Project description:ObjectivesDiabetes places a substantial economic burden on countries worldwide. The costs associated with diabetes management, including healthcare services, medications, monitoring equipment, and productivity losses, are substantial. The International Diabetes Federation has estimated that global healthcare expenditures associated with diabetes and its complications exceed hundreds of billions of dollars annually. Therefore, a critical need exists to develop drugs that are highly effective, affordable, and easily accessible to society.MethodsThis study explored the structural modification of 1,4-DHP derivatives to identify specific α-amylase inhibitors, with the aim of developing more effective and accessible drugs for diabetes. We evaluated the activity and binding ability of the designed compounds. In addition, we performed drug-likeness and pharmacokinetic studies on the modified compounds.ResultsEquation (1) had the highest accuracy, on the basis of internal and external assessment parameters, including R2int = 0.852, R2adj = 0.803, Q2cv = 0.731, and R2ext = 0.884. Moreover, the five potent analogs identified through structure-based drug design demonstrated a more favorable interaction than observed for the template or acarbose. Additionally, comprehensive studies on the drug-like properties and pharmacokinetics of the designed compounds supported their oral safety and favorable pharmacokinetic profiles.ConclusionsThe designed analogs show promise for developing new hypoglycemic agents. Their positive attributes and performance suggest that they may potentially serve as candidates for further research in improving treatments for high blood sugar-associated conditions.
Project description:Fragment screening is frequently used for hit identification. However, there was no report starting from a small fragment for the development of an anaplastic lymphoma kinase (ALK) inhibitor, despite the number of ALK inhibitors reported. We began our research with the fragment hit F-1 and our subsequent linker design, and its docking analysis yielded novel cis-1,2,2-trisubstituted cyclopropane 1. The fragment information was integrated with a structure-based approach to improve upon the selectivity over tropomyosin receptor kinase A, leading to the potent and highly selective ALK inhibitor, 4-trifluoromethylphenoxy-cis-1,2,2-trisubstituted cyclopropane 12. This work shows that fragments become a powerful tool for both lead generation and optimization, such as the improvement of selectivity, by combining them with a structure-based drug design approach, resulting in the fast and efficient development of a novel, potent, and highly selective compound.
Project description:Developing new, more effective antibiotics against resistant Mycobacterium tuberculosis that inhibit its essential proteins is an appealing strategy for combating the global tuberculosis (TB) epidemic. Finding a compound that can target a particular cavity in a protein and interrupt its enzymatic activity is the crucial objective of drug design and discovery. Such a compound is then subjected to different tests, including clinical trials, to study its effectiveness against the pathogen in the host. In recent times, new techniques, which involve computational and analytical methods, enhanced the chances of drug development, as opposed to traditional drug design methods, which are laborious and time-consuming. The computational techniques in drug design have been improved with a new generation of software used to develop and optimize active compounds that can be used in future chemotherapeutic development to combat global tuberculosis resistance. This review provides an overview of the evolution of tuberculosis resistance, existing drug management, and the design of new anti-tuberculosis drugs developed based on the contributions of computational techniques. Also, we show an appraisal of available software and databases on computational drug design with an insight into the application of this software and databases in the development of anti-tubercular drugs. The review features a perspective involving machine learning, artificial intelligence, quantum computing, and CRISPR combination with available computational techniques as a prospective pathway to design new anti-tubercular drugs to combat resistant tuberculosis.
Project description:Alzheimer disease and related dementias are major challenges, demanding urgent needs for earliest possible diagnosis to optimize the success rate in finding effective therapeutic interventions. Mounting solid scientific premises point at the core acetylcholine-biosynthesizing cholinergic enzyme, ChAT as a legitimate in vivo target for developing positron emission tomography biomarker for early diagnosis and/or monitoring therapeutic responses in the neurodegenerative dementias. Up-to-date, no PET tracer ligands for ChAT are available. Here we report for the first time a novel hierarchical virtual screening approach on a commercial library of ~300,000 compounds, followed by in vitro screening of the hits by a new High-Throughput ChAT assay. We report detailed pharmacodynamic data for three identified selective novel ChAT ligands with IC50 and K i values ranging from ~7 to 26?µM. In addition, several novel selective inhibitors of the acetylcholine-degrading enzymes, AChE and BuChE were identified, with one of the compounds showing an IC50-value of ~6?µM for AChE. In conclusion, this report provides an excellent starting platform for designing and optimizing potent and selective ChAT ligands, with high potential as PET-imaging probe for early diagnosis of AD, and related dementias, such as Down's syndrome and Lewy body disorders.
