Evaluation of atomic level mean force potentials via inverse folding and inverse refinement of protein structures: Atomic burial position and pairwise non-bonded interactions
Evaluation of atomic level mean force potentials via inverse folding and inverse refinement of protein structures: Atomic burial position and pairwise non-bonded interactions
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DOI：
10.1093/protein/9.8.637
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发表时间：
1996-08-01
期刊：
影响因子：
--
通讯作者：
Skolnick, J
中科院分区：
文献类型：
--
作者：
DeBolt, SE;Skolnick, J
基于原子水平知识，提出了两个平均力相互作用势（KBP），一个中心对称掩埋位置项和一个长程成对项，并通过比较三种结构无关蛋白质的多种构型进行了测试，发现它们成功地（i）在反折叠测试中区分天然状态蛋白质和严重错误折叠的结构，（ii）使用KBP能量/r.m.s.d.相关性，从逐渐不像本地的通过分子动力学采样产生的（紧凑和扩张的）结构，在逆细化测试中提供从部分未折叠结构向近天然状态倾斜的能量梯度，（iii）通过对抗真空中分子机械势的局部最小值来平滑扩张的非天然结构区域中的总体势能表面，以及（iv）在模拟温度淬灭研究期间用作局部最小值检测器，这些原子KBP以比基于残基的成对相互作用势或基于原子接触体积占有的有效溶剂化势更大的总体灵敏度区分天然结构和非天然结构，这里提出的KBP是立即有用的工具，用于选择“良好的细化候选人”从任意收集的蛋白质配置，并可能发挥作用，在动态计算蛋白质细化。
Two atomic level knowledge-based mean force interaction potentials (KBPs), a centrosymmetric burial position term and a long-range pairwise term, were developed, These were tested by comparing multiple configurations of three structurally unrelated proteins and were found successfully to (i) discriminate native state proteins from grossly misfolded structures in inverse folding tests, (ii) rank identify, using the KBP energy/r.m.s.d. correlation, native from progressively less native-like (compact and dilated) structures generated via molecular dynamics sampling, providing an energy gradient sloping from partially unfolded structures towards near-native states in inverse refinement tests, (iii) smooth the overall potential energy surface in the region of dilated non-native structures by countering local minima of the in vacuo molecular mechanical potential and (iv) serve as a local minimum detector during simulated temperature quenching studies, These atomic KBPs discriminated native from non-native structures with greater overall sensitivity than did either a residue-based pairwise interaction potential or an effective solvation potential based on atomic contact volume occupancy, The KBPs presented here are immediately useful as a tool for selecting 'good refinement candidates' from an arbitrary collection of protein configurations and may play a role in dynamic computational protein refinement.