Drug discovery: past, present and future

Investigation of small molecules disrupting dengue virus assembly by inhibiting capsid protein and blocking RNA encapsulation

Dengue fever is a significant global public health concern, causing substantial morbidity and mortality worldwide. The disease can manifest in various forms, from mild fever to potentially life-threatening complications. Developing effective treatments remains a critical challenge to healthcare systems. Despite extensive research, no antiviral drugs have been approved for either the prevention or treatment of dengue. Targeting the virus during its early phase of attachment is essential to inhibit viral replication. The capsid protein plays a crucial role in the virus's structural integrity, assembly, and viral genome release. In the present study, we employed a computational approach focused on the capsid protein to identify possible potent inhibitors against the dengue virus from a library of FDA-approved drugs. We employed high-throughput virtual screening on FDA-approved drugs to identify drug molecules that could potentially combat the disease and save both cost and time. The screening process identified four drug molecules (Nordihydroguaiaretic acid, Ifenprodil tartrate, Lathyrol, and Safinamide Mesylate) based on their highest binding affinity and MM/GBSA scores. Among these, Nordihydroguaiaretic acid showed higher binding affinity than the reference molecule with - 11.66 kcal/mol. In contrast, Ifenprodil tartrate and Lathyrol showed similar results to the reference molecule, with binding energies of - 9.42 kcal/mol and - 9.29 kcal/mol, respectively. Following the screening, molecular dynamic simulations were performed to explore the molecular stability and conformational possibilities. The drug molecules were further supported by post-molecular simulation analysis. Furthermore, binding energies were also computed using the MM/GBSA approach, and the free energy landscape was used to calculate the different transition states, revealing that the drugs exhibited significant transition states. Specifically, Nordihydroguaiaretic acid and Ifenprodil tartrate displayed higher flexibility, while Lathyrol and Safinamide Mesylate showed more predictable and consistent protein folding. This significant breakthrough offers new hope against dengue, highlighting the power of computational drug discovery in identifying potent inhibitors and paving the way for novel treatment approaches.

Performing an In Silico Repurposing of Existing Drugs by Combining Virtual Screening and Molecular Dynamics Simulation

Drug repurposing has become one of the most widely used methods that can make drug discovery more efficient and less expensive. Additionally, computational methods such as structure-based drug designing can be utilized to make drug discovery more efficient and more accurate. Now imagine what can be achieved by combining drug repurposing and computational methods together in drug discovery, "in silico repurposing." In this chapter, we tried to describe a method that combines structure-based virtual screening and molecular dynamics simulation which can find effective compounds among existing drugs that may affect on a specific molecular target. By using molecular docking as a tool for the screening process and then by calculating ligand binding in an active receptor site using scoring functions and inspecting the proper orientation of pharmacophores in the binding site, the potential compounds will be chosen. After that, in order to test the potential compounds in a realistic environment, molecular dynamics simulation and related analysis have to be carried out for separating the false positives and the true positives from each other and finally identifying true "Hit" compounds. It's good to emphasize that if any of these identified potential compounds turn out to have the efficacy to affect that specific molecular target, it can be taken to the phase 2 clinical trials straightaway.

Assemble-And-Match: A Novel Hybrid Tool for Enhancing Education and Research in Rational Structure Based Drug Design

Rational drug design is the process of finding new medication that can activate or inhibit the biofunction of a target molecule by binding to it and forming a molecular complex. Here, shape and charge complementarities between drug and target are key. To help find effective drug molecules out of a huge pool of possibilities, physical and computer aided tools have been developed. Former offers a tangible experience of the molecular interactions yet lacks measurement and evaluation capabilities. Latter enables accurate and fast evaluations, but does not deliver the interactive tangible experience of physical models. We introduce a novel hybrid model called "Assemble-And-Match" where, we enhance and combine the unique features of the two categories. Assemble-And-Match works based on fabrication of customized molecular fragments using our developed software and a 3D printer. Fragments are hinged to each other in different combinations and form flexible peptide chains, conformable to tertiary structures, to fit in the binding pocket of a (3D printed) target molecule. Through embedded measurement marks, the molecular model is reconstructed in silico and its properties are evaluated. We expect Assemble-And-Match tool can enable combination of visuospatial perception with in silico computational power to aid research and education in drug design.

Discovery of novel 1,2,3-triazole derivatives as anticancer agents using QSAR and in silico structural modification

Considerable attention has been given on the search for novel anticancer drugs with respect to the disease sequelae on human health and well-being. Triazole is considered to be an attractive scaffold possessing diverse biological activities. Structural modification on the privileged structures is noted as an effective strategy towards successful design and development of novel drugs. The quantitative structure–activity relationships (QSAR) is well-known as a powerful computational tool to facilitate the discovery of potential compounds. In this study, a series of thirty-two 1,2,3-triazole derivatives (1–32) together with their experimentally measured cytotoxic activities against four cancer cell lines i.e., HuCCA-1, HepG2, A549 and MOLT-3 were used for QSAR analysis. Four QSAR models were successfully constructed with acceptable predictive performance affording R_CV ranging from 0.5958 to 0.8957 and RMSE_CV ranging from 0.2070 to 0.4526. An additional set of 64 structurally modified triazole compounds (1A–1R, 2A–2R, 7A–7R and 8A–8R) were constructed in silico and their predicted cytotoxic activities were obtained using the constructed QSAR models. The study suggested crucial moieties and certain properties essential for potent anticancer activity and highlighted a series of promising compounds (21, 28, 32, 1P, 8G, 8N and 8Q) for further development as novel triazole-based anticancer agents.

Comparison of library screening techniques used in the development of dsDNA ligands

The gel retardation and FID (fluorescent intercalator displacement) techniques have been compared for the selection of dsDNA binding ligands out of library mixtures. The selection procedure involves the synthesis and screening of unnatural oligopeptide libraries based on an iterative deconvolution procedure. Both methods yield comparable selection results and binding constants for the selected compounds, meaning that they can be considered as complementary in the discovery process of new antigene compounds. Furthermore, a quinazolin-2,4-dione amino acid has been identified as possessing interesting properties for interaction with dsDNA.

Barriers to Alzheimer disease drug discovery and development in the biotechnology industry

The major barrier to Alzheimer disease (AD) drug discovery and development in the biotechnology industry is scale. Most biotechnology companies do not have the personnel or expertise to carry a drug from the bench to the market. Much effort in the industry has been directed toward the elucidation of molecular mechanisms of AD and the identification of new targets. Advances in biotechnology have generated new insights into disease mechanisms, increased the number of lead compounds, and accelerated biologic screening. The majority of costs associated with drug development are in clinical testing and development activities, many of which are driven by regulatory issues. For most biotechnology companies, the costs of such trials and the infrastructure necessary to support them are prohibitive. Another significant barrier is the definition of therapeutic benefit for AD drugs; Food and Drug Administration (FDA) precedent has established that a drug must show superiority to placebo on a performance-based test of cognition and a measure of global clinical function. This restrictive definition is biased toward drugs that enhance performance on memory-based tests. Newer AD drugs are targeted toward slowing disease progression; however, there is currently no accepted definition of what constitutes efficacy in disease progression. Despite these obstacles, the biotechnology industry has much to offer AD drug discovery and development. Biotechnology firms have already developed essential technology for AD drug development and will continue to do so. Biotechnology companies can move more quickly; of course, the trick is to move quickly in the right direction. Speed may offset some of the problems associated with lack of scale. Additionally, biotechnology companies can afford to address markets that may be too restricted for larger pharmaceutical companies. This advantage will have increasing importance, as therapies are developed to address subtypes of AD.