Matthew P Jacobson
University Of California San Francisco
Project start date: 2009-02-01
Project end date: 2013-01-31
Sponsored Links Excellgen http://Excellgen.com
UNDERSTANDING, PREDICTING, AND ENGINEERING MEMBRANE PERMEABILITY
Matthew P Jacobson, Associate Professor
University Of California San Francisco, 3333 California St., Ste 315, San Francisco, Ca 94143-0962
Grant 5R01GM086602-02 from National Institute Of General Medical Sciences
Abstract: The ability of small molecules to enter cells is a critical parameter in development of pharmaceutical agents and tools for chemical biology. Most synthetic compounds enter cells by passive diffusion across the membrane. The goal of this proposal is to increase our understanding of, and ability to predict, passive membrane permeation. The ultimate test of this understanding will be rationally modifying compounds to improve membrane permeation. The work proposed here builds on existing models of membrane permeation, but the model we are developing differs from most in practical use by being more directly based on an understanding of the physics of passive membrane permeation. As such, it is systematically improvable, and has broad applicability. We propose to 1. Implement and test a physics-based model for passive membrane permeability. A first generation of this model has been described in a series of papers by the PI, and has emphasized the role of conformational flexibility and the ability to form internal hydrogen bonds in promoting membrane permeation. We will extend this model to include other critical aspects of the physics, including entropic losses upon membrane insertion and the semi-ordered hydrophobic environment of the membrane interior, comparing to both literature data and new data generated in Aims 2 and 3. 2. Interrogate key aspects of membrane permeation using cyclic peptides, and use this knowledge to design highly permeable cyclic peptides. We propose to use cyclic peptides as a challenging model system for studying passive membrane permeation. The relative synthetic ease of creating cyclic peptides facilitates developing series of compounds that differ in well-defined ways, such as stereochemistry, rigidity, size, hydrophobicity, etc. As in our earlier work, computational predictions will always be made prior to experimental testing, and the results will probe specific aspects of the physics of membrane permeation. 3. Interrogate key aspects of membrane permeation using non-peptidic small molecules, and use this knowledge in practical efforts to optimize the chemical properties of protein inhibitors. One of the collaborative projects involves improving membrane permeability for inhibitors of parasite cysteine proteases, which have typically had poor bioavailability. A central element of this proposal is collaborations with chemists Scott Lokey (UCSC) and Adam Renslo (UCSF) to test and apply the computational models. Tight coupling between computational modeling and experimental testing is central to this proposal, allowing iterative improvement of our physical understanding of passive membrane permeability and computational methods that encapsulate that understanding. Success of this work will enable hypothesis-driven ("engineering") approaches to improving membrane permeability. One important property of drugs is their ability to enter cells, especially for drugs that are taken orally. This proposal is concerned with developing new computer programs that can predict the ability of compounds to enter cells, and experimental testing of these methods. Success of this work has the potential to reduce the time and cost of early-stage drug discovery, such as the proposed project to develop improved drug candidates for "sleeping sickness", a serious parasitic disease common in Africa
Keywords: Africa; African Sleeping Sickness; African Trypanosomiasis; Articulation; Bioavailability; Biologic Availability; Biological Availability; Biological Models; Biology; Cell Membrane Permeability; Cells; Chemicals; Collaborations; Computer Programs and Programming; Computer Simulation; Computerized Models; Computing Methodologies; Coupling; Cyclic Peptides; Cysteine Endopeptidases; Cysteine Protease; Cysteine Proteinases; Data; Development; Diffusion; Drugs; Elements; Encapsulated; Engineering; Engineerings; Environment; Generations; Goals; Hydrogen Bonding; Hydrophobicity; Joints; Knowledge; Lead; Literature; Mathematical Model Simulation; Mathematical Models and Simulations; Medication; Membrane; Methods; Model System; Modeling; Models, Biologic; Models, Computer; Muscle Rigidity; Paper; Parasites; Parasitic Diseases; Pb element; Permeability; Pharmaceutic Preparations; Pharmaceutical