Dynamic undocking and the quasi-bound state as tools for drug discovery

There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein–ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other ‘thermodynamic’ methods. We demonstrate the potential of the docking–undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40

Rapid optimisation of fragments and hits to lead compounds from screening of crude reaction mixtures

Fragment based methods are now widely used to identify starting points in drug discovery and generation of tools for chemical biology. A significant challenge is optimization of these weak binding fragments to hit and lead compounds. We have developed an approach where individual reaction mixtures of analogues of hits can be evaluated without purification of the product. Here, we describe experiments to optimise the processes and then assess such mixtures in the high throughput crystal structure determination facility, XChem. Diffraction data for crystals of the proteins Hsp90 and PDHK2 soaked individually with 83 crude reaction mixtures are analysed manually or with the automated XChem procedures. The results of structural analysis are compared with binding measurements from other biophysical techniques. This approach can transform early hit to lead optimisation and the lessons learnt from this study provide a protocol that can be used by the community

Whole genome analysis of linezolid resistance in Streptococcus pneumoniae reveals resistance and compensatory mutations

<p>Abstract</p> <p>Background</p> <p>Several mutations were present in the genome of <it>Streptococcus pneumoniae </it>linezolid-resistant strains but the role of several of these mutations had not been experimentally tested. To analyze the role of these mutations, we reconstituted resistance by serial whole genome transformation of a novel resistant isolate into two strains with sensitive background. We sequenced the parent mutant and two independent transformants exhibiting similar minimum inhibitory concentration to linezolid.</p> <p>Results</p> <p>Comparative genomic analyses revealed that transformants acquired G2576T transversions in every gene copy of 23S rRNA and that the number of altered copies correlated with the level of linezolid resistance and cross-resistance to florfenicol and chloramphenicol. One of the transformants also acquired a mutation present in the parent mutant leading to the overexpression of an ABC transporter (spr1021). The acquisition of these mutations conferred a fitness cost however, which was further enhanced by the acquisition of a mutation in a RNA methyltransferase implicated in resistance. Interestingly, the fitness of the transformants could be restored in part by the acquisition of altered copies of the L3 and L16 ribosomal proteins and by mutations leading to the overexpression of the spr1887 ABC transporter that were present in the original linezolid-resistant mutant.</p> <p>Conclusions</p> <p>Our results demonstrate the usefulness of whole genome approaches at detecting major determinants of resistance as well as compensatory mutations that alleviate the fitness cost associated with resistance.</p

Establishing Drug Discovery and Identification of Hit Series for the Anti-apoptotic Proteins, Bcl-2 and Mcl-1

We describe our work to establish structure- and fragment-based drug discovery to identify small molecules that inhibit the anti-apoptotic activity of the proteins Mcl-1 and Bcl-2. This identified hit series of compounds, some of which were subsequently optimized to clinical candidates in trials for treating various cancers. Many protein constructs were designed to identify protein with suitable properties for different biophysical assays and structural methods. Fragment screening using ligand-observed NMR experiments identified several series of compounds for each protein. The series were assessed for their potential for subsequent optimization using 1H and 15N heteronuclear single-quantum correlation NMR, surface plasmon resonance, and isothermal titration calorimetry measurements to characterize and validate binding. Crystal structures could not be determined for the early hits, so NMR methods were developed to provide models of compound binding to guide compound optimization. For Mcl-1, a benzodioxane/benzoxazine series was optimized to a Kd of 40 μM before a thienopyrimidine hit series was identified which subsequently led to the lead series from which the clinical candidate S 64315 (MIK 665) was identified. For Bcl-2, the fragment-derived series were difficult to progress, and a compound derived from a published tetrahydroquinone compound was taken forward as the hit from which the clinical candidate (S 55746) was obtained. For both the proteins, the work to establish a portfolio of assays gave confidence for identification of compounds suitable for optimization