2016
DOI: 10.1007/s00894-016-3116-8
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PyCPR – a python-based implementation of the Conjugate Peak Refinement (CPR) algorithm for finding transition state structures

Abstract: Conjugate peak refinement (CPR) is a powerful and robust method to search transition states on a molecular potential energy surface. Nevertheless, the method was to the best of our knowledge so far only implemented in CHARMM. In this paper, we present PyCPR, a new Python-based implementation of the CPR algorithm within the pDynamo framework. We provide a detailed description of the theory underlying our implementation and discuss the different parts of the implementation. The method is applied to two different… Show more

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Cited by 10 publications
(9 citation statements)
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“…The RMS gradient threshold for all minimizations and surface scans was set to 0.02 kcal/(mol Å). The stable minimized intermediates and transition state estimates from surface scans were further refined using the PyCPR implementation of the conjugated peak refinement (CPR) method in order to obtain estimates of the transition states. In addition, PyCPR was also used to derive a path between two stable intermediates de novo, or a roughly optimized path obtained from the growing string method was used as an input.…”
Section: Methodsmentioning
confidence: 99%
“…The RMS gradient threshold for all minimizations and surface scans was set to 0.02 kcal/(mol Å). The stable minimized intermediates and transition state estimates from surface scans were further refined using the PyCPR implementation of the conjugated peak refinement (CPR) method in order to obtain estimates of the transition states. In addition, PyCPR was also used to derive a path between two stable intermediates de novo, or a roughly optimized path obtained from the growing string method was used as an input.…”
Section: Methodsmentioning
confidence: 99%
“…A first estimate for the reaction coordinate was obtained by potential energy surface scan (PES), followed by minimization. Promising pathways were then optimized by modified nudged elastic band (NEB) 40 and conjugate peak refinement (CPR) 41 with our own python implementation PyCPR 42 , using the BP86 functional as the QM method. Energetically feasible reaction paths were further refined using CPR and the B3LYP functional, which was also used for vibration frequency calculations.…”
Section: Methodsmentioning
confidence: 99%
“…Its trajectory was simulated using quantum-mechanical (QM)/MM calculations by starting from the reduced anionic FMNH – state. Using PyCPR 34 , we found a transition state at 16 kcal mol −1 in which the proton of FMNH − is at half distance between N1 of FMN and C6 of NCoA, and the HOMO is delocalized over both ring systems (Fig. 9).…”
Section: Resultsmentioning
confidence: 99%
“…The RMS gradient threshold of 0.04 kcal (mol Å) −1 was used for all minimizations and surface scans. For finding reliable transition states, we started from these estimates of the intermediates and transition state and applied the PyCPR 34 implementation of the conjugated peak refinement method 60 .…”
Section: Methodsmentioning
confidence: 99%