Agent; Pharmaceutical Preparations; Pharmaceuticals; Pharmacologic Substance; Pharmacological Substance; Physics; Physiologic Availability; Preparation; Property; Property, LOINC Axis 2; Proteins; Publications; Relative; Relative (related person); Rigidity; Rigidity, Muscular; Role; Scientific Publication; Series; Simulation, Computer based; Staging; Test Result; Testing; Thiol Protease; Time; Trypanosomiasis, African; Work; base; bioavailability of drug; chemical property; computational methodology; computational methods; computational modeling; computational models; computational simulation; computer based models; computer methods; computer program; computer programming; computerized modeling; computerized simulation; cost; design; designing; drug candidate; drug discovery; drug/agent; flexibility; gene product; heavy metal Pb; heavy metal lead; improved; in silico; inhibitor; inhibitor/antagonist; membrane model; membrane permeability; membrane structure; public health relevance; sleeping sickness; small molecule; social role; stereochemistry; success; tool; virtual simulation
Project start date: 2009-02-01
Project end date: 2013-01-31
Budget start date: 1-FEB-2010
Budget end date: 31-JAN-2011
PFA/PA: PA-07-070
5R01GM086602-02 (2010): $253227
Grants awarded to Matthew P Jacobson
PHYSICS-BASED REFINEMENT OF COMPARATIVE PROTEIN MODELS
Matthew P Jacobson
Department/ Educational Institution Type:
Grant 5R01GM081710-03 from National Institute Of General Medical Sciences
Abstract: We propose physics-based methods that will assist in comparative protein structure modeling. Although ab initio methods won´t soon replace comparative modeling, particularly for large proteins, multiple domains, or genome-wide studies, we believe that physics-based methods are now poised to play a big role in improving comparative models. By improving the efficiency of conformational sampling and the accuracy of atomistic energy functions, we propose ways to circumvent alignment problems where sequence identity is low, and to give atom-level refinements where sequence identity is high. Our aims are aligned with both comparative modeling goals identified in RFA-GM-07-003, "High Accuracy Protein Structure Modeling." (1) Better sampling using kinematics. To improve the modeling of concerted motions in constrained structures, like loops and helices, we will use analytical kinematics methods that we have recently developed, resembling those used in robotics of systems of linked rods. We will combine the kinematics with a powerful multiple temperature scheme (replica exchange) to further increase sampling efficiency. We will apply these methods primarily to homology models having good sequence alignments (typically >30% sequence identity). (2) Better sampling using "Zipping an Assembly" with bioinformatics restraints. The advance here is a new highly efficient protein-folding mechanism-based search method called zipping and assembly, which is recently CASP-tested. Two key features of this approach are that it should (a) tolerate sequence alignment errors, and (b) provide models for large insertions, which are not aligned to template residues. Our goal here is to help remote comparative modeling. (3) Better atomistic energy-based scoring functions. The end game in protein structure prediction requires scoring functions that are correct in detail, hence correct in the physics. We propose two ways to improve them. First, we will improve a key defect in implicit solvent models by including a better treatment of the first shell of water around the molecule. Second, we have previously developed a general approach to parameter optimization, called MOPED, which is applicable to complex nonlinear multi-parameter models. We will apply it to improving parameters, using the large datasets generated in aims 1 and 2. We will test our approaches in blind predictions including CASP. We will make our results freely available through modular source codes and executable programs
Keywords: Algorithms; Amber; base; Bio-Informatics; Bioinformatics; blind; clinical data repository; clinical data warehouse; Collaborations; comparative; Complex; Data Banks; Data Bases; data repository; Data Set; Databank, Electronic; Databanks; Database, Electronic; Databases; Dataset; Defect; Dill; Dill Weed; gene product; genome wide association scan; genome wide association studies; genome wide association study; genome-wide scan; genomewide association scan; genomewide association studies; genomewide association study; genomewide scan; Goals; GWAS; Homology Modeling; Hydrogen Oxide; improved; Investigators; Ions; kinematics; knowledge base; Link; Linux; Methods; Modeling; molecular dynamics; Molecular Dynamics Simulation; Motion; neglect; Physics; Play; programs; Programs (PT); Programs [Publication Type]; protein folding; protein structure; protein structure prediction; Proteins; Publishing; relational database; Research Personnel; Researchers; restraint; Robotics; Rod; rod cell; Rod Photoreceptors; Rods (Eye); Rods (Retina); Role; Route; Sampling; Scheme; Sequence Alignment; social role; Solvents; Source Code; Structure; System; System, LOINC Axis 4; Temperature; Testing; Water; whole genome association studies; whole genome association study
