Simulating Protein Structures, Complexes, And Dynamics

模拟蛋白质结构、复合物和动力学

• 批准号: 10255220
• 负责人: PETER J STEINBACH
• 金额: $ 81.3万
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10255220
• 关键词: ARRB2; Acids; Address; Affinity; Agonist; Alleles; Amino Acids; Antibodies; Antidiabetic Drugs; Applied Research; Area; Attention; Basic Science; Behavior; Binding; Binding Proteins; Biological; Brain imaging; CNR1 gene; Cells; Chemicals; Cholestasis; Clinical Trials; Collaborations; Complex; Computer Analysis; Computer Models; Computer Simulation; Computer software; Computing Methodologies; Crowding; Cyclic Peptides; Data; Development; Disease; Drug Delivery Systems; Eczema; Engineering; Environment; Experimental Models; Florida; Fluorine; Fragile X Syndrome; GTP-Binding Proteins; Geometry; Goals; Grant; Health; Hepatic; Heterogeneity; Homology Modeling; Hormonal; Human; Hydrocarbons; Image; Ions; Isomerism; Kinetics; Label; Lanthanoid Series Elements; Lead; Legal patent; Ligands; Magnetic Resonance Imaging; Male Contraceptive Agents; Manuscripts; Mass Spectrum Analysis; Mechanics; Membrane Proteins; Methodology; Methods; Modeling; Molecular; Molecular Chaperones; Molecular Conformation; Molecular Structure; Multiprotein Complexes; Mus; Mutation; Nanostructures; National Institute of Diabetes and Digestive and Kidney Diseases; Neuropathy; Obesity; Opioid; Opioid Analgesics; Outcome; Paper; Patients; Pattern Recognition; Peptides; Photons; Physiological; Play; Positron-Emission Tomography; Preparation; Process; Property; Proteins; Pruritus; Psoriasis; Publishing; Quantum Mechanics; RNA; RNA Helicase; Reaction; Regulation; Role; Salts; Scleroderma; Series; Serum; Speed; Structural Biologist; Structural Models; Structure; Structure-Activity Relationship; System; Techniques; Testing; Thermodynamics; Time; Translational Research; Universities; Uremia; Ventilatory Depression; Work; World Health Organization; addiction; artificial neural network; base; biological systems; chemical reaction; chemical substitution; chronic pain; crosslink; delta opioid receptor; design; enzyme mechanism; experimental study; fluoroform; gonadotropin inhibitor; improved; inhibitor/antagonist; insight; interest; macromolecule; molecular dynamics; molecular mechanics; molecular modeling; mouse model; nanoGold; nanoparticle; nanosecond; non-opioid analgesic; novel; peptide structure; pharmacophore; precision medicine; prevent; protein function; protein structure; quantum; quantum chemistry; receptor; respiratory; side effect; simulation; small molecule; stem cell model; structural biology; tool

We develop, implement, and apply computational methods to study the structure, dynamics, and functional mechanisms of biomolecules. Over the last year, we have worked in three main areas: i) refinement of a continuum model to represent molecular interactions in solutions, the predictive power of which was demonstrated in the prediction of peptide structures from primary sequences, ii) development of a self-guided multiscale method for modeling many-protein systems in realistic crowded environments, and iii) use of ab-initio quantum chemistry to investigate the geometry and energetics of bioactive compounds. This quantum mechanical approach is particularly useful in elucidating the transition states of chemical reactions that cannot be probed experimentally. The mechanistic understanding provides a firm structural/theoretical basis for controlling the outcome of chemical reactions, e.g., the ratio of possible products (two patents granted). We have begun to develop and apply pattern-recognition techniques, including artificial neural networks (ANN), to identify non-obvious behaviors in biological systems. We are using ANN in two projects with potential impact in translational science: to predict the physiological effects of opioid analgesics from interactions at the receptor level, and to reverse-engineer nanostructures that interact with membranes and proteins in specific ways. This approach has implications in basic and applied research, including precision medicine. Opioid analgesics used to treat chronic pain lead to addiction and have other serious side effects, including potential respiratory arrest. We are carrying out dynamics simulations to study the roles of agonists and antagonists of mu and delta opioid receptors in activating G-protein. We are combining computational modeling techniques developed for small molecules and for macromolecules to propose chemical substitutions that may lead to a deeper understanding of the effects of both opioid-like and non-opioid compounds. We are focusing our attention on a new series of compounds recently found to have G-protein biased properties. These properties are emerging as essential for avoiding side effects, such as respiratory depression. Using computer simulations, we have identified the residues that potentiate the beta-arrestin-2 bias to the cannabinoid receptor 1 (CB1R) antagonists. We have also provided a molecular rationale to design and synthesize biased antagonists that can have a better anti-diabetic and anti-obesity efficacy. A manuscript is in preparation. We have studied gold nanoparticles in serum and in cell media to optimize strategies for drug delivery and imaging. We have used a recently developed multiscaling technique to realistically represent biological media, an approach that speeds up both Monte Carlo and molecular dynamics simulations of multiprotein-multiparticle solutions. With this method, we were able to carry out systematic studies of ultrasmall nanostructures of different designs and have demonstrated that they can be rationally designed to interact with biological matter in specific ways. We are currently using the same approach to predict binding modes, affinities, and kinetics in nanoparticle-protein binding, and to assess whether protein function can be modulated. We have carried out quantum chemical calculations to elucidate the fluorination mechanism of diaryliodonium salts at the atomic level. An understanding of this process is essential in the development of novel 18F-labeled PET probes for brain imaging. Ongoing studies of fluorination include the elucidation of the hydrocarbon fluorination catalyzed by CoF3 as well as the trifluoromethylation mechanism of aryliodonium salts with CuCF3. These studies will provide insight into the efficient synthesis of 11C-labeled fluoroform, e.g. (11C)CHF3, for PET imaging. Male contraceptives have been pursued worldwide, but all clinical trials by the World Health Organization have failed at different stages because of long-term health concerns due to their hormonal basis. This project is centered on finding inhibitors of the Gonadotropin Regulated Testicular RNA Helicase (GRTH/DDX25), a novel protein discovered by our IRP collaborators, which may lead to the development of a non-hormonal contraceptive. Using a variety of molecular modeling techniques, we have developed a reliable model of DDX25 that we have used to develop a series of pharmacophores. We are now using the most promising ones to design a macro-cyclic peptide inhibitor of DDX25 activity. We have synthesized and tested two specific peptides that display the beneficial properties predicted computationally. We have developed a collaboration with structural biologists (NMR Center at Carnegie Mellon University) to characterize the peptide experimentally. This project is also the basis for new methodological developments for reverse-engineering of cyclic peptides. We are investigating the structure and energetics of polymethylated 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) ligand complexed with lanthanide ions. Quantum chemical calculations are being carried out to determine the structural requirements that modulate the thermochemical stability of one isomer over the other. These complexes find application in magnetic resonance imaging and protein-structure studies. We have modeled a major ternary complex that contains a protein recently discovered by one of our IRP collaborators and shown to be a key player in itch sensation associated with eczema, psoriasis, hepatic cholestasis, uremia, and some neuropathies. Using a battery of experimental and computer modeling tools, we were able to design an antibody to inhibit the protein and prevent itch in mice. We proposed a rather general experimental-modeling approach to find inhibitors of complexes with limited structural information based on cross-linking mass spectrometry (XL-MS). We are now applying the same technique to a series of chaperones/co-chaperones (multiprotein complexes and aggregates, where Hsp90 plays the central role) involved in the folding and regulation of protein function. We use known protein structures and homology modeling to interpret the structure-function effects of mutations, including those observed in patients. We are working with NIDDK to study protein-RNA interfaces using computational analyses and experimental verification. Also with NIDDK, we modeled the mouse MLH3 protein to help interpret the elimination of repeat expansions in a mouse stem cell model of the Fragile X-related disorders. In another study, we helped characterize HLA alleles and amino acid residues associated with scleroderma. We have expanded the capabilities of our MemExp software, which is used world-wide to recover distributions of effective lifetimes from kinetics data. The analysis of time-correlated single-photon counting experiments has been improved. With colleagues at Florida State University, we published a paper interpreting the nanosecond-timescale dynamics and conformational heterogeneity in human GCK regulation and disease. Version 6.0 of MemExp was made available.

