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J Skolnick

Publications and source records attributed to J Skolnick.

At least 37 records · Page 2Linked to original sources
PubMed1999

Correlation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipper.

The relationship between the unfolding pseudo free energies of reduced and detailed atomic models of the GCN4 leucine zipper is examined. Starting from the native crystal structure, a large number of conformations ranging from folded to unfolded were generated by all-atom molecular dynamics unfolding simulations in an aqueous environment at elevated temperatures. For the detailed atomic model, the pseudo free energies are obtained by combining the CHARMM all-atom potential with a solvation component from the generalized Born, surface accessibility, GB/SA, model. Reduced model energies were evaluated using a knowledge-based potential. Both energies are highly correlated. In addition, both show a good correlation with the root mean square deviation, RMSD, of the backbone from native. These results suggest that knowledge-based potentials are capable of describing at least some of the properties of the folded as well as the unfolded states of proteins, even though they are derived from a database of native protein structures. Since only conformations generated from an unfolding simulation are used, we cannot assess whether these potentials can discriminate the native conformation from the manifold of alternative, low-energy misfolded states. Nevertheless, these results also have significant implications for the development of a methodology for multiscale modeling of proteins that combines reduced and detailed atomic models.

DNA-Binding Proteins↗
PubMed1999

Averaging interaction energies over homologs improves protein fold recognition in gapless threading.

Protein structure prediction is limited by the inaccuracy of the simplified energy functions necessary for efficient sorting over many conformations. It was recently suggested (Finkelstein, Phys Rev Lett 1998;80:4823-4825) that these errors can be reduced by energy averaging over a set of homologous sequences. This conclusion is confirmed in this study by testing protein structure recognition in gapless threading. The accuracy of recognition was estimated by the Z-score values obtained in gapless threading tests. For threading, we used 20 target proteins, each having from 20 to 70 homologs taken from the HSSP sequence base. The energy of the native structures was compared with the energy from 34 to 75 thousand of alternative structures generated by threading. The energy calculations were done with our recently developed Calpha atom-based phenomenological potentials. We show that averaging of protein energies over homologs reduces the Z-score from approximately -6.1 (average Z-score for individual chains) to approximately -8.1. This means that a correct fold can be found among 3 x 10(9) random folds in the first case and among 3 x 10(15) in the second. Such increase in selectivity is important for recognition of protein folds.

Cytochrome c Group↗
PubMed1999

Ab initio folding of proteins using restraints derived from evolutionary information.

We present our predictions in the ab initio structure prediction category of CASP3. Eleven targets were folded, using a method based on a Monte Carlo search driven by secondary and tertiary restraints derived from multiple sequence alignments. Our results can be qualitatively summarized as follows: The global fold can be considered "correct" for targets 65 and 74, "almost correct" for targets 64, 75, and 77, "half-correct" for target 79, and "wrong" for targets 52, 56, 59, and 63. Target 72 has not yet been solved experimentally. On average, for small helical and alpha/beta proteins (on the order of 110 residues or smaller), the method predicted low resolution structures with a reasonably good prediction of the global topology. Most encouraging is that in some situations, such as with target 75 and, particularly, target 77, the method can predict a substantial portion of a rare or even a novel fold. However, the current method still fails on some beta proteins, proteins over the 110-residue threshold, and sequences in which only a poor multiple sequence alignment can be built. On the other hand, for small proteins, the method gives results of quality at least similar to that of threading, with the advantage of not being restricted to known folds in the protein database. Overall, these results indicate that some progress has been made on the ab initio protein folding problem. Detailed information about our results can be obtained by connecting to http:/(/)www.bioinformatics.danforthcenter.org/+ ++CASP3.

Algorithms↗
PubMed1999

De novo simulations of the folding thermodynamics of the GCN4 leucine zipper.

