bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intermediate basal cells of the prostate: In vitro and in vivo characterization
Authors: Garraway Levi A. , Lin Douglas , Signoretti Sabina , Waltregny David , Dilks James , Bhattacharya Nandita , Loda Massimo 
Published: April 2003

AbstractBackgroundProgenitor cells within the prostate basal layer may play important roles in differentiation and carcinogenesis; however, prostate stem cell populations remain uncharacterized.MethodsImmunohistochemical and immunoblot analyses were used to characterize prostate epithelial cells (PrEC), a commercially available prostate basal cell isolate.ResultsProliferating PrECs exhibited immunophenotypic characteristics most consistent with basal cells, but during senescence PrECs up‐regulated androgen receptor (AR) mRNA, p27, and low‐molecular‐weight cytokeratin (LMWCK) expression, suggestive of partial differentiation. PrECs also stained strongly for involucrin, which marked a subset of intermediate prostate basal cells in vivo. Basal hyperplasia consisting of involucrin‐positive cells was prevalent in prostate tissue from androgen‐ablated patients, and formed epithelial clusters flanked by involucrin‐negative basal and luminal monolayers. Cultivation of PrECs on matrigel together with androgen‐treated stromal conditioned media resulted in dense aggregates, with a peripheral rim of basal‐like cells expressing p63 and basal cytokeratins.ConclusionsPrEC represents an epithelial population whose basal characteristics are modified in response to matrigel, stromal factors, and senescence, consistent with a transient amplifying population. These cells may derive from a previously unrecognized, involucrin‐positive subset present in vivo. Prostate 55: 206–218, 2003. © 2003 Wiley‐Liss, Inc.
Algorithms for computational solvent mapping of proteins
Authors: Kortvelyesi Tamas , Dennis Sheldon , Silberstein Michael , Brown Lawrence , Vajda Sandor 
Published: April 2003

AbstractComputational mapping methods place molecular probes (small molecules or functional groups) on a protein surface to identify the most favorable binding positions by calculating an interaction potential. We have developed a novel computational mapping program called CS‐Map (computational solvent mapping of proteins), which differs from earlier mapping methods in three respects: (i) it initially moves the ligands on the protein surface toward regions with favorable electrostatics and desolvation, (ii) the final scoring potential accounts for desolvation, and (iii) the docked ligand positions are clustered, and the clusters are ranked on the basis of their average free energies. To understand the relative importance of these factors, we developed alternative algorithms that use the DOCK and GRAMM programs for the initial search. Because of the availability of experimental solvent mapping data, lysozyme and thermolysin are considered as test proteins. Both DOCK and GRAMM speed up the initial search, and the combined algorithms yield acceptable mapping results. However, the DOCK‐based approaches place the consensus site farther from its experimentally determined position than CS‐Map, primarily because of the lack of a solvation term in the initial search. The GRAMM‐based program also finds the correct consensus site for thermolysin. We conclude that good sampling is the most important requirement for successful mapping, but accounting for desolvation and clustering of ligand positions also help to reduce the number of false positives. Proteins 2003;51:340–351. © 2003 Wiley‐Liss, Inc.
Characterization of carbonic anhydrases from Riftia pachyptila, a symbiotic invertebrate from deep‐sea hydrothermal vents
Authors: De Cian Marie‐Cécile , Bailly Xavier , Morales Julia , Strub Jean‐Marc , Van Dorsselaer Alain , Lallier François H. 
Published: April 2003

