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PubMed1989

A custom-designed computer network for a dental clinical school.

A local area computer network has been designed and implemented to service predominantly the patient-related administrative needs of the Westmead Dental Clinical School. The appropriate software has been developed in-house over a period of time and introduced as the complexity and volume of the tasks increased and as more sophisticated hardware became available. The present arrangement utilizes NEC APC III and NEC APC IV computers with ACSinet networking hardware added to an OMNInet system. Primary functions include the management of extensive patient waiting lists (up to 16,000), treatment lists and laboratory work flow, as well as the provision of a wide range of related statistical information. Wordprocessing is a large scale daily activity. More specialized secondary functions include monitoring of patients allocated to dental students, support of the management of appointments, recalls, mailing lists and some specific research projects including data collection for a quality assurance programme. The network functions separately but simultaneously alongside an extensive hospital-wide VAX cluster and has greatly simplified the handling and management of a vast array of data essential to the management and evaluation of the treatment provided in the Dental Clinical School.

Computer Systems↗
PubMed2006

Simulation of biological ion channels with technology computer-aided design.

Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.

Computer-Aided Design↗
PubMed2005

Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design.

The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.

Algorithms↗
PubMed2006

Mis-translation of a computationally designed protein yields an exceptionally stable homodimer: implications for protein engineering and evolution.

We recently used computational protein design to create an extremely stable, globular protein, Top7, with a sequence and fold not observed previously in nature. Since Top7 was created in the absence of genetic selection, it provides a rare opportunity to investigate aspects of the cellular protein production and surveillance machinery that are subject to natural selection. Here we show that a portion of the Top7 protein corresponding to the final 49 C-terminal residues is efficiently mis-translated and accumulates at high levels in Escherichia coli. We used circular dichroism, size-exclusion chromatography, small-angle X-ray scattering, analytical ultra-centrifugation, and NMR spectroscopy to show that the resulting C-terminal fragment (CFr) protein adopts a compact, extremely stable, homo-dimeric structure. Based on the solution structure, we engineered an even more stable variant of CFr by disulfide-induced covalent circularisation that should be an excellent platform for design of novel functions. The accumulation of high levels of CFr exposes the high error rate of the protein translation machinery. The rarity of correspondingly stable fragments in natural proteins coupled with the observation that high quality ribosome binding sites are found to occur within E. coli protein-coding regions significantly less often than expected by random chance implies a stringent evolutionary pressure against protein sub-fragments that can independently fold into stable structures. The symmetric self-association between two identical mis-translated CFr sub-domains to generate an extremely stable structure parallels a mechanism for natural protein-fold evolution by modular recombination of protein sub-structures.

Amino Acid Sequence↗
PubMed2006

Computationally designed libraries of fluorescent proteins evaluated by preservation and diversity of function.

To determine which of seven library design algorithms best introduces new protein function without destroying it altogether, seven combinatorial libraries of green fluorescent protein variants were designed and synthesized. Each was evaluated by distributions of emission intensity and color compiled from measurements made in vivo. Additional comparisons were made with a library constructed by error-prone PCR. Among the designed libraries, fluorescent function was preserved for the greatest fraction of samples in a library designed by using a structure-based computational method developed and described here. A trend was observed toward greater diversity of color in designed libraries that better preserved fluorescence. Contrary to trends observed among libraries constructed by error-prone PCR, preservation of function was observed to increase with a library's average mutation level among the four libraries designed with structure-based computational methods.

Combinatorial Chemistry Techniques↗
PubMed2001

A 915-MHz antenna for microwave thermal ablation treatment: physical design, computer modeling and experimental measurement.

A 915-MHz antenna design that produces specific absorption rate distributions with preferential power deposition in tissues surrounding and including the distal end of the catheter antenna is described. The design features minimal reflected microwave current from the antenna flowing up the transmission line. This cap-choke antenna consists of an annular cap and a coaxial choke which matches the antenna to the coaxial transmission line. The design minimizes heating of the coaxial cable and its performance is not affected by the depth of insertion of the antenna into tissue. The paper provides a comparison of results obtained from computer modeling and experimental measurements made in tissue equivalent phantom materials. There is excellent agreement between numerical modeling and experimental measurement. The cap-choke, matched-dipole type antenna is suitable for intracavitary microwave thermal ablation therapy.

Computer Simulation↗
PubMed2003

Mimicking photosynthesis in a computationally designed synthetic metalloprotein.