Entropy Sampling Monte Carlo (ESMC) simulations were carried out to study the thermodynamics of the folding transition in the GCN4 leucine zipper (GCN4-lz) in the context of a reduced model. Using the calculated partition functions for the monomer and dimer, and taking into account the equilibrium between the monomer and dimer, the average helix content of the GCN4-lz was computed over a range of temperatures and chain concentrations. The predicted helix contents for the native and denatured states of GCN4-lz agree with the experimental values. Similar to experimental results, our helix content versus temperature curves show a small linear decline in helix content with an increase in temperature in the native region. This is followed by a sharp transition to the denatured state. van't Hoff analysis of the helix content versus temperature curves indicates that the folding transition can be described using a two-state model. This indicates that knowledge-based potentials can be used to describe the properties of the folded and unfolded states of proteins.

Computer Simulation↗
PubMed1999

Dynamics and thermodynamics of beta-hairpin assembly: insights from various simulation techniques.

Small peptides that might have some features of globular proteins can provide important insights into the protein folding problem. Two simulation methods, Monte Carlo Dynamics (MCD), based on the Metropolis sampling scheme, and Entropy Sampling Monte Carlo (ESMC), were applied in a study of a high-resolution lattice model of the C-terminal fragment of the B1 domain of protein G. The results provide a detailed description of folding dynamics and thermodynamics and agree with recent experimental findings (. Nature. 390:196-197). In particular, it was found that the folding is cooperative and has features of an all-or-none transition. Hairpin assembly is usually initiated by turn formation; however, hydrophobic collapse, followed by the system rearrangement, was also observed. The denatured state exhibits a substantial amount of fluctuating helical conformations, despite the strong beta-type secondary structure propensities encoded in the sequence.

Amino Acid Sequence↗
PubMed1999

Structure-based functional motif identifies a potential disulfide oxidoreductase active site in the serine/threonine protein phosphatase-1 subfamily.

In previous work, 3-dimensional descriptors of protein function ('fuzzy functional forms') were used to identify disulfide oxidoreductase active sites in high-resolution protein structures. During this analysis, a potential disulfide oxidoreductase active site in the serine/threonine protein phosphatase-1 (PP1) crystal structure was discovered. In PP1, the potential redox active site is located in close proximity to the phosphatase active site. This result is interesting in view of literature suggesting that serine/threonine phosphatases could be subject to redox control mechanisms within the cell; however, the actual source of this control is unknown. Additional analysis presented here shows that the putative oxidoreductase active site is highly conserved in the serine/threonine phosphatase-1 subfamily, but not in the serine/threonine phosphatase-2A or -2B subfamilies. These results demonstrate the significant advantages of using structure-based motifs for protein functional site identification. First, a putative disulfide oxidoreductase active site has been identified in serine-threonine phosphatases using a descriptor built from the glutaredoxin/thioredoxin family, proteins that have no apparent evolutionary relationship whatsoever to the PP1 proteins. Second, the proximity of the putative disulfide oxidoreductase active site to the phosphatase active site provides evidence toward a regulatory control mechanism. No sequence-based method could provide either piece of information.

Amino Acid Sequence↗
PubMed1999

Family accommodation of obsessive-compulsive symptoms: instrument development and assessment of family behavior.

Relatives frequently accommodate patients' obsessive-compulsive symptoms and clinicians hypothesize that such accommodations adversely affect patient outcome. This study's purpose was to develop a valid and reliable measure, the Family Accommodation Scale for Obsessive-Compulsive Disorder (FAS), and to investigate the family accommodation construct. We administered the FAS and additional family and patient measures to 36 adult obsessive-compulsive patients and their primary caregivers. The FAS demonstrated excellent interrater reliability and good internal consistency and performed well on assessment of its convergent and discriminant validity. Family accommodation was significantly associated with patient symptom severity and functioning, and with relatives' own obsessive-compulsive symptoms. Although most relatives accommodated patient symptoms, many did not believe that such accommodations improved the patient's clinical status. The FAS will provide researchers and clinicians with a useful tool for assessing family accommodation and for identifying families who may benefit from interventions aimed at developing more adaptive coping strategies.

Adaptation, Psychological↗
PubMed1999

From fold predictions to function predictions: automation of functional site conservation analysis for functional genome predictions.

A database of functional sites for proteins with known structures, SITE, is constructed and used in conjunction with a simple pattern matching program SiteMatch to evaluate possible function conservation in a recently constructed database of fold predictions for Escherichia coli proteins (Rychlewski L et al., 1999, Protein Sci 8:614-624). In this and other prediction databases, fold predictions are based on algorithms that can recognize weak sequence similarities and putatively assign new proteins into already characterized protein families. It is not clear whether such sequence similarities arise from distant homologies or general similarity of physicochemical features along the sequence. Leaving aside the important question of nature of relations within fold superfamilies, it is possible to assess possible function conservation by looking at the pattern of conservation of crucial functional residues. SITE consists of a multilevel function description based on structure annotations and structure analyses. In particular, active site residues, ligand binding residues, and patterns of hydrophobic residues on the protein surface are used to describe different functional features. SiteMatch, a simple pattern matching program, is designed to check the conservation of residues involved in protein activity in alignments generated by any alignment method. Here, this procedure is used to study conservation of functional features in alignments between protein sequences from the E. coli genome and their optimal structural templates. The optimal templates were identified and alignments taken from the database of genomic structural predictions was described in a previous publication (Rychlewski L et al., 1999, Protein Sci 8:614-624). An automated assessment of function conservation is used to analyze the relation between fold and function similarity for a large number of fold predictions. For instance, it is shown that identifying low significance predictions with a high level of functional residue conservations can be used to extend the prediction sensitivity for fold prediction methods. Over 100 new fold/function predictions in this class were obtained in the E. coli genome. At the same time, about 30% of our previous fold predictions are not confirmed as function predictions, further highlighting the problem of function divergence in fold superfamilies.

Algorithms↗
PubMed1998

Functional analysis of the Escherichia coli genome using the sequence-to-structure-to-function paradigm: identification of proteins exhibiting the glutaredoxin/thioredoxin disulfide oxidoreductase activity.

The application of an automated method for the screening of protein activity based on the sequence-to-structure-to-function paradigm is presented for the complete Escherichia coli genome. First, the structure of the protein is identified from its sequence using a threading algorithm, which aligns the sequences to the best matching structure in a structural database and extends sequence analysis well beyond the limits of local sequence identity. Then, the active site is identified in the resulting sequence-to-structure alignment using a "fuzzy functional form" (FFF), a three-dimensional descriptor of the active site of a protein. Here, this sequence-to-structure-to-function concept is applied to analysis of the complete E. coli genome, i.e. all E. coli open reading frames (ORFs) are screened for the thiol-disulfide oxidoreductase activity of the glutaredoxin/thioredoxin protein family. We show that the method can identify the active sites in ten sequences that are known to or proposed to exhibit this activity. Furthermore, oxidoreductase activity is predicted in two other sequences that have not been identified previously. This method distinguishes protein pairs with similar active sites from proteins pairs that are just topological cousins, i.e. those having similar global folds, but not necessarily similar active sites. Thus, this method provides a novel approach for extraction of active site and functional information based on three-dimensional structures, rather than simple sequence analysis. Prediction of protein activity is fully automated and easily extendible to new functions. Finally, it is demonstrated here that the method can be applied to complete genome database analysis.

Algorithms↗
PubMed1998

Method for prediction of protein function from sequence using the sequence-to-structure-to-function paradigm with application to glutaredoxins/thioredoxins and T1 ribonucleases.

