A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones  to build Markov State Models  . If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM  in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it shown to correctly identify the known metastable states in the dihedral angle space of the molecule without a priori information about these states. It is also applied to analyze the folding landscape of the Beta3s min-protein , where it is shown to identify the folded basin as a connecting hub between a high entropy helix-rich region  and a beta-rich kinetic trap region .
A method is proposed to identify target states that optimize a metastability index amongst a set of trial states and use these target states as milestones (or core sets) to build Markov State Models (MSMs) . If the optimized metastability index is small, this automatically guarantees the accuracy of the MSM , in the sense that the transitions between the target milestones is indeed approximately Markovian. The method is simple to implement and use, it does not require that the dynamics on the trial milestones be Markovian, and it also offers the possibility to partition the system's state-space by assigning every trial milestone to the target milestones it is most likely to visit next and to identify transition state regions. Here the method is tested on the Gly-Ala-Gly peptide, where it shown to correctly identify the expected metastable states in the dihedral angle space of the molecule without a~priori information about these states. It is also applied to analyze the folding landscape of the Beta3s mini-protein , where it is shown to identify the folded basin as a connecting hub between an helix-rich region , which is entropically stabilized, and a beta-rich region, which is energetically stabilized and acts as a kinetic trap .
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(or core sets)
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(MSMs)
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,
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known
expected
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a priori
a~priori
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min-protein
mini-protein
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a high entropy
an
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, which is entropically stabilized,
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kinetic trap region
region, which is energetically stabilized and acts as a kinetic trap