我们开发、实施和应用计算方法来研究生物分子的结构、动力学和功能机制。在过去的一年里，我们在三个主要领域进行了工作：1)改进连续体模型来表示溶液中的分子相互作用，其预测能力在从初级序列预测肽结构中得到了证明；2)开发一种自我引导的多尺度方法来模拟现实拥挤环境中的多蛋白质系统；3)使用从头算量子化学来研究生物活性化合物的几何和能量学。这种量子力学方法在解释化学反应的过渡态时特别有用，而化学反应是不能用实验来探测的。机理的理解为控制化学反应的结果提供了坚实的结构/理论基础，例如，可能产物的比例（已授予两项专利）。我们已经开始开发和应用模式识别技术，包括人工神经网络（ANN），以识别生物系统中的非明显行为。我们正在两个对转化科学有潜在影响的项目中使用人工神经网络：从受体水平的相互作用来预测阿片类镇痛药的生理效应，以及以特定方式与膜和蛋白质相互作用的纳米结构的逆向工程。这种方法对基础研究和应用研究，包括精准医学都有影响。

项目成果

Computational Study of the Forces Driving Aggregation of Ultrasmall Nanoparticles in Biological Fluids.

• DOI: 10.1021/acsnano.7b00981
• 发表时间: 2017-04-25
• 期刊: ACS nano
• 影响因子: 17.1
• 作者: Hassan SA

Intramolecular disulfide bonds of the prolactin receptor short form are required for its inhibitory action on the function of the long form of the receptor.

催乳素受体短型的分子内二硫键是其对长型受体功能的抑制作用所必需的。

• DOI: 10.1128/mcb.01716-08
• 发表时间: 2009
• 期刊: Molecular and cellular biology
• 影响因子: 5.3
• 作者: Xie,Y-L;Hassan,SA;Qazi,AM;Tsai-Morris,CH;Dufau,ML
• 通讯作者: Dufau,ML

Filtering artifacts from lifetime distributions when maximizing entropy using a bootstrapped model.

• DOI: 10.1016/j.ab.2012.04.008
• 发表时间: 2012-08-01
• 期刊: Analytical biochemistry
• 影响因子: 2.9
• 作者: Steinbach PJ

Self-adaptive multiscaling algorithm for efficient simulations of many-protein systems in crowded conditions.

• DOI: 10.1039/c8cp05517c
• 发表时间: 2018-11-21
• 期刊: Physical chemistry chemical physics : PCCP
• 作者: Hassan SA

Binding kinetics of ultrasmall gold nanoparticles with proteins.

• DOI: 10.1039/c7nr06810g
• 发表时间: 2018-02-15
• 期刊: Nanoscale
• 影响因子: 6.7
• 作者: Lira AL ;Ferreira RS ;Torquato RJS ;Zhao H ;Oliva MLV ;Hassan SA ;Schuck P ;Sousa AA
• 通讯作者: Sousa AA