Phylogenetic Classification of Protozoa Based on the Structure of the Linker Domain in the Bifunctional Enzyme, Dihydrofolate Reductase-Thymidylate Synthase

Abstract

We have determined the crystal structure of dihydrofolate reductase-thymidylate synthase (DHFR-TS) from Cryptosporidium hominis, revealing a unique linker domain containing an 11-residue ␣-helix that has extensive interactions with the opposite DHFR-TS monomer of the homodimeric enzyme. Analysis of the structure of DHFR-TS from C. hominis and of previously solved structures of DHFR-TS from Plasmodium falciparum and Leishmania major reveals that the linker domain primarily controls the relative orientation of the DHFR and TS domains. Using the tertiary structure of the linker domains, we have been able to place a number of protozoa in two distinct and dissimilar structural families corresponding to two evolutionary families and provide the first structural evidence validating the use of DHFR-TS as a tool of phylogenetic classification. Furthermore, the structure of C. hominis DHFR-TS calls into question surface electrostatic channeling as the universal means of dihydrofolate transport between TS and DHFR in the bifunctional enzyme.Thymidylate synthase (TS) 1 and dihydrofolate reductase (DHFR) are essential enzymes in the cell cycle of all organisms, since they catalyze the production of dTMP, required for DNA replication. TS converts the substrate, dUMP, to dTMP by reductive methylation using the cofactor, 5,10-methylene tetrahydrofolate, and releases dihydrofolate (1). In the presence of the cofactor NADPH, DHFR reduces dihydrofolate to tetrahydrofolate. The folate cycle is completed by serine hydroxymethyl transferase, which converts tetrahydrofolate back to 5,10-methylene tetrahydrofolate.Recently, Stechmann and Cavalier-Smith (2) have addressed the problem of locating the root of the eukaryotic tree, one of the most challenging evolutionary problems. In several protozoa, including Alveolates and Euglenozoa, and in some plants, the genes for DHFR and TS are translated as a single polypeptide, forming a bifunctional enzyme (DHFR-TS), whereas in most animals, fungi, and bacteria, these two enzymes are monofunctional. The monofunctional form of DHFR is a monomer, and that of TS is a dimer. The currently held hypothesis is that the primordial form of DHFR and TS is the monofunctional form and that the genes for DHFR and TS became fused at a single evolutionary point. If the DHFR-TS gene fusion occurred just once, then the fused gene provides an excellent phylogenetic marker, since reversing the fusion would require multiple genetic events. Stechmann and Cavalier-Smith have used the derived gene fusion between DHFR and TS to place the root of the tree below the common ancestor of plants, Alveolates, and Euglenozoa (Fig.

Algorithmic Challenges in Structural Molecular Biology and Proteomics

“…In X-ray crystallography, the molecular replacement technique (used in [14,17,16]) allows solution of the crystallographic phase problem when a "close" or homologous structural model is known a priori, thereby facilitating rapid structure determination. In contrast, a key bottleneck in NMR structural biology is the resonance assignment problem.…”

“…Our work spans a number of projects in computational structural biology, including algorithms for automated assignment and structure determination in NMR structural biology [3,9,6,19,10,5,7,18,4], protein redesign [13], computer-aided drug design [1,15,13], computational molecular replacement in X-ray crystallography [14,17,16], and other related projects [2,11,8]. To pursue research in the field of structural genomics is to study the geometric structures of proteins.…”

“…The problem may be reduced to clustering in SO(3) modulo a finite group, and solved efficiently by "factoring" into a clustering on the unit circle followed by clustering on the 2-sphere S 2 , plus some group-theoretic calculations [14]. This yields a polynomial-time algorithm that is efficient in practice, and which enabled us to collaborate with biological crystallographers to reveal the architecture of a parasite's enzyme, which could help researchers reduce the threat of certain diseases among those with weak immune systems [17,16]. As another example, we recently employed geometric techniques from statistical estimation and machine learning to develop an algorithm for cancer proteomics, in which we use data from a mass spectrometer to distinguish between healthy and diseased blood in humans [12].…”

“…I'm also interested in collaborating with structural biologists to develop novel algorithms and apply them to biological systems of significant biochemical and pharmacological importance. A model for this kind of work is our collaboration on the structure of dihydrofolate reductase-thymidylate synthase (DHFR-TS) from Cryptosporidium hominis [14,17,16]. Cryptosporidium is an organism high on the bioterrorism list of the Center for Disease Control (CDC), a Category B bioterrorist threat.…”

“…I'll briefly discuss some recent results from my lab, including new algorithms for interpreting X-ray crystallography [14,17,16] and NMR (nuclear magnetic resonance) data [3,9,6,19,10,5,7,18,4], disease classification using mass spectrometry of human serum [12], and protein redesign [13]. Our algorithms have recently been used, respectively, to reveal the enzymatic architecture of organisms high on the CDC bioterrorism watch-list [17,16], for probabilistic cancer classification from human peripheral blood [12], and to redesign an antibioticproducing enzyme to bind a novel substrate [13]. I'll overview these projects, and highlight some of the algorithmic and computational challenges.…”