Hume and the argument for biological design

There seems to be a widespread conviction — evidenced, for example, in the work of Mackie, Dawkins and Sober — that it is Darwinian rather than Humean considerations which deal the fatal logical blow to arguments for intelligent design. I argue that this conviction cannot be well-founded. If there are current logically decisive objections to design arguments, they must be Humean — for Darwinian considerations count not at all against design arguments based upon apparent cosmological fine-tuning. I argue, further, that there are good Humean reasons for atheists and agnostics to resist the suggestion that apparent design — apparent biological design and/or apparent cosmological fine-tuning — establishes (or even strongly supports) the hypothesis of intelligent design.     

Computational de novo design of a four-helix bundle protein—DND_4HB

The de novo design of proteins is a rigorous test of our understanding of the key determinants of protein structure. The helix bundle is an interesting de novo design model system due to the diverse topologies that can be generated from a few simple α-helices. Previously, noncomputational studies demonstrated that connecting amphipathic helices together with short loops can sometimes generate helix bundle proteins, regardless of the bundle''s exact sequence. However, using such methods, the precise positions of helices and side chains cannot be predetermined. Since protein function depends on exact positioning of residues, we examined if sequence design tools in the program Rosetta could be used to design a four-helix bundle with a predetermined structure. Helix position was specified using a folding procedure that constrained the design model to a defined topology, and iterative rounds of rotamer-based sequence design and backbone refinement were used to identify a low energy sequence for characterization. The designed protein, DND_4HB, unfolds cooperatively (T_m >90°C) and a NMR solution structure shows that it adopts the target helical bundle topology. Helices 2, 3, and 4 agree very closely with the design model (backbone RMSD = 1.11 Å) and >90% of the core side chain χ1 and χ2 angles are correctly predicted. Helix 1 lies in the target groove against the other helices, but is displaced 3 Å along the bundle axis. This result highlights the potential of computational design to create bundles with atomic-level precision, but also points at remaining challenges for achieving specific positioning between amphipathic helices.     

Slow and Bimolecular Folding of a De Novo Designed Monomeric Protein DS119

De novo protein design offers a unique means to test and advance our understanding of how proteins fold. However, most current design methods are native structure eccentric and folding kinetics has rarely been considered in the design process. Here, we show that a de novo designed mini-protein DS119, which folds into a βαβ structure, exhibits unusually slow and concentration-dependent folding kinetics. For example, the folding time for 50 μM of DS119 was estimated to be ∼2 s. Stopped-flow fluorescence resonance energy transfer experiments further suggested that its folding was likely facilitated by a transient dimerization process. Taken together, these results highlight the need for consideration of the entire folding energy landscape in de novo protein design and provide evidence suggesting nonnative interactions can play a key role in protein folding.     

A Data-Driven Design Evaluation Tool for Handheld Device Soft Keyboards

Thumb interaction is a primary technique used to operate small handheld devices such as smartphones. Despite the different techniques involved in operating a handheld device compared to a personal computer, the keyboard layouts for both devices are similar. A handheld device keyboard that considers the physical capabilities of the thumb may improve user experience. We developed and applied a design evaluation tool for different geometries of the QWERTY keyboard using a performance evaluation model. The model utilizes previously collected data on thumb motor performance and posture for different tap locations and thumb movement directions. We calculated a performance index (PI_TOT, 0 is worst and 2 is best) for 663 designs consisting in different combinations of three variables: the keyboard''s radius of curvature (R) (mm), orientation (O) (°), and vertical location on the screen (L). The current standard keyboard performed poorly (PI_TOT = 0.28) compared to other designs considered. Keyboard location (L) contributed to the greatest variability in performance out of the three design variables, suggesting that designers should modify this variable first. Performance was greatest for designs in the middle keyboard location. In addition, having a slightly upward curve (R = −20 mm) and orientated perpendicular to the thumb''s long axis (O = −20°) improved performance to PI_TOT = 1.97. Poorest performances were associated with placement of the keyboard''s spacebar in the bottom right corner of the screen (e.g., the worst was for R = 20 mm, O = 40°, L =  Bottom (PI_TOT = 0.09)). While this evaluation tool can be used in the design process as an ergonomic reference to promote user motor performance, other design variables such as visual access and usability still remain unexplored.     

