A molecular dynamics investigation of chiral discrimination complexes as chiral stationary-phase models: Methyl N-(2-naphthyl)alaninate with N-(3,5-dinitrobenzoyl)leucine n-propylamide

Molecular dynamics simulations were performed on complexes of (S)-methyl N-(2-naphthyl)alaninate (NAP) with the enantiomers of N-(3,5-dinitrobenzoyl)leucine n-propylamide (DNB), which are used as models for chiral stationary-phase systems developed by Pirkle and co-workers. These studies were undertaken to qualitatively examine (pictorially) the role of entropic effects in these systems. The results of the dynamics calculations were used to refine the search for low-energy conformers. The structures were refined by the use of BioDesign's molecular mechanics method implemented in Biograf. The results of the structural refinements support our previous observation that the SR complex can achieve the same three primary interactions which are observed in the SS structure (i.e., two intermolecular hydrogen bonds and pi stacking) without a significant increase in energy. In addition, these primary interactions are conserved during molecular dynamics simulations with the occurrence of conformations which differ only in the rotational states of the alkyl side chains and ester group (which bears two potential hydrogen bond acceptors utilized in both the homo- and heterochiral complexes). The major difference in the two complexes is the relative position of the sec-butyl group and hydrogen atom on DNB's chiral center, both of which are outside the primary interaction region. All other local minima which have different relative pi orientations (“front–back,” “back–back,” and “back–front” as defined herein) are not sufficiently populated to make more than a negligible contribution to the statistical (time- or energy-averaged) analysis of the (SS)- and (SR)-NAP–DNB complexes. Thus the entropic effects observed in this study (e.g., alkyl side chain or ester group rotations) do not show evidence of qualitative differential effects on the maintenance of the same three primary interactions by both the homo- and heterochiral complexes. The reliability of the present study, which provides pictorial representations of the entropic effects, is not sufficient to determine whether the entropic effects observed herein are sufficient to achieve enantiomeric discrimination alone or in conjunction with other factors (e.g., conformational strain energy). Thus, all of the computational studies we have performed to date (i.e., our previous studies, which include strain energy and through-space field effects, and the present study, which includes entropic effects) show no evidence of any qualitative difference in the homo- and heterochiral complexes in terms of maintaining the same three “contact points”.     

Hydrophobic patches on the surfaces of protein structures

A survey of hydrophobic patches on the surface of 112 soluble, monomeric proteins is presented. The largest patch on each individual protein averages around 400 Ų but can range from 200 to 1,200 Ų. These areas are not correlated to the sizes of the proteins and only weakly to their apolar surface fraction. Ala, Lys, and Pro have dominating contributions to the apolar surface for smaller patches, while those of the hydrophobic amino acids become more important as the patch size Increases. The hydrophilic amino acids expose an approximately constant fraction of their apolar area independent of patch size; the hydrophobic residue types reach similar exposure only in the larger patches. Though the mobility of residues on the surface is generally higher, it decreases for hydrophilic residues with Increasing patch size. Several characteristics of hydrophobic patches catalogued here should prove useful in the design and engineering of proteins. © 1996 Wiley-Liss, Inc.     

人工智能与物理原理融合驱动的蛋白计算模拟技术

计算模拟驱动的生物元件、代谢网络乃至细胞系统的机理解析、定向改造和按需设计,可为解决不同层次的生物学问题提供新的技术方案,已成为生物制造的核心研究内容。在蛋白元件的计算模拟方面,基于物理原理的传统方法利用计算机软件和数学模型来模拟生物体系中蛋白行使功能的物理和化学过程,是理解复杂生物体系和指导实验设计的有力工具。随着生物系统模拟尺度的不断扩大,传统计算模拟技术面临计算精度和计算速度难以平衡的困境。近年来,生物数据量呈现爆炸式增长,使得构建高性能人工智能(artificial intelligence, AI)模型成为可能,为蛋白计算模拟带来了新思路和新契机,AI和物理原理融合驱动的蛋白计算模拟技术应运而生。本文对基于物理原理的传统蛋白计算模拟方法及其应用进行了详细介绍,并对融合AI和物理原理的最新计算模拟技术进行了梳理和讨论,进而提出在AI模型中结合严谨的化学知识和既定的物理原理,可有效提升数据处理和模式识别能力,从而提高计算效率和预测的准确性,使其具有更强的解释能力、通用性和稳健性。目前,AI与物理原理融合驱动的计算模拟技术已在生物催化领域展现出巨大的潜力和价值。本文聚焦于主流和先进的蛋白计算模拟技术,通过对这些技术的系统性回顾和前瞻性分析,梳理了蛋白质计算模拟技术的发展脉络,以推动其在酶催化机制解析、蛋白从头设计与理性改造等领域的应用,助力生物制造的发展。     

