Using Machine learning  modeling to mitigate the Climatic fluctuations on  Angiotensin  converting enzyme (ACE) inhibition activity.

Abstract.

Currently, the anticipated climatic change hazards redirect  the emergency plans to adapt and control their worldwide risk .That's why, the continuous data sharing from medical platforms on climate change  should be strengthened, to translate the outcomes of climate change into biological and medical insights .  In this commentary,  we develop an initiative paradigm to model the climatic fluctuations on marine-sourced hydrolysates that affects directly on  ACE inhibition activity in drug industry . On top, the further aim is to regulate a descriptive network starting from the climate change features , passing by the aquatic ecosystem alterations  to finally  predict the Angiotensin  converting enzyme (ACE) inhibition activity on hypertensive patients.  For this,  (please Mohamed describe the model with professional way in related to the topic showing its compatibility with the scenario of climate change and pharmaceutical).

Introduction 

Climate change alarm a striking change on human health in different settings especially in various adaptation capacities[1]. For this, scientists from different localities generate enormous amount of data describing both direct and indirect climatic effects in relation to the biomedical research. A factual example that correlates both effects is the water biology. Noteworthy, the recent hypertension cases were founded to be associated with drinking water salinization that is intimately related with climate change [2].
In 2017, scientists have reported the relationship between the structure of peptides and ACE inhibition has not been fully elucidated [4]. With this, we developed a machine learning model that can predict the altered peptides bioactivity in a wake of  temperature fluctuations [3]. In turn,  this unveils the hidden role of climate change on the frequent uncontrolled alteration in the ACE-inhibitory activity.  Therefore, it is of significance to model this alteration for keeping  the sustainable mitigation strategies updated. (Please Mohamed add a descriptive paragraph about the features that will be used in that trend and I will be further melt it with another descriptive criteria)

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