While advances in protein design have made possible the construction of protein architectures with nativelike properties and predictable structures and function, there are as of yet no examples of functional, protein-based, solar energy conversion systems. This communication describes the design and characterization of an artificial reaction center (RC) protein that closely resembles the function of the natural photosynthetic RC. The synthetic protein, designed by the protein design program CORE, participates in multiple reduction/oxidation cycles with exogenous acceptors/donors following photoexcitation. The designed metalloprotein, aRC, consists of a tetrahelical bundle functionalized with two bis-histidine bound metal cofactors: a Ru(bpy)2 moiety and a heme group. Two distinct bis-histidine binding sites were engineered for each of these metal centers. Photoexcitation of aRC results in rapid ET from the RuII complex to the heme group (kET >/= 5 x 1010 s-1) yielding a long-lived (70 ns) charge-separated state (CSS), RuIII/FeII. This long-lived CSS participates in subsequent ET reactions with exogenous donors and acceptors in multiple photocycles, thus mimicking the basic function of native photosynthetic RCs. This study illustrates the successful design and construction of a protein-based functional charge separation device using a combination of automated computational protein design and knowledge of the engineering principles of biological electron tunneling extracted from natural electron-transfer systems. To our knowledge, this represents the first example of a functional protein-based artificial reaction center.

2,2'-Dipyridyl↗
PubMed2006

Affinity enhancement of an in vivo matured therapeutic antibody using structure-based computational design.

Improving the affinity of a high-affinity protein-protein interaction is a challenging problem that has practical applications in the development of therapeutic biomolecules. We used a combination of structure-based computational methods to optimize the binding affinity of an antibody fragment to the I-domain of the integrin VLA1. Despite the already high affinity of the antibody (Kd approximately 7 nM) and the moderate resolution (2.8 A) of the starting crystal structure, the affinity was increased by an order of magnitude primarily through a decrease in the dissociation rate. We determined the crystal structure of a high-affinity quadruple mutant complex at 2.2 A. The structure shows that the design makes the predicted contacts. Structural evidence and mutagenesis experiments that probe a hydrogen bond network illustrate the importance of satisfying hydrogen bonding requirements while seeking higher-affinity mutations. The large and diverse set of interface mutations allowed refinement of the mutant binding affinity prediction protocol and improvement of the single-mutant success rate. Our results indicate that structure-based computational design can be successfully applied to further improve the binding of high-affinity antibodies.

Amino Acid Substitution↗
PubMed1991

Computer design of bioactive molecules: a method for receptor-based de novo ligand design.

The design of molecules to bind specifically to protein receptors has long been a goal of computer-assisted molecular design. Given detailed structural knowledge of the target receptor, it should be possible to construct a model of a potential ligand, by algorithmic connection of small molecular fragments, that will exhibit the desired structural and electrostatic complementarity with the receptor. However, progress in this area of receptor-based, de novo ligand design has been hampered by the complexity of the construction process, in which potentially huge numbers of structures must be considered. By limiting the scope of the structure-space examined to one particular class of ligands--namely, peptides and peptide-like compounds--the problem complexity has been reduced to the point that successful, de novo design is now possible. The methodology presented employs a large template set of amino acid conformations which are iteratively pieced together in a model of the target receptor. Each stage of ligand growth is evaluated according to a molecular mechanics-based energy function, which considers van der Waals and coulombic interactions, internal strain energy of the lengthening ligand, and desolvation of both ligand and receptor. The search space is managed by use of a data tree which is kept under control by pruning according to the energy evaluation. Ligands grown by this procedure are subjected to follow-up evaluation in which an approximate binding enthalpy is determined. This methodology has proven useful as a precise model-builder and has also shown the ability to design bioactive ligands.

Algorithms↗
PubMed2000

Computational design of D-peptide inhibitors of hepatitis delta antigen dimerization.

Hepatitis delta virus (HDV) encodes a single polypeptide called hepatitis delta antigen (DAg). Dimerization of DAg is required for viral replication. The structure of the dimerization region, residues 12 to 60, consists of an anti-parallel coiled coil [Zuccola et al., Structure, 6(1998)821]. Multiple Copy Simultaneous Searches (MCSS) of the hydrophobic core region formed by the bend in the helix of one monomer of this structure were carried out for many diverse functional groups. Six critical interaction sites were identified. The Protein Data Bank was searched for backbone templates to use in the subsequent design process by matching to these sites. A 14 residue helix expected to bind to the D-isomer of the target structure was selected as the template. Over 200,000 mutant sequences of this peptide were generated based on the MCSS results. A secondary structure prediction algorithm was used to screen all sequences. and in general only those that were predicted to be highly helical were retained. Approximately 100 of these 14-mers were model built as D-peptides and docked with the L-isomer of the target monomer. Based on calculated interaction energies, predicted helicity, and intrahelical salt bridge patterns, a small number of peptides were selected as the most promising candidates. The ligand design approach presented here is the computational analogue of mirror image phage display. The results have been used to characterize the interactions responsible for formation of this model anti-parallel coiled coil and to suggest potential ligands to disrupt it.

Algorithms↗
PubMedDate not supplied

Computational design and experimental performance testing of an axial-flow pediatric ventricular assist device.

