Dataset Information

Engineering Allostery into Proteins.

ABSTRACT: Our ability to engineer protein structure and function has grown dramatically over recent years. Perhaps the next level in protein design is to develop proteins whose function can be regulated in response to various stimuli, including ligand binding, pH changes, and light. Endeavors toward these goals have tested and expanded on our understanding of protein function and allosteric regulation. In this chapter, we provide examples from different methods for developing new allosterically regulated proteins. These methods range from whole insertion of regulatory domains into new host proteins, to covalent attachment of photoswitches to generate light-responsive proteins, and to targeted changes to specific amino acid residues, especially to residues identified to be important for relaying allosteric information across the protein framework. Many of the examples we discuss have already found practical use in medical and biotechnology applications.

SUBMITTER: Gorman SD

PROVIDER: S-EPMC7508002 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Engineering Allostery into Proteins.

Gorman Scott D SD D'Amico Rebecca N RN Winston Dennis S DS Boehr David D DD

Advances in experimental medicine and biology 20190101

Our ability to engineer protein structure and function has grown dramatically over recent years. Perhaps the next level in protein design is to develop proteins whose function can be regulated in response to various stimuli, including ligand binding, pH changes, and light. Endeavors toward these goals have tested and expanded on our understanding of protein function and allosteric regulation. In this chapter, we provide examples from different methods for developing new allosterically regulated ...[more]

PMID: 31707711

Similar Datasets

Project description:Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various substrates at distal points from the active sites. A recently developed method, bond-to-bond propensity analysis, has proven capable of predicting allosteric sites in a wide range of proteins using an energy-weighted atomistic graph obtained from the protein structure and given knowledge only of the location of the active site. Bond-to-bond propensity establishes if energy fluctuations at given bonds have significant effects on any other bond in the protein, by considering their propagation through the protein graph. In this work, we use bond-to-bond propensity analysis to study different aspects of ATCase activity using three different protein structures and sources of fluctuations. First, we predict key residues and bonds involved in the transition between inactive (T) and active (R) states of ATCase by analysing allosteric substrate binding as a source of energy perturbations in the protein graph. Our computational results also indicate that the effect of multiple allosteric binding is non linear: a switching effect is observed after a particular number and arrangement of substrates is bound suggesting a form of long range communication between the distantly arranged allosteric sites. Second, cooperativity is explored by considering a bisubstrate analogue as the source of energy fluctuations at the active site, also leading to the identification of highly significant residues to the T???R transition that enhance cooperativity across active sites. Finally, the inactive (T) structure is shown to exhibit a strong, non linear communication between the allosteric sites and the interface between catalytic subunits, rather than the active site. Bond-to-bond propensity thus offers an alternative route to explain allosteric and cooperative effects in terms of detailed atomistic changes to individual bonds within the protein, rather than through phenomenological, global thermodynamic arguments.

Dataset Information

Engineering Allostery into Proteins.

Publications

Engineering Allostery into Proteins.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure