Analysis of innovative two-stage seamless adaptive design with different endpoints and population shift

In recent years, clinical trials utilizing a two-stage seamless adaptive trial design have become very popular in drug development. A typical example is a phase 2/3 adaptive trial design, which consists of two stages. As an example, stage 1 is for a phase 2 dose-finding study and stage 2 is for a phase 3 efficacy confirmation study. Depending upon whether or not the target patient population, study objectives, and study endpoints are the same at different stages, Chow (2020) classified two-stage seamless adaptive design into eight categories. In practice, standard statistical methods for group sequential design with one planned interim analysis are often wrongly directly applied for data analysis. In this article, following similar ideas proposed by Chow and Lin (2015) and Chow (2020), a statistical method for the analysis of a two-stage seamless adaptive trial design with different study endpoints and shifted target patient population is discussed under the fundamental assumption that study endpoints have a known relationship. The proposed analysis method should be useful in both clinical trials with protocol amendments and clinical trials with the existence of disease progression utilizing a two-stage seamless adaptive trial design.

Decoupling the dynamic mechanism revealed by FGFR2 mutation-induced population shift

The fibroblast growth factor receptor 2 (FGFR2) is a key component in cellular signaling networks, and its dysfunctional activation has been implicated in various diseases including cancer and developmental disorders. Mutations at the activation loop (A-loop) have been suggested to trigger an increased basal kinase activity. However, the molecular mechanism underlying this highly dynamic process has not been fully understood due to the limitation of static structural information. Here, we conducted multiple, large-scale Gaussian accelerated molecular dynamics simulations of five (K659E, K659N, K659M, K659Q, and K659T) FGFR2 mutants at the A-loop, and comprehensively analyzed the dynamic molecular basis of FGFR2 activation. The results quantified the population shift of each system, revealing that all mutants had a higher proportion of active-like states. Using Markov state models, we extracted the representative structure of different conformational states and identified key residues related to the increased kinase activity. Furthermore, community network analysis showed enhanced information connections in the mutants, highlighting the long-range allosteric communication between the A-loop and the hinge region. Our findings may provide insights into the dynamic mechanism for FGFR2 dysfunctional activation and allosteric drug discovery.Communicated by Ramaswamy H. Sarma.

Decision region analysis for generalizability of artificial intelligence models: estimating model generalizability in the case of cross-reactivity and population shift

Purpose

Understanding an artificial intelligence (AI) model's ability to generalize to its target population is critical to ensuring the safe and effective usage of AI in medical devices. A traditional generalizability assessment relies on the availability of large, diverse datasets, which are difficult to obtain in many medical imaging applications. We present an approach for enhanced generalizability assessment by examining the decision space beyond the available testing data distribution.

Approach

Vicinal distributions of virtual samples are generated by interpolating between triplets of test images. The generated virtual samples leverage the characteristics already in the test set, increasing the sample diversity while remaining close to the AI model's data manifold. We demonstrate the generalizability assessment approach on the non-clinical tasks of classifying patient sex, race, COVID status, and age group from chest x-rays.

Results

Decision region composition analysis for generalizability indicated that a disproportionately large portion of the decision space belonged to a single "preferred" class for each task, despite comparable performance on the evaluation dataset. Evaluation using cross-reactivity and population shift strategies indicated a tendency to overpredict samples as belonging to the preferred class (e.g., COVID negative) for patients whose subgroup was not represented in the model development data.

Conclusions

An analysis of an AI model's decision space has the potential to provide insight into model generalizability. Our approach uses the analysis of composition of the decision space to obtain an improved assessment of model generalizability in the case of limited test data.

A population shift between two heritable cell types of the pathogen Candida albicans is based both on switching and selective proliferation

Differentiated cell types often retain their characteristics through many rounds of cell division. A simple example is found in Candida albicans, a member of the human microbiota and also the most prevalent fungal pathogen of humans; here, two distinct cell types (white and opaque) exist, and each one retains its specialized properties across many cell divisions. Switching between the two cell types is rare in standard laboratory medium (2% glucose) but can be increased by signals in the environment, for example, certain sugars. When these signals are removed, switching ceases and cells remain in their present state, which is faithfully passed on through many generations of daughter cells. Here, using an automated flow cytometry assay to monitor white-opaque switching over 96 different sugar concentrations, we observed a wide range of opaque-to-white switching that varied continuously across different sugar compositions of the medium. By also measuring white cell proliferation rates under each condition, we found that both opaque-to-white switching and selective white cell proliferation are required for entire populations to shift from opaque to white. Moreover, the switching frequency correlates with the preference of the resulting cell type for the growth medium; that is, the switching is adjusted to increase in environments that favor white cell proliferation. The widely adjustable, all-or-none nature of the switch, combined with the long-term heritability of each state, is distinct from conventional forms of gene regulation, and we propose that it represents a strategy used by C. albicans to efficiently colonize different niches of its human host.

