Heuristic energy landscape paving for protein folding problem in the three-dimensional HP lattice model

2012 ◽  
Vol 38 ◽  
pp. 17-26 ◽  
Author(s):  
Jingfa Liu ◽  
Gang Li ◽  
Jun Yu ◽  
Yonglei Yao
2021 ◽  
Author(s):  
Klara Markova ◽  
Antonin Kunka ◽  
Klaudia Chmelova ◽  
Martin Havlasek ◽  
Petra Babkova ◽  
...  

<p>The functionality of a protein depends on its unique three-dimensional structure, which is a result of the folding process when the nascent polypeptide follows a funnel-like energy landscape to reach a global energy minimum. Computer-encoded algorithms are increasingly employed to stabilize native proteins for use in research and biotechnology applications. Here, we reveal a unique example where the computational stabilization of a monomeric α/β-hydrolase enzyme (<i>T</i><sub>m</sub> = 73.5°C; Δ<i>T</i><sub>m</sub> > 23°C) affected the protein folding energy landscape. Introduction of eleven single-point stabilizing mutations based on force field calculations and evolutionary analysis yielded catalytically active domain-swapped intermediates trapped in local energy minima. Crystallographic structures revealed that these stabilizing mutations target cryptic hinge regions and newly introduced secondary interfaces, where they make extensive non-covalent interactions between the intertwined misfolded protomers. The existence of domain-swapped dimers in a solution is further confirmed experimentally by data obtained from SAXS and crosslinking mass spectrometry. Unfolding experiments showed that the domain-swapped dimers can be irreversibly converted into native-like monomers, suggesting that the domain-swapping occurs exclusively <i>in vivo</i>. Our findings uncovered hidden protein-folding consequences of computational protein design, which need to be taken into account when applying a rational stabilization to proteins of biological and pharmaceutical interest.</p>


2021 ◽  
Author(s):  
Klara Markova ◽  
Antonin Kunka ◽  
Klaudia Chmelova ◽  
Martin Havlasek ◽  
Petra Babkova ◽  
...  

<p>The functionality of a protein depends on its unique three-dimensional structure, which is a result of the folding process when the nascent polypeptide follows a funnel-like energy landscape to reach a global energy minimum. Computer-encoded algorithms are increasingly employed to stabilize native proteins for use in research and biotechnology applications. Here, we reveal a unique example where the computational stabilization of a monomeric α/β-hydrolase enzyme (<i>T</i><sub>m</sub> = 73.5°C; Δ<i>T</i><sub>m</sub> > 23°C) affected the protein folding energy landscape. Introduction of eleven single-point stabilizing mutations based on force field calculations and evolutionary analysis yielded catalytically active domain-swapped intermediates trapped in local energy minima. Crystallographic structures revealed that these stabilizing mutations target cryptic hinge regions and newly introduced secondary interfaces, where they make extensive non-covalent interactions between the intertwined misfolded protomers. The existence of domain-swapped dimers in a solution is further confirmed experimentally by data obtained from SAXS and crosslinking mass spectrometry. Unfolding experiments showed that the domain-swapped dimers can be irreversibly converted into native-like monomers, suggesting that the domain-swapping occurs exclusively <i>in vivo</i>. Our findings uncovered hidden protein-folding consequences of computational protein design, which need to be taken into account when applying a rational stabilization to proteins of biological and pharmaceutical interest.</p>


2013 ◽  
Vol 88 (5) ◽  
Author(s):  
Jingfa Liu ◽  
Beibei Song ◽  
Zhaoxia Liu ◽  
Weibo Huang ◽  
Yuanyuan Sun ◽  
...  

2006 ◽  
Vol 05 (03) ◽  
pp. 587-594 ◽  
Author(s):  
JINGFA LIU ◽  
WENQI HUANG

We studied two three-dimensional off-lattice protein models with two species of monomers, hydrophobic and hydrophilic. Low energy configurations in both models were optimized using the energy landscape paving (ELP) method and subsequent gradient descent. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. For all sequences with lengths 13 ≤ n ≤ 55, the algorithm finds states with lower energy than previously proposed putative ground states.


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