A model-based approach for assessing in vivo combination therapy interactions

We present an approach for evaluating the efficacy of combination antitumor agent schedules that accounts for order and timing of drug administration. Our model-based approach compares in vivo tumor volume data over a time course and offers a quantitative definition for additivity of drug effects, relative to which synergism and antagonism are interpreted. We begin by fitting data from individual mice receiving at most one drug to a differential equation tumor growth/drug effect model and combine individual parameter estimates to obtain population statistics. Using two null hypotheses: (i) combination therapy is consistent with additivity or (ii) combination therapy is equivalent to treating with the more effective single agent alone, we compute predicted tumor growth trajectories and their distribution for combination treated animals. We illustrate this approach by comparing entire observed and expected tumor volume trajectories for a data set in which HER-2/neu-overexpressing MCF-7 human breast cancer xenografts are treated with a humanized, anti-HER-2 monoclonal antibody (rhuMAb HER-2), doxorubicin, or one of five proposed combination therapy schedules.

The binding conformation of Taxol in β-tubulin: A model based on electron crystallographic density

The chemotherapeutic drug Taxol is known to interact within a specific site on β-tubulin. Although the general location of the site has been defined by photoaffinity labeling and electron crystallography, the original data were insufficient to make an absolute determination of the bound conformation. We have now correlated the crystallographic density with analysis of Taxol conformations and have found the unique solution to be a T-shaped Taxol structure. This T-shaped or butterfly structure is optimized within the β-tubulin site and exhibits functional similarity to a portion of the B9-B10 loop in the α-tubulin subunit. The model provides structural rationalization for a sizeable body of Taxol structure–activity relationship data, including binding affinity, photoaffinity labeling, and acquired mutation in human cancer cells.

From residue matching patterns to protein folding topographies: General model and bovine pancreatic trypsin inhibitor

A coarse-grained model for protein-folding dynamics is introduced based on a discretized representation of torsional modes. The model, based on the Ramachandran map of the local torsional potential surface and the class (hydrophobic/polar/neutral) of each residue, recognizes patterns of both torsional conformations and hydrophobic-polar contacts, with tolerance for imperfect patterns. It incorporates empirical rates for formation of secondary and tertiary structure. The method yields a topological representation of the evolving local torsional configuration of the folding protein, modulo the basins of the Ramachandran map. The folding process is modeled as a sequence of transitions from one contact pattern to another, as the torsional patterns evolve. We test the model by applying it to the folding process of bovine pancreatic trypsin inhibitor, obtaining a kinetic description of the transitions between the contact patterns visited by the protein along the dominant folding pathway. The kinetics and detailed balance make it possible to invert the result to obtain a coarse topographic description of the potential energy surface along the dominant folding pathway, in effect to go backward or forward between a topological representation of the chain conformation and a topographical description of the potential energy surface governing the folding process. As a result, the strong structure-seeking character of bovine pancreatic trypsin inhibitor and the principal features of its folding pathway are reproduced in a reasonably quantitative way.

Evidence in support of a four transmembrane-pore-transmembrane topology model for the Arabidopsis thaliana Na+/K+ translocating AtHKT1 protein, a member of the superfamily of K+ transporters

The Arabidopsis thaliana AtHKT1 protein, a Na+/K+ transporter, is capable of mediating inward Na+ currents in Xenopus laevis oocytes and K+ uptake in Escherichia coli. HKT1 proteins are members of a superfamily of K+ transporters. These proteins have been proposed to contain eight transmembrane segments and four pore-forming regions arranged in a mode similar to that of a K+ channel tetramer. However, computer analysis of the AtHKT1 sequence identified eleven potential transmembrane segments. We have investigated the membrane topology of AtHKT1 with three different techniques. First, a gene fusion alkaline phosphatase study in E. coli clearly defined the topology of the N-terminal and middle region of AtHKT1, but the model for membrane folding of the C-terminal region had to be refined. Second, with a reticulocyte-lysate supplemented with dog-pancreas microsomes, we demonstrated that N-glycosylation occurs at position 429 of AtHKT1. An engineered unglycosylated protein variant, N429Q, mediated Na+ currents in X. laevis oocytes with the same characteristics as the wild-type protein, indicating that N-glycosylation is not essential for the functional expression and membrane targeting of AtHKT1. Five potential glycosylation sites were introduced into the N429Q. Their pattern of glycosylation supported the model based on the E. coli-alkaline phosphatase data. Third, immunocytochemical experiments with FLAG-tagged AtHKT1 in HEK293 cells revealed that the N and C termini of AtHKT1, and the regions containing residues 135–142 and 377–384, face the cytosol, whereas the region of residues 55–62 is exposed to the outside. Taken together, our results show that AtHKT1 contains eight transmembrane-spanning segments.

