Search

Background: Mixed solvents MD (MDmix) simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery. One of the assumptions behind the methodology is the transferability of free energy values from the simulated cosolvent molecules to larger drug-like molecules. However, the binding free energy maps (ΔGbind) calculated for the different moieties of the cosolvent molecules (e.g. a hydroxyl map for the ethanol) are largely influenced by the rest of the solvent molecule and do not reflect the intrinsic affinity of the moiety in question. As such, they are hardly transferable to different molecules., Method: To achieve transferable energies, we present here a method for decomposing the molecular binding free energy into accurate atomic contributions., Result: We demonstrate with two qualitative visual examples how the corrected energy maps better match known binding hotspots and how they can reveal hidden hotspots with actual drug design potential., Conclusion: Atomic decomposition of binding free energies derived from MDmix simulations provides transferable and quantitative binding free energy maps., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The intrinsic dynamics of macromolecules is an essential property to relate the structure of biomolecular systems with their function in the cell. In the field of ligand-receptor recognition, numerous evidences have revealed the limitations of the lock-and-key theory, and the need to elaborate models that take into account the inherent plasticity of biomolecules, such as the induced-fit model or the existence of an ensemble of pre-equilibrated conformations. Depending on the nature of the target system, ligand binding can be associated with small local adjustments in side chains or even the backbone to large-scale motions of structural fragments, domains or even subunits. Reproducing the inherent flexibility of biomolecules has thus become one of the most challenging issues in molecular modeling and simulation studies, as it has direct implications in our understanding of the structure-function relationships, but even in areas such as virtual screening and structure-based drug discovery. Given the intrinsic limitation of conventional simulation tools, only events occurring in short time scales can be reproduced at a high accuracy level through all-atom techniques such as Molecular Dynamics simulations. However, larger structural rearrangements demand the use of enhanced sampling methods relying on modified descriptions of the biomolecular system or the potential surface. This review illustrates the crucial role that structural plasticity plays in mediating ligand recognition through representative examples. In addition, it discusses some of the most powerful computational tools developed to characterize the conformational flexibility in ligand-receptor complexes.

Recent advances in structure determination and computational methods have encouraged the development of structure-based virtual screening. Here we survey progress in the field and review the most recent methods, validation experiments and real applications, including an in-house example of hit identification for the oncology target Hsp90. These results provide a basis for discussing the current state of structure-based virtual screening and to outline the developments that are expected to have a major impact in the near future.

A large amount of structural information on AChE and AChE-inhibitor complexes is currently available. Based on that, molecular modeling studies can be intensively used to gain insight into the mechanism of action of the enzyme and the molecular determinants that modulate the potency of inhibitors. In turn, this knowledge can be exploited to design new compounds leading to more effective cholinergic strategies. This manuscript reviews recent developments in the design of reversible acetylcholinesterase inhibitors.

During the last years, solving the X-ray crystallographic structure of both the unliganded acetylcholinesterase (AChE) and AChE complexes with various inhibitors has provided valuable knowledge of the interactions that mediate inhibitor binding. This structural information allows us to rationalize differences in binding affinities for related analogues, and more importantly opens new strategies to design compounds with improved pharmacological properties. This is illustrated in the case of the recently reported huprines, which are a new class of very potent and selective acetylcholinesterase inhibitors.