Prediction of the tertiary structure of parathyroid-hormone-related protein (residues 1–34) by the island model

Prediction of the tertiary structure of a 34 residue N-terminal fragment of parathyroid-hormone-related protein was carried out by the island model. This peptide is known as a major causative agent of humoral hypercalcemia of malignancy, but structural information studied by X-ray diffraction has not been reported. We adopted the secondary structure determined by NMR and packed on the basis of island model of protein folding developed by us. Predicted structure is discussed in connection with the interaction of active sites.     

Prediction of the three-dimensional structure of human growth hormone

In recent years, the protein-folding problem has attracted the attention of molecular biologists. Efforts have focused on developing heuristic and energy-based algorithms to predict the three-dimensional structure of a protein from its amino acid sequence. We have applied a series of heuristic algorithms to the sequence of human growth hormone. A family of five structures which are generically right-handed fourfold alpha-helical bundles are found from an investigation of approximately 10(8) structures. A plausible receptor binding site is suggested. Independent crystallographic analysis confirms some aspects of these predictions. These methods only deal with the "core" structure, and conformations of many residues are not defined. Further work is required to identify a unique set of coordinates and to clarify the topological alternative available to alpha-helical proteins.     

Pfam: A comprehensive database of protein domain families based on seed alignments

Databases of multiple sequence alignments are a valuable aid to protein sequence classification and analysis. One of the main challenges when constructing such a database is to simultaneously satisfy the conflicting demands of completeness on the one hand and quality of alignment and domain definitions on the other. The latter properties are best dealt with by manual approaches, whereas completeness in practice is only amenable to automatic methods. Herein we present a database based on hidden Markov model profiles (HMMs), which combines high quality and completeness. Our database, Pfam, consists of parts A and B. Pfam-A is curated and contains well-characterized protein domain families with high quality alignments, which are maintained by using manually checked seed alignments and HMMs to find and align all members. Pfam-B contains sequence families that were generated automatically by applying the Domainer algorithm to cluster and align the remaining protein sequences after removal of Pfam-A domains. By using Pfam, a large number of previously unannotated proteins from the Caenorhabditis elegans genome project were classified. We have also identified many novel family memberships in known proteins, including new kazal, Fibronectin type III, and response regulator receiver domains. Pfam-A families have permanent accession numbers and form a library of HMMs available for searching and automatic annotation of new protein sequences. Proteins: 28:405–420, 1997. © 1997 Wiley-Liss, Inc.     

Rebuilding flavodoxin from C alpha coordinates: a test study

The tertiary structure of flavodoxin has been model built from only the X-ray crystallographic alpha-carbon coordinates. Main-chain atoms were generated from a dictionary of backbone structures. Side-chain conformations were initially set according to observed statistical distributions, clashes were resolved with reference to other knowledge-based parameters, and finally, energy minimization was applied. The RMSD of the model was 1.7 A across all atoms to the native structure. Regular secondary structural elements were modeled more accurately than other regions. About 40% of the chi 1 torsional angles were modeled correctly. Packing of side chains in the core was energetically stable but diverged significantly from the native structure in some regions. The modeling of protein structures is increasing in popularity but relatively few checks have been applied to determine the accuracy of the approach. In this work a variety of parameters have been examined. It was found that close contacts, and hydrogen-bonding patterns could identify poorly packed residues. These tests, however, did not indicate which residues had a conformation different from the native structure or how to move such residues to bring them into agreement. To assist in the modeling of interacting side chains a database of known interactions has been prepared.     

Detecting the coevolution of biosequences--an example of RNA interaction prediction

A probabilistic graphical model is proposed in order to detect the coevolution between different sites in biological sequences. The model extends the continuous-time Markov process of sequence substitution for single nucleic or amino acids and imposes general constraints regarding simultaneous changes on the substitution rate matrix. Given a multiple sequence alignment for each molecule of interest and a phylogenetic tree, the model can predict potential interactions within or between nucleic acids and proteins. Initial validation of the model is carried out using tRNA and 16S rRNA sequence data. The model accurately identifies the secondary interactions of tRNA as well as several known tertiary interactions. In addition, results on 16S rRNA data indicate this general and simple coevolutionary model outperforms several other parametric and nonparametric methods in predicting secondary interactions. Furthermore, the majority of the putative predictions exhibit either direct contact or proximity of the nucleotide pairs in the 3-dimensional structure of the Thermus thermophilus ribosomal small subunit. The results on RNA data suggest a general model of coevolution might be applied to other types of interactions between protein, DNA, and RNA molecules.     

Importance of long-range interactions in (α/β)8 barrel fold

Protein structures are stabilized by both local and long-range interactions. In this work, we analyzed the importance of long-range interactions in (α/β)₈ barrel proteins in terms of residue distances. We found that the residues occurring in the range of 21–30 residues apart contribute more toward long-range contacts. Indeed, about 50% of successive strands in these proteins are found to occur at a sequential distance of 21–30 residues. The aromatic amino acid residues Phe, Trp, and Tyr prefer the 4–10 range and all other residues prefer the 21–30 range. Hydrophobic-hydrophobic resideu pairs are the most preferred ones for long-range interactions and they may play a key role in the folding and stabilization of (α/β)₈ barrel proteins.     

Importance of long-range interactions in (α/β)8 barrel fold

Protein structures are stabilized by both local and long-range interactions. In this work, we analyzed the importance of long-range interactions in (α/β)₈ barrel proteins in terms of residue distances. We found that the residues occurring in the range of 21–30 residues apart contribute more toward long-range contacts. Indeed, about 50% of successive strands in these proteins are found to occur at a sequential distance of 21–30 residues. The aromatic amino acid residues Phe, Trp, and Tyr prefer the 4–10 range and all other residues prefer the 21–30 range. Hydrophobic-hydrophobic resideu pairs are the most preferred ones for long-range interactions and they may play a key role in the folding and stabilization of (α/β)₈ barrel proteins.