The prediction of ligand binding sites is an essential part of the drug discovery process. Knowing the location of binding sites greatly facilitates the search for hits, the lead optimization process, the design of site-directed mutagenesis experiments and the hunt for structural features that influence the selectivity of binding in order to minimize the drug's adverse effects. However, docking...

Near-native selections from docking decoys have proved challenging especially when unbound proteins are used in the molecular docking. One reason is that significant atomic clashes in docking decoys lead to poor predictions of binding affinities of near native decoys. Atomic clashes can be removed by structural refinement through energy minimization. Such an energy minimization, however, will l...

The 'new view' of proteins sees protein reactions as parallel processes occurring along funnelled energy landscapes. These landscapes are generally not smooth, but are superimposed by hills and valleys of different heights and widths leading to roughness on the energy surface. In the present paper, we describe the origins of protein energy landscape roughness, measurements of its scale and its ...

  Objective(s): A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Artificial neural networks (ANNs) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. We proposed a structure that obtains binding energy using physicochemical molecular descripti...

Identifying sets of metastable conformations is a major research topic in RNA energy landscape analysis, and recently several methods have been proposed for finding local minima in landscapes spawned by RNA secondary structures. An important and time-critical component of such methods is steepest, or gradient, descent in attraction basins of local minima. We analyse the speed-up achievable by r...

In this study we investigate π-stacking interactions of a variety of aromatic heterocycles with benzene using dispersion corrected density functional theory. We calculate extensive potential energy surfaces for parallel-displaced interaction geometries. We find that dispersion contributes significantly to the interaction energy and is complemented by a varying degree of electrostatic interactio...

We develop a statistical mechanical theory for the free energy landscapes for complexes of double-stranded chain molecules. The theory is based on the generalized polymer graph, a graphical representation for the conformations of the complexes. We compute the partition functions by ‘‘dividing and conquering’’ on the generalized polymer graph: we decompose a graph into simple subunits, calculate...

Many problems in physics, material sciences, chemistry and biology can be abstractly formulated as a system that navigates over a complex energy landscape of high or infinite dimensions. Well-known examples include phase transitions of condensed matter, conformational changes of biopolymers, and chemical reactions. The energy landscape typically exhibits multiscale features, giving rise to the ...

Kinetic transition networks can now be calculated for small proteins using geometry optimisation to characterise minima, transition states and pathways, and unimolecular rate theory to supply rate constants corresponding to each transition state. The networks can be visualised by constructing disconnectivity graphs, revealing striking differences between good structure-seeking systems and a mod...