AbstractThe symbiotic hydrothermal vent tubeworm Riftia pachyptila needs to supply its internal bacterial symbionts with carbon dioxide, their inorganic carbon source. Our aim in this study was to characterize the carbonic anhydrase (CA) involved in CO2 transport and conversion at various steps in the plume and the symbiotic tissue, the trophosome. A complete 1209 kb cDNA has been sequenced from the trophosome and identified as a putative α‐CA based on BLAST analysis and the similarities of total deduced amino‐acid sequence with those from the GenBank database. In the plume, the putative CA sequence obtained from cDNA library screening was 90% identical to the trophosome CA, except in the first 77 nucleotides downstream from the initiation site identified on trophosome CA. A phylogenetic analysis showed that the annelidan Riftia CA (CARp) emerges clustered with invertebrate CAs, the arthropodan Drosophila CA and the cnidarian Anthopleura CA. This invertebrate cluster appeared as a sister group of the cluster comprising mitochondrial and cytosolic isoforms in vertebrates: CAV, CAI II and III, and CAVII. However, amino acid sequence alignment showed that Riftia CA was closer to cytosolic CA than to mitochondrial CA. Combined biochemical approaches revealed two cytosolic CAs with different molecular weights and pI's in the plume and the trophosome, and the occurrence of a membrane‐bound CA isoform in addition to the cytosolic one in the trophosome. The physiologic roles of cytosolic CA in both tissues and supplementary membrane‐bound CA isoform in the trophosome in the optimization of CO2 transport and conversion are discussed. Proteins 2003;51:327–339. © 2003 Wiley‐Liss, Inc.
An empirical model for electrostatic interactions in proteins incorporating multiple geometry‐dependent dielectric constants
Authors: Wisz Michael S. , Hellinga Homme W. 
Published: April 2003

AbstractHere we introduce an electrostatic model that treats the complexity of electrostatic interactions in a heterogeneous protein environment by using multiple parameters that take into account variations in protein geometry, local structure, and the type of interacting residues. The optimal values for these parameters were obtained by fitting the model to a large dataset of 260 experimentally determined pKa values distributed over 41 proteins. We obtain fits between the calculated and observed values that are significantly better than the null model. The model performs well on the groups that exhibit large pKa shifts from solution values in response to the protein environment and compares favorably with other, successful continuum models. The empirically determined values of the parameters correlate well with experimentally observed contributions of hydrogen bonds and ion pairs as well as theoretically predicted magnitudes of charge‐charge and charge‐polar interactions. The magnitudes of the dielectric constants assigned to different regions of the protein rank according to the strength of the relaxation effects expected for the core, boundary, and surface. The electrostatic interactions in this model are pairwise decomposable and can be calculated rapidly. This model is therefore well suited for the large computations required for simulating protein properties and especially for prediction of mutations for protein design. Proteins 2003;51:360–377. © 2003 Wiley‐Liss, Inc.
A novel shape complementarity scoring function for protein‐protein docking
Authors: Chen Rong , Weng Zhiping 
Published: April 2003

AbstractShape complementarity is the most basic ingredient of the scoring functions for protein‐protein docking. Most grid‐based docking algorithms use the total number of grid points at the binding interface to quantify shape complementarity. We have developed a novel Pairwise Shape Complementarity (PSC) function that is conceptually simple and rapid to compute. The favorable component of PSC is the total number of atom pairs between the receptor and the ligand within a distance cutoff. When applied to a benchmark of 49 test cases, PSC consistently ranks near‐native structures higher and produces more near‐native structures than the traditional grid‐based function, and the improvement was seen across all prediction levels and in all categories of the benchmark. Without any post‐processing or biological information about the binding site except the complementarity‐determining region of antibodies, PSC predicts the complex structure correctly for 6 test cases, and ranks at least one near‐native structure in the top 20 predictions for 18 test cases. Our docking program ZDOCK has been parallelized and the average computing time is 4 minutes using sixteen IBM SP3 processors. Both ZDOCK and the benchmark are freely available to academic users (http://zlab.bu.edu/∼rong/dock). Proteins 2003;51:397–408. © 2003 Wiley‐Liss, Inc.
Molecular dynamics simulations of enhanced green fluorescent proteins: Effects of F64L, S65T and T203Y mutations on the ground‐state proton equilibria
Authors: Nifosì R. , Tozzini V. 
Published: April 2003

