UCSF Chimera, MODELLER, and IMP: an integrated modeling system

Structural modeling of macromolecular complexes greatly benefits from interactive visualization capabilities. Here we present the integration of several modeling tools into UCSF Chimera. These include comparative modeling by MODELLER, simultaneous fitting of multiple components into electron microscopy density maps by IMP MultiFit, computing of small-angle X-ray scattering profiles and fitting of the corresponding experimental profile by IMP FoXS, and assessment of amino acid sidechain conformations based on rotamer probabilities and local interactions by Chimera.

Elemental and non-elemental olfactory learning in Drosophila

Brain complexity varies across many orders of magnitude between animals, and it is often assumed that complexity underpins cognition. It is thus important to explore the cognitive capacity of widely used model organisms such as Drosophila. We systematically investigated the fly's ability to learn discriminations involving compound olfactory stimuli associated with shock. Flies could distinguish binary mixtures (AB+ CD-), including overlapping mixtures (AB+ BC-). They could learn positive patterning (AB+A- B-) but could not learn negative patterning (A+ B+ AB-) or solve a biconditional discrimination task (AB+ CD+ AC- BD-). Learning about the elements of a compound (AB+) was not affected by prior conditioning of one of the elements (A+ AB+): flies do not exhibit blocking in this task. We compare these results with the predictions from simulation of several well-known theoretical models of learning, and find none are fully consistent with the overall pattern of observed behaviour.

Integrative structure modeling of macromolecular assemblies from proteomics data

Proteomics techniques have been used to generate comprehensive lists of protein interactions in a number of species. However, relatively little is known about how these interactions result in functional multiprotein complexes. This gap can be bridged by combining data from proteomics experiments with data from established structure determination techniques. Correspondingly, integrative computational methods are being developed to provide descriptions of protein complexes at varying levels of accuracy and resolution, ranging from complex compositions to detailed atomic structures.

Comparative protein structure modeling using MODELLER

Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Comparative protein structure modeling using Modeller

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Protein structure fitting and refinement guided by cryo-EM density

For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.

Protein structure modeling with MODELLER

Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. This chapter presents an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of similar protocols (correction of protcols) has resulted in models of useful accuracy for domains in more than half of all known protein sequences.

Processing of first-order motion in marmoset visual cortex is influenced by second-order motion

We measured the responses of single neurons in marmoset visual cortex (V1, V2, and the third visual complex) to moving first-order stimuli and to combined first- and second-order stimuli in order to determine whether first-order motion processing was influenced by second-order motion. Beat stimuli were made by summing two gratings of similar spatial frequency, one of which was static and the other was moving. The beat is the product of a moving sinusoidal carrier (first-order motion) and a moving low-frequency contrast envelope (second-order motion). We compared responses to moving first-order gratings alone with responses to beat patterns with first-order and second-order motion in the same direction as each other, or in opposite directions to each other in order to distinguish first-order and second-order direction-selective responses. In the majority (72%, 67/93) of cells (V1 73%, 45/62; V2 70%, 16/23; third visual complex 75%, 6/8), responses to first-order motion were significantly influenced by the addition of a second-order signal. The second-order envelope was more influential when moving in the opposite direction to the first-order stimulus, reducing first-order direction sensitivity in V1, V2, and the third visual complex. We interpret these results as showing that first-order motion processing through early visual cortex is not separate from second-order motion processing; suggesting that both motion signals are processed by the same system.

A model of antennal wall-following and escape in the cockroach

Cockroaches exploit tactile cues from their antennae to avoid predators. During escape running the same sensors are used to follow walls. We hypothesise that selection of these mutually exclusive behaviours can be explained without representation of the stimulus or an explicit switching mechanism. A neural model is presented that embodies this hypothesis. The model incorporates behavioural and neurophysiological data and is embedded in a mobile robot in order to test the response to stimuli in the real world. The system is shown to account for data on escape direction and high-speed wall-following in the cockroach, including the counter-intuitive observation that faster running cockroaches maintain a closer distance to the wall. The wall-following behaviour is extended to include discrimination of tactile escape cues according to behavioural context. We conclude by highlighting questions arising from the robot experiments that suggest interesting hypotheses to test in the cockroach.