Effect of constituting amino acid residue numbers on molecularly imprinted chiral recognition sites

In the present study, the effect of constituting amino acid residue numbers of oligopeptide derivatives, which are candidate materials to construct molecular recognition sites, on chiral recognition ability was investigated. Chiral recognition sites were formed from oligopeptide derivatives, of which constituting amino acid residue numbers were three to six, by adopting an alternative molecular imprinting. It was made clear that the number four, in other words, the tetrapeptide derivative, is the best candidate material to form a chiral recognition site.     

Computational analysis and prediction for exons of PAC579 genomic sequence

To isolate the novel genes related to human hepatocellular carcinoma (HCC), we sequenced P1-derived artificial chromosome PAC579 (D17S926 locus) mapped in the minimum LOH (loss of heterozygosity) deletion region of chromosome 17p13.3 in HCC. Four novel genes mapped in this genomic sequence area were isolated and cloned by wet-lab experiments, and the exons of these genes were located. 0–60 kb of this genomic sequence including the genes of interest was scanned with five different computational exon prediction programs as well as four splice site recognition programs. After analyzing and comparing the computationally predicted results with the wet-lab experiment results, some potential exons were predicted in the genomic sequence by using these programs.     

Sequence dependence of amyloid fibril formation: insights from molecular dynamics simulations

The clarification of the physico-chemical determinants underlying amyloid deposition is critical for our understanding of misfolding diseases. With this purpose we have performed a systematic all-atom molecular dynamics (MD) study of a series of single point mutants of the de novo designed amyloidogenic peptide STVIIE. Sixteen different 50ns long simulations using explicit solvent have been carried out starting from four different conformations of a polymeric six-stranded beta-sheet. The simulations have provided evidence for the influence of a small number of site-specific hydrophobic interactions on the packing and stabilization of nascent aggregates, as well as the interplay between side-chain interactions and the net charge of the molecule on the strand arrangement of polymeric beta-sheets. This MD analysis has also shed light into the origin of the position dependence on mutation of beta-sheet polymerization that was found experimentally for this model system. Our results suggest that MD can be applied to detect critical positions for beta-sheet aggregation within a given amyloidogenic stretch. Studies similar to the one presented here can guide site-directed mutations or the design of drugs that specifically disrupt the key stabilizing interactions of beta-sheet aggregates.     

分子表面的计算机表示

提出了一种用于生成分子光滑表面的新算法.该算法从分布在一个包含整个分子表面的椭球上的三角网络开始,逐步收缩网络直到所有的三角形最佳贴近分子表面.所使用的收缩包络椭球的技术只要稍加修改就可用于蛋白质空腔的表示.     

Optimal atomic-resolution structures of prion AGAAAAGA amyloid fibrils

X-ray crystallography is a powerful tool to determine the protein 3D structure. However, it is time-consuming and expensive, and not all proteins can be successfully crystallized, particularly for membrane proteins. Although nuclear magnetic resonance (NMR) spectroscopy is indeed a very powerful tool in determining the 3D structures of membrane proteins, it is also time-consuming and costly. To the best of the authors' knowledge, there is little structural data available on the AGAAAAGA palindrome in the hydrophobic region (113-120) of prion proteins due to the noncrystalline and insoluble nature of the amyloid fibril, although many experimental studies have shown that this region has amyloid fibril forming properties and plays an important role in prion diseases. In view of this, the present study is devoted to address this problem from computational approaches such as global energy optimization, simulated annealing, and structural bioinformatics. The optimal atomic-resolution structures of prion AGAAAAGA amyloid fibils reported in this paper have a value to the scientific community in its drive to find treatments for prion diseases.