AbstractMolecular dynamics simulations with the Amber force field are carried out to study two mutants of the green fluorescent protein (GFP), namely EGFP (F64L/S65T) and T203Y‐EGFP (E2GFP). Those variants display an opposite equilibrium between the structural A and B states, associated with neutral and anionic protonation forms of the chromophore. Configurations of those two states are simulated for each variant and the energetics of their equilibrium in the two mutants is studied by evaluating the change in the relative free energy of A and B states (ΔGAB) upon T203Y mutation. The resulting ΔΔGAB agrees with the value inferred from absorption measurements. A comparison of the hydrogen bond network around the chromophore rationalizes the different population of state A and B in EGFP and E2GFP. On the basis of structural and energetic considerations, a mechanism for destabilization of the neutral chromophore in S65T mutants is proposed. Simulations of the B state of the S65T variant and of WT GFP are also performed for comparison and to test the force field parameters of the chromophore derived for the present calculations. Possible paths of proton transfer leading to nonfluorescent states of the chromophore are discussed in light of the photodynamical behavior of GFP, as revealed by fluorescence correlation spectroscopy and single‐molecule experiments. Proteins 2003;51:378–389. © 2003 Wiley‐Liss, Inc.
Monte Carlo estimation of the number of possible protein folds: Effects of sampling bias and folds distributions
Authors: Leonov Hadas , Mitchell Joseph S.B. , Arkin Isaiah T. 
Published: April 2003

AbstractThe estimation of the number of protein folds in nature is a matter of considerable interest. In this study, a Monte Carlo method employing the broken stick model is used to assign a given number of proteins into a given number of folds. Subsequently, random, integer, non‐repeating numbers are generated in order to simulate the process of fold discovery. With this conceptual framework at hand, the effects of two factors upon the fold identification process were investigated: (1) the nature of folds distributions and (2) preferential sampling bias of previously identified folds. Depending on the type of distribution, dividing 100,000 proteins into 1,000 folds resulted in 10–30% of the folds having 10 proteins or less per fold, approximately 10% of the folds having 10–20 proteins per fold, 31–45% having 20–100 proteins per fold, and >30% of the folds having more than 100 proteins per fold. After randomly sampling one tenth of the proteins, 68–96% of the folds were identified. These percentages depend both on folds distribution and biased/non‐biased sampling. Only upon increasing the sampling bias for previously identified folds to 1,000, did the model result in a reduction of the number of proteins identified by an order of magnitude (approximately 9%). Thus, assuming the structures of one tenth of the population of proteins in nature have been solved, the results of the Monte Carlo simulation are more consistent with recent lower estimates of the number of folds, ≤1,000. Any deviation from this estimate would reflect significant bias in the experimental sampling of protein structure, and/or substantially nonuniform folds distribution, manifested in a large number of single‐fold proteins. Proteins 2003;51:352–359. © 2003 Wiley‐Liss, Inc.
Increased detection of structural templates using alignments of designed sequences
Authors: Larson Stefan M. , Garg Amit , Desjarlais John R. , Pande Vijay S. 
Published: April 2003

AbstractProtein structure prediction by comparative modeling benefits greatly from the use of multiple sequence alignment information to improve the accuracy of structural template identification and the alignment of target sequences to structural templates. Unfortunately, this benefit is limited to those protein sequences for which at least several natural sequence homologues exist. We show here that the use of large diverse alignments of computationally designed protein sequences confers many of the same benefits as natural sequences in identifying structural templates for comparative modeling targets. A large‐scale massively parallelized application of an all‐atom protein design algorithm, including a simple model of peptide backbone flexibility, has allowed us to generate 500 diverse, non‐native, high‐quality sequences for each of 264 protein structures in our test set. PSI‐BLAST searches using the sequence profiles generated from the designed sequences (“reverse” BLAST searches) give near‐perfect accuracy in identifying true structural homologues of the parent structure, with 54% coverage. In 41 of 49 genomes scanned using reverse BLAST searches, at least one novel structural template (not found by the standard method of PSI‐BLAST against PDB) is identified. Further improvements in coverage, through optimizing the scoring function used to design sequences and continued application to new protein structures beyond the test set, will allow this method to mature into a useful strategy for identifying distantly related structural templates. Proteins 2003;51:390–396. © 2003 Wiley‐Liss, Inc.
Cooperative fluctuations of unliganded and substrate‐bound HIV‐1 protease: A structure‐based analysis on a variety of conformations from crystallography and molecular dynamics simulations
Authors: Kurt Nese , Scott Walter R.P. , Schiffer Celia A. , Haliloglu Turkan 
Published: April 2003