Project description:Human Epidermal Growth Factor Receptor-1 (EGFR), a transmembrane tyrosine kinase receptor (RTK), has been associated with several types of cancer, including breast, lung, ovarian, and anal cancers. Thus, the receptor was targeted by a variety of therapeutic approaches for cancer treatments. A series of chalcone derivatives are among the most highly potent and selective inhibitors of EGFR described to date. A series of chalcone derivatives were proposed in this study to investigate the intermolecular interactions in the active site utilizing molecular docking and molecular dynamics simulations. After a careful analysis of docking results, compounds 1a and 1d were chosen for molecular dynamics simulation study. Extensive hydrogen bond analysis throughout 7 ns molecular dynamics simulation revealed the ability of compounds 1a and 1d to retain the essential interactions needed for the inhibition, especially MET 93. Finally, MM-GBSA calculations highlight on the capability of the ligands to bind strongly within the active site with binding energies of -44.04 and -56.6 kcal/mol for compounds 1a and 1d, respectively. Compound 1d showed to have a close binding energy with TAK-285 (-66.17 kcal/mol), which indicates a high chance for compound 1d to exhibit inhibitory activity, thus recommending to synthesis it to test its biological activity. It is anticipated that the findings reported here may provide very useful information for designing effective drugs for the treatment of EGFR-related cancer disease.
Project description:Therapeutics are currently unavailable for Venezuelan equine encephalitis virus (VEEV), which elicits flu-like symptoms and encephalitis in humans, with an estimated 14% of cases resulting in neurological disease. Here we identify anti-VEEV agents using in silico structure-based-drug-design (SBDD) for the first time, characterising inhibitors that block recognition of VEEV capsid protein (C) by the host importin (IMP) ?/?1 nuclear transport proteins. From an initial screen of 1.5 million compounds, followed by in silico refinement and screening for biological activity in vitro, we identified 21 hit compounds which inhibited IMP?/?1:C binding with IC50s as low as 5?µM. Four compounds were found to inhibit nuclear import of C in transfected cells, with one able to reduce VEEV replication at µM concentration, concomitant with reduced C nuclear accumulation in infected cells. Further, this compound was inactive against a mutant VEEV that lacks high affinity IMP?/?1:C interaction, supporting the mode of its antiviral action to be through inhibiting C nuclear localization. This successful application of SBDD paves the way for lead optimization for VEEV antivirals, and is an exciting prospect to identify inhibitors for the many other viral pathogens of significance that require IMP?/?1 in their infectious cycle.
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of coronavirus disease 2019 (COVID-19), in which the main protease (Mpro) plays an important role in the virus's life cycle. In this work, two representative peptide inhibitors (11a and PF-07321332) were selected, and their interaction mechanisms of non-covalently bound with Mpro were firstly investigated by means of molecular dynamical simulation. Then, using the fragment-based drug design method, some fragments from the existing SARS-CoV and SARS-CoV-2 inhibitors were selected to replace the original P2 and P3 fragments, resulting in some new molecules. Among them, two molecules (O-74 and N-98) were confirmed by molecular docking and molecular dynamics simulation, and ADMET properties prediction was employed for further verification. The results shown that they presented excellent activity and physicochemical properties, and had the potential to be new inhibitors for SARS-CoV-2 main protease.
Project description:The ATPase subunit of DNA gyrase B is an attractive antibacterial target due to high conservation across bacteria and the essential role it plays in DNA replication. A novel class of pyrazolopyridone inhibitors was discovered by optimizing a fragment screening hit scaffold using structure guided design. These inhibitors show potent Gram-positive antibacterial activity and low resistance incidence against clinically important pathogens.
Project description:The accumulation of abnormal prion protein (PrP(Sc)) converted from the normal cellular isoform of PrP (PrP(C)) is assumed to induce pathogenesis in prion diseases. Therefore, drug discovery studies for these diseases have focused on the protein conversion process. We used a structure-based drug discovery algorithm (termed Nagasaki University Docking Engine: NUDE) that ran on an intensive supercomputer with a graphic-processing unit to identify several compounds with anti-prion effects. Among the candidates showing a high-binding score, the compounds exhibited direct interaction with recombinant PrP in vitro, and drastically reduced PrP(Sc) and protein-aggresomes in the prion-infected cells. The fragment molecular orbital calculation showed that the van der Waals interaction played a key role in PrP(C) binding as the intermolecular interaction mode. Furthermore, PrP(Sc) accumulation and microgliosis were significantly reduced in the brains of treated mice, suggesting that the drug candidates provided protection from prion disease, although further in vivo tests are needed to confirm these findings. This NUDE-based structure-based drug discovery for normal protein structures is likely useful for the development of drugs to treat other conformational disorders, such as Alzheimer's disease.
Project description:Bromodomains (BRDs) are epigenetic readers that recognize acetylated-lysine (KAc) on proteins and are implicated in a number of diseases. We describe a virtual screening approach to identify BRD inhibitors. Key elements of this approach are the extensive design and use of substructure queries to compile a set of commercially available compounds featuring novel putative KAc mimetics and docking this set for final compound selection. We describe the validation of this approach by applying it to the first BRD of BRD4. The selection and testing of 143 compounds lead to the discovery of six novel hits, including four unprecedented KAc mimetics. We solved the crystal structure of four hits, determined their binding mode, and improved their potency through synthesis and the purchase of derivatives. This work provides a validated virtual screening approach that is applicable to other BRDs and describes novel KAc mimetics that can be further explored to design more potent inhibitors.