Detection of HCV and HIV-1 antibody negative infections in Scottish and Northern Ireland blood donations by nucleic acid amplification testing

BACKGROUND AND OBJECTIVES

To reduce the risk of transfusion-transmissible viruses entering the blood supply, the nucleic acid amplification testing (NAT) was implemented to screen Scottish and Northern Irish blood donations in minipools. After 5 years of NAT for hepatitis C virus (HCV) and 2 years for human immunodeficiency virus-1 (HIV-1), the yield of serologically negative, nucleic acid positive 'window donations' and cost-benefit of NAT is under review.

MATERIALS AND METHODS

When the Scottish National Blood Transfusion Service (SNBTS) implemented NAT in 1999, a fully automated 'black box' system was not available. Therefore, an 'in-house' assimilated NAT assay was developed, validated and implemented. The system is flexible and allows testing for additional viral markers to be introduced with relative ease.

RESULTS

The HCV and HIV NAT assays have 95% detection levels of 7.25 IU/ml and 39.8 IU/ml, respectively, as determined by probit analysis. One HCV (1 in 1.9 million) and one HIV (1 in 0.77 million) window donation have been detected in 5 and 2 years, respectively, of NAT.

CONCLUSION

The SNBTS NAT assays are robust and have performed consistently over the last 5 years. The design of the in-house system allowed HIV NAT to be added in 2003 at a relatively small additional cost per sample, although for both assays, the royalty fee far exceeds the cost of the test itself. Clearly NAT has a benefit in improving the safety of the blood supply although the risks of transfusion-transmitted viral infections, as reported in the Serious Hazards of Transfusion (SHOT) report, are extremely low. Also, in UK the yield of HCV antibody negative, NAT positive donations is far lower than predicted although the early detection of an HIV window period donation and the increase of HIV in the blood donor and general populations may provide a stronger case for HIV NAT. SUMMARY SENTENCE: The yield of HCV and HIV NAT in UK is significantly less than that anticipated from statistical models.

MODBASE, a database of annotated comparative protein structure models, and associated resources

MODBASE (http://salilab.org/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on the MODELLER package for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE uses the MySQL relational database management system for flexible querying and CHIMERA for viewing the sequences and structures (http://www.cgl.ucsf.edu/chimera/). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different data sets. The largest data set contains 1,26,629 models for domains in 659,495 out of 1,182,126 unique protein sequences in the complete Swiss-Prot/TrEMBL database (August 25, 2003); only models based on alignments with significant similarity scores and models assessed to have the correct fold despite insignificant alignments are included. Another model data set supports target selection and structure-based annotation by the New York Structural Genomics Research Consortium; e.g. the 53 new structures produced by the consortium allowed us to characterize structurally 24,113 sequences. MODBASE also contains binding site predictions for small ligands and a set of predicted interactions between pairs of modeled sequences from the same genome. Our other resources associated with MODBASE include a comprehensive database of multiple protein structure alignments (DBALI, http://salilab.org/dbali) as well as web servers for automated comparative modeling with MODPIPE (MODWEB, http://salilab. org/modweb), modeling of loops in protein structures (MODLOOP, http://salilab.org/modloop) and predicting functional consequences of single nucleotide polymorphisms (SNPWEB, http://salilab. org/snpweb).

Anxiety-related bias in the classification of emotionally ambiguous facial expressions

High- and low-trait socially anxious individuals classified the emotional expressions of photographic quality continua of interpolated ("morphed") facial images that were derived from combining 6 basic prototype emotional expressions to various degrees, with the 2 adjacent emotions arranged in an emotion hexagon. When fear was 1 of the 2 component emotions, the high-trait group displayed enhanced sensitivity for fear. In a 2nd experiment where a mood manipulation was incorporated, again, the high-trait group exhibited enhanced sensitivity for fear. The low-trait group was sensitive for happiness in the control condition. The mood-manipulated group had increased sensitivity for anger expressions, and trait anxiety did not moderate these effects. Interpretations of the results related to the classification of fearful expressions are discussed.

