Toward the Accuracy and Speed of Protein Side-Chain Packing: A Systematic Study on Rotamer Libraries

Protein rotamers refer to the conformational isomers taken by the side-chains of amino acids to accommodate specific structural folding environments. Since accurate modeling of atomic interactions is difficult, rotamer information collected from experimentally solved protein structures is often used to guide side-chain packing in protein folding and sequence design studies. Many rotamer libraries have been built in the literature but there is little quantitative guidance on which libraries should be chosen for different structural modeling studies. Here, we performed a comparative study of six widely used rotamer libraries and systematically examined their suitability for protein folding and sequence design in four aspects: (1) side-chain match accuracy, (2) side-chain conformation prediction, (3) de novo protein sequence design, and (4) computational time cost. We demonstrated that, compared to the backbone-dependent rotamer libraries (BBDRLs), the backbone-independent rotamer libraries (BBIRLs) generated conformations that more closely matched the native conformations due to the larger number of rotamers in the local rotamer search spaces. However, more practically, using an optimized physical energy function incorporated into a simulated annealing Monte Carlo searching scheme, we showed that utilization of the BBDRLs could result in higher accuracies in side-chain prediction and higher sequence recapitulation rates in protein design experiments. Detailed data analyses showed that the major advantage of BBDRLs lies in the energy term derived from the rotamer probabilities that are associated with the individual backbone torsion angle subspaces. This term is important for distinguishing between amino acid identities as well as the rotamer conformations of an amino acid. Meanwhile, the backbone torsion angle subspace-specific rotamer search drastically speeds up the searching time, despite the significantly larger number of total rotamers in the BBDRLs. These results should provide important guidance for the development and selection of rotamer libraries for practical protein design and structure prediction studies

Use of an Improved Matching Algorithm to Select Scaffolds for Enzyme Design Based on a Complex Active Site Model - Fig 1

Schematic diagram of complex active site models for scaffolds: (A) 1c2t; (B) 1jcl. The catalytic residues are colored in blue, the residues that stabilize the catalytic residues are colored in pink, and the residues that stabilize the TS are colored in green.</p

Use of an Improved Matching Algorithm to Select Scaffolds for Enzyme Design Based on a Complex Active Site Model

<div><p>Active site preorganization helps native enzymes electrostatically stabilize the transition state better than the ground state for their primary substrates and achieve significant rate enhancement. In this report, we hypothesize that a complex active site model for active site preorganization modeling should help to create preorganized active site design and afford higher starting activities towards target reactions. Our matching algorithm ProdaMatch was improved by invoking effective pruning strategies and the native active sites for ten scaffolds in a benchmark test set were reproduced. The root-mean squared deviations between the matched transition states and those in the crystal structures were < 1.0 Å for the ten scaffolds, and the repacking calculation results showed that 91% of the hydrogen bonds within the active sites are recovered, indicating that the active sites can be preorganized based on the predicted positions of transition states. The application of the complex active site model for <i>de novo</i> enzyme design was evaluated by scaffold selection using a classic catalytic triad motif for the hydrolysis of <i>p</i>-nitrophenyl acetate. Eighty scaffolds were identified from a scaffold library with 1,491 proteins and four scaffolds were native esterase. Furthermore, enzyme design for complicated substrates was investigated for the hydrolysis of cephalexin using scaffold selection based on two different catalytic motifs. Only three scaffolds were identified from the scaffold library by virtue of the classic catalytic triad-based motif. In contrast, 40 scaffolds were identified using a more flexible, but still preorganized catalytic motif, where one scaffold corresponded to the α-amino acid ester hydrolase that catalyzes the hydrolysis and synthesis of cephalexin. Thus, the complex active site modeling approach for <i>de novo</i> enzyme design with the aid of the improved ProdaMatch program is a promising approach for the creation of active sites with high catalytic efficiencies towards target reactions.</p></div

Side chain repacking results for seven scaffolds.

<p>Side chain repacking results for seven scaffolds.</p

Superposition of native and predicted active sites for hydrolysis of PNPA on scaffolds.

(A) 1f6w; (B) 1jkm; (C) 1qe3; (D) 3m83. The transition states are shown in ball and stick model and colored in pink. The active site residues are shown in stick model. Atoms O, N, and C in crystal structures are colored in red, teal, and gray, respectively. Matched residues are colored in red. The hydrogen bonds in crystal structures are shown in dotted green lines, and the predicted hydrogen bonds are shown in dotted pink lines. The distances between hydrogen bonding donors and acceptors are shown in Å and labeled besides the dotted lines.</p

Complex active site models for PNPA and cephalexin based on different catalytic motifs.

<p>(A) Classic catalytic triad motif for hydrolysis of PNPA; (B) Classic catalytic triad motif for hydrolysis of cephalexin; (C) Flexible catalytic triad motif for hydrolysis of cephalexin.</p

Selected scaffolds by ProdaMatch for hydrolytic reactions of PNPA and cephalexin using catalytic triad based motifs.

<p>Selected scaffolds by ProdaMatch for hydrolytic reactions of PNPA and cephalexin using catalytic triad based motifs.</p

Reaction schemes of hydrolysis of PNPA and cephalexin.

<p>PNPA: <i>p</i>-nitrophenyl acetate; 7-ADCA: 7-amino desacetoxycephalosporanic acid.</p

Recapitulation of native active sites by ProdaMatch for ten scaffolds.

<p>Recapitulation of native active sites by ProdaMatch for ten scaffolds.</p

Matching results and active site residue sidechain repacking results in scaffold 1mpx.

<p>(A) Superposition of native and matched active sites for hydrolysis of cephalexin on scaffold 1mpx. (B) Conformations of repacked residues based on matched cephalexin on scaffold 1mpx. The transition states are shown in ball and stick model and colored in pink. The active site residues are shown in stick model. Atoms O, N, and C in crystal structures are colored in red, teal, and gray, respectively. Matched residues are colored in red. The hydrogen bonds in crystal structures are shown in dotted green lines, and the predicted hydrogen bonds are shown in dotted pink lines. The distances between hydrogen bonding donors and acceptors are shown in Å and labeled besides the dotted lines.</p