Computational modeling of structural experimental data.
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Base Sequence↗
Biomedical subjects
R B Altman
Publications and source records attributed to R B Altman.
Calculation of the relative geometry of tRNAs in the ribosome from directed hydroxyl-radical probing data.
The many interactions of tRNA with the ribosome are fundamental to protein synthesis. During the peptidyl transferase reaction, the acceptor ends of the aminoacyl and peptidyl tRNAs must be in close proximity to allow peptide bond formation, and their respective anticodons must base pair simultaneously with adjacent trinucleotide codons on the mRNA. The two tRNAs in this state can be arranged in two nonequivalent general configurations called the R and S orientations, many versions of which have been proposed for the geometry of tRNAs in the ribosome. Here, we report the combined use of computational analysis and tethered hydroxyl-radical probing to constrain their arrangement. We used Fe(II) tethered to the 5' end of anticodon stem-loop analogs (ASLs) of tRNA and to the 5' end of deacylated tRNA(Phe) to generate hydroxyl radicals that probe proximal positions in the backbone of adjacent tRNAs in the 70S ribosome. We inferred probe-target distances from the resulting RNA strand cleavage intensities and used these to calculate the mutual arrangement of A-site and P-site tRNAs in the ribosome, using three different structure estimation algorithms. The two tRNAs are constrained to the S configuration with an angle of about 45 degrees between the respective planes of the molecules. The terminal phosphates of 3'CCA are separated by 23 A when using the tRNA crystal conformations, and the anticodon arms of the two tRNAs are sufficiently close to interact with adjacent codons in mRNA.
Anticodon↗
Are predicted structures good enough to preserve functional sites?
BACKGROUND: A principal goal of structure prediction is the elucidation of function. We have studied the ability of computed models to preserve the microenvironments of functional sites. In particular, 653 model structures of a calcium-binding protein (generated using an ab initio folding protocol) were analyzed, and the degree to which calcium-binding sites were recognizable was assessed. RESULTS: While some model structures preserve the calcium-binding microenvironments, many others, including some with low root mean square deviations (rmsds) from the crystal structure of the native protein, do not. There is a very weak correlation between the overall rmsd of a structure and the preservation of calcium-binding sites. Only when the quality of the model structure is high (rmsd less than 2 A for atoms in the 7 A local neighborhood around calcium) does the modeling of the binding sites become reliable. CONCLUSIONS: Protein structure prediction methods need to be assessed in terms of their preservation of functional sites. High-resolution structures are necessary for identifying binding sites such as calcium-binding sites.
Animals↗
Using imperfect secondary structure predictions to improve molecular structure computations.
MOTIVATION: Until ab initio structure prediction methods are perfected, the estimation of structure for protein molecules will depend on combining multiple sources of experimental and theoretical data. Secondary structure predictions are a particularly useful source of structural information, but are currently only approximately 70% correct, on average. Structure computation algorithms which incorporate secondary structure information must therefore have methods for dealing with predictions that are imperfect. EXPERIMENTS PERFORMED: We have modified our algorithm for probabilistic least squares structural computations to accept 'disjunctive' constraints, in which a constraint is provided as a set of possible values, each weighted with a probability. Thus, when a helix is predicted, the distances associated with a helix are given most of the weight, but some weights can be allocated to the other possibilities (strand and coil). We have tested a variety of strategies for this weighting scheme in conjunction with a baseline synthetic set of sparse distance data, and compared it with strategies which do not use disjunctive constraints. RESULTS: Naive interpretations in which predictions were taken as 100% correct led to poor-quality structures. Interpretations that allow disjunctive constraints are quite robust, and even relatively poor predictions (58% correct) can significantly increase the quality of computed structures (almost halving the RMS error from the known structure). CONCLUSIONS: Secondary structure predictions can be used to improve the quality of three-dimensional structural computations. In fact, when interpreted appropriately, imperfect predictions can provide almost as much improvement as perfect predictions in three-dimensional structure calculations.
Algorithms↗
Twenty years of progress in avian anesthesia and surgery.
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Anesthesia↗
Hierarchical organization of molecular structure computations.