Solution structure of the carboxyl-terminal cysteine-rich domain of the VHv1.1 polydnaviral gene product: comparison with other cystine knot structural folds

Polydnaviruses are an unusual group of insect viruses that have an obligate symbiotic association with certain parasitic wasps. These viruses are transmitted with the wasp egg during oviposition into lepidopteran insects, enabling the survival and development of the egg inside the host larvae. We report the three-dimensional structure of a novel polydnaviral cysteine-rich motif (cys-motif), identified as the carboxyl-terminal domain of a two cys-motif containing polydnaviral VHv1.1 gene product, abbreviated "C-term VHv1.1". This 65-residue domain was identified experimentally by limited proteolysis of the full-length protein and was subsequently cloned in a bacterial expression system for NMR studies. The C-term VHv1.1 3D structure was determined in solution by two-dimensional (1)H NMR spectroscopy. Calculation of the structure was based on a total of 300 upper distance restraints and 20 dihedral angle constraints, and resulted in an ensemble of 25 representative conformers with an average rmsd of 0.47 A from the mean structure for core backbone atoms. The protein core is made of a four beta-strand scaffold held together in a compact structure by three disulfide bonds, which form a cystine knot. The four beta-strands are arranged in an unusual configuration to form a triple-stranded beta-sheet and double-stranded beta-sheet. Comparison with other classes of cystine knots provides indication that C-term VHv1.1 represents a new and distinct cystine knot motif. This analysis provides a structural basis for interpretation of the genetic and amino acid sequence data classifying polydnavirus gene products as members of cysteine-rich protein families.

Can robots make good models of biological behaviour?

How should biological behaviour be modelled? A relatively new approach is to investigate problems in neuroethology by building physical robot models of biological sensorimotor systems. The explication and justification of this approach are here placed within a framework for describing and comparing models in the behavioural and biological sciences. First, simulation models--the representation of a hypothesis about a target system--are distinguished from several other relationships also termed "modelling" in discussions of scientific explanation. Seven dimensions on which simulation models can differ are defined and distinctions between them discussed: 1.

RELEVANCE

whether the model tests and generates hypotheses applicable to biology. 2. Level: the elemental units of the model in the hierarchy from atoms to societies. 3. Generality: the range of biological systems the model can represent. 4. Abstraction: the complexity, relative to the target, or amount of detail included in the model. 5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour. 6. Performance match: to what extent the model behaviour matches the target behaviour. 7. Medium: the physical basis by which the model is implemented. No specific position in the space of models thus defined is the only correct one, but a good modelling methodology should be explicit about its position and the justification for that position. It is argued that in building robot models biological relevance is more effective than loose biological inspiration; multiple levels can be integrated; that generality cannot be assumed but might emerge from studying specific instances; abstraction is better done by simplification than idealisation; accuracy can be approached through iterations of complete systems; that the model should be able to match and predict target behaviour; and that a physical medium can have significant advantages. These arguments reflect the view that biological behaviour needs to be studied and modelled in context, that is, in terms of the real problems faced by real animals in real environments.

An exploratory study in a community National Health Service Trust to understand why enrolled nurses choose not to convert to first-level registration

AIM

The aim of this research study was to more fully understand at local level what it was that prevented enrolled nurses (ENs) coming forward for conversion to the first level of the United Kingdom Central Council for Nursing, Midwifery and Health Visiting (UKCC) nursing register.

BACKGROUND

An NHS Trust had first-level nursing shortages and looked to the 69 ENs nurses -- 12% of the nursing workforce -- to meet that shortfall via conversion to first-level UKCC nurse registration. Based on local surveys, their intention to convert was the same as national findings, in that high numbers said they wanted to convert. In addition, this NHS Trust provided support and fully funded conversion courses, yet they did not come forward.

METHODS

A qualitative approach based on focus groups with ENs was adopted to research this 'problem' within the local organizational context.

FINDINGS

ENs were unaware that fully funded course places were available, extremely fearful of the academic expectations of the conversion course and highly committed to family needs. Conclusions Nationally, policymakers advocated the retention of and/or the conversion of ENs, on the grounds that research participants did not perceive or believe that managers were supportive of this proposal.

