Expert Opinion on Drug Discovery最新文献

Introduction: Atogepant is a selective calcitonin gene-related peptide (CGRP) receptor antagonist that is utilized in adults for the prevention of episodic and chronic migraine. Cumulative findings support the involvement of CGRP in migraine pathophysiology, and atogepant functions by competitively antagonizing CGRP receptors, which results in the inhibition of trigeminovascular nociception. The mechanism of action addresses the cause of migraine pain, providing an effective preventive treatment option.

Areas covered: The key milestones in its development, including preclinical achievements, phase I, II, and III clinical trials, and regulatory approvals are reviewed. Additionally, clinical efficacy, safety profile, and tolerability of atogepant are discussed. The literature review is based on a comprehensive search of English peer-reviewed articles from various electronic databases, including PubMed and ClinicalTrials.gov.

Expert opinion: The development of atogepant represents a significant breakthrough in migraine prevention, particularly due to its improved safety profile that reduces the risk of liver injury, which was a major limitation of first-generation gepants. Drug-drug interaction studies with atogepant highlight the necessity for more inclusive study populations. Given that migraine disproportionately affects females, future clinical development programs should include diverse patient demographics to ensure the findings are generalizable to all individuals suffering from migraine.

Introduction: High-throughput mass spectrometry that could deliver > 10 times faster sample readout speed than traditional LC-based platforms has emerged as a powerful analytical technique, enabling the rapid analysis of complex biological samples. This increased speed of MS data acquisition has brought a critical demand for automatic data processing capabilities that should match or surpass the speed of data acquisition. Those data processing capabilities should serve the different requirements of drug discovery workflows.

Areas covered: This paper introduced the key steps of the automatic data processing workflows for high-throughput MS technologies. Specific examples and requirements are detailed for different drug discovery applications.

Expert opinion: The demand for automatic data processing in high-throughput mass spectrometry is driven by the need to keep pace with the accelerated speed of data acquisition. The seamless integration of processing capabilities with LIMS, efficient data review mechanisms, and the exploration of future features such as real-time feedback, automatic method optimization, and AI model training is crucial for advancing the drug discovery field. As technology continues to evolve, the synergy between high-throughput mass spectrometry and intelligent data processing will undoubtedly play a pivotal role in shaping the future of high-throughput drug discovery applications.

Introduction: Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of cancer deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many patients eventually develop disease recurrence and metastasis. Without effective treatments, patients with aggressive PC display very poor survival. To curb the current high mortality rate, many investigations have been carried out to identify efficacious therapeutics. Compared to de novo drug designs, computational methods have been widely employed to offer actionable drug predictions in a fast and cost-efficient way. Particularly, powered by an increasing availability of next-generation sequencing molecular profiles from PC patients, computer-aided approaches can be tailored to screen for candidate drugs.

Areas covered: Herein, the authors review the recent advances in computational methods for drug discovery utilizing molecular profiles from PC patients. Given the uniqueness in PC therapeutic needs, they discuss in detail the drug discovery goals of these studies, highlighting their translational values for clinically impactful drug nomination.

Expert opinion: Evolving molecular profiling techniques may enable new perspectives for computer-aided approaches to offer drug candidates for different tumor microenvironments. With ongoing efforts to incorporate new compounds into large-scale high-throughput screens, the authors envision continued expansion of drug candidate pools.

Introduction: The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed.

Areas covered: This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process.

Expert opinion: The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.

Introduction: Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of global morbidity and mortality. Lipid lowering therapy (LLT) constitutes the cornerstone of ASCVD prevention and treatment. However, several patients fail to achieve therapeutic goals due to low treatment adherence or limitations of standard-of-care (SoC) LLTs. Inclisiran represents a pivotal low-density lipoprotein cholesterol (LDL-C) lowering agent aiming to address current unmet needs in LLT. It is the first available small interfering RNA (siRNA) LLT, specifically targeting PCSK9 mRNA and leading to post-transcriptional gene silencing (PTGS) of the PCSK9 gene.

Areas covered: Promising phase III trials revealed an ~ 50% reduction in LDL-C levels with subcutaneous inclisiran administration on days 1 and 90, followed by semiannual booster shots. Coupled with inclisiran's favorable safety profile, these findings led to its approval by both the EMA and FDA. Herein, the authors highlight the preclinical discovery and development of this agent and provide the reader with their expert perspectives.

Expert opinion: The evolution of gene-silencing treatments offers new perspectives in therapeutics. Inclisiran appears to have the potential to revolutionize ASCVD prevention and treatment, benefiting millions of patients. Ensuring widespread availability of Inclisiran, as well as managing additional healthcare costs that may arise, should be of paramount importance.

Introduction: Hydrophobic tagging (HyT) technology presents a distinct therapeutic strategy diverging from conventional small molecule drugs, providing an innovative approach to drug design. This review aims to provide an overview of the HyT literature and future outlook to offer guidance for drug design.

Areas covered: In this review, the authors introduce the composition, mechanisms and advantages of HyT technology, as well as summarize the detailed applications of HyT technology in anti-cancer, neurodegenerative diseases (NDs), autoimmune disorders, cardiovascular diseases (CVDs), and other fields. Furthermore, this review discusses key aspects of the future development of HyT molecules.

Expert opinion: HyT emerges as a highly promising targeted protein degradation (TPD) strategy, following the successful development of proteolysis targeting chimeras (PROTAC) and molecular glue. Based on exploring new avenues, modification of the HyT molecule itself potentially enhances the technology. Improved synthetic pathways and emphasis on pharmacokinetic (PK) properties will facilitate the development of HyT. Furthermore, elucidating the biochemical basis by which the compound's hydrophobic moiety recruits the protein homeostasis network will enable the development of more precise assays that can guide the optimization of the linker and hydrophobic moiety.

Introduction: For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs.

Areas covered: End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants ($k_{\mathrm{off}}$ and $k_{\mathrm{on}}$) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations.

Expert opinion: The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.