The task of computing molecular structure from combinations of experimental and theoretical constraints is expensive because of the large number of estimated parameters (the 3D coordinates of each atom) and the rugged landscape of many objective functions. For large molecular ensembles with multiple protein and nucleic acid components, the problem of maintaining tractability in structural computations becomes critical. A well-known strategy for solving difficult problems is divide-and-conquer. For molecular computations, there are two ways in which problems can be divided: (1) using the natural hierarchy within biological macromolecules (taking advantage of primary sequence, secondary structural subunits and tertiary structural motifs, when they are known); and (2) using the hierarchy that results from analyzing the distribution of structural constraints (providing information about which substructures are constrained to one another). In this paper, we show that these two hierarchies can be complementary and can provide information for efficient decomposition of structural computations. We demonstrate five methods for building such hierarchies--two automated heuristics that use both natural and empirical hierarchies, one knowledge-based process using both hierarchies, one method based on the natural hierarchy alone, and for completeness one random hierarchy oblivious to auxiliary information--and apply them to a data set for the procaryotic 30S ribosomal subunit using our probabilistic least squares structure estimation algorithm. We show that the three methods that combine natural hierarchies with empirical hierarchies create decompositions which increase the efficiency of computations by as much as 50-fold. There is only half this gain when using the natural decomposition alone, while the random hierarchy suggests that a speedup of about five can be expected just by virtue of having a decomposition. Although the knowledge-based method performs marginally better, the automatic heuristics are easier to use, scale more reliably to larger problems, and can match the performance of knowledge-based methods if provided with basic structural information.
Algorithms↗
A curriculum for bioinformatics: the time is ripe.
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Computational Biology↗
Recognizing protein binding sites using statistical descriptions of their 3D environments.
We have developed a new method for recognizing sites in three-dimensional protein structures. Our method is based on our previously reported algorithm for creating descriptions of protein microenvironments using physical and chemical properties at multiple levels of detail (including features at the atomic, chemical group, residue, and secondary structural levels). The recognition method takes three inputs: a set of sites that share some structural or functional role, a set of control nonsites that lack this role, and a single query site. The values of properties for the query site are compared to the distributions of values for both sites and nonsites to determine the group to which it is most similar. A log-odds scoring function, based on Bayes' Rule, computes a score that indicates the likelihood that the query region is a site of interest. In this paper, we apply the method to the task of identifying calcium binding sites in proteins. Cross-validation analysis shows that this recognition approach has high sensitivity and specificity. We also describe the results of scanning four calcium binding proteins (with the calcium removed) using a three-dimensional grid of probe points at 2 A spacing. The probe points that have high scores cluster around the true calcium binding sites, with the highest scoring points at or near the binding sites. The method fails in only one case where a calcium binding site is created by four proteins in the crystal lattice, and is thus not recognizable within the crystallographic asymmetric unit. Our results show that property-based descriptions can be used for recognizing protein sites in unannotated structures.
Bayes Theorem↗
A surface measure for probabilistic structural computations.
Computing three-dimensional structures from sparse experimental constraints requires method for combining heterogeneous sources of information, such as distances, angles, and measures of total volume, shape, and surface. For some types of information, such as distances between atoms, numerous methods are available for computing structures that satisfy the provided constraints. It is more difficult, however, to use information about the degree to which an atom is on the surface or buried as a useful constraint during structure computations. Surface measures have been used as accept/reject criteria for previously computed structures, but this is not an efficient strategy. In this paper, we investigate the efficacy of applying a surface measure in the computation of molecular structure, using a method of probabilistic least square computations which facilitates the introduction of multiple, noisy, heterogeneous data sources. For this purpose, we introduce a simple purely geometrical measure of surface proximity called maximal conic view (MCV). MCV is efficiently computable and differentiable, and is hence well suited to driving a structural optimization method based, in part, on surface data. As an initial validation, we show that MCV correlates well with known measures for total exposed surface area. We use this measure in our experiments to show that information about surface proximity (derived from theory or experiment, for example) can be added to a set of distance measurements to increase significantly the quality of the computed structure. In particular, when 30 to 50 percent of all possible short-range distances are provided, the addition of surface information improves the quality of the computed structure (as measured by RMS fit) by as much as 80 percent. Our results demonstrate that knowledge of which atoms are on the surface and which are buried can be used as a powerful constraint in estimating molecular structure.
Animals↗
Bioinformatics in support of molecular medicine.
Bioinformatics studies two important information flows in modern biology. The first is the flow of genetic information from the DNA of an individual organism up to the characteristics of a population of such organisms (with an eventual passage of information back to the genetic pool, as encoded within DNA). The second is the flow of experimental information from observed biological phenomena to models that explain them, and then to new experiments in order to test these models. The discipline of bioinformatics has its roots in a number of activities, including the organization of DNA sequence and protein three-dimensional structural data collections in the 1960's and 1970's. It has become a booming academic and industrial enterprise with the introduction of biological experiments that rapidly produce massive amounts of data (such as the multiple genome sequencing projects, the large scale analysis of gene expression, and the large scale analysis of protein-protein interactions). Basic biological science has always had an impact on clinical medicine (and clinical medical information systems), and is creating a new generation of epidemiologic, diagnostic, prognostic, and treatment modalities. Bioinformatics efforts that appear to be wholly geared towards basic science are likely to become relevant to clinical informatics in the coming decade. For example, DNA sequence information and sequence annotations will appear in the medical chart with increasing frequency. The algorithms developed for research in bioinformatics will soon become part of clinical information systems.
Computational Biology↗
Updating a bibliography using the related articles function within PubMed.
Comprehensive bibliographies are useful for conducting reviews of the literature, and for assessing the progress within a field. These bibliographies may be broad and inclusive, or focused and precise in their inclusion criteria. In either case, the task of maintaining a complete bibliography within a particular area of research is made difficult by the diversity, complexity and huge volume of newly published literature. In an effort to effectively and automatically retrieve relevant literature, different search strategies and indexing tools have been developed, including the RELATED ARTICLES function provided with the PubMed system. In this paper, we report a program for incremental updates of a bibliography using the PubMed RELATED ARTICLES function. Given a highly specialized starting bibliography of experimental measurements of the structure of the 30S bacterial ribosomal subunit, the system was applied to find additional relevant references. For this particular task, the system has a recall of 75%, a strict precision of 32% and a partial precision of 42%. Our results are notable because although the RELATED ARTICLES function is purely statistical, it is nonetheless able to select a very narrowly defined set of articles from the literature. We discuss the tradeoffs between having a user to evaluate many articles of possible interest in a single session, versus asking a user to evaluate a small set of articles on a periodic basis.
Bacteria↗
MHCWeb: converting a WWW database into a knowledge-based collaborative environment.
The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary. We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The OWEB environment allows for flexible access to the data by both users and computer programs.
Artificial Intelligence↗
RNA secondary structure as a reusable interface to biological information resources.
The dissemination of biological information has become critically dependent on the Internet and World Wide Web (WWW), which enable distributed access to information in a platform independent manner. The mode of interaction between biologists and on-line information resources, however, has been mostly limited to simple interface technologies such has hypertext links, tables and forms. The introduction of platform-independent runtime environments facilitates the development of more sophisticated WWW-based user interfaces. Until recently, most such interfaces have been tightly coupled to the underlying computation engines, and not separated as reusable components. We believe that many subdisciplines of biology have intuitive and familiar graphical representations of knowledge that can serve as multipurpose user interface elements. We call such graphical idioms "domain graphics". In order to illustrate the power of such graphics, we have built a reusable interface based on the standard two dimensional (2D) layout of RNA secondary structure. The interface can be used to represent any pre-computed layout of RNA, and takes as a parameters the sets of actions to be performed as a user interacts with the interface. It can provide to any associated application program information about the base, helix, or subsequence selected by the user. We show the versatility of this interface by using it as a special purpose interface to BLAST, Medline and the RNA MFOLD search/compute engines. These demonstrations are available at: http://www-smi.stanford.edu/projects/helix/pubs/ gene-combis-96/
Base Sequence↗
LPFC: an Internet library of protein family core structures.
As the number of protein molecules with known, high-resolution structures increases, it becomes necessary to organize these structures for rapid retrieval, comparison, and analysis. The Protein Data Bank (PDB) currently contains nearly 5,000 entries and is growing exponentially. Most new structures are similar structurally to ones reported previously and can be grouped into families. As the number of members in each family increases, it becomes possible to summarize, statistically, the commonalities and differences within each family. We reported previously a method for finding the atoms in a family alignment that have low spatial variance and those that have higher spatial variance (i.e., the "core" atoms that have the same relative position in all family members and the "non-core" atoms that do not). The core structures we compute have biological significance and provide an excellent quantitative and visual summary of a multiple structural alignment. In order to extend their utility, we have constructed a library of protein family cores, accessible over the World Wide Web at http:/ /www-smi.stanford.edu/projects/helix/LPFC/. This library is generated automatically with publicly available computer programs requiring only a set of multiple alignments as input. It contains quantitative analysis of the spatial variation of atoms within each protein family, the coordinates of the average core structures derived from the families, and display files (in bitmap and VRML formats). Here, we describe the resource and illustrate its applicability by comparing three multiple alignments of the globin family. These three alignments are found to be similar, but with some significant differences related to the diversity of family members and the specific method used for alignment.
