- B.S., 1997, Texas A&M University, Molecular and Cell Biology.
- Ph.D., 2002, UT Southwestern Medical Center, Molecular Biophysics.
- Postdoctoral research: The Rockefeller University.
Joined the department in 2009.
College Station, TX 77843-3474
Interdisciplinary Life Sciences Building
Interdisciplinary Life Sciences Building
|Information Processing In Biological Systems
Intracellular signaling relies on the efficient transfer of information between proteins. For example, the activation of G-protein coupled receptors by small peptides, other proteins and even photons triggers a cascade of protein-protein interactions that culminates in a single signaling output, such as transcription. Many protein families have evolved to recognize diverse substrates at distinct sites, which allows them to combine multiple sensory inputs to generate highly integrated responses. How can one decipher the molecular origins of these two distinct aspects of information processing by proteins – the recognition of substrates and their integration into a single output?
We previously developed and experimentally validated an approach that exploits compensatory mutations appearing in homologous protein sequences to infer functional interactions among residues. When these interacting sets of amino acids are mapped onto the structures of allosterically regulated proteins, such as GPRCs and globins, they often form spatially contiguous networks of residues that radiate from active sites to points of allosteric regulation. We hypothesize that these networks of functionally interacting residues operate as conduits for information flow in proteins and that their surface termini are hot spots for the evolution of novel substrate recognition.
We are currently testing this hypothesis in the context of two complementary model systems:
- Hedgehog processing domains to understand how diverse substrates, such as cholesterol or polypeptides, are recognized and processed by a conserved protein fold and catalytic mechanism.
- Ion channels to explore how multiple distinct regulatory signals are sensed and integrated into a cohesive output.
An understanding of signal integration and substrate recognition, together with knowledge of the constraints they impose on one another during evolution, should reveal fundamental aspects of information processing by proteins. Principles learned from these studies could be used to create allosterically regulated proteins for nanotechnology, to generate enzymes that recognize non-native substrates, and to understand protein-signaling diseases.
- Huang H, Levin EJ, Liu S, Bai Y, Lockless SW & Zhou M (2014) Structure of a membrane-embedded prenyltransferase homologous to UBIAD1. PLoS Biol 12:e1001911 Full text
- Liu S & Lockless SW (2013) Equilibrium selectivity alone does not create K+-selective ion conduction in K+ channels. Nat Commun 4:2746 Full text
- Liu S, Bian X & Lockless SW (2012) Preferential binding of K+ ions in the selectivity filter at equilibrium explains high selectivity of K+ channels. J Gen Physiol 140:671-9 Full text
- Lockless SW & Muir TW (2009) Traceless protein splicing utilizing evolved split inteins. Proc Natl Acad Sci U S A 106:10999-1004 Full text
- Lockless SW, Zhou M & MacKinnon R (2007) Structural and thermodynamic properties of selective ion binding in a K+ channel. PLoS Biol 5:e121 Full text
- Socolich M, Lockless SW, Russ WP, Lee H, Gardner KH & Ranganathan R (2005) Evolutionary information for specifying a protein fold. Nature 437:512-8 Full text
- Vergani P, Lockless SW, Nairn AC & Gadsby DC (2005) CFTR channel opening by ATP-driven tight dimerization of its nucleotide-binding domains. Nature 433:876-80 Full text
- Hatley ME, Lockless SW, Gibson SK, Gilman AG & Ranganathan R (2003) Allosteric determinants in guanine nucleotide-binding proteins. Proc Natl Acad Sci U S A 100:14445-50 Full text
- Süel GM, Lockless SW, Wall MA & Ranganathan R (2003) Evolutionarily conserved networks of residues mediate allosteric communication in proteins. Nat Struct Biol 10:59-69 Full text
- Lockless SW & Ranganathan R (1999) Evolutionarily conserved pathways of energetic connectivity in protein families. Science 286:295-9 Full text