An important problem in high-throughput protein crystallography is constructing a protein model from an electron-density map. Previous work by some of this paper's authors [1] describes an automated approach to this otherwise time-consuming process. An important step in the previous method requires searching the density map for many small template protein-fragments. This previous approach uses Fourier convolution to quickly match some rotation of the template to the entire density map. This paper proposes an alternate approach that makes use of the spherical-harmonic decomposition of the template and of some region in the density map. This new framework allows us to mask specific regions of the map, enabling a first-pass filter to eliminate a majority of the density map without requiring an expensive rotational search. We show our new template matching method improves accuracy and reduces running time, compared to our previous approach. Protein models constructed using this matching also show significant accuracy improvement.

X-ray crystallography is currently the most common way protein structures are elucidated. One of the most time-consuming steps in the crystallographic process is interpretation of the electron density map, a task that involves finding patterns in a three-dimensional picture of a protein. This paper describes DEFT (DEFormable Template), an algorithm using pictorial structures to build a flexible protein model from the protein's amino-acid sequence. Matching this pictorial structure into the density map is a way of automating density-map interpretation. Also described are several extensions to the pictorial structure matching algorithm necessary for this automated interpretation. DEFT is tested on a set of density maps ranging from 2 to 4Å resolution, producing root- mean-squared errors ranging from 1.38 to 1.84Å.

Proteins are involved either directly or indirectly in all biological processes in living organisms. It is now widely accepted that conformational changes of proteins can critically affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods such as X-ray crystallography produce rather few structures, while computational methods such as Molecular Dynamics are too slow for routine use with large systems. A medium sized protein typically has a few thousands of degrees of freedom. This paper shows how to obtain a reduced basis representation of protein flexibility. We use the Principal Component Analysis method, a dimensionality reduction technique, to transform the original high dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of the protein. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.

This paper reports on the problem of docking a highly flexible small molecule to the pocket of a highly flexible receptor macromolecule. The prediction of the intermolecular complex is of vital importance for the development of new therapeutics as docking can alter the chemical behavior of the receptor macromolecule. We first present current methods for docking, which have several limitations. Some of these methods consider only the flexibility of the ligand solving a problem with a few tens of degrees of freedom. When the receptor flexibility is taken into account several hundreds or even thousands of degrees of freedom need to be considered. Most methods take into account only a small number of these degrees of freedom by using chemical knowledge specific to the problem. We show how to use a singular value decomposition of molecular dynamics trajectories to automatically obtain information about the global flexibility of the receptor and produce interesting conformations that can be used for docking purposes.