Gene content phylogeny of herpesviruses

Clusters of orthologous groups [COGs; Tatusov, R. L., Koonin, E. V. & Lipman, D. J. (1997) Science 278, 631–637] were identified for a set of 13 completely sequenced herpesviruses. Each COG represented a family of gene products conserved across several herpes genomes. These families were defined without using an arbitrary threshold criterion based on sequence similarity. The COG technique was modified so that variable stringency in COG construction was possible. High stringencies identify a core set of highly conserved genes. Varying COG stringency reveals differences in the degree of conservation between functional classes of genes. The COG data were used to construct whole-genome phylogenetic trees based on gene content. These trees agree well with trees based on other methods and are robust when tested by bootstrap analysis. The COG data also were used to construct a reciprocal tree that clustered genes with similar phylogenetic profiles. This clustering may give clues to genes with related functions or with related histories of acquisition and loss during herpesvirus evolution.

PCR candidate region mismatch scanning: adaptation to quantitative, high-throughput genotyping

Linkage and association analyses were performed to identify loci affecting disease susceptibility by scoring previously characterized sequence variations such as microsatellites and single nucleotide polymorphisms. Lack of markers in regions of interest, as well as difficulty in adapting various methods to high-throughput settings, often limits the effectiveness of the analyses. We have adapted the Escherichia coli mismatch detection system, employing the factors MutS, MutL and MutH, for use in PCR-based, automated, high-throughput genotyping and mutation detection of genomic DNA. Optimal sensitivity and signal-to-noise ratios were obtained in a straightforward fashion because the detection reaction proved to be principally dependent upon monovalent cation concentration and MutL concentration. Quantitative relationships of the optimal values of these parameters with length of the DNA test fragment were demonstrated, in support of the translocation model for the mechanism of action of these enzymes, rather than the molecular switch model. Thus, rapid, sequence-independent optimization was possible for each new genomic target region. Other factors potentially limiting the flexibility of mismatch scanning, such as positioning of dam recognition sites within the target fragment, have also been investigated. We developed several strategies, which can be easily adapted to automation, for limiting the analysis to intersample heteroduplexes. Thus, the principal barriers to the use of this methodology, which we have designated PCR candidate region mismatch scanning, in cost-effective, high-throughput settings have been removed.

Biological impact on mineral dissolution: Application of the lichen model to understanding mineral weathering in the rhizosphere

Microorganisms modify rates and mechanisms of chemical and physical weathering and clay growth, thus playing fundamental roles in soil and sediment formation. Because processes in soils are inherently complex and difficult to study, we employ a model based on the lichen–mineral system to identify the fundamental interactions. Fixed carbon released by the photosynthetic symbiont stimulates growth of fungi and other microorganisms. These microorganisms directly or indirectly induce mineral disaggregation, hydration, dissolution, and secondary mineral formation. Model polysaccharides were used to investigate direct mediation of mineral surface reactions by extracellular polymers. Polysaccharides can suppress or enhance rates of chemical weathering by up to three orders of magnitude, depending on the pH, mineral surface structure and composition, and organic functional groups. Mg, Mn, Fe, Al, and Si are redistributed into clays that strongly adsorb ions. Microbes contribute to dissolution of insoluble secondary phosphates, possibly via release of organic acids. These reactions significantly impact soil fertility. Below fungi–mineral interfaces, mineral surfaces are exposed to dissolved metabolic byproducts. Through this indirect process, microorganisms can accelerate mineral dissolution, leading to enhanced porosity and permeability and colonization by microbial communities.

A model of self-thinning through local competition.

Explanations of self-thinning in plant populations have focused on plant shape and packing. A dynamic model based on the structure of local interactions successfully reproduces the pattern and can be approximated to identify key parameters and relationships. The approach generates testable new explanations for differences between species and populations, unifies self-thinning with other patterns in plant population dynamics, and indicates why organisms other than plants can follow the law.

Comparative analysis of ribonuclease P RNA using gene sequences from natural microbial populations reveals tertiary structural elements.

PCR amplification of template DNAs extracted from mixed, naturally occurring microbial populations, using oligonucleotide primers complementary to highly conserved sequences, was used to obtain a large collection of diverse RNase P RNA-encoding genes. An alignment of these sequences was used in a comparative analysis of RNase P RNA secondary and tertiary structure. The new sequences confirm the secondary structure model based on sequences from cultivated organisms (with minor alterations in helices P12 and P18), providing additional support for nearly every base pair. Analysis of sequence covariation using the entire RNase P RNA data set reveals elements of tertiary structure in the RNA; the third nucleotides (underlined) of the GNRA tetraloops L14 and L18 are seen to interact with adjacent Watson-Crick base pairs in helix P8, forming A:G/C or G:A/U base triples. These experiments demonstrate one way in which the enormous diversity of natural microbial populations can be used to elucidate molecular structure through comparative analysis.