Binding pocket analysis is an active area of research that includes pocket detection and characterization, druggability prediction, and binding site flexibility studies. The introduction of the Protein Data Bank (PDB2) has sparked the development of a number of software programs intended to simplify macromolecule pocket investigation. More programs with increased accuracy and more complex algorithms for pocket characterization have been created in recent years. Analysis services for macromolecule/small molecule binding pockets are offered to customers by Alfa Chemistry. These services offer significant insights on molecular id and receptor dynamics.
Why Perform Pocket Analysis?
Receptor dynamics can be studied using pocket analysis. One can get a good idea of the whole spectrum of potential binding pocket conformational states by acquiring numerous structures and comparing pocket volumes and, in particular, shapes. Through these comparisons, it is possible to find novel binding pocket conformations that are pertinent to pharmacology as well as transient binding pockets that are not readily obvious when only a few static structures are taken into account.
Additionally, pocket analysis can be applied to computer-aided drug discovery (CADD). In a nutshell, the complementarity of receptor/ligand forms plays a critical part in molecular recognition and a ligand will typically not attach to a receptor if it does not physically fit into the binding pocket. In order to support CADD efforts aiming at predicting ligand binding, pocket characteristics are thus employed, whether through virtual screening or volume similarity searches.
POcket Volume Measurer (POVME)
Widespread use of the POVME algorithm as a simple tool for measuring and describing pocket volumes and shapes has been made possible. POVME floods a pocket with equidistant points, removes those points close to the receptor atoms, and calculates the volume from the remaining points. The points can be kept intact and serve as a precise representation of the pocket's shape.
Fig 1. Thermodynamic cycle of the RBFE calculation. The RBFE difference between molecules A and B can be calculated by two possible paths. (Durrant J. D, et al. 2014)
We have used POVME 2.0 here, which is an order of magnitude faster, more accurate, has a graphical user interface, and can produce volume density maps for better pocket analysis, we have been able to improve upon pocket analysis.
ImprintPocket is an algorithm for fast, accurate and automatic identification of negative images of binding pockets in protein structures for structure-based virtual screening. The CASTp suite of tools, which locates pockets and cavities in protein crystal structures and measures their size, is extended to do negative image search. The approach is based on discrete flow theory and computational geometry processing of complicated structures using alpha shapes. Although the algorithm is strong enough to examine any molecular system, including nucleic acids or inorganic materials, the imprinted pockets were created particularly for proteins. Calculations can be performed using discrete structures from crystallographic analysis and NMR experiments as well as trajectories from molecular dynamics simulations.
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Successful use of POVME consists of three required steps and two optional steps.
- The user defines an inclusion region.
- The user defines an exclusion region.
- The portion of the inclusion region that is not also in the exclusion region is flooded with equidistant points.
- Any of the points that are close to receptor atoms are deleted.
- Any points outside the convex hull are optionally deleted.
- The user can optionally define a contiguous-points region. All points that are not contiguous with that region are similarly deleted.
Based on alpha shapes and the discrete flow method, ImprintPocket creates negative images of pockets following seven steps.
- Identify the atoms forming the pocket.
- Calculation of the volume and area of the pockets.
- Identification of the "edges" of the pocket openings of the formed atoms.
- Calculating the number of openings for each pocket.
- Calculation of the area and perimeter of the openings.
- Locating the cavities and measuring their size.
- Constructing negative images of pockets from pocket tetrahedra.
Our binding pocket calculation service significantly reduces costs, facilitates further experimentation, and accelerates the drug design process for our global customers. Our personalized, full-service approach will meet your innovative learning needs. If you are interested in our services, please feel free to contact us. We will be happy to work with you and see you succeed!
- Durrant J. D, et al. (2014). "POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics." J Chem Theory Comput. 10(11): 5047-5056.