. Leypold, and S. A. Siegelbaum. 1998. J. Biol. Chem. 273:4497-4505; Zong, X., H. Zucker, F. Hofmann, and M. Biel. 1998. EMBO J. 17:353-362; Matulef, K., G. E. Flynn, and W. N. Zagotta. 1999. Neuron. 24:443-452; Paoletti, P., E. C. Young, and S. A. Siegelbaum. 1999. J. Gen. Physiol. 113:17-33; Johnson, J. P., and W. N. Zagotta. 2001. Nature. 412:917-921). To investigate these movements, cysteine mutation was performed on each of the 28 residues (Leu-583 to Asn-610), which span the agonist-binding domain of the alpha-subunit of the bovine rod cyclic nucleotide-gated channel. The effects of Cd(2+) ions, 2-trimethylammonioethylmethane thiosulfonate (MTSET) and copper phenanthroline (CuP) on channel activity were examined, in excised inside-out patches in the presence and in the absence of a saturating concentration of cGMP. The application of 100 microM Cd(2+) in the presence of saturating concentration of cGMP caused an irreversible and almost complete reduction of the current in mutant channels E594C, I600C, and L601C. In the absence of cGMP, the presence of 100 microM Cd(2+) caused a strong current reduction in all cysteine mutants from Asp-588 to Leu-607, with the exception of mutant channels A589C, M592C, M602C, K603C, and L606C. The selective effect of Cd(2+) ions was very similar to that observed when adding the oxidizing agent CuP to the bath medium, except for mutant channel G597C, where CuP caused a stronger current decrease (67 +/- 7%) than Cd(2+) (23 +/- 4%). In the absence of cGMP, MTSET caused a reduction of the current by >40% in mutant channels L607C, L601C, I600C, G597C, and E594C, whereas in the presence of cGMP only mutant channel L601C was affected. The application of MTSET protected many mutant channels from the effects of Cd(2+) and CuP. These results suggest that, when CNG channels are in the open state, residues from Asp-588 to Leu-607 are in an alpha-helical structure, homologous to the C-helix of the catabolite gene activator protein (Weber, I. T., and T. A. Steitz. 1987. J. Mol. Biol. 198:311-326). Furthermore, residues Glu-594, Gly-597, Ile-600, and Leu-601 of these helices belonging to two different subunits must be in close proximity. In the closed state the C-helices are in a different configuration and undergo significant fluctuations.

Amino Acid Sequence↗