Active Site Conformational Dynamics in Human Uridine Phosphorylase 1

Uridine phosphorylase (UPP) is a central enzyme in the pyrimidine salvage pathway, catalyzing the reversible phosphorolysis of uridine to uracil and ribose-1-phosphate. Human UPP activity has been a focus of cancer research due to its role in activating fluoropyrimidine nucleoside chemotherapeutic agents such as 5-fluorouracil (5-FU) and capecitabine. Additionally, specific molecular inhibitors of this enzyme have been found to raise endogenous uridine concentrations, which can produce a cytoprotective effect on normal tissues exposed to these drugs. Here we report the structure of hUPP1 bound to 5-FU at 2.3 Å resolution. Analysis of this structure reveals new insights as to the conformational motions the enzyme undergoes in the course of substrate binding and catalysis. The dimeric enzyme is capable of a large hinge motion between its two domains, facilitating ligand exchange and explaining observed cooperativity between the two active sites in binding phosphate-bearing substrates. Further, a loop toward the back end of the uracil binding pocket is shown to flexibly adjust to the varying chemistry of different compounds through an “induced-fit” association mechanism that was not observed in earlier hUPP1 structures. The details surrounding these dynamic aspects of hUPP1 structure and function provide unexplored avenues to develop novel inhibitors of this protein with improved specificity and increased affinity. Given the recent emergence of new roles for uridine as a neuron protective compound in ischemia and degenerative diseases, such as Alzheimer's and Parkinson's, inhibitors of hUPP1 with greater efficacy, which are able to boost cellular uridine levels without adverse side-effects, may have a wide range of therapeutic applications

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges

Visualizing chaperone-assisted protein folding

Challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding, where obtaining structural ensembles of chaperone:substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a novel structural biology approach based on X-ray crystallography, termed Residual Electron and Anomalous Density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the E. coli chaperone Spy. This study resulted in a series of snapshots depicting the various folding states of Im7 while bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded and native-like states, and reveals how a substrate can explore its folding landscape while bound to a chaperone