Efficiency of New Dose Escalation Designs in Dose-Finding Phase I Trials of Molecularly Targeted Agents

Background

Statistical simulations have consistently demonstrated that new dose-escalation designs such as accelerated titration design (ATD) and continual reassessment method (CRM)-type designs outperform the standard “3+3” design in phase I cancer clinical trials.

Methods

We evaluated the actual efficiency of different dose escalation methods employed in first-in-human phase I clinical trials of targeted agents administered as single agents published over the last decade.

Results

Forty-nine per cent of the 84 retrieved trials used the standard “3+3” design. Newer designs used included ATD in 42%, modified CRM [mCRM] in 7%, and pharmacologically guided dose escalation in 1%. The median numbers of dose levels explored in trials using “3+3”, ATD and mCRM designs were 6, 8 and 10, respectively. More strikingly, the mean MTD to starting dose ratio appeared to be at least twice as high for trials using mCRM or ATD designs as for trials using a standard “3+3” design. Despite this, the mean number of patients exposed to a dose below the MTD was similar in trials using “3+3”, ATD and mCRM designs.

Conclusion

Our results support a more extensive implementation of innovative dose escalation designs such as mCRM and ATD in phase I cancer clinical trials of molecularly targeted agents.     

A comparison of the responses of two microcosm designs to a toxic input of copper

Two microcosm designs were compared for their sensitivity to toxic concentrations of copper. One design simulated a littoral zone, including macrophytes, sediment, and associated organisms. The other design used a periphyton community collected on polyurethane foam artificial substrata. Microcosms were dosed with copper sulfate (0–300 µg Cu 1^–1, nominal concentrations) and monitored for changes in several structural and process variables. Coefficients of variation of responses measured from the littoral microcosms were greater than from responses measured from the artificial-substrata microcosms. Effects were detected more frequently at lower concentrations of copper in the artificial-substrata microcosms than in the littoral microcosms. Lowest observable effect concentrations (LOECs) for measures of community structure ranged from 20.2–42.8 µg Cu 1^–1 in the artificial-substrata microcosms and from 24.0–98.5 µg Cu 1^–1 in the littoral microcosms. LOECs for measures of community process ranged from 42.8–310.3 µg 1^–1 in the artificial substrata microcosms. Significant differences from controls for community process were detected only at 304.7 µg Cu 1^–1 in the littoral microcosms. While there were differences between the two microcosm designs in the concentrations of copper that resulted in adverse effects, response trends were similar. Often, dose-response relationships between variables and copper concentrations were not log-linear, but showed stimulations at intermediate concentrations of copper (10–100 µg 1^–1, nominal concentrations). The choice of microcosm design should be dependent on the particular research question, as the designs differ in complexity and in the ease of construction and maintenance.     

Selective inhibition of 11β-hydroxysteroid dehydrogenase 1 by 18α-glycyrrhetinic acid but not 18β-glycyrrhetinic acid

Elevated cortisol concentrations have been associated with metabolic diseases such as diabetes type 2 and obesity. 11β-hydroxysteroid dehydrogenase (11β-HSD) type 1, catalyzing the conversion of inactive 11-ketoglucocorticoids into their active 11β-hydroxy forms, plays an important role in the regulation of cortisol levels within specific tissues. The selective inhibition of 11β-HSD1 is currently considered as promising therapeutic strategy for the treatment of metabolic diseases. In recent years, natural compound-derived drug design has gained considerable interest. 18β-glycyrrhetinic acid (GA), a metabolite of the natural product glycyrrhizin, is not selective and inhibits both 11β-HSD1 and 11β-HSD2. Here, we compare the biological activity of 18β-GA and its diastereomer 18α-GA against the two enzymes in lysates of transfected HEK-293 cells and show that 18α-GA selectively inhibits 11β-HSD1 but not 11β-HSD2. This is in contrast to 18β-GA, which preferentially inhibits 11β-HSD2. Using a pharmacophore model based on the crystal structure of the GA-derivative carbenoxolone in complex with human 11β-HSD1, we provide an explanation for the differences in the activities of 18α-GA and 18β-GA. This model will be used to design novel selective derivatives of GA.     

