scholarly journals An Algorithm for Computing Side Chain Conformational Variations of a Protein Tunnel/Channel

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2459
Author(s):  
Udeok Seo ◽  
Ku-Jin Kim ◽  
Beom Kang
Keyword(s):  
Amino Acids ◽  
Maximum Size ◽  
Protein Molecule ◽  
Divide And Conquer ◽  
Side Chain ◽  
Conformational Variations ◽  
Novel Method ◽  
Pass Through ◽  
Chain Conformations ◽  
Local Side

In this paper, a novel method to compute side chain conformational variations for a protein molecule tunnel (or channel) is proposed. From the conformational variations, we compute the flexibly deformed shapes of the initial tunnel, and present a way to compute the maximum size of the ligand that can pass through the deformed tunnel. By using the two types of graphs corresponding to amino acids and their side chain rotamers, the suggested algorithm classifies amino acids and rotamers which possibly have collisions. Based on the divide and conquer technique, local side chain conformations are computed first, and then a global conformation is generated by combining them. With the exception of certain cases, experimental results show that the algorithm finds up to 327,680 valid side chain conformations from 128~1233 conformation candidates within three seconds.

BIOSYNTHESIS OF THE PHENYLPROPANOID MOIETY OF CHLORAMPHENICOL

1964 ◽  
Vol 10 (5) ◽  
pp. 705-716 ◽  
Author(s):  
L. C. Vining ◽  
D. W. S. Westlake
Keyword(s):  
Amino Acids ◽  
Shikimic Acid ◽  
Aromatic Amino Acids ◽  
Side Chain ◽  
Streptomyces Sp ◽  
Pass Through

Cultures of Streptomyces sp. 3022a were grown in the presence of C14-labelled substrates and incorporation of radioactivity into chloramphenicol measured. D-Glucose, labelled in carbons 1 or 2 or uniformly, was an efficient precursor of the p-nitrophenylserinol moiety and of the phenylpropanoid amino acids of the mycelium. The distribution of label in the ring and side-chain carbon atoms of p-nitrophenylserinol and cellular phenylalanine from experiments in which glucose-1-C14, glucose-2-C14, and glycine-2-C14 were fed provided evidence that the two phenylpropanoid systems had a common biosynthetic origin. The results were also consistent with their formation via the shikimic acid – prephenic acid route. Uniformly C14-labelled shikimic acid, though poorly utilized by this organism, was incorporated selectively into both the aromatic portion of chloramphenicol and the aromatic amino acids in the mycelium. L-Phenylalanine-U-C14, L-phenylalanine-carboxyl-C14, L-tyrosine-carboxyl-C14, DL-p-hydroxyphenylserine-2-C14, and acetate-2-C14 were poor precursors of the p-nitrophenylserinol moiety. Since phenylalanine and tyrosine were incorporated into the mycelium the biosynthetic route to the phenylpropanoid portion of chloramphenicol evidently does not pass through either of these amino acids but branches at an earlier step.

scholarly journals DLPacker: Deep Learning for Prediction of Amino Acid Side Chain Conformations in Proteins

2021 ◽  
Author(s):  
Mikita Misiura ◽  
Raghav Shroff ◽  
Ross Thyer ◽  
Anatoly Kolomeisky
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Design ◽  
Structure Prediction ◽  
Deep Neural Networks ◽  
Side Chain ◽  
Amino Acid Side Chain ◽  
Image Transformation ◽  
Hydrophobic Amino Acids ◽  
Chain Conformations

Prediction of side chain conformations of amino acids in proteins (also termed 'packing') is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have been developed but more accurate ones are still needed. Machine learning (ML) methods have recently become a powerful tool for solving various problems in diverse areas of science, including structural biology. In this work we evaluate the potential of Deep Neural Networks (DNNs) for prediction of amino acid side chain conformations. We formulate the problem as image-to-image transformation and train a U-net style DNN to solve the problem. We show that our method outperforms other physics-based methods by a significant margin: reconstruction RMSDs for most amino acids are about 20% smaller compared to SCWRL4 and Rosetta Packer with RMSDs for bulky hydrophobic amino acids Phe, Tyr and Trp being up to 50% smaller.

A phase transition from monoclinicC2 withZ′ = 1 to triclinicP1 withZ′ = 4 for the quasiracemateL-2-aminobutyric acid–D-methionine (1/1)

2016 ◽  
Vol 72 (7) ◽  
pp. 536-543 ◽  
Author(s):  
Carl Henrik Görbitz ◽  
David S. Wragg ◽  
Ingrid Marie Bergh Bakke ◽  
Christian Fleischer ◽  
Gaute Grønnevik ◽  
...  
Keyword(s):  
Phase Transition ◽  
Amino Acids ◽  
Room Temperature ◽  
Aminobutyric Acid ◽  
Side Chain ◽  
Side Chains ◽  
Significant Difference ◽  
Hydrophobic Amino Acids ◽  
Chain Conformations ◽  
Triclinic Form

Racemates of hydrophobic amino acids with linear side chains are known to undergo a unique series of solid-state phase transitions that involve sliding of molecular bilayers upon heating or cooling. Recently, this behaviour was shown to extend also to quasiracemates of two different amino acids with opposite handedness [Görbitz & Karen (2015).J. Phys. Chem. B,119, 4975–4984]. Previous investigations are here extended to an L-2-aminobutyric acid–D-methionine (1/1) co-crystal, C4H9NO2·C5H11NO2S. The significant difference in size between the –CH2CH3and –CH2CH2SCH3side chains leads to extensive disorder at room temperature, which is essentially resolved after a phase transition at 229 K to an unprecedented triclinic form where all four D-methionine molecules in the asymmetric unit have different side-chain conformations and all three side-chain rotamers are used for the four partner L-2-aminobutyric acid molecules.

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