The emergence of SARS-CoV-2 and its variants that critically affect global public health requires characterization of mutations and their evolutionary pattern from specific Variants of Interest (VOIs) to Variants of Concern (VOCs). Leveraging the concept of equilibrium statistical mechanics, we introduce a new responsive quantity defined as “Mutational Response Function (MRF)” aptly quantifying domain-wise average entropy-fluctuation in the spike glycoprotein sequence of SARS-CoV-2 based on its evolutionary database. As the evolution transits from a specific variant to VOC, we find that the evolutionary crossover is accompanied by a dramatic change in MRF, upholding the characteristic of a dynamic phase transition. With this entropic information, we have developed an ancestral-based machine learning method that helps predict future domain-specific mutations. The feedforward binary classification model pinpoints possible residues prone to future mutations that have implications for enhanced fusogenicity and pathogenicity of the virus. We believe such MRF analyses followed by a statistical mechanics augmented ML approach could help track different evolutionary stages of such species and identify a critical evolutionary transition that is alarming.

Whole genome sequencing has rapidly progressed in recent years, with sequencing the SARS-CoV-2 genomes, making it a more reliable clinical tool for public health surveillance. This development has resulted in the production of a large amount of genomic data used for various types of genomic exploration. However, without a proper standard protocol, the usage of genomic data for analyzing various biological phenomena, such as mutation and evolution, may result in a propagating risk of using an unvalidated data set. This process could lead to irregular data being generated along with a high risk of altered analysis. Thus, the current study lays out the foundation for a preprocess pipeline using data analysis to analyze the genomic data set for its accuracy. We have used the recent example of SARS-CoV-2 to demonstrate the process overflow that can be utilized for various kinds of biological exploration such as understanding mutational events, evolutionary divergence, and speciation. Our analysis reveals a significant amount of sequence divergence in the gamma variant as compared with the reference genome thereby making the variant less infective and deadly. Moreover, we found regions in the genomic sequence that is more prone to mutational localization thereby altering the structural integrity of the virus resulting in a more reliable molecular viral mechanism. We believe that the current work will help for an initial check of the genomic data followed by the biological assessment of the process overflow which will be beneficial for the variant analysis and mutational uprising.

Aim: With several experimental studies establishing the role of Bacopa monnieri as an effective neurological medication, less focus has been employed to explore how effectively Bacopa monnieri brings about this property. The current work focuses on understanding the molecular interaction of the phytochemicals of the plant against different neurotrophic factors to explore their role and potential as potent anti-neurodegenerative drugs. Background: Neurotrophins play a crucial role in the development and regulation of neurons. Alterations in the functioning of these Neurotrophins lead to several Neurodegenerative Disorders. Albeit engineered medications are accessible for the treatment of Neurodegenerative Disorders, due to their numerous side effects, it becomes imperative to formulate and synthesize novel drug candidates. Objective: This study aims to investigate the potential of Bacopa monnieri phytochemicals as potent anti-neurodegenerative drugs by inspecting the interactions between Neurotrophins and target proteins. Methods: The current study employs molecular docking and molecular dynamic simulation studies to examine the molecular interactions of phytochemicals with respective Neurotrophins. Further inspection of the screened phytochemicals was performed to analyze the ADME-Tox properties in order to classify the screened phytochemicals as potent drug candidates. Conclusion: Our study provides an in-silico approach toward understanding the anti-neurodegenerative property of Bacopa monnieri phytochemicals and establishes the role of four major phytochemicals which can be utilized as a replacement for synthetic drugs against several neurodegenerative disorders.

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