AbstractThe dynamics of HIV‐1 protease, both in unliganded and substrate‐bound forms have been analyzed by using an analytical method, Gaussian network model (GNM). The method is applied to different conformations accessible to the protein backbone in the native state, observed in crystal structures and snapshots from fully atomistic molecular dynamics (MD) simulation trajectories. The modes of motion obtained from GNM on different conformations of HIV‐1 protease are conserved throughout the MD simulations. The flaps and 40's loop of the unliganded HIV‐1 protease structure are identified as the most mobile regions. However, in the liganded structure these flaps lose mobility, and terminal regions of the monomers become more flexible. Analysis of the fast modes shows that residues important for stability are in the same regions of all the structures examined. Among these, Gly86 appears to be a key residue for stability. The contribution of residues in the active site region and flaps to the stability is more pronounced in the substrate‐bound form than in the unliganded form. The convergence of modes in GNM to similar regions of HIV‐1 protease, regardless of the conformation of the protein, supports the robustness of GNM as a potentially useful and predictive tool. Proteins 2003;51:409–422. © 2003 Wiley‐Liss, Inc.
Solvation parameters for predicting the structure of surface loops in proteins: Transferability and entropic effects
Authors: Das Bedamati , Meirovitch Hagai 
Published: April 2003

AbstractA new procedure for optimizing parameters of implicit solvation models introduced by us has been applied successfully first to cyclic peptides and more recently to three surface loops of ribonuclease A (Das and Meirovitch, Proteins 2001;43:303–314) using the simplified model Etot = EFF(ε = nr) + Σi σiAi, where σi are atomic solvation parameters (ASPs) to be optimized, Ai is the solvent accessible surface area of atom i, EFF(ε = nr) is the AMBER force‐field energy of the loop‐loop and loop‐template interactions with a distance‐dependent dielectric constant, ε = nr, where n is a parameter. The loop is free to move while the protein template is held fixed in its X‐ray structure; an extensive conformational search for energy minimized loop structures is carried out with our local torsional deformation method. The optimal ASPs and n are those for which the structure with the lowest minimized energy [Etot(n,σi)] becomes the experimental X‐ray structure, or less strictly, the energy gap between these structures is within 2–3 kcal/mol. To check if a set of ASPs can be defined, which is transferable to a large number of loops, we optimize individual sets of ASPs (based on n = 2) for 12 surface loops from which an “averaged” best‐fit set is defined. This set is then applied to the 12 loops and an independent “test” group of 8 loops leading in most cases to very small RMSD values; thus, this set can be useful for structure prediction of loops in homology modeling. For three loops we also calculate the free energy gaps to find that they are only slightly smaller than their energy counterparts, indicating that only larger n will enable reducing too large gaps. Because of its simplicity, this model allowed carrying out an extensive application of our methodology, providing thereby a large number of benchmark results for comparison with future calculations based on n > 2 as well as on more sophisticated solvation models with as yet unknown performance for loops. Proteins 2003;51:470–483. © 2003 Wiley‐Liss, Inc.
3D‐SHOTGUN: A novel, cooperative, fold‐recognition meta‐predictor
Authors: Fischer Daniel 
Published: April 2003