The practical exploitation of the vast numbers of sequences in the genome sequence databases is crucially dependent on the ability to identify the function of each sequence. Unfortunately, current methods, including global sequence alignment and local sequence motif identification, are limited by the extent of sequence similarity between sequences of unknown and known function; these methods increasingly fail as the sequence identity diverges into and beyond the twilight zone of sequence identity. To address this problem, a novel method for identification of protein function based directly on the sequence-to-structure-to-function paradigm is described. Descriptors of protein active sites, termed "fuzzy functional forms" or FFFs, are created based on the geometry and conformation of the active site. By way of illustration, the active sites responsible for the disulfide oxidoreductase activity of the glutaredoxin/thioredoxin family and the RNA hydrolytic activity of the T1 ribonuclease family are presented. First, the FFFs are shown to correctly identify their corresponding active sites in a library of exact protein models produced by crystallography or NMR spectroscopy, most of which lack the specified activity. Next, these FFFs are used to screen for active sites in low-to-moderate resolution models produced by ab initio folding or threading prediction algorithms. Again, the FFFs can specifically identify the functional sites of these proteins from their predicted structures. The results demonstrate that low-to-moderate resolution models as produced by state-of-the-art tertiary structure prediction algorithms are sufficient to identify protein active sites. Prediction of a novel function for the gamma subunit of a yeast glycosyl transferase and prediction of the function of two hypothetical yeast proteins whose models were produced via threading are presented. This work suggests a means for the large-scale functional screening of genomic sequence databases based on the prediction of structure from sequence, then on the identification of functional active sites in the predicted structure.

Algorithms↗
PubMed1998

Assembly of protein structure from sparse experimental data: an efficient Monte Carlo model.

A new, efficient method for the assembly of protein tertiary structure from known, loosely encoded secondary structure restraints and sparse information about exact side chain contacts is proposed and evaluated. The method is based on a new, very simple method for the reduced modeling of protein structure and dynamics, where the protein is described as a lattice chain connecting side chain centers of mass rather than Calphas. The model has implicit built-in multibody correlations that simulate short- and long-range packing preferences, hydrogen bonding cooperativity and a mean force potential describing hydrophobic interactions. Due to the simplicity of the protein representation and definition of the model force field, the Monte Carlo algorithm is at least an order of magnitude faster than previously published Monte Carlo algorithms for structure assembly. In contrast to existing algorithms, the new method requires a smaller number of tertiary restraints for successful fold assembly; on average, one for every seven residues as compared to one for every four residues. For example, for smaller proteins such as the B domain of protein G, the resulting structures have a coordinate root mean square deviation (cRMSD), which is about 3 A from the experimental structure; for myoglobin, structures whose backbone cRMSD is 4.3 A are produced, and for a 247-residue TIM barrel, the cRMSD of the resulting folds is about 6 A. As would be expected, increasing the number of tertiary restraints improves the accuracy of the assembled structures. The reliability and robustness of the new method should enable its routine application in model building protocols based on various (very sparse) experimentally derived structural restraints.

Algorithms↗
PubMed1998

Coupling the folding of homologous proteins.

The empirical observation that homologous proteins fold to similar structures is used to enhance the capabilities of an ab initio algorithm to predict protein conformations. A penalty function that forces homologous proteins to look alike is added to the potential and is employed in the coupled energy optimization of several homologous proteins. Significant improvement in the quality of the computed structures (as compared with the computational folding of a single protein) is demonstrated and discussed.

Amino Acid Sequence↗
PubMed1998

Fold assembly of small proteins using monte carlo simulations driven by restraints derived from multiple sequence alignments.

The feasibility of predicting the global fold of small proteins by incorporating predicted secondary and tertiary restraints into ab initio folding simulations has been demonstrated on a test set comprised of 20 non-homologous proteins, of which one was a blind prediction of target 42 in the recent CASP2 contest. These proteins contain from 37 to 100 residues and represent all secondary structural classes and a representative variety of global topologies. Secondary structure restraints are provided by the PHD secondary structure prediction algorithm that incorporates multiple sequence information. Predicted tertiary restraints are derived from multiple sequence alignments via a two-step process. First, seed side-chain contacts are identified from correlated mutation analysis, and then a threading-based algorithm is used to expand the number of these seed contacts. A lattice-based reduced protein model and a folding algorithm designed to incorporate these predicted restraints is described. Depending upon fold complexity, it is possible to assemble native-like topologies whose coordinate root-mean-square deviation from native is between 3.0 A and 6.5 A. The requisite level of accuracy in side-chain contact map prediction can be roughly 25% on average, provided that about 60% of the contact predictions are correct within +/-1 residue and 95% of the predictions are correct within +/-4 residues. Precision in tertiary contact prediction is more critical than absolute accuracy. Furthermore, only a subset of the tertiary contacts, on the order of 25% of the total, is sufficient for successful topology assembly. Overall, this study suggests that the use of restraints derived from multiple sequence alignments combined with a fold assembly algorithm holds considerable promise for the prediction of the global topology of small proteins.

