Design of anti-fungal agents by 3D-QSAR

An increase in the number of invasive fungal infections especially in immunocompromised patients is increasing the mortality rate worldwide. Due to the emergence of drug-resistant fungi, the currently available antifungal drugs have become ineffective. Because no alternative treatment is available, some existing drugs are still used. Therefore, there is a need to design and develop novel and effective anti-fungal drugs. Molecular docking and 3-dimensional quantitative structure-activity relationship (3D-QSAR) methods have been useful approaches for the design of novel molecules. A set of 30 molecules reported in the literature containing azoles and non-azoles have been used in this study to derive 3D-QSAR.CoMFA and CoMSIA models for the most active compound and least active compounds have been developed. The structural requirements were obtained by analysing the contour maps. The partial least square analysis for CoMFA and CoMSIA showed a significant cross-validated correlation coefficient of 0.625 and 0.67 and a non-cross validated correlation coefficient of 0.991 and 0.99, respectively. The model was validated by observing the predicted correlation for test molecules with the value of 0.699 and 0.659, respectively

Design of anti-fungal agents by 3D-QSAR

744-754An increase in the number of invasive fungal infections especially in immunocompromised patients is increasing the mortality rate worldwide. Due to the emergence of drug-resistant fungi, the currently available antifungal drugs have become ineffective. Because no alternative treatment is available, some existing drugs are still used. Therefore, there is a need to design and develop novel and effective anti-fungal drugs. Molecular docking and 3-dimensional quantitative structure-activity relationship (3D-QSAR) methods have been useful approaches for the design of novel molecules. A set of 30 molecules reported in the literature containing azoles and non-azoles have been used in this study to derive 3DQSAR. CoMFA and CoMSIA models for the most active compound and least active compounds have been developed. The structural requirements were obtained by analysing the contour maps. The partial least square analysis for CoMFA and CoMSIA showed a significant cross-validated correlation coefficient of 0.625 and 0.67 and a non-cross validated correlation coefficient of 0.991 and 0.99, respectively. The model was validated by observing the predicted correlation for test molecules with the value of 0.699 and 0.659, respectively

Therapeutic Approaches to Amyotrophic Lateral Sclerosis from the Lab to the Clinic

Amyotrophic Lateral Sclerosis (ALS) is a terminal neuro-degenerative disorder that is clinically recognized as a gradual degeneration of the upper and lower motor neurons, with an average duration of 3 to 5 years from initial of symptoms to death. The mechanisms underlying the pathogenesis and progression of the disease are multifactorial. Therefore, to find effective treatments, it is necessary to understand the heterogeneity underlying the progression of ALS. Recent developments in gene therapy have opened a new avenue to treat this condition, especially for the characterized genetic types. Gene therapy methods have been studied in various pre-clinical settings and clinical trials, and they may be a promising path for developing an effective and safe ALS cure. A growing body of evidence demonstrates abnormalities in metabolic energy at the cellular and whole-body level in animal models and people living with ALS. Using and incorporatig high-throughput "omics" methods have radically transformed our thoughts about ALS, strengthened our understanding of the disease's dynamic molecular architecture, differentiated distinct patient subtypes, and created a reasonable basis for identifying biomarkers and novel individualised treatments. Future clinical and laboratory trials would also focus on the diverse relationships between metabolism and ALS to address the issue of whether targeting poor metabolism in ALS is an effective way to change disease progression. In this review, we focus on the detailed pathogenesis of ALS and highlight principal genes, i.e., SOD1, TDP-43, C9orf72, and FUS, as well as targeted ALS therapies. An attempt is made to provide up-to-date clinical outcomes, including various biomarkers that are thought to be important players in early ALS detection