KEY RECOMMENDATIONS

Create managers who looked beyond the immediate 'problem' of nursing shortages and invested in ENs to retain them in the NHS workforce. Establish local policy and an implementation plan to address the needs of ENs in line with clinical governance and the local nurse retention strategy. Empower ENs who would secure solutions to the issues for themselves.

Demonstration of different patterns of musculoskeletal, soft tissue and visceral involvement in melioidosis using 99m Tc stannous colloid white cell scanning

Melioidosis is an infectious disease that can present with multiple foci of disease involvement. Assessment of disease extent can be difficult, especially in musculoskeletal, visceral and soft tissue infection. This study examined the usefulness of white cell scans in this condition. 99mTc stannous colloid white cell scanning was performed in 21 patients with culture-proven melioidosis. Scan results were compared with clinical assessment and correlated with other forms of imaging. White cell scans demonstrated all but one of the clinically apparent sites of musculoskeletal, visceral and other soft tissue infection. Unsuspected disseminated soft tissue lesions were seen in two patients, including femoral node uptake in both, and these patients subsequently presented with relapsing musculoskeletal disease. Unsuspected musculoskeletal disease was found in one patient. Clinically suspected musculoskeletal disease was accurately excluded by white cell scan in another patient. The results of white cell scanning were also examined in disease of other viscera. Renal and prostatic disease were visualized. Unsuspected parotid involvement was found in two patients. Only one of two spinal lesions was visualized. Pulmonary disease was not necessarily associated with abnormal uptake. White cell scanning is a quick and effective way of assessing the extent of musculoskeletal, visceral and soft tissue disease in melioidosis.

View from the boundary

Re-implementing biological mechanisms on robots not only has technological application but can provide a unique perspective on the nature of sensory processing in animals. To make a robot work, we need to understand the function as part of an embodied, behaving system. I argue that this perspective suggests that the terms "representation" and "information processing" can be misleading when we seek to understand how neurobiological mechanisms carry out perceptual processes. This argument is presented here with reference to a robot model of cricket behavior, which has demonstrated competence comparable to that of the insect, but utilizes surprisingly simple central processing. Instead it depends on sensory interfaces that are well matched to the task, and on the link between environment, action, and perception.

What does robotics offer animal behaviour?

There is a growing body of robot-based research that makes a serious claim to be a new methodology for biology. Robots can be used as models of specific animal systems to test hypotheses regarding the control of behaviour. At levels from learning algorithms to specific dendritic circuits, implementing a proposed controller in a robotic device tests it against real environments in a way that is difficult to simulate. This often provides insight into the true nature of the problem. It also enforces complete specifications and combines bodies of data. Current work can sometimes be criticized for drawing unjustified conclusions given the limited evaluation and inevitable inaccuracies of robot models. Nevertheless, this approach has led to novel hypotheses for animal behaviour and seems likely to provide fruitful results in the future. Copyright 2000 The Association for the Study of Animal Behaviour.

Enrolled nurse conversion: a review of the literature

AIM

The aim of this literature review was to examine the policies and professional literature from the last 50 years about the introduction, the role and subsequent plight of the enrolled nurse (also known as second level nurses), and the need to convert to the first level of the UKCC nursing register.

BACKGROUND

Nurse shortages within the NHS have been cyclical since its inception in 1948. The policy decision to cease the training of enrolled nurses within the frame of modernizing the education and training of the nursing workforce had two distinct implications for enrolled nurses. Firstly, they could choose to stay as enrolled nurses or convert to first level nursing. Nevertheless, enrolled nurses have cited the lack of funded conversion course places, and managerial support for non-conversion.

METHODS

A critical review of the national policies and professional literature concerned with the evaluation of enrolled nurses' contribution to the NHS.

FINDINGS

It was argued that national policy needs to be supported on the ground, whereby enrolled nurses are proactively supported to come forward for conversion and/or meaningful roles are created and sustained where enrolled nurses continue to make a valuable contribution to the NHS agenda. Finally, the paper challenges all NHS organizations to consider the profile and value of enrolled nurses and become proactive in their recruitment and retention of this nursing group.