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Zhiping Weng

Publications and source records attributed to Zhiping Weng.

51 records · Page 3Linked to original sources
PubMed2003

ZDOCK predictions for the CAPRI challenge.

The CAPRI Challenge is a blind test of protein-protein-docking algorithms that predict the complex structure from the crystal structures of the interacting proteins. We participated in both rounds of this blind test and submitted predictions for all seven targets, relying mainly on our Fast Fourier Transform based algorithm ZDOCK that combines shape complementarity, desolvation, and electrostatics. Our group made good predictions for three targets and had at least some success with three others. Implications of the treatment of prior biological information as well as contributions of manual inspection to docking predictions are also discussed.

Algorithms↗
PubMed2003

ZDOCK: an initial-stage protein-docking algorithm.

The development of scoring functions is of great importance to protein docking. Here we present a new scoring function for the initial stage of unbound docking. It combines our recently developed pairwise shape complementarity with desolvation and electrostatics. We compare this scoring function with three other functions on a large benchmark of 49 nonredundant test cases and show its superior performance, especially for the antibody-antigen category of test cases. For 44 test cases (90% of the benchmark), we can retain at least one near-native structure within the top 2000 predictions at the 6 degrees rotational sampling density, with an average of 52 near-native structures per test case. The remaining five difficult test cases can be explained by a combination of poor binding affinity, large backbone conformational changes, and our algorithm's strong tendency for identifying large concave binding pockets. All four scoring functions have been integrated into our Fast Fourier Transform based docking algorithm ZDOCK, which is freely available to academic users at http://zlab.bu.edu/~ rong/dock.

Algorithms↗
PubMed2003

A protein-protein docking benchmark.

We have developed a nonredundant benchmark for testing protein-protein docking algorithms. Currently it contains 59 test cases: 22 enzyme-inhibitor complexes, 19 antibody-antigen complexes, 11 other complexes, and 7 difficult test cases. Thirty-one of the test cases, for which the unbound structures of both the receptor and ligand are available, are classified as follows: 16 enzyme-inhibitor, 5 antibody-antigen, 5 others, and 5 difficult. Such a centralized resource should benefit the docking community not only as a large curated test set but also as a common ground for comparing different algorithms. The benchmark is available at (http://zlab.bu.edu/~rong/dock/benchmark.shtml).

Algorithms↗
PubMed2003

Cluster-Buster: Finding dense clusters of motifs in DNA sequences.

The signals that determine activation and repression of specific genes in response to appropriate stimuli are one of the most important, but least understood, types of information encoded in genomic DNA. The nucleotide sequence patterns, or motifs, preferentially bound by various transcription factors have been collected in databases. However, these motifs appear to be individually too short and degenerate to enable detection of functional enhancer and silencer elements within a large genome. Several groups have proposed that dense clusters of motifs may diagnose regulatory regions more accurately. Cluster-Buster is the third incarnation of our software for finding clusters of pre-specified motifs in DNA sequences. We offer a Cluster-Buster web server at http://zlab.bu.edu/cluster-buster/.

Binding Sites↗
PubMed2003

PromoSer: A large-scale mammalian promoter and transcription start site identification service.

Proximal promoters have a major impact on transcriptional regulation. Studies of the sequence-based nature of this regulation usually require collection of proximal promoter sequences for large sets of co-regulated genes. We report a newly implemented web service that facilitates extraction of user specified regions around the transcription start site of all annotated human, mouse or rat genes. The transcription start sites have been identified computationally by considering alignments of a large number of partial and full-length mRNA sequences to genomic DNA, with provision for alternative promoters. The service is publicly available at http://biowulf.bu.edu/zlab/PromoSer/.

Animals↗
PubMed2003

A novel shape complementarity scoring function for protein-protein docking.

Shape 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).

Binding Sites↗
PubMed2003

SeqVISTA: a graphical tool for sequence feature visualization and comparison.

BACKGROUND: Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. RESULTS: SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. CONCLUSION: SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.