AbstractTo gain a better understanding of the biological role of proteins encoded in genome sequences, knowledge of their three‐dimensional (3D) structure and function is required. The computational assignment of folds is becoming an increasingly important complement to experimental structure determination. In particular, fold‐recognition methods aim to predict approximate 3D models for proteins bearing no sequence similarity to any protein of known structure. However, fully automated structure‐prediction methods can currently produce reliable models for only a fraction of these sequences. Using a number of semiautomated procedures, human expert predictors are often able to produce more and better predictions than automated methods. We describe a novel, fully automatic, fold‐recognition meta‐predictor, named 3D‐SHOTGUN, which incorporates some of the strategies human predictors have successfully applied. This new method is reminiscent of the so‐called cooperative algorithms of Computer Vision. The input to 3D‐SHOTGUN are the top models predicted by a number of independent fold‐recognition servers. The meta‐predictor consists of three steps: (i) assembly of hybrid models, (ii) confidence assignment, and (iii) selection. We have applied 3D‐SHOTGUN to an unbiased test set of 77 newly released protein structures sharing no sequence similarity to proteins previously released. Forty‐six correct rank‐1 predictions were obtained, 30 of which had scores higher than that of the first incorrect prediction—a significant improvement over the performance of all individual servers. Furthermore, the predicted hybrid models were, on average, more similar to their corresponding native structures than those produced by the individual servers. This opens the possibility of generating more accurate, full‐atom homology models for proteins with no sequence similarity to proteins of known structure. These improvements represent a step forward toward the wider applicability of fully automated structure‐prediction methods at genome scales. Proteins 2003;51:434–441. © 2003 Wiley‐Liss, Inc.
Role of β‐lactam carboxyl group on binding of penicillins and cephalosporins to class C β‐lactamases
Authors: Fenollar‐Ferrer Cristina , Frau Juan , Donoso Josefa , Muñoz Francisco 
Published: April 2003

AbstractMolecular models for the Henry Michaelis complexes of Enterobacter cloacae, a class C β‐lactamase, with penicillin G and cephalotin have been constructed by using molecular mechanic calculations, based on the AMBER force field, to examine the molecular differentiation mechanisms between cephalosporins and penicillins in β‐lactamases. Ser318Ala and Thr316Ala mutations in both complexes and Asn346Ala and Thr316Ala/Asn346Ala double mutation in penicillin G complex have also been studied. Results confirm that Thr316, Ser318, and Asn346 play a crucial role in the substrate recognition, via their interactions with one of the oxygens of the antibiotic carboxyl group. Both mutation Ser318Ala and Thr316Ala strongly affect the correct binding of cephalotin to P99, the first mainly by precluding the discriminating salt bridge between carboxyl and serine OH groups, and the second one by the Ser318, Lys315, and Tyr150 spatial rearrangements. On the other hand, Ser318Ala mutation has little effect on penicillin G binding, but the Thr316Ala/Asn346Ala double mutation causes the departure of the antibiotic from the oxyanion hole. Molecular dynamic simulations allow us to interpret the experimental results of some class C and A β‐lactamases. Proteins 2003;51:442–452. © 2003 Wiley‐Liss, Inc.
Atomic resolution structure of prokaryotic phospholipase A2: Analysis of internal motion and implication for a catalytic mechanism
Authors: Matoba Yasuyuki , Sugiyama Masanori 
Published: April 2003

AbstractWe have found a secreted phospholipase A2 (PLA2, EC 3.1.1.4) from Streptomyces violaceoruber A‐2688, which is the first PLA2 identified in prokaryote, and determined its tertiary structure by NMR and X‐ray analyses. In this study, we collected the X‐ray diffraction data of the bacterial PLA2 at room temperature (297 K) using conventional MoKα radiation and refined the structure at a 1.05 Å resolution. The atomic resolution analysis led us to introduce disordered conformations and hydrogen atoms into a full anisotropic model. The molecular motion, which is expressed as the sum of rigid‐body motion and internal motion of protein, is roughly estimated as the thermal motion when the X‐ray diffraction data are collected at room temperature. In this study, we applied a TLS (rigid‐body motion in terms of translation, libration, and screw motions) model to analyze the rigid‐body motion of the bacterial PLA2 and calculated the internal motion by subtracting the estimate of the rigid‐body motion from the observed anisotropic temperature factor. We also subjected the TLS model to estimate the internal motion of the bovine pancreatic PLA2 using the anisotropic temperature factor deposited in the Protein Data Bank. Both results indicate that the localization of regions exhibiting larger internal motion in the bacterial PLA2 is almost the same as that in the bovine pancreatic PLA2, suggesting that although the tertiary structure of the bacterial PLA2 is strikingly different from that of the bovine pancreatic PLA2, the internal motion, which is associated with the calcium(II) ion‐binding, phospholipid‐binding, and allosteric interfacial activation, is commonly observed in both PLA2s. Proteins 2003;51:453–469. © 2003 Wiley‐Liss, Inc.