Optimal design of genetic studies of gene expression with two-color microarrays in outbred crosses

Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the “distant pair design” maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the “optimal pair design,” for use with F₂ crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance.     

Factorial design and response surface optimization of crude violacein for Chromobacterium violaceum production

Initially an eleven variable, sixteen assay 2^15–11 fractional factorial design, was used to determine the key factors in the production of violacein produced by Chromobacterium violaceum, CCT 3496. Subsequently five and three factor central composite designs were executed to determine response surfaces with the aim of optimizing cellular mass and crude violacein production. The 7.5 g l^–1 dry cell mass and 0.17 g l^–1 crude violacein productions obtained with our initial culture medium were increased to 21 g l^–1 and 0.43 g l^–1, respectively, for a medium investigated in the three factor design.     

The optimization of Marasmius androsaceus submerged fermentation conditions in five-liter fermentor

Using desirability function, four indexes including mycelium dry weight, intracellular polysaccharide, adenosine and mannitol yield were uniformed into one expected value (Da) which further served as the assessment criteria. In our present study, Plackett–Burman design was applied to evaluate the effects of eight variables including initial pH, rotating speed, culture temperature, inoculum size, ventilation volume, culture time, inoculum age and loading volume on Da value during Marasmius androsaceus submerged fermentation via a five-liter fermentor. Culture time, initial pH and rotating speed were found to influence Da value significantly and were further optimized by Box–Behnken design. Results obtained from Box–Behnken design were analyzed by both response surface regression (Design-Expert.V8.0.6.1 software) and artificial neural network combining the genetic algorithm method (Matlab2012a software). After comparison, the optimum M. androsaceus submerged fermentation conditions via a five-liter fermentor were obtained as follows: initial pH of 6.14, rotating speed of 289.3 rpm, culture time of 6.285 days, culture temperature of 26 °C, inoculum size of 5%, ventilation volume of 200 L/h, inoculum age of 4 days, and loading volume of 3.5 L/5 L. The predicted Da value of the optimum model was 0.4884 and the average experimental Da value was 0.4760. The model possesses well fitness and predictive ability.     

Simultaneous determination of citalopram, fluoxetine, paroxetine and their metabolites in plasma and whole blood by high-performance liquid chromatography with ultraviolet and fluorescence detection

A method for the simultaneous determination of the three selective serotonin reuptake inhibitors (SSRIs) citalopram, fluoxetine, paroxetine and their metabolites in whole blood and plasma was developed. Sample clean-up and separation were achieved using a solid-phase extraction method with C₈ non-endcapped columns followed by reversed-phase high-performance liquid chromatography with fluorescence and ultraviolet detection. The robustness of the solid-phase extraction method was tested for citalopram, fluoxetine, paroxetine, Cl-citalopram and the internal standard, protriptyline, using a fractional factorial design with nine factors at two levels. The fractional factorial design showed two significant effects for paroxetine in whole blood. The robustness testing for citalopram, fluoxetine, Cl-citalopram and the internal standard revealed no significant main effects in whole blood and plasma. The optimization and the robustness of the high-performance liquid chromatographic separation were investigated with regard to pH and relative amount of acetonitrile in the mobile phase by a central composite design circumscribed. No alteration in the elution order and no significant change in resolution for a deviation of ±1% acetonitrile and ±0.3 pH units from the specified conditions were observed. The method was validated for the concentration range 0.050–5.0 μmol/l with fluorescence detection and 0.12–5.0 μmol/l with ultraviolet detection. The limits of quantitation were 0.025 μmol/l for citalopram and paroxetine, 0.050 μmol/l for desmethyl citalopram, di-desmethyl citalopram and citalopram-N-oxide, 0.12 μmol/l for the paroxetine metabolites by fluorescence detection, and 0.10 μmol/l for fluoxetine and norfluoxetine by ultraviolet detection. Relative standard deviations for the within-day and between-day precision were in the ranges 1.4–10.6% and 3.1–20.3%, respectively. Recoveries were in the 63–114% range for citalopram, fluoxetine and paroxetine, and in the 38–95% range for the metabolites. The method has been used for the analysis of whole blood and plasma samples from SSRI-exposed patients and forensic cases.     

The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10⁻⁶) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10⁻¹²). Performance of the Potts model (r = −0.73, p = 9.7×10⁻⁹) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion, and harnessing this knowledge for immunogen design.     