Amino Acid Sequence↗
PubMed2002

A computational framework for optimal masking in the synthesis of oligonucleotide microarrays.

High-throughput genomic technologies are revolutionizing modern biology. In particular, DNA microarrays have become one of the most powerful tools for profiling global mRNA expression in different tissues and environmental conditions, and for detecting single nucleotide polymorphisms. The broad applicability of gene expression profiling to the biological and medical realms has generated expanding demand for mass production of microarrays, which in turn has created considerable interest in improving the cost effectiveness of microarray fabrication techniques. We have developed the computational framework for an optimal synthesis strategy for oligonucleotide microarrays. The problem was introduced by Hubbell et al. Here, we formalize the problem, obtain precise bounds on its complexity and devise several computational solutions.

Algorithms↗
PubMed2002

Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.

The human genome encodes the transcriptional control of its genes in clusters of cis-elements that constitute enhancers, silencers and promoter signals. The sequence motifs of individual cis- elements are usually too short and degenerate for confident detection. In most cases, the requirements for organization of cis-elements within these clusters are poorly understood. Therefore, we have developed a general method to detect local concentrations of cis-element motifs, using predetermined matrix representations of the cis-elements, and calculate the statistical significance of these motif clusters. The statistical significance calculation is highly accurate not only for idealized, pseudorandom DNA, but also for real human DNA. We use our method 'cluster of motifs E-value tool' (COMET) to make novel predictions concerning the regulation of genes by transcription factors associated with muscle. COMET performs comparably with two alternative state-of-the-art techniques, which are more complex and lack E-value calculations. Our statistical method enables us to clarify the major bottleneck in the hard problem of detecting cis-regulatory regions, which is that many known enhancers do not contain very significant clusters of the motif types that we search for. Thus, discovery of additional signals that belong to these regulatory regions will be the key to future progress.

Algorithms↗
PubMed2002

Docking unbound proteins using shape complementarity, desolvation, and electrostatics.

A comprehensive docking study was performed on 27 distinct protein-protein complexes. For 13 test systems, docking was performed with the unbound X-ray structures of both the receptor and the ligand. For the remaining systems, the unbound X-ray structure of only molecule was available; therefore the bound structure for the other molecule was used. Our method optimizes desolvation, shape complementarity, and electrostatics using a Fast Fourier Transform algorithm. A global search in the rotational and translational space without any knowledge of the binding sites was performed for all proteins except nine antibodies recognizing antigens. For these antibodies, we docked their well-characterized binding site-the complementarity-determining region defined without information of the antigen-to the entire surface of the antigen. For 24 systems, we were able to find near-native ligand orientations (interface C(alpha) root mean square deviation less than 2.5 A from the crystal complex) among the top 2,000 choices. For three systems, our algorithm could identify the correct complex structure unambiguously. For 13 other complexes, we either ranked a near-native structure in the top 20 or obtained 20 or more near-native structures in the top 2,000 or both. The key feature of our algorithm is the use of target functions that are highly tolerant to conformational changes upon binding. If combined with a post-processing method, our algorithm may provide a general solution to the unbound docking problem. Our program, called ZDOCK, is freely available to academic users (http://zlab.bu.edu/~rong/dock/).

Algorithms↗
PubMed2002

HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues.

High-density oligonucleotide arrays are a powerful tool for uncovering changes in global gene expression in various disease states. To this end, it is essential to first characterize the variations of gene expression in normal physiological processes. We established the Human Gene Expression (HuGE) Index database (www.HugeIndex.org) to serve as a public repository for gene expression data on normal human tissues using high-density oligonucleotide arrays. This resource currently contains the results of 59 gene expression experiments on 19 human tissues. We provide interactive tools for researchers to query and visualize our data over the Internet. To facilitate data analysis, we cross-reference each gene on the array with its annotation in the LocusLink database at NCBI.

Computer Graphics↗
PubMed2002

Gene discovery in the auditory system: characterization of additional cochlear-expressed sequences.

