Bohdan Waszkowycz

PRO_LIGAND: An approach to de novo molecular design. 1. Application to the design of organic molecules

SummaryAn approach to de novo molecular design, PRO_LIGAND, has been developed that, in the environment of a large, integrated molecular design and simulation system, provides a unified framework for the generation of novel molecules which are either similar or complementary to a specified target. The approach is based on a methodology that has proved to be effective in other studies-placing molecular fragments upon target interaction sites-but incorporates many novel features such as the use of a rapid graph-theoretical algorithm for fragment placing, a generalised driver for structure generation which offers a large variety of fragment assembly strategies to the user and the pre-screening of library fragments. After a detailed description of the relevant modules of the package, PRO_LIGANDs efficacy in aiding rational drug design is demonstrated by its ability to design mimics of methotrexate and potential inhibitors for dihydrofolate reductase and HIV-1 protease.

Large-scale virtual screening for discovering leads in the postgenomic era

Virtual screening, or in silico screening, is a new approach attracting increasing levels of interest in the pharmaceutical industry as a productive and cost-effective technology in the search for novel lead compounds. Although the principles involved--the computational analysis of chemical databases to identify compounds appropriate for a given biological receptor--have been pursued for several years in molecular modeling groups, the availability of inexpensive high-performance computing platforms has transformed the process so that increasingly complex and more accurate analyses can be performed on very large data sets. The virtual screening technology of Protherics Molecular Design Ltd. is based on its integrated software environment for receptor-based drug design, called Prometheus. In particular, molecular docking is used to predict the binding modes and binding affinities of every compound in the data set to a given biological receptor. This method represents a very detailed and relevant basis for prioritizing compounds for biological screening. This paper discusses the broader scope of virtual screening and, as an example, describes our recent work in docking one million compounds into the estrogen hormone receptor in order to highlight the technical feasibility of performing very large-scale virtual screening as a route to identifying novel drug leads.

Towards improving compound selection in structure-based virtual screening

Structure-based virtual screening is now an established technology for supporting hit finding and lead optimisation in drug discovery. Recent validation studies have highlighted the poor performance of currently used scoring functions in estimating binding affinity and hence in ranking large datasets of docked ligands. Progress in the analysis of large datasets can be made through the use of appropriate data mining techniques and the derivation of a broader range of descriptors relevant to receptor-ligand binding. In addition, simple scoring functions can be supplemented by simulation-based scoring protocols. Developments in workflow design allow the automation of repetitive tasks, and also encourage the routine use of simulation-based methods and the rapid prototyping of novel modelling and analysis procedures.

Identification of Imidazo-Pyrrolopyridines as Novel and Potent JAK1 Inhibitors.

A therapeutic rationale is proposed for the treatment of inflammatory diseases, such as rheumatoid arthritis (RA), by specific targeting of the JAK1 pathway. Examination of the preferred binding conformation of clinically effective, pan-JAK inhibitor 1 led to identification of a novel, tricyclic hinge binding scaffold 3. Exploration of SAR through a series of cycloamino and cycloalkylamino analogues demonstrated this template to be highly tolerant of substitution, with a predisposition to moderate selectivity for the JAK1 isoform over JAK2. This study culminated in the identification of subnanomolar JAK1 inhibitors such as 22 and 49, having excellent cell potency, good rat pharmacokinetic characteristics, and excellent kinase selectivity. Determination of the binding modes of the series in JAK1 and JAK2 by X-ray crystallography supported the design of analogues to enhance affinity and selectivity.

Outstanding challenges in protein–ligand docking and structure-based virtual screening

With an ever‐increasing number of protein structures being solved by X‐ray crystallography, the use of protein–ligand docking algorithms to assess candidate ligands for a binding site has become commonplace. In particular, over the last decade, high‐throughput docking has been widely applied to the virtual screening of large chemical databases for supporting hit‐finding programs in drug discovery. However, the techniques and practice of protein–ligand docking in general, and of structure‐based virtual screening in particular, are still evolving and significant limitations remain to be addressed. In this review, we seek to highlight some of the active areas of research and debate in this promising, but challenging, field.

PRO_SELECT: Combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology

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.

PRO_LIGAND: An approach to de novo molecular design. 3. A genetic algorithm for structure refinement

SummaryRecently, the development of computer programs which permit the de novo design of molecular structures satisfying a set of steric and chemical constraints has become a burgeoning area of research and many operational systems have been reported in the literature. Experience with PRO_LIGAND—the de novo design methodology embodied in our in-house molecular design and simulation system PRO-METHEUS—has suggested that the addition of a genetic algorithm (GA) structure refinement procedure can ‘add value’ to an already useful tool. Starting with the set of designed molecules as an initial population, the GA can combine features from both high- and low-scoring structures and, over a number of generations, produce individuals of better score than any of the starting structures. This paper describes how we have implemented such a procedure and demonstrates its efficacy in improving two sets of molecules generated by different de novo design projects.

Discovery of Novel PI3-Kinase δ Specific Inhibitors for the Treatment of Rheumatoid Arthritis: Taming CYP3A4 Time-Dependent Inhibition

PI3Kδ is a lipid kinase and a member of a larger family of enzymes, PI3K class IA(α, β, δ) and IB (γ), which catalyze the phosphorylation of PIP2 to PIP3. PI3Kδ is mainly expressed in leukocytes, where it plays a critical, nonredundant role in B cell receptor mediated signaling and provides an attractive opportunity to treat diseases where B cell activity is essential, e.g., rheumatoid arthritis. We report the discovery of novel, potent, and selective PI3Kδ inhibitors and describe a structural hypothesis for isoform (α, β, γ) selectivity gained from interactions in the affinity pocket. The critical component of our initial pharmacophore for isoform selectivity was strongly associated with CYP3A4 time-dependent inhibition (TDI). We describe a variety of strategies and methods for monitoring and attenuating TDI. Ultimately, a structure-based design approach was employed to identify a suitable structural replacement for further optimization.

Targeted molecular diversity in drug discovery: Integration of structure-based design and combinatorial chemistry

A powerful new approach emerging in drug discovery research combines computational screening of virtual combinatorial libraries against a therapeutic target and targeted combinatorial library synthesis. This new approach includes positive features from both structure-based design and combinatorial chemistry. It has the potential of producing combinatorial libraries with a high hit rate, and hence accelerates the generation of quality lead compounds. The effectiveness of this novel approach has been shown by the design and synthesis of potent inhibitors for serine and aspartyl proteases.

Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer

Approximately 70% of patients with non–small-cell lung cancer present with late-stage disease and have limited treatment options, so there is a pressing need to develop efficacious targeted therapies for these patients. This remains a major challenge as the underlying genetic causes of ∼50% of non–small-cell lung cancers remain unknown. Here we demonstrate that a targeted genetic dependency screen is an efficient approach to identify somatic cancer alterations that are functionally important. By using this approach, we have identified three kinases with gain-of-function mutations in lung cancer, namely FGFR4, MAP3K9, and PAK5. Mutations in these kinases are activating toward the ERK pathway, and targeted depletion of the mutated kinases inhibits proliferation, suppresses constitutive activation of downstream signaling pathways, and results in specific killing of the lung cancer cells. Genomic profiling of patients with lung cancer is ushering in an era of personalized medicine; however, lack of actionable mutations presents a significant hurdle. Our study indicates that targeted genetic dependency screens will be an effective strategy to elucidate somatic variants that are essential for lung cancer cell viability.