MODELING HYDROPHOBIC AND HYDROPHILIC INTERACTIONS

复杂液体和生物系统的计算机建模是一个 生物化学中的重要工具。 随着现代社会的日益强大， 计算机使设计新药和新的仿生药物成为可能， 材料，并获得分子识别的理解， 突变对蛋白质折叠的影响。其中一个主要目的是 建议是发明，扩展和应用新方法， 加速的构象状态的刺激和采样 生物分子系统 我们的目标是进一步发展在此期间发明的方法， 最后一个资助期，用于处理具有多个时间尺度的系统， 作为我们的可逆参考系传播算法。 蒙特卡罗 和分子动力学方法的采样构象状态的 生物分子通常本质上是准遍历的。 这意味着 从一种稳定的构象开始，不是所有其他构象都可以 在一个实际的时间尺度上。 我们的目标是制定方法， 蛋白质系统和其他系统中的构象空间采样 以粗糙的能源景观为特征，并应用这些新方法， 涉及肽与酶结合的重要问题， 到肽的构象转变。 我们的目标是开发下一代可极化力场， 这是合理药物设计的主要障碍。约束力预测 能量取决于力场的质量。 现有 力场并不能解释原子电荷的已知变化， 肽经历构象变化。 这种影响需要一个 化学上精确的极化力场， 特定的氢键能。 在上一次赠款期间 在此期间，我们引入了一个简单的力场， 电负性均衡，在 预测水、NMA和丙氨酸二肽的性质。 我们有 表明该模型正确地解释了许多三体能量， 不同种类的三聚体（例如丙氨酸二肽和水的簇 分子）。 这项建议的主要目标之一是设计 下一代可极化的力场， 结合自由能计算的化学准确性， 使用新的采样方法在模拟中正确实施 上面讨论过。 本文的研究也将提供新的方法和算法 作为下一代力场用于生物模拟。 这些方法将用于研究环孢菌素A与 亲环蛋白和HIV-1蛋白酶的构象转变。

Computer modeling of complex liquids and biological systems is an important tool in biochemistry. With the increasing power of modern computers it is becoming possible to design new drugS and new biomimetic materials, and to gain understanding of molecular recognition, and the effects of mutationS on protein folding. One of the major aims of this proposal is the invention, extension and application of new methods to accelerate the stimulation and sampling of conformational states of biomolecular systems. We aim to further develop methods invented during the last grant period to treat systems with multiple time scales such as our reversible reference system propagator algorithms. Monte Carlo and molecular dynamics methods for sampling conformational states of biomolecules are often inherently quasi-ergodic. This means that starting in one stable conformation, not all other conformations can be reached on a practical time scale. We aim to devise methods for sampling conformation space in protein systems and other systems characterized by rough energy landscapes, and to apply these new methods to important problems involving the binding of peptides to enzymes and to conformational transitions of peptides. We aim to develop next generation polarizable force fields in order to deal a major impediment to rational drug design. Predictions of binding energies are dependent on the quality of the force field. Existing force fields do not account for known changes in atomic charges when a peptide undergoes a conformation change. Such effects require a chemically accurate polarizable force field that can correctly account for specific hydrogen bonding energies. During the preceding grant period we introduced a simple force field based on the principle of electronegativity equalization which has had remarkable success in predicting properties of water, NMA and analine dipeptide. We have shown that this model correctly accounts for three-body energies of many different kinds of trimers (eg clusters of analine dipeptide and water molecules). One of the major objectives of this proposal is to devise next generation polarizable force fields for peptides capable of giving chemical accuracy in the calculation of binding free energies when properly implemented in simulations using the new sampling methods discussed above. The proposed research will provide new methods and algorithms as well as a next generation force field for use in biological simulations. These methods will be used to study the binding of cyclosporin A to cyclophilin and the conformational transitions in HIV-1 protease.