Hidden electrostatic basis of dynamic allostery in a PDZ domain

Allosteric effect implies ligand binding at one site leading to structural and/or dynamical changes at a distant site. PDZ domains are classic examples of dynamic allostery without conformational changes, where distal side-chain dynamics is modulated on ligand binding and the origin has been attributed to entropic effects. In this work, we unearth the energetic basis of the observed dynamic allostery in a PDZ3 domain protein using molecular dynamics simulations. We demonstrate that electrostatic interaction provides a highly sensitive yardstick to probe the allosteric modulation in contrast to the traditionally used structure-based parameters. There is a significant population shift in the hydrogen-bonded network and salt bridges involving side chains on ligand binding. The ligand creates a local energetic perturbation that propagates in the form of dominolike changes in interresidue interaction pattern. There are significant changes in the nature of specific interactions (nonpolar/polar) between interresidue contacts and accompanied side-chain reorientations that drive the major redistribution of energy. Interestingly, this internal redistribution and rewiring of side-chain interactions led to large cancellations resulting in small change in the overall enthalpy of the protein, thus making it difficult to detect experimentally. In contrast to the prevailing focus on the entropic or dynamic effects, we show that the internal redistribution and population shift in specific electrostatic interactions drive the allosteric modulation in the PDZ3 domain protein.

Multiple Conformations of Gal3 Protein Drive the Galactose-Induced Allosteric Activation of the GAL Genetic Switch of Saccharomyces cerevisiae

Gal3p is an allosteric monomeric protein that activates the GAL genetic switch of Saccharomyces cerevisiae in response to galactose. Expression of constitutive mutant of Gal3p or overexpression of wild-type Gal3p activates the GAL switch in the absence of galactose. These data suggest that Gal3p exists as an ensemble of active and inactive conformations. Structural data have indicated that Gal3p exists in open (inactive) and closed (active) conformations. However, a mutant of Gal3p that predominantly exists in inactive conformation and is yet capable of responding to galactose has not been isolated. To understand the mechanism of allosteric transition, we have isolated a triple mutant of Gal3p with V273I, T404A, and N450D substitutions, which, upon overexpression, fails to activate the GAL switch on its own but activates the switch in response to galactose. Overexpression of Gal3p mutants with single or double mutations in any of the three combinations failed to exhibit the behavior of the triple mutant. Molecular dynamics analysis of the wild-type and the triple mutant along with two previously reported constitutive mutants suggests that the wild-type Gal3p may also exist in super-open conformation. Furthermore, our results suggest that the dynamics of residue F237 situated in the hydrophobic pocket located in the hinge region drives the transition between different conformations. Based on this study, we suggest that conformational selection mechanism is the driving force in the allosteric transition of Gal3p, which may have implications in other signaling pathways involving monomeric proteins.

Conformational shift in the closed state of GroEL induced by ATP-binding triggers a transition to the open state

We investigated the effect of ATP binding to GroEL and elucidated a role of ATP in the conformational change of GroEL. GroEL is a tetradecamer chaperonin that helps protein folding by undergoing a conformational change from a closed state to an open state. This conformational change requires ATP, but does not require the hydrolysis of the ATP. The following three types of conformations are crystalized and the atomic coordinates are available; closed state without ATP, closed state with ATP and open state with ADP. We conducted simulations of the conformational change using Elastic Network Model from the closed state without ATP targeting at the open state, and from the closed state with ATP targeting at the open state. The simulations emphasizing the lowest normal mode showed that the one started with the closed state with ATP, rather than the one without ATP, reached a conformation closer to the open state. This difference was mainly caused by the changes in the positions of residues in the initial structure rather than the changes in "connectivity" of residues within the subunit. Our results suggest that ATP should behave as an insulator to induce conformation population shift in the closed state to the conformation that has a pathway leading to the open state.

Efficacy evaluation of managed population shift in Ukraine from zone of obligate (compulsory) resettlement as a measure of public radiation protection

OBJECTIVE

Evaluation of efficacy of the managed population transmigration from zone of obligate (compulsory) resettlement as a measure of civil protection after the Chernobyl NPP accident from the perspective of radiation biology.

MATERIALS AND METHODS

Legislative and statutory tutorial documents that regulate the managed population shift from radiologically contaminated territories of Ukraine and data from the Ukrainian State Service of Statistics on time limits and scopes of population transmigration from contaminated settlements were the informational back ground of the study. Data on retrospective and expected/anticipated radiation doses in population of settlements exposed to radiological contamination in Ukraine after the Chernobyl disaster summarized for the 1986-1997 peri od and up to 2055 were the information source for calculation of averted doses due to population shift. Battery of basic research empirical evidence review methods was applied under the calculation, systemic, and biomedical approach.

