Alessandro Senes

Associate Professor

Picture of Alessandro SenesHector F. DeLuca Biochemistry Laboratories
Room 415C
433 Babcock Drive
Madison, WI 53706-1544
Phone: (608) 890-2584
Overview · Publications · Lab Website


B.S.: University of Sassari, Italy
Ph.D.: Yale University
Postdoc: MIT, University of Pennsylvania

Areas of Study

Biomolecular Folding & Interactions
Chemical Biology
Membrane Dynamics & Proteins
Quantitative Biology
Structural Biology

Research Overview

Biochemical and computational studies of membrane protein interactions

My laboratory combines biochemical, biophysical, biological and computational techniques to understand how membrane proteins  assemble.

We study the organization of an important biological complex of membrane proteins, the bacterial divisome.  We are also interested in understanding and predicting important membrane protein interaction motifs

1. Understanding the structural organization of the membrane proteins of the bacterial divisome

Our biological system is the divisome, the complex that is responsible for cell division in bacteria. Cell division is a fundamental process and a promising target for the development of new antibiotics. However, the macromolecular structure of the extensive transmembrane region of the complex so far has been elusive.

We study the association of the divisome membrane proteins with a number of experimental methods.  These range from FRET using synthetic peptides, to genetic reporter assays, mutagenesis, X-ray crystallography, and in vivo phenotypic analysis. We combine these experiments with computational methods to obtain structural models of the complexes.

Using this multi-disciplinary approach, we have recently demonstrated that the division proteins FtsB and FtsL form a highly stable higher-oligomer that is mediated by their transmembrane helices (Fig. 1). 

Structural organization of the FtsB-FtsL complex

Fig. 1 FtsB and FtsL form a higher-oligomeric complex that is mediated by hydrogen bonding. 

2. Understanding important membrane protein interaction motifs and predicting their structure

The transmembrane helices of membrane proteins that span the bilayer once are active domains.  They very oftenoligomerize, and oligomerization plays essential roles in assembly, signaling, and regulation. Understanding the physical rules that determine transmembrane association is important to fully comprehend many biological systems. To understand these rules we have been studying frequent association motif in helices.

Analysis of carbon hydrogen bonding in transmembrane dimers
Fig. 2 A geometric analysis of transmembrane dimers demonstrates that the important GAS-right motif is optimized to form carbon hydrogen bonds

Using a computer simulation, we have recently demonstrated that one of the most frequent association motifs – GAS-right – is optimized for the formation of carbon hydrogen bonds at the helix-helix interface (Fig. 2). This is consistent with the theory that carbon hydrogen bonds are important determinants of association.

We have also developed a method for predicting the structure of GAS-right motifs from the amino acid sequence alone (Fig. 3). This method provides us with an unprecedented opportunity for a structure-based experimental analysis of the physical basis of GAS-right association.  It also produces leads for identifying important GAS-right motifs that may still be hiding among the 2,200 single-span membrane proteins in the human genome.

Structural prediction of GAS-right motifs

Fig. 3 The program CATM predicts the structure of GAS-right transmembrane motifs at near atomic resolution. 

3. Development of computational macromolecular modeling methods

Advanced computation requires a powerful, flexible code-base for translating ideas into efficient programs, but no general open platform was available for supporting the development of molecular modeling algorithms. We created MSL to fill this gap. With over 95,000 lines of code and 155 modules, MSL supports structure building, backbone and side chain flexibility, conformational search algorithms, mutation, geometric analysis, many energy functions, and more. MSL is open source and available for download at

MSL logo

Fig. 4 Logo of the MSL libraries