Methods that survey protein surfaces for binding hotspots can help to evaluate target tractability and guide exploration of potential ligand binding regions. Fragment Hotspot Maps builds upon interaction data mined from the CSD (Cambridge Structural Database) and exploits the idea of identifying hotspots using small chemical fragments, which is now widely used to design new drug leads. Prior to this publication, Fragment Hotspot Maps was only publicly available through a web application. To increase the accessibility of this algorithm we present the Hotspots API (application programming interface), a toolkit that offers programmatic access to the core Fragment Hotspot Maps algorithm, thereby facilitating the interpretation and application of the analysis. To demonstrate the package's utility, we present a workflow which automatically derives protein hydrogen-bond constraints for molecular docking with GOLD. The Hotspots API is available from https://github.com/prcurran/hotspots under the MIT license and is dependent upon the commercial CSD Python API.

Small molecule binding hotspots are regions within a protein pocket that contribute a disproportionately large amount to the overall binding energy.Consequently, fragments which bind to hotspots are anchored in place, providing an energetic foothold from which structure-based methods can efficiently guide designs towards ligand efficient lead molecules.Radoux et al. (J.Med.Chem., 2016, 59 (9), pp 4314-4325) developed a fast, knowledge-based method to characterise the location and critical intermolecular interactions in these regions, using data derived from the Cambridge Structural Database (CSD).Since this publication, we have continued to develop this algorithm and design workflows to utilise these valuable insights.To enable this, we have recently released the Hotspots API, a Python API built upon the CSD Python API (https://github.com/prcurran/hotspots).This talk will outline some exemplar use cases, including tractability assessment, assignment of docking constraints and generation of pharmacophoric models.We also outline broader plans to use this tool for the design of small molecule screening libraries.

PRO_ANALOG is a suite of utilities which addresses the matter of expanding the analog space around a lead molecule. It has been implemented within the Prometheus suite of "computer-aided molecular design" programs. A lead molecule will have a large number of possible derivatives which should be investigated for pharmaceutical activity. It is likely that a medicinal chemist would only consider an incomplete set of these. We have implemented functionalities which allow a medicinal chemist or molecular modeller to select categories of possible transformations and derivatisation sites and, in a combinatorial sense, produce a library of all the analog molecules that would arise from such modifications. Molecular transformations are encoded with a new SMILES-string matching technology. Use of predefined lists of familiar functional groups from the medicinal chemistry literature ensures that the derived molecular structures are likely to be synthetically accessible. A range of transformation classes enables almost any molecular structure to be constructed. Statistical techniques used in molecular diversity can be applied to cluster the structures and ranking can be achieved by passing them to ligandreceptor docking software. The members of the libraries may then be assessed for their likely efficacy prior to embarking on laboratory synthesis. The method is illustrated here with a set of thrombin inhibitors.

The selection and modification of atoms or functional groups underly many of the manipulations central to molecular modeling. It has become even more important to automate these tasks with the current prevalence of work with large databases of molecules. We have devised SUPER-SMILES, a conceptually simple set of extensions to the SMILES line notation, whose key features are addition and deletion facilities, macros, atom tagging, disjunctions, and constraints. This superset of SMILES enables us to carry out transformations on individual molecular structures or across members of a database with a pattern-matching protocol. The principal advantage of SUPER-SMILES is the ability to specify chemical reactions with a very simple augmentation of the SMILES line notation. For example, in conjunction with macros, it is possible to represent the displacement of tosylate with phenoxy by the expression "(Delete Tosyl) (Add Phenoxy)". SUPER-SMILES thus represents a unified approach to molecular structure specification and modification and can easily be applied to large datasets of molecules. This functionality has been implemented within the PROMETHEUS suite of CAMD programs. We demonstrate its use in carrying out such operations as atom-type assignment, protonation of molecules, valency checking, and hydrogen addition. Further applications such as library design and construction immediately suggest themselves.

This paper describes a novel methodology, PRO_SELECT, which combines elements of structure-based drug design and combinatorial chemistry to create a new paradigm for accelerated lead discovery. Starting with a synthetically accessible template positioned in the active site of the target of interest, PRO_SELECT employs database searching to generate lists of potential substituents for each substituent position on the template. These substituents are selected on the basis of their being able to couple to the template using known synthetic routes and their possession of the correct functionality to interact with specified residues in the active site. The lists of potential substituents are then screened computationally against the active site using rapid algorithms. An empirical scoring function, correlated to binding free energy, is used to rank the substituents at each position. The highest scoring substituents at each position can then be examined using a variety of techniques and a final selection is made. Combinatorial enumeration of the final lists generates a library of synthetically accessible molecules, which may then be prioritised for synthesis and assay. The results obtained using PRO_SELECT to design thrombin inhibitors are briefly discussed.

Two new computational tools, PRO_PHARMEX and PRO_SCOPE, for use in active-site-directed searching of 3D databases are described. PRO_PHARMEX is a flexible, graphics-based program facilitating the extraction of pharmacophores from the active site of a target macromolecule. These pharmacophores can then be used to search a variety of databases for novel lead compounds. Such searches can often generate many 'hits' of varying quality. To aid the user in setting priorities for purchase, synthesis or testing, PRO_SCOPE can be used to dock molecules rapidly back into the active site and to assign them a score using an empirical scoring function correlated to the free energy of binding. To illustrate how these tools can add value to existing 3D database software, their use in the design of novel thrombin inhibitors is described.