首页|University of Pisa Reports Findings in Machine Learning (Predicting Solvatochrom ism of Chromophores in Proteins through QM/MM and Machine Learning)
University of Pisa Reports Findings in Machine Learning (Predicting Solvatochrom ism of Chromophores in Proteins through QM/MM and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Pisa, Italy, by NewsRx correspondents, research stated, “Solvatochromism occurs in both homo geneous solvents and more complex biological environments, such as proteins. Whi le in both cases the solvatochromic effects report on the surroundings of the ch romophore, their interpretation in proteins becomes more complicated not only be cause of structural effects induced by the protein pocket but also because the p rotein environment is highly anisotropic.” Our news editors obtained a quote from the research from the University of Pisa, “This is particularly evident for highly conjugated and flexible molecules such as carotenoids, whose excitation energy is strongly dependent on both the geome try and the electrostatics of the environment. Here, we introduce a machine lear ning (ML) strategy trained on quantum mechanics/molecular mechanics calculations of geometrical and electrochromic contributions to carotenoids’ excitation ener gies. We employ this strategy to compare solvatochromism in protein and solvent environments.”
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