The Virginia Artificial Heart Institute continues to design and develop an axial-flow pediatric ventricular assist device (PVAD) for infants and children in the United States. Our research team has created a database to track potential PVAD candidates at the University of Virginia Children's Hospital. The findings of this database aided with need assessment and design optimization of the PVAD. A numerical analysis of the optimized PVAD1 design (PVAD2 model) was also completed using computational fluid dynamics (CFD) to predict pressure-flow performance, fluid force estimations, and blood damage levels in the flow domain. Based on the PVAD2 model and after alterations to accommodate manufacturing, a plastic prototype for experimental flow testing was constructed via rapid prototyping techniques or stereolithography. CFD predictions demonstrated a pressure rise range of 36-118 mm Hg and axial fluid forces of 0.8-1.7 N for flows of 0.5-3 l/min over 7000-9000 rpm. Blood damage indices per CFD ranged from 0.24% to 0.35% for 200 massless and inert particles analyzed. Approximately 187 (93.5%) of the particles took less than 0.14 seconds to travel completely through the PVAD. The mean residence time was 0.105 seconds with a maximum time of 0.224 seconds. Additionally, in a water/glycerin blood analog solution, the plastic prototype produced pressure rises of 20-160 mm Hg for rotational speeds of 5960 +/- 18 rpm to 9975 +/- 31 rpm over flows from 0.5 to 4.5 l/min. The numerical results for the PVAD2 and the prototype hydraulic testing indicate an acceptable design for the pump, represent a significant step in the development phase of this device, and encourage manufacturing of a magnetically levitated prototype for animal experiments.

Adolescent↗
PubMed1993

Recent developments in drug design: computational chemistry and models of the interaction of ligands with receptors.

Recent articles and advertisements suggest that drug design is within the reach of any chemically oriented scientist who obtains the latest three-dimensional computer graphics programs for his personal computer. This sort of "rational" drug design has however had limited success. When it has been successful, it has required the rigorous application of computational chemistry. Bowen et al. in their accompanying paper provide a summary of a number of approaches and the assumptions involved. The papers by McDonnell et al. and Hendry describe two different approaches: utilizing molecular genetics to test the effective interaction in vitro of ligands with their receptors and utilizing the model structure of DNA as a blueprint for the structure of the intracellular targets of drugs.

Computer Graphics↗
PubMed2002

Computer-aided design of chiral ligands. Part III. A novel ligand for asymmetric allylation designed using computational techniques.

[reaction: see text] Computer-aided design protocols to identify new chiral ligands for reactions proceeding through well-defined transition states are outlined. Ligand families are discovered via computational screening of large structural databases such as the Cambridge Structural Database. Using this method, a novel cis-decalin ligand has been identified as a chiral auxiliary for the allylboration of aldehydes. Synthesis, resolution, and evaluation revealed that this new auxiliary provided the aldehyde facial approach upon which the design was predicated.

Computer-Aided Design↗
PubMed1998

Patenting computer-designed peptides.

The problem of designing new peptides that possess specific properties, such as bactericidal activity, is of wide interest. Recently, attention has focused on the use of Computer-Aided Molecular Design techniques in parallel with more traditional 'synthesise and test' methods. These techniques may typically use Genetic Algorithms to optimise molecules based on Neural Network models that predict activity. In this paper we describe a successful application of this Molecular Design methodology that has resulted in novel bactericidal peptides of real value. A key issue for commercial utilisation of such results is the ability to protect the intellectual property rights associated with the discovery of new molecules. Typically peptide patents use structural templates of amino acid hydrophobicity-hydrophilicity that define highly regular peptide patent spaces. In an extension of established patenting practice we describe a patent application that uses a Neural Net predictive model to define the regions of peptide space that we claim within the patent. This formalism makes no a priori assumptions about the regularity of the patent space. A preliminary comparative investigation of the shape and size of this and other bactericidal peptide patent spaces is conducted.

Algorithms↗
PubMed2000

Artificial neural networks: fundamentals, computing, design, and application.

Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. The attractiveness of ANNs comes from their remarkable information processing characteristics pertinent mainly to nonlinearity, high parallelism, fault and noise tolerance, and learning and generalization capabilities. This paper aims to familiarize the reader with ANN-based computing (neurocomputing) and to serve as a useful companion practical guide and toolkit for the ANNs modeler along the course of ANN project development. The history of the evolution of neurocomputing and its relation to the field of neurobiology is briefly discussed. ANNs are compared to both expert systems and statistical regression and their advantages and limitations are outlined. A bird's eye review of the various types of ANNs and the related learning rules is presented, with special emphasis on backpropagation (BP) ANNs theory and design. A generalized methodology for developing successful ANNs projects from conceptualization, to design, to implementation, is described. The most common problems that BPANNs developers face during training are summarized in conjunction with possible causes and remedies. Finally, as a practical application, BPANNs were used to model the microbial growth curves of S. flexneri. The developed model was reasonably accurate in simulating both training and test time-dependent growth curves as affected by temperature and pH.

Humans↗