R software for QSAR analysis in phytopharmacological studies.

Introduction: In recent decades, quantitative structure-activity relationship (QSAR) analysis has become an important method for drug design and natural product research. With the availability of bioinformatic and cheminformatic tools, a vast number of descriptors have been generated, making it challenging to select potential independent variables that are accurately related to the dependent response variable. Objective: The objective of this study is to demonstrate various descriptor selection procedures, such as the Boruta approach, all subsets regression, the ANOVA approach, the AIC method, stepwise regression, and genetic algorithm, that can be used in QSAR studies. Additionally, we performed regression diagnostics using R software to test parameters such as normality, linearity, residual histograms, PP plots, multicollinearity, and homoscedasticity. Results: The workflow designed in this study highlights the different descriptor selection procedures and regression diagnostics that can be used in QSAR studies. The results showed that the Boruta approach and genetic algorithm performed better than other methods in selecting potential independent variables. The regression diagnostics parameters tested using R software, such as normality, linearity, residual histograms, PP plots, multicollinearity, and homoscedasticity, helped in identifying and diagnosing model errors, ensuring the reliability of the QSAR model. Conclusion: QSAR analysis is vital in drug design and natural product research. To develop a reliable QSAR model, it is essential to choose suitable descriptors and perform regression diagnostics. This study offers an accessible, customizable approach for researchers to select appropriate descriptors and diagnose errors in QSAR studies

Rapid Transition from Continental Breakup to Igneous Oceanic Crust in the South China Sea

Continental breakup represents the successful process of rifting and thinning of the continental lithosphere, leading to plate rupture and initiation of oceanic crust formation. Magmatism during breakup seems to follow a path of either excessive, transient magmatism (magma-rich margins) or of igneous starvation (magma-poor margins). The latter type is characterized by extreme continental lithospheric extension and mantle exhumation prior to igneous oceanic crust formation. Discovery of magma-poor margins has raised fundamental questions about the onset of ocean-floor type magmatism, and has guided interpretation of seismic data across many rifted margins, including the highly extended northern South China Sea margin. Here we report International Ocean Discovery Program drilling data from the northern South China Sea margin, testing the magma-poor margin model outside the North Atlantic. Contrary to expectations, results show initiation of Mid-Ocean Ridge basalt type magmatism during breakup, with a narrow and rapid transition into igneous oceanic crust. Coring and seismic data suggest that fast lithospheric extension without mantle exhumation generated a margin structure between the two endmembers. Asthenospheric upwelling yielding Mid-Ocean Ridge basalt-type magmatism from normal-temperature mantle during final breakup is interpreted to reflect rapid rifting within thin pre-rift lithosphere