Position-dependent effects of locked nucleic acid (LNA) on DNA sequencing and PCR primers

Genomes are becoming heavily annotated with important features. Analysis of these features often employs oligonucleotides that hybridize at defined locations. When the defined location lies in a poor sequence context, traditional design strategies may fail. Locked Nucleic Acid (LNA) can enhance oligonucleotide affinity and specificity. Though LNA has been used in many applications, formal design rules are still being defined. To further this effort we have investigated the effect of LNA on the performance of sequencing and PCR primers in AT-rich regions, where short primers yield poor sequencing reads or PCR yields. LNA was used in three positional patterns: near the 5′ end (LNA-5′), near the 3′ end (LNA-3′) and distributed throughout (LNA-Even). Quantitative measures of sequencing read length (Phred Q30 count) and real-time PCR signal (cycle threshold, C_T) were characterized using two-way ANOVA. LNA-5′ increased the average Phred Q30 score by 60% and it was never observed to decrease performance. LNA-5′ generated cycle thresholds in quantitative PCR that were comparable to high-yielding conventional primers. In contrast, LNA-3′ and LNA-Even did not improve read lengths or C_T. ANOVA demonstrated the statistical significance of these results and identified significant interaction between the positional design rule and primer sequence.     

Ligand Clouds around Protein Clouds: A Scenario of Ligand Binding with Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) were found to be widely associated with human diseases and may serve as potential drug design targets. However, drug design targeting IDPs is still in the very early stages. Progress in drug design is usually achieved using experimental screening; however, the structural disorder of IDPs makes it difficult to characterize their interaction with ligands using experiments alone. To better understand the structure of IDPs and their interactions with small molecule ligands, we performed extensive simulations on the c-Myc_370–409 peptide and its binding to a reported small molecule inhibitor, ligand 10074-A4. We found that the conformational space of the apo c-Myc_370–409 peptide was rather dispersed and that the conformations of the peptide were stabilized mainly by charge interactions and hydrogen bonds. Under the binding of the ligand, c-Myc_370–409 remained disordered. The ligand was found to bind to c-Myc_370–409 at different sites along the chain and behaved like a ‘ligand cloud’. In contrast to ligand binding to more rigid target proteins that usually results in a dominant bound structure, ligand binding to IDPs may better be described as ligand clouds around protein clouds. Nevertheless, the binding of the ligand and a non-ligand to the c-Myc_370–409 target could be clearly distinguished. The present study provides insights that will help improve rational drug design that targets IDPs.     

A Unique Primer with an Inosine Chain at the 5′-Terminus Improves the Reliability of SNP Analysis Using the PCR-Amplified Product Length Polymorphism Method

Polymerase chain reaction-amplified product length polymorphism (PCR-APLP) is one of the most convenient and reliable methods for single nucleotide polymorphism (SNP) analysis. This method is based on PCR, but uses allele-specific primers containing SNP sites at the 3′-terminus of each primer. To use this method at least two allele-specific primers and one “counter-primer”, which serves as a common forward or reverse primer of the allele-specific primers, are required. The allele-specific primers have SNP sites at the 3′-terminus, and another primer should have a few non-complementary flaps at the 5′-terminus to detect SNPs by determining the difference of amplicon length by PCR and subsequent electrophoresis. A major disadvantage of the addition of a non-complementary flap is the non-specific annealing of the primer with non-complementary flaps. However, a design principle for avoiding this undesired annealing has not been fully established, therefore, it is often difficult to design effective APLP primers. Here, we report allele-specific primers with an inosine chain at the 5′-terminus for PCR-APLP analysis. This unique design improves the competitiveness of allele-specific primers and the reliability of SNP analysis when using the PCR-APLP method.     

