首页|Department of Chemical Sciences Reports Findings in Machine Learning (A Mode Evo lution Metric to Extract Reaction Coordinates for Biomolecular Conformational Tr ansitions)
Department of Chemical Sciences Reports Findings in Machine Learning (A Mode Evo lution Metric to Extract Reaction Coordinates for Biomolecular Conformational Tr ansitions)
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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 out of Mumbai, India, by News Rx editors, research stated, “The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, d imensionality reduction approaches and machine learning (ML) schemes are employe d to obtain CVs from molecular dynamics (MD)/Monte Carlo (MC) trajectories or st ructural databanks for biomolecules.” Our news journalists obtained a quote from the research from the Department of C hemical Sciences, “However, minimum sampling conditions to generate reliable CVs that accurately describe the underlying energy landscape remain unclear. Here, we address this issue by developing a ode volution Metric (MeM) to extract CVs t hat can pinpoint new states and describe local transitions in the vicinity of a reference minimum from nonequilibrated MD/MC trajectories. We present a general mathematical formulation of MeM for both statistical dimensionality reduction an d machine learning approaches. Application of MeM to MC trajectories of model po tential energy landscapes and MD trajectories of solvated alanine dipeptide reve als that the principal components which locate new states in the vicinity of a r eference minimum emerge well before the trajectories locally equilibrate between the associated states. Finally, we demonstrate a possible application of MeM in designing efficient biased sampling schemes to construct accurate energy landsc ape slices that link transitions between states.”
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