Sequence-structure-function relationships

Moreover, molecular modeling is one key method of a wide range of computer-assisted methods to analyze and predict relationships between protein sequence, 3D-molecular structure, and biological function (sequence-structure-function relationships). In molecular pharmacology these methods focus predominantly on analysis of interactions between different proteins, and between ligands (hormones, drugs) and proteins as well gaining information at the amino acid and even to atomic level. 

The constantly increasing amount of data coming from high throughput experimental methods, from genome sequences, from functional- and structural genomics has given a rise to a need for computer-assisted methods to elucidate sequence-structure-function relationships. 

There are two different dimensions, breadth and depth, used to reveal sequence-structure -functional relationships by computational methods [1]. 

Efforts to investigate the questions posed here will lead to more useful peptoid designs while simultaneously leading to a better fundamental understanding of molecular recognition and sequence/structure/function relationships in non-natural, sequence-specific peptidomimetic ohgomers. 

With directed evolution we can engineer enzyme properties rapidly and with a high probability of success. Many enzymes that have been improved by directed evolution are listed in Tab. 4-3. This powerful biocatalyst engineering strategy creates new opportunities in organic synthesis new and improved bioconversion processes can be developed and novel compounds that are otherwise inaccessible by classical chemistry can be synthesized. In addition, the molecules created by directed evolution offer an excellent opportunity for improving our still poor understanding of sequence-structure-function relationships. 

Structure—function relationships of prolactin among a variety of species have been pubUshed (17,18). Only one gene for prolactin appears to exist (19). Although classically placed in the category of simple protein hormones, prolactin can be glycosylated. Carbohydrate attachment occurs at Asn-31, where the consensus glycosylation sequence Asn—X—Ser is found. 

RNA structures, compared to the helical motifs that dominate DNA, are quite diverse, assuming various loop conformations in addition to helical structures. This diversity allows RNA molecules to assume a wide variety of tertiary structures with many biological functions beyond the storage and propagation of the genetic code. Examples include transfer RNA, which is involved in the translation of mRNA into proteins, the RNA components of ribosomes, the translation machinery, and catalytic RNA molecules. In addition, it is now known that secondary and tertiary elements of mRNA can act to regulate the translation of its own primary sequence. Such diversity makes RNA a prime area for the study of structure-function relationships to which computational approaches can make a significant contribution. 

The aim of the second dimension depth is to consider protein 3D-stmctures to uncover structure-function relationships. Starting from the protein sequences, the steps in the depth dimension are structure prediction, homology modeling of protein structures, and the simulation of protein-protein interactions and ligand-complexes. 

A cloned complementary DNA to a neurotoxin precursor RNA extracted from the venom glands of Laticauda semifasciata was isolated and its nucleotide sequence was identified 11). The cloning of neurotoxin should aid the understanding of structure—function relationship eventually. 

Historically the Shaker (Sh) K channel was the first K channel which was cloned and characterized [6-10]. Subsequently many more channel cDNAs and genes have been isolated and studied. Yet Sh channels remained in the forefront of channel research. The study of Sh channel mutants has provided the most thorough insight into structure-function relationships of K channels to date. I will first discuss in this chapter the primary sequences of voltage-gated channels. I will only use a few selected examples for discussion. As of this time, so many related K channel protein sequences have been published that it is not feasible to discuss all of them. Subsequently, I will describe in detail the present knowledge about functional K" " channel domains which are implicated in activation, inactivation and selectivity of the channel. 

The cloning, sequencing and expression of several transporter proteins, including that for 5-HT, has aided considerably in understanding structure/function relationships of transporter proteins [12]. The cDNA for the SERT isolated from rat brain predicts a protein containing... 

The history of molecular biology has been a history of technological developments for determining the primary and tertiary structures of protein and nucleic acid molecules. Once the molecular structure is known, it provides clues to molecular functions. This is the principle of the structure-function relationship. Based on this principle the analysis of the amino acid sequence is performed to decipher the functional information from the sequence information. The analysis usually involves detection and prediction of empirical sequence—function relationships with additional consideration of known or predicted three-dimensional (3D) structures. Thus, the process can be represented schematically as ... 

Gorbalenya, A.E. and Koonin, E.V. (1993) Helicases amino acid sequence comparisons and structure-function relationships. Curr. Opin. Struct. Biol. 3, 419-429. 

The knowledge of amino acid sequences of proteins may provide their three-dimensional structures if CD predictions are valid. However, the CD prediction for the secondary structure of a given protein, especially having (3-sheet structures, is not valid enough to probe the structure-function relationships in native proteins. We are awaiting the development of a more precise prediction method for secondary structures of proteins. 

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