Amino Acid Sequence↗
PubMed1998

Tertiary structure prediction of the KIX domain of CBP using Monte Carlo simulations driven by restraints derived from multiple sequence alignments.

Using a recently developed protein folding algorithm, a prediction of the tertiary structure of the KIX domain of the CREB binding protein is described. The method incorporates predicted secondary and tertiary restraints derived from multiple sequence alignments in a reduced protein model whose conformational space is explored by Monte Carlo dynamics. Secondary structure restraints are provided by the PHD secondary structure prediction algorithm that was modified for the presence of predicted U-turns, i.e., regions where the chain reverses global direction. Tertiary restraints are obtained via a two-step process: First, seed side-chain contacts are identified from a correlated mutation analysis, and then, a threading-based algorithm expands the number of these seed contacts. Blind predictions indicate that the KIX domain is a putative three-helix bundle, although the chirality of the bundle could not be uniquely determined. The expected root-mean-square deviation for the correct chirality of the KIX domain is between 5.0 and 6.2 A. This is to be compared with the estimate of 12.9 A that would be expected by a random prediction, using the model of F. Cohen and M. Sternberg (J. Mol. Biol. 138:321-333, 1980).

Algorithms↗
PubMed1998

Nativelike topology assembly of small proteins using predicted restraints in Monte Carlo folding simulations.

By incorporating predicted secondary and tertiary restraints derived from multiple sequence alignments into ab initio folding simulations, it has been possible to assemble native-like tertiary structures for a test set of 19 nonhomologous proteins ranging from 29 to 100 residues in length and representing all secondary structural classes. Secondary structural restraints are provided by the PHD secondary structure prediction algorithm that incorporates multiple sequence information. Multiple sequence alignments also provide predicted tertiary restraints via a two-step process: First, seed side chain contacts are selected from a correlated mutation analysis, and then an inverse folding algorithm expands these seed contacts. The predicted secondary and tertiary restraints are incorporated into a lattice-based, reduced protein model for structure assembly and refinement. The resulting native-like topologies exhibit a coordinate root-mean-square deviation from native for the whole chain between 3.1 and 6.7 A, with values ranging from 2.6 to 4.1 A over approximately 80% of the structure. Overall, this study suggests that the use of restraints derived from multiple sequence alignments combined with a fold assembly algorithm is a promising approach to the prediction of the global topology of small proteins.

Algorithms↗
PubMed1998

How do potentials derived from structural databases relate to "true" potentials?

Knowledge-based potentials are used widely in protein folding and inverse folding algorithms. Two kinds of derivation methods are used. (1) The interactions in a database of known protein structures are assumed to obey a Boltzmann distribution. (2) The stability of the native folds relative to a manifold of misfolded structures is optimized. Here, a set of previously derived contact and secondary structure propensity potentials, taken as the "true" potentials, are employed to construct an artificial protein structural database from protein fragments. Then, new sets of potentials are derived to see how they are related to the true potentials. Using the Boltzmann distribution method, when the stability of the structures in the database lies within a certain range, both contact potentials and secondary structure propensities can be derived separately with remarkable accuracy. In general, the optimization method was found to be less accurate due to errors in the "excess energy" contribution. When the excess energy terms are kept as a constraint, the true potentials are recovered exactly.

Algorithms↗