Designed leucine‐rich repeat proteins bind two muramyl dipeptide ligands

Designed protein receptors hold diagnostic and therapeutic promise. We now report the design of five consensus leucine‐rich repeat proteins (CLRR4–8) based on the LRR domain of nucleotide‐binding oligomerization domain (NOD)‐like receptors involved in the innate immune system. The CLRRs bind muramyl dipeptide (MDP), a bacterial cell wall component, with micromolar affinity. The overall K _{d app} values ranged from 1.0 to 57 μM as measured by fluorescence quenching experiments. Biphasic fluorescence quenching curves were observed in all CLRRs, with higher affinity K _d1 values ranging from 0.04 to 4.5 μM, and lower affinity K _d2 values ranging from 3.1 to 227 μM. These biphasic binding curves, along with the docking studies of MDP binding to CLRR4, suggest that at least two MDPs bind to each protein. Previously, only single MDP binding was reported. This high‐capacity binding of MDP promises small, soluble, stable CLRR scaffolds as candidates for the future design of pathogen biosensors.     

Emergence of protein fold families through rational design

Diverse proteins with similar structures are grouped into families of homologs and analogs, if their sequence similarity is higher or lower, respectively, than 20%–30%. It was suggested that protein homologs and analogs originate from a common ancestor and diverge in their distinct evolutionary time scales, emerging as a consequence of the physical properties of the protein sequence space. Although a number of studies have determined key signatures of protein family organization, the sequence-structure factors that differentiate the two evolution-related protein families remain unknown. Here, we stipulate that subtle structural changes, which appear due to accumulating mutations in the homologous families, lead to distinct packing of the protein core and, thus, novel compositions of core residues. The latter process leads to the formation of distinct families of homologs. We propose that such differentiation results in the formation of analogous families. To test our postulate, we developed a molecular modeling and design toolkit, Medusa, to computationally design protein sequences that correspond to the same fold family. We find that analogous proteins emerge when a backbone structure deviates only 1–2 Å root-mean-square deviation from the original structure. For close homologs, core residues are highly conserved. However, when the overall sequence similarity drops to ~25%–30%, the composition of core residues starts to diverge, thereby forming novel families of protein homologs. This direct observation of the formation of protein homologs within a specific fold family supports our hypothesis. The conservation of amino acids in designed sequences recapitulates that of the naturally occurring sequences, thereby validating our computational design methodology.     

Tailoring RNA modular units on a common scaffold: A modular ribozyme with a catalytic unit for β-nicotinamide mononucleotide-activated RNA ligation

A novel ribozyme that accelerates the ligation of β-nicotinamide mononucleotide (β-NMN)-activated RNA fragments was isolated and characterized. This artificial ligase ribozyme (YFL ribozyme) was isolated by a “design and selection” strategy, in which a modular catalytic unit was generated on a rationally designed modular scaffold RNA. Biochemical analyses of the YFL ribozyme revealed that it catalyzes RNA ligation in a template-dependent manner, and its activity is highly dependent on its architecture, which consists of a modular scaffold and a catalytic unit. As the design and selection strategy was used for generation of DSL ribozyme, isolation of the YFL ribozyme indicated the versatility of this strategy for generation of functional RNAs with modular architectures. The catalytic unit of the YFL ribozyme accepts not only β-NMN but also inorganic pyrophosphate and adenosine monophosphate as leaving groups for RNA ligation. This versatility of the YFL ribozyme provides novel insight into the possible roles of β-NMN (or NADH) in the RNA world.     

Design and synthesis of peptides that bind α-bungarotoxin with high affinity and mimic the three-dimensional structure of the binding-site of acetylcholine receptor

α-Bungarotoxin (α-BTX) is a highly toxic snake neurotoxin that binds to acetylcholine receptor (AChR) at the neuromuscular junction, and is a potent inhibitor of this receptor. In the following we review multi-phase research of the design, synthesis and structure analysis of peptides that bind α-BTX and inhibit its binding to AChR. Structure-based design concomitant with biological information of the α-BTX/AChR system yielded 13-mer peptides that bind to α-BTX with high affinity and are potent inhibitors of α-BTX binding to AChR (IC₅₀ of 2 nM). X-Ray and NMR spectroscopy reveal that the high-affinity peptides fold into an anti-parallel β-hairpin structure when bound to α-BTX. The structures of the bound peptides and the homologous loop of acetylcholine binding protein, a soluble analog of AChR, are remarkably similar. Their superposition indicates that the toxin wraps around the binding-site loop, and in addition, binds tightly at the interface of two of the receptor subunits and blocks access of acetylcholine to its binding site. The procedure described in this article may serve as a paradigm for obtaining high-affinity peptides in biochemical systems that contain a ligand and a receptor molecule.