RESULTS AND CONCLUSIONS

Population shift from zone of obligate (compulsore) resettlement (hereafter referred to as Zone 2) to stop the radiation exposure as a tool of civil protection from emergency ionizing radiation after the Chernobyl NPP accident was scientifically substantiated and expedient from the perspective of radiation biology. Estimability of a managed population shift from "dose effect" perspective and "benefit/harm" principle is worse because of data absence on individual radiation doses to migrants in the country. Public shift in 1990 and 1991 was most effective from the viewpoint of level of averted lifetime dose. Due to transmigration the averted lifetime dose to the most vulnerable group of the Chernobyl disaster survivors i.e. children aged 0 years varied from 11.2 to 28.8 mSv (calculated for the Perejizdiv village council of Zhytomyr province). Since 2000 there was almost no public shift being not accomplished in the scheduled scope. Delay and incompleteness of transmigration have diminished the efficacy of this measure in the framework of radiological protection of population.

Population shift of binding pocket size and dynamic correlation analysis shed new light on the anticooperative mechanism of PII protein

PII protein is one of the largest families of signal transduction proteins in archaea, bacteria, and plants, controlling key processes of nitrogen assimilation. An intriguing characteristic for many PII proteins is that the three ligand binding sites exhibit anticooperative allosteric regulation. In this work, PII protein from Synechococcus elongatus, a model for cyanobacteria and plant PII proteins, is utilized to reveal the anticooperative mechanism upon binding of 2-oxoglutarate (2-OG). To this end, a method is proposed to define the binding pocket size by identifying residues that contribute greatly to the binding of 2-OG. It is found that the anticooperativity is realized through population shift of the binding pocket size in an asymmetric manner. Furthermore, a new algorithm based on the dynamic correlation analysis is developed and utilized to discover residues that mediate the anticooperative process with high probability. It is surprising to find that the T-loop, which is believed to be responsible for mediating the binding of PII with its target proteins, also takes part in the intersubunit signal transduction process. Experimental results of PII variants further confirmed the influence of T-loop on the anticooperative regulation, especially on binding of the third 2-OG. These discoveries extend our understanding of the PII T-loop from being essential in versatile binding of target protein to signal-mediating in the anticooperative allosteric regulation.

Two-state dynamics of the SH3-SH2 tandem of Abl kinase and the allosteric role of the N-cap

The regulation and localization of signaling enzymes is often mediated by accessory modular domains, which frequently function in tandems. The ability of these tandems to adopt multiple conformations is as important for proper regulation as the individual domain specificity. A paradigmatic example is Abl, a ubiquitous tyrosine kinase of significant pharmacological interest. SH3 and SH2 domains inhibit Abl by assembling onto the catalytic domain, allosterically clamping it in an inactive state. We investigate the dynamics of this SH3-SH2 tandem, using microsecond all-atom simulations and differential scanning calorimetry. Our results indicate that the Abl tandem is a two-state switch, alternating between the conformation observed in the structure of the autoinhibited enzyme and another configuration that is consistent with existing scattering data for an activated form. Intriguingly, we find that the latter is the most probable when the tandem is disengaged from the catalytic domain. Nevertheless, an amino acid stretch preceding the SH3 domain, the so-called N-cap, reshapes the free-energy landscape of the tandem and favors the interaction of this domain with the SH2-kinase linker, an intermediate step necessary for assembly of the autoinhibited complex. This allosteric effect arises from interactions between N-cap and the SH2 domain and SH3-SH2 connector, which involve a phosphorylation site. We also show that the SH3-SH2 connector plays a determinant role in the assembly equilibrium of Abl, because mutations thereof hinder the engagement of the SH2-kinase linker. These results provide a thermodynamic rationale for the involvement of N-cap and SH3-SH2 connector in Abl regulation and expand our understanding of the principles of modular domain organization.

The spatial structure of cell signaling systems

The spatial structure of the cell is highly organized at all levels: from small complexes and assemblies, to local nano- and microclusters, to global, micrometer scales across and between cells. We suggest that this multiscale spatial cell organization also organizes signaling and coordinates cellular behavior. We propose a new view of the spatial structure of cell signaling systems. This new view describes cell signaling in terms of dynamic allosteric interactions within and among distinct, spatially organized transient clusters. The clusters vary over time and space and are on length scales from nanometers to micrometers. When considered across these length scales, primary factors in the spatial organization are cell membrane domains and the actin cytoskeleton, both also highly dynamic. A key challenge is to understand the interplay across these multiple scales, link it to the physicochemical basis of the conformational behavior of single molecules and ultimately relate it to cellular function. Overall, our premise is that at these scales, cell signaling should be thought of not primarily as a sequence of diffusion-controlled molecular collisions, but instead transient, allostery-driven cluster re-forming interactions.

Structural and Entropic Allosteric Signal Transduction Strength via Correlated Motions

Allosteric signal transduction in biomacromolecules can play an essential role in their function. Internal motional correlations in proteins provide a possible communication mechanism, but the quantitative relationship between statistical correlations and allostery is unknown. Quantitative relationships between internal motional correlations and the efficiency of propagation of allosteric structural and entropic effects are introduced and validated against conformational ensembles obtained from molecular dynamics simulations. This framework can explain a range of phenomena, such as the occurrence of an allosteric entropy change in the absence of any noticeable structural change.