Elucidation of molecular kinetic schemes from macroscopic traces using system identification

Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully applied to accurately derive molecular kinetic schemes from experimental macroscopic traces, and we anticipate that it may be useful in the study of a wide variety of biological systems

Ligand-Receptor Interactions

The formation and dissociation of specific noncovalent interactions between a variety of macromolecules play a crucial role in the function of biological systems. During the last few years, three main lines of research led to a dramatic improvement of our understanding of these important phenomena. First, combination of genetic engineering and X ray cristallography made available a simultaneous knowledg of the precise structure and affinity of series or related ligand-receptor systems differing by a few well-defined atoms. Second, improvement of computer power and simulation techniques allowed extended exploration of the interaction of realistic macromolecules. Third, simultaneous development of a variety of techniques based on atomic force microscopy, hydrodynamic flow, biomembrane probes, optical tweezers, magnetic fields or flexible transducers yielded direct experimental information of the behavior of single ligand receptor bonds. At the same time, investigation of well defined cellular models raised the interest of biologists to the kinetic and mechanical properties of cell membrane receptors. The aim of this review is to give a description of these advances that benefitted from a largely multidisciplinar approach

A new look at an old view of denaturant induced protein unfolding

We re-examine a site-binding approach independently proposed by Schellman (Schellman, J.A. (1958) Compt. rend. Lab. Carlsberg Ser. Chim. 30, 439-449) and Aune and Tanford (Aune, K.C. and Tanford, D. (1969) Biochemistry, 8, 4586-4590) for explicitly including the denaturant concentration within the protein unfolding equilibrium. We extend and formalize the approach through development of a multi-dimensional analytical model in which the folding reaction coordinate is defined by the number of denaturant molecules bound to sites located on either the initially folded, or unfolded, states of the protein. We use the developed method to re-examine the mechanistic determinants underlying the sigmoidal shape of the unfolding transition. A natural feature of our method is that it presents a landscape picture of the denaturant induced protein unfolding reaction

Review of Data Sources, QSARs and Integrated Testing Strategies for Skin Sensitisation

This review collects information on sources of skin sensitisation data and computational tools for the estimation of skin sensitisation potential, such as expert systems and (quantitative) structure-activity relationship (QSAR) models. The review also captures current thinking of what constitutes an integrated testing strategy (ITS) for this endpoint. The emphasis of the review is on the usefulness of the models for the regulatory assessment of chemicals, particularly for the purposes of the new European legislation for the Registration, Evaluation, Authorisation and Restriction of CHemicals (REACH), which entered into force on 1 June 2007. Since there are no specific databases for skin sensitisation currently available, a description of experimental data found in various literature sources is provided. General (global) models, models for specific chemical classes and mechanisms of action and expert systems are summarised. This review was prepared as a contribution to the EU funded Integrated Project, OSIRIS.JRC.I.3-Consumer products safety and qualit

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology

Publications of the Jet Propulsion Laboratory, July 1964 through June 1965

JPL publications bibliography with abstracts - reports on DSIF, Mariner program, Ranger project, Surveyor project, and other space programs, and space science