The Mycobacterium tuberculosis dosRS two-component system is induced by multiple stresses.

Induction of the Mycobacterium tuberculosis dosR gene, which is known to respond to hypoxia, was measured using RTq-PCR following exposure to different stresses. Increased expression was seen after exposure to S-nitrosoglutathione (GSNO), ethanol and (to a lesser extent) H2O2, but not heat- or cold-shock. We also demonstrated that hspX, which is dependent on dosR for expression, is induced when cultures are left standing for 30 min, while significant but minor induction was seen following a 10 min centrifugation. Microarray analysis was used to compare gene expression in wild-type and deltadosR strains following 30 min standing. Fifty-two genes were significantly up-regulated, and 19 genes were down-regulated. These included genes that had previously been reported as being part of the dosR regulon, and also some novel ones.

Automatic procedures for protein design.

This review describes computational procedures for deriving the amino acid sequences that are compatible with a given protein backbone structure. Such procedures can be used to gain insight into the constraints imposed by the 3D structure of the protein sequence, or to design proteins that are likely to adopt a given backbone conformation. We start by presenting a short overview of the various types of approaches to protein design developed over more than a decade. This is followed by a more detailed presentation of a recently developed sequence selection procedure DESIGNER. This latter presentation illustrates the basic principles underlying this type of procedures, described what they may teach us when applied to small proteins, and highlights issues that need to be addressed in order to go forward.

Representing and analysing molecular and cellular function using the computer.

Determining the biological function of a myriad of genes, and understanding how they interact to yield a living cell, is the major challenge of the post genome-sequencing era. The complexity of biological systems is such that this cannot be envisaged without the help of powerful computer systems capable of representing and analysing the intricate networks of physical and functional interactions between the different cellular components. In this review we try to provide the reader with an appreciation of where we stand in this regard. We discuss some of the inherent problems in describing the different facets of biological function, give an overview of how information on function is currently represented in the major biological databases, and describe different systems for organising and categorising the functions of gene products. In a second part, we present a new general data model, currently under development, which describes information on molecular function and cellular processes in a rigorous manner. The model is capable of representing a large variety of biochemical processes, including metabolic pathways, regulation of gene expression and signal transduction. It also incorporates taxonomies for categorising molecular entities, interactions and processes, and it offers means of viewing the information at different levels of resolution, and dealing with incomplete knowledge. The data model has been implemented in the database on protein function and cellular processes 'aMAZE' (http://www.ebi.ac.uk/research/pfbp/), which presently covers metabolic pathways and their regulation. Several tools for querying, displaying, and performing analyses on such pathways are briefly described in order to illustrate the practical applications enabled by the model.

Automatic protein design with all atom force-fields by exact and heuristic optimization.

A fully automatic procedure for predicting the amino acid sequences compatible with a given target structure is described. It is based on the CHARMM package, and uses an all atom force-field and rotamer libraries to describe and evaluate side-chain types and conformations. Sequences are ranked by a quantity akin to the free energy of folding, which incorporates hydration effects. Exact (Branch and Bound) and heuristic optimisation procedures are used to identifying highly scoring sequences from an astronomical number of possibilities. These sequences include the minimum free energy sequence, as well as all amino acid sequences whose free energy lies within a specified window from the minimum. Several applications of our procedure are illustrated. Prediction of side-chain conformations for a set of ten proteins yields results comparable to those of established side-chain placement programs. Applications to sequence optimisation comprise the re-design of the protein cores of c-Crk SH3 domain, the B1 domain of protein G and Ubiquitin, and of surface residues of the SH3 domain. In all calculations, no restrictions are imposed on the amino acid composition and identical parameter settings are used for core and surface residues. The best scoring sequences for the protein cores are virtually identical to wild-type. They feature no more than one to three mutations in a total of 11-16 variable positions. Tests suggest that this is due to the balance between various contributions in the force-field rather than to overwhelming influence from packing constraints. The effectiveness of our force-field is further supported by the sequence predictions for surface residues of the SH3 domain. More mutations are predicted than in the core, seemingly in order to optimise the network of complementary interactions between polar and charged groups. This appears to be an important energetic requirement in absence of the partner molecules with which the SH3 domain interacts, which were not included in the calculations. Finally, a detailed comparison between the sequences generated by the heuristic and exact optimisation algorithms, commends a note of caution concerning the efficiency of heuristic procedures in exploring sequence space.

Identification of structural domains in proteins by a graph heuristic.

A novel automatic procedure for identifying domains from protein atomic coordinates is presented. The procedure, termed STRUDL (STRUctural Domain Limits), does not take into account information on secondary structures and handles any number of domains made up of contiguous or non-contiguous chain segments. The core algorithm uses the Kernighan-Lin graph heuristic to partition the protein into residue sets which display minimum interactions between them. These interactions are deduced from the weighted Voronoi diagram. The generated partitions are accepted or rejected on the basis of optimized criteria, representing basic expected physical properties of structural domains. The graph heuristic approach is shown to be very effective, it approximates closely the exact solution provided by a branch and bound algorithm for a number of test proteins. In addition, the overall performance of STRUDL is assessed on a set of 787 representative proteins from the Protein Data Bank by comparison to domain definitions in the CATH protein classification. The domains assigned by STRUDL agree with the CATH assignments in at least 81% of the tested proteins. This result is comparable to that obtained previously using PUU (Holm and Sander, Proteins 1994;9:256-268), the only other available algorithm designed to identify domains with any number of non-contiguous chain segments. A detailed discussion of the structures for which our assignments differ from those in CATH brings to light some clear inconsistencies between the concept of structural domains based on minimizing inter-domain interactions and that of delimiting structural motifs that represent acceptable folding topologies or architectures. Considering both concepts as complementary and combining them in a layered approach might be the way forward.

Representation of amino acid sequences as two-dimensional point patterns.

An algorithm for the representation of amino acid sequences as two-dimensional point patterns (2-D plot) is described. The algorithm is based on chaos game representation (CGR) for DNA sequences and was extended for amino acid sequences. The 2-D plot depicts the sequentiality of amino acids and the amino acid composition of a protein. Changes in a protein sequence as insertion, deletion and repeats of amino acids are characterized by specific geometrical properties and changes in the 2-D plots. The 2-D plot may be considered as a two-dimensional "fingerprint" of a protein. The properties of the algorithm are explained by user-defined amino acid sequences. As an example the 2-D plots of two selected heart proteins are generated. The sequences of these proteins are obtained from the protein sequence database SWISS-PROT.