Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece.

Fragment-based drug discovery (FBDD) has emerged as a powerful strategy to confront the challenges faced by conventional drug development approaches, particularly in the context of central nervous system (CNS) disorders. FBDD involves the screening of libraries that comprise thousands of small molecular fragments, each no greater than 300 Da in size. Unlike the generally larger molecules from high-throughput screening that limit customisation, fragments offer a more strategic starting point. These fragments are inherently compact, providing a strong foundation with good binding affinity for the development of drug candidates. The minimal elaboration required to transition the hit into a drug-like molecule is not only accelerated, but also it allows for precise modifications to enhance both their activity and pharmacokinetic properties. This shift towards a fragment-centric approach has seen commercial success and holds considerable promise in the continued streamlining of the drug discovery and development process. In this review, we highlight how FBDD can be integrated into the CNS drug discovery process to enhance the exploration of a target. Furthermore, we provide recent examples where FBDD has been an integral component in CNS drug discovery programs, enabling the improvement of pharmacokinetic properties that have previously proven challenging. The FBDD optimisation process provides a systematic approach to explore this vast chemical space, facilitating the discovery and design of compounds piece by piece that are capable of modulating crucial CNS targets.

Identifying Preferred Features of Weight Loss Programs for Adults With or at Risk of Type 2 Diabetes: A Discrete Choice Experiment With 3,960 Adults in the U.K.

OBJECTIVE: To understand preferences for features of weight loss programs among adults with or at risk of type 2 diabetes in the U.K. RESEARCH DESIGN AND METHODS: We conducted a discrete choice experiment with 3,960 U.K. adults living with overweight (n = 675 with type 2 diabetes). Preferences for seven characteristics of weight loss programs were analyzed. Simulations from choice models using the experimental data predicted uptake of available weight loss programs. Patient groups comprising those who have experience with weight loss programs, including from minority communities, informed the experimental design. RESULTS: Preferences did not differ between individuals with and without type 2 diabetes. Preferences were strongest for type of diet. Healthy eating was most preferred relative to total diet replacement (odds ratio [OR] 2.24; 95% CI 2.04-2.44). Individual interventions were more popular than group interventions (OR 1.40; 95% CI 1.34-1.47). Participants preferred programs offering weight loss of 10-15 kg (OR 1.37; 95% CI 1.28-1.47) to those offering loss of 2-4 kg. Online content was preferred over in-person contact (OR 1.24; 95% CI 1.18-1.30). There were few differences in preferences by gender or ethnicity, although weight loss was more important to women than to men, and individuals from ethnic minority populations identified more with programs where others shared their characteristics. Modeling suggested that tailoring programs to individual preferences could increase participation by ∼17 percentage points (68% in relative terms). CONCLUSIONS: Offering a range of weight loss programs targeting the preferred attributes of different patient groups could potentially encourage more people to participate in weight loss programs and support those living with overweight to reduce their weight.

Interrogating Aptamer Chemical Space Through Modified Nucleotide Substitution Facilitated by Enzymatic DNA Synthesis.

Chemical modification of aptamers is an important step to improve their performance and stability in biological media. This can be performed either during their identification (mod-SELEX) or after the in vitro selection process (post-SELEX). In order to reduce the complexity and workload of the post-SELEX modification of aptamers, we have evaluated the possibility of improving a previously reported, chemically modified aptamer by combining enzymatic synthesis and nucleotides bearing bioisosteres of the parent cubane side-chains or substituted cubane moieties. This method lowers the synthetic burden often associated with post-SELEX approaches and allowed to identify one additional sequence that maintains binding to the PvLDH target protein, albeit with reduced specificity. In addition, while bioisosteres often improve the potency of small molecule drugs, this does not extend to chemically modified aptamers. Overall, this versatile method can be applied for the post-SELEX modification of other aptamers and functional nucleic acids.

An update on late-stage functionalization in today's drug discovery.

INTRODUCTION: Late-stage functionalization (LSF) allows for the introduction of new chemical groups toward the end of a synthetic sequence, which means new molecules can be rapidly accessed without laborious de novo chemical synthesis. Over the last decade, medicinal chemists have begun to implement LSF strategies into their drug discovery programs, affording benefits such as efficient access to diverse libraries to explore structure-activity relationships and the improvement of physicochemical and pharmacokinetic properties. AREAS COVERED: An overview of the key advancements in LSF methodology development from 2019 to 2022 and their applicability to drug discovery is provided. In addition, several examples from both academia and industry where LSF methodologies have been applied by medicinal chemists to their drug discovery programs are presented. EXPERT OPINION: Utilization of LSF by medicinal chemists is on the rise, both in academia and in industry. The maturation of the LSF field to produce methodologies bearing increased regioselectivity, scope, and functional group tolerance is envisaged to narrow the gap between methodology development and medicinal chemistry research. The authors predict that the sheer versatility of these techniques in facilitating challenging chemical transformations of bioactive molecules will continue to increase the efficiency of the drug discovery process.

'One size doesn't fit all': Lessons from interaction analysis on tailoring Open Science practices to qualitative research.

The Open Science Movement aims to enhance the soundness, transparency, and accessibility of scientific research, and at the same time increase public trust in science. Currently, Open Science practices are mainly presented as solutions to the 'reproducibility crisis' in hypothetico-deductive quantitative research. Increasing interest has been shown towards exploring how these practices can be adopted by qualitative researchers. In reviewing this emerging body of work, we conclude that the issue of diversity within qualitative research has not been adequately addressed. Furthermore, we find that many of these endeavours start with existing solutions for which they are trying to find matching problems to be solved. We contrast this approach with a natural incorporation of Open Science practices within interaction analysis and its constituent research traditions: conversation analysis, discursive psychology, ethnomethodology, and membership categorisation analysis. Zooming in on the development of conversation analysis starting in the 1960s, we highlight how practices for opening up and sharing data and analytic thinking have been embedded into its methodology. On the basis of this presentation, we propose a series of lessons learned for adopting Open Science practices in qualitative research.