To identify genes involved in hearing, 8494 expressed sequence tags (ESTs) were generated from a human fetal cochlear cDNA library in two distinct sequencing projects. Analysis of the first set of 4304 ESTs revealed clones representing 517 known human genes, 41 mammalian genes not previously detected in human tissues, 487 ESTs from other human tissues, and 541 cochlear-specific ESTs (http://hearing.bwh.harvard.edu). We now report results of a DNA sequence similarity (BLAST) analysis of an additional 4190 cochlear ESTs and a comparison to the first set. Among the 4190 new cochlear ESTs, 959 known human genes were identified; 594 were found only among the new ESTs and 365 were found among ESTs from both sequencing projects. COL1A2 was the most abundant transcript among both sets of ESTs, followed in order by COL3A1, SPARC, EEFY1A1, and TPTI. An additional 22 human homologs of known nonhuman mammalian genes and 1595 clusters of ESTs, of which 333 are cochlear-specific, were identified among the new cochlear ESTs. Map positions were determined for 373 of the new cochlear ESTs and revealed 318 additional loci. Forty-nine of the mapped ESTs are located within the genetic interval of 23 deafness loci. Reanalysis of unassigned ESTs from the prior study revealed 338 additional known human genes. The total number of known human genes identified from 8494 cochlear ESTs is 1449 and is represented by 4040 ESTs. Among the known human genes are 14 deafness-associated genes, including GJB2 (connexin 26) and KVLQT1. The total number of nonhuman mammalian genes identified is 43 and is represented by 58 ESTs. The total number of ESTs without sequence similarity to known genes is 4055. Of these, 778 also do not have sequence similarity to any other ESTs, are categorized into 700 clusters, and may represent genes uniquely or preferentially expressed in the cochlea. Identification of additional known genes, ESTs, and cochlear-specific ESTs provides new candidate genes for both syndromic and nonsyndromic deafness disorders.

Auditory Pathways↗
PubMed2002

Identification and validation of a novel cell-recognition site (KNEED) on the 8th type III domain of fibronectin.

Interactions between cell-surface integrins and extracellular matrix proteins underlie a versatile recognition system providing cells with anchorage, traction for migration or matrix remodeling, as well as signals for polarity, differentiation and growth. Short peptide sequences of fibronectin (FN), most notably RGD found on a loop in the 10th type III domain, are effective in promoting cell adhesion when immobilized to a biomaterial scaffold. Additional sequences (e.g. PHSRN) have been shown to act synergistically to enhance cell adhesion and other cellular processes. Using bioinformatics, we identified a candidate cell-binding peptide sequence, KNEED, located on the loop region of the 8th domain of FN that from in vitro studies appears to participate in cell attachment and spreading. Computational analysis revealed that KNEED exhibits both high solvent accessibility and sequence conservation values across FN sequences from seven species. We demonstrate the importance of the KNEED sequence using a solution-phase competitive inhibition assay utilizing soluble peptides. Results indicate that the presence of soluble KNEED peptides inhibits the attachment and spreading of 3T3 balb/c fibroblasts on FN-coated surfaces in a concentration-dependent manner. As more sequence and crystallographic data become available, computational approaches may aid in the identification of new targets for applications where biorecognition plays a key role.

3T3 Cells↗
PubMed2002

Protein therapeutics: promises and challenges for the 21st century.

Recent advances in massively parallel experimental and computational technologies are leading to radically new approaches to the early phases of the drug production pipeline. The revolution in DNA microarray technologies and the imminent emergence of its analogue for proteins, along with machine learning algorithms, promise rapid acceleration in the identification of potential drug targets, and in high-throughput screens for subpopulation-specific toxicity. Similarly, advances in structural genomics in conjunction with in vitro and in silico evolutionary methods will rapidly accelerate the number of lead drug candidates and substantially augment their target specificity. Taken collectively, these advances will usher in an era of predictive medicine, which will move medical practice from reactive therapy after disease onset, to proactive prevention.

Animals↗