Application of asymmetric statistical potentials to antibody-protein docking.

Motivation: An effective docking algorithm for antibody-protein antigen complex prediction is an important first step toward design of biologics and vaccines. We have recently developed a new class of knowledge-based interaction potentials called Decoys as the Reference State (DARS) and incorporated DARS into the docking program PIPER based on the fast Fourier transform correlation approach. Although PIPER was the best performer in the latest rounds of the CAPRI protein docking experiment, it is much less accurate for docking antibody-protein antigen pairs than other types of complexes, in spite of incorporating sequence-based information on the location of the paratope.

Computational mapping reveals dramatic effect of Hoogsteen breathing on duplex DNA reactivity with formaldehyde.

Formaldehyde has long been recognized as a hazardous environmental agent highly reactive with DNA. Recently, it has been realized that due to the activity of histone demethylation enzymes within the cell nucleus, formaldehyde is produced endogenously, in direct vicinity of genomic DNA. Should it lead to extensive DNA damage? We address this question with the aid of a computational mapping method, analogous to X-ray and nuclear magnetic resonance techniques for observing weakly specific interactions of small organic compounds with a macromolecule in order to establish important functional sites.

Minimal ensembles of side chain conformers for modeling protein-protein interactions.

The goal of this article is to reduce the complexity of the side chain search within docking problems. We apply six methods of generating side chain conformers to unbound protein structures and determine their ability of obtaining the bound conformation in small ensembles of conformers. Methods are evaluated in terms of the positions of side chain end groups.

Structural conservation of druggable hot spots in protein-protein interfaces.

Despite the growing number of examples of small-molecule inhibitors that disrupt protein-protein interactions (PPIs), the origin of druggability of such targets is poorly understood. To identify druggable sites in protein-protein interfaces we combine computational solvent mapping, which explores the protein surface using a variety of small "probe" molecules, with a conformer generator to account for side-chain flexibility. Applications to unliganded structures of 15 PPI target proteins show that the druggable sites comprise a cluster of binding hot spots, distinguishable from other regions of the protein due to their concave topology combined with a pattern of hydrophobic and polar functionality.

Achieving reliability and high accuracy in automated protein docking: ClusPro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19.

Our approach to protein-protein docking includes three main steps. First, we run PIPER, a rigid body docking program based on the Fast Fourier Transform (FFT) correlation approach, extended to use pairwise interactions potentials. Second, the 1000 best energy conformations are clustered, and the 30 largest clusters are retained for refinement.

Binding hot spots and amantadine orientation in the influenza a virus M2 proton channel.

Structures of truncated versions of the influenza A virus M2 proton channel have been determined recently by x-ray crystallography in the open conformation of the channel, and by NMR in the closed state. The structures differ in the position of the bound inhibitors. The x-ray structure shows a single amantadine molecule in the middle of the channel, whereas in the NMR structure four drug molecules bind at the channel's outer surface.

Structural insights into recognition of beta2-glycoprotein I by the lipoprotein receptors.

The interactions of beta2 glycoprotein I (B2GPI) with the receptors of the low-density lipoprotein receptor (LDLR) family are implicated in the clearance of negatively charged phospholipids and apoptotic cells and, in the presence of autoimmune anti-B2GPI antibodies, in cell activation, which might play a role in the pathology of antiphospholipid syndrome (APS). The ligand-binding domains of the lipoprotein receptors consist of multiple homologous LA modules connected by flexible linkers. In this study, we investigated at the atomic level the features of the LA modules required for binding to B2GPI.

Detection of ligand binding hot spots on protein surfaces via fragment-based methods: application to DJ-1 and glucocerebrosidase.

The identification of hot spots, i.e., binding regions that contribute substantially to the free energy of ligand binding, is a critical step for structure-based drug design.

Fragment-based identification of druggable 'hot spots' of proteins using Fourier domain correlation techniques.

Motivation: The binding sites of proteins generally contain smaller regions that provide major contributions to the binding free energy and hence are the prime targets in drug design. Screening libraries of fragment-sized compounds by NMR or X-ray crystallography demonstrates that such 'hot spot' regions bind a large variety of small organic molecules, and that a relatively high 'hit rate' is predictive of target sites that are likely to bind drug-like ligands with high affinity. Our goal is to determine the 'hot spots' computationally rather than experimentally.

DARS (Decoys As the Reference State) potentials for protein-protein docking.

Decoys As the Reference State (DARS) is a simple and natural approach to the construction of structure-based intermolecular potentials. The idea is generating a large set of docked conformations with good shape complementarity but without accounting for atom types, and using the frequency of interactions extracted from these decoys as the reference state. In principle, the resulting potential is ideal for finding near-native conformations among structures obtained by docking, and can be combined with other energy terms to be used directly in docking calculations.

ClusPro: performance in CAPRI rounds 6-11 and the new server.

ClusPro is the first fully automated, web-based program for docking protein structures. Users may upload the coordinate files of two protein structures through ClusPro's web interface, or enter the PDB codes of the respective structures. The server performs rigid body docking, energy screening, and clustering to produce models.

Docking with PIPER and refinement with SDU in rounds 6-11 of CAPRI.

Our approach to protein-protein docking includes three main steps. First we run PIPER, a new rigid body docking program. PIPER is based on the Fast Fourier Transform (FFT) correlation approach that has been extended to use pairwise interactions potentials, thereby substantially increasing the number of near-native structures generated.

PIPER: an FFT-based protein docking program with pairwise potentials.

The Fast Fourier Transform (FFT) correlation approach to protein-protein docking can evaluate the energies of billions of docked conformations on a grid if the energy is described in the form of a correlation function. Here, this restriction is removed, and the approach is efficiently used with pairwise interaction potentials that substantially improve the docking results. The basic idea is approximating the interaction matrix by its eigenvectors corresponding to the few dominant eigenvalues, resulting in an energy expression written as the sum of a few correlation functions, and solving the problem by repeated FFT calculations.