Computer Communication Networks↗
Informatics in the care of patients: ten notable challenges.
What is medical informatics, and why should practicing physicians care about it? Medical informatics is the study of the concepts and conceptual relationships within biomedical information and how they can be harnessed for practical applications. In the past decade, the field has exploded as health professionals recognize the importance of strategic information management and the inadequacies of traditional tools for information storage, retrieval, and analysis. At the same time that medical informatics has established a presence within many academic and industrial research facilities, its goals and methods have become less clear to practicing physicians. In this article, I outline 10 challenges in medical informatics that provide a framework for understanding developments in the field. These challenges have been divided into those relating to infrastructure, specific performance, and evaluation. The primary goals of medical informatics, as for any other branch of biomedical research, are to improve the overall health of patients by combining basic scientific and engineering insights with the useful application of these insights to important problems.
California↗
Standardized representations of the literature: combining diverse sources of ribosomal data.
We are building a knowledge base (KB) of published structural data on the 30s ribosomal subunit in prokaryotes. Our KB is distinguished by a standardized representation of biological experiments and their results, in a reusable format. It can be accessed by computer programs that exploit the rich interconnections within the data. The KB is designed to support the construction of 3D models of the 30S subunit, as well as the analysis and extension of relevant functional and phylogenetic information. Most published information about the structure of the ubiquitous ribosome focuses on E. coli as a model system. At the same time, thousands of RNA sequences for the ribosome have been gathered and cataloged. The volume and complexity of these data can complicate attempts to separate structural data peculiar to E. coli from data of universal relevance. We have written an application that dynamically queries the KB and the Ribosome Database Project, a repository of ribosomal RNA sequences from other organisms, in order to assess the relevance of structural data to particular organisms. The application uses the RDP alignment to determine whether a set of data refer primarily to conserved, mismatched, or gapped positions. For a set of 16 representative articles evaluated over 211 sequences, 73% of observations have unambiguous translations from E. coli to the other organisms, 21% have somewhat ambiguous translations, and 6% have no translations. There is a wide variation in these numbers over different articles and organisms, confirming that some articles report structural information specific to E. coli while others report information that is quite general.
Artificial Intelligence↗
RIBOWEB: linking structural computations to a knowledge base of published experimental data.
The world wide web (WWW) has become critical for storing and disseminating biological data. It offers an additional opportunity, however, to support distributed computation and sharing of results. Currently, computational analysis tools are often separated from the data in a manner that makes iterative hypothesis testing cumbersome. We hypothesize that the cycle of scientific reasoning (using data to build models, and evaluating models in light of data) can be facilitated with resources that link computations with semantic models of the data. Riboweb is an on-line knowledge-based resource that supports the creation of three-dimensional models of the 30S ribosomal subunit. It has three components: (I) a knowledge base containing representations of the essential physical components and published structural data, (II) computational modules that use the knowledge base to build or analyze structural models, and (III) a web-based user interface that supports multiple users, sessions and computations. We have built a prototype of Riboweb, and have used it to refine a rough model of the central domain of the 30S subunit from E. coli. procedure. Our results suggest that sophisticated and integrated computational capabilities can be delivered to biologists using this simple three-component architecture.
Artificial Intelligence↗
Using the radial distributions of physical features to compare amino acid environments and align amino acid sequences.
We have performed a comprehensive analysis of the microenvironments surrounding the twenty amino acids. Our analysis includes comparison of amino acid environments with random control environments as well as with each of the other amino acid environments. We describe the amino acid environments with a set of 21 features summarizing atomic, chemical group, residue, and secondary structural features. The environments are divided into radial shells of 1 A thickness to represent the distance of the features from the amino acid C beta atoms. We make the results of our analysis available graphically over the world wide web. To illustrate the validity and utility of our analysis, we used the amino acid comparative profiles to construct a substitution matrix, the WAC matrix, based on a simple summary of the computed environmental differences. We compared our matrix to BLOSUM62 and PAM250 in BLAST searches with query sequences selected from 39 protein families found in the PROSITE database. Although BLOSUM62 was the most sensitive matrix overall, our matrix was more sensitive for some families, and exhibited overall performance similar to PAM250. Our results suggest that the radial distribution of biochemical and biophysical features is useful for comparing amino acid environments, and that similarity matrices based on the geometric distribution of features around amino acids may produce improved search sensitivity.
Amino Acid Sequence↗