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Sterol 14α-demethylase (cytochrome P450 family 51 (CYP51)) is an essential enzyme occurring in all biological kingdoms. In eukaryotes, it is located in the membrane of the endoplasmic reticulum. Selective inhibitors of trypanosomal CYP51s that do not affect the human CYP51 have been discovered in vitro and found to cure acute and chronic mouse Chagas disease without severe side effects in vivo. Crystal structures indicate that CYP51 may be more rigid than most CYPs, and it has been proposed that this property may facilitate antiparasitic drug design. Therefore, to investigate the dynamics of trypanosomal CYP51, we built a model of membrane-bound Trypanosoma brucei CYP51 and then performed molecular dynamics simulations of T. brucei CYP51 in membrane-bound and soluble forms. We compared the dynamics of T. brucei CYP51 with those of human CYP51, CYP2C9, and CYP2E1. In the simulations, the CYP51s display low mobility in the buried active site although overall mobility is similar in all the CYPs studied. The simulations suggest that in CYP51, pathway 2f serves as the major ligand access tunnel, and both pathways 2f (leading to membrane) and S (leading to solvent) can serve as ligand egress tunnels. Compared with the other CYPs, the residues at the entrance of the ligand access tunnels in CYP51 have higher mobility that may be necessary to facilitate the passage of its large sterol ligands. The water (W) tunnel is accessible to solvent during most of the simulations of CYP51, but its width is affected by the conformations of the heme's two propionate groups. These differ from those observed in the other CYPs studied because of differences in their hydrogen-bonding network. Our simulations give insights into the dynamics of CYP51 that complement the available experimental data and have implications for drug design against CYP51 enzymes., (Copyright © 2015 John Wiley & Sons, Ltd.)

Protein-surface interactions are fundamental in natural processes, and have great potential for applications ranging from nanotechnology to medicine. A recent workshop highlighted the current achievements and the main challenges in the field., ((c) 2009 John Wiley & Sons, Ltd.)

Given the three-dimensional structure of a protein, how can one find the sites where other molecules might bind to it? Do these sites have the properties necessary for high affinity binding? Is this protein a suitable target for drug design? Here, we discuss recent developments in computational methods to address these and related questions. Geometric methods to identify pockets on protein surfaces have been developed over many years but, with new algorithms, their performance is still improving. Simulation methods show promise in accounting for protein conformational variability to identify transient pockets but lack the ease of use of many of the (rigid) shape-based tools. Sequence and structure comparison approaches are benefiting from the constantly increasing size of sequence and structure databases. Energetic methods can aid identification and characterization of binding pockets, and have undergone recent improvements in the treatment of solvation and hydrophobicity. The "druggability" of a binding site is still difficult to predict with an automated procedure. The methodologies available for this purpose range from simple shape and hydrophobicity scores to computationally demanding free energy simulations., (2009 John Wiley & Sons, Ltd.)

How are proteins recognized as substrates for ubiquitination? Here we summarize insights from recent experiments that address this issue. These highlight the diversity and complexity of determinants for substrate recognition, and raise many questions for further investigation., (Copyright 2002 John Wiley & Sons, Ltd.)

When two proteins diffuse together to form a bound complex, an intermediate is formed at the end-point of diffusional association which is called the encounter complex. Its characteristics are important in determining association rates, yet its structure cannot be directly observed experimentally. Here, we address the problem of how to construct the ensemble of three-dimensional structures which constitute the protein-protein diffusional encounter complex using available experimental data describing the dependence of protein association rates on mutation and on solvent ionic strength and viscosity. The magnitude of the association rates is fitted well using a variety of definitions of encounter complexes in which the two proteins are located at up to about 17 A root-mean-squared distance from their relative arrangement in the bound complex. Analysis of the ionic strength dependence of bimolecular association rates shows that this is determined to a greater extent by the (protein charge) - (salt ion) separation distance than by the protein-protein charge separation distance. Consequently, ionic strength dependence of association rates provides little information about the geometry of the encounter complex. On the other hand, experimental data on electrostatic rate enhancement, mutation and viscosity dependence suggest a model of the encounter complex in which the two proteins form a subset of the contacts present in the bound complex and are significantly desolvated., (Copyright 1999 John Wiley & Sons, Ltd.)