Project start date: 2007-08-01
Project end date: 2011-07-31
Budget start date: 1-AUG-2009
Budget end date: 31-JUL-2011
PFA/PA: RFA-GM-07-003
5R01GM081710-03 (2009): $289542
5R01GM081710-02 (2008): $289542
1R01GM081710-01 (2007): $302509
REFINEMENT AND RESCORING THE DOCKING RESULTS
Matthew P Jacobson, Associate Professor
University Of California San Francisco, 3333 California St., Ste 315, San Francisco, Ca 94143-0962
Abstract: This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We have developed a new methodlogy to refine and rescore the docking results. The docking programs use scoring function to determine the relative binding affinity of ligands and rank order them. These scoring functions are often approximate and empirical in nature. We believe that the large number of false positives seen in the docking results are due to the inadequacy in the docking scoring functions. We have developed a method based on all-atom force field with implicit solvation. Our method is quite robust and very fast. For instance it takes only 45 seconds to refine a ligand. We have applied the method to identify putative substrates for enolase superfamily enzymes and also identify inhibitors against E.coli DHFR receptor
Keywords: 2-Phospho-D-Glycerate Hydrolase; 2-Phospho-D-glycerate hydro-lyase; Affinity; Binding; Binding (Molecular Function); Biomedical Computing; CRISP; Computer Retrieval of Information on Scientific Projects Database; DHFR; DHFR gene; Docking; Enzymes; Funding; Grant; Imagery; Informatics; Institution; Investigators; Ligands; Methods; Molecular Interaction; NIH; National Institutes of Health; National Institutes of Health (U.S.); Nature; Phosphopyruvate Hydratase; Programs (PT); Programs [Publication Type]; Receptor Protein; Relative; Relative (related person); Research; Research Personnel; Research Resources; Researchers; Resources; Source; United States National Institutes of Health; Visualization; base; bio-computation; bio-computing; biocomputing; biomedical computation; enolase; inhibitor; inhibitor/antagonist; phosphoglycerate dehydratase; phosphoglycerate hydro lyase; programs; receptor
Project start date: 2009-07-01
Project end date: 2010-06-30
Budget start date: 1-JUL-2009
Budget end date: 30-JUN-2010
5P41RR001081-32_5725 (2009): $8911
MODULATING STRUCTURE AND DYNAMICS AT ALLOSTERIC SITES USING SMALL MOLECULES
Matthew P Jacobson, Associate Professor
University Of California San Francisco, 3333 California St., Ste 315, San Francisco, Ca 94143-0962
Abstract: This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Allosteric sites have shown great potential for selective inhibition of particular protein targets but limited exploration. Such sites are difficult to target with small molecules because they are highly flexible, and because binding may not be sufficient to cause the desired effect. I am developing a molecular dynamics analysis method to search for correlated motions to identify allosteric sites and allosteric networks of coupled residues. I am also developing an all-atoms, physics-based torsion-angle sampling molecular mechanics approach to predict bound geometries of cysteine-conjugating compounds and am studying the allosteric effects of these covalent compounds using molecular dynamics
Keywords: Allosteric Site; Binding; Binding (Molecular Function); Biomedical Computing; CRISP; Computer Retrieval of Information on Scientific Projects Database; Coupled; Cysteine; Funding; Grant; Half-Cystine; Imagery; Informatics; Institution; Investigators; L-Cysteine; Methods; Molecular Dynamics Simulation; Molecular Interaction; Motion; NIH; National Institutes of Health; National Institutes of Health (U.S.); Physics; Proteins; Research; Research Personnel; Research Resources; Researchers; Resources; Sampling; Site; Source; Structure; Torsion; Torsion (malposition); United States National Institutes of Health; Visualization; base; bio-computation; bio-computing; biocomputing; biomedical computation; flexibility; gene product; molecular dynamics; molecular mechanics; small molecule
Project start date: 2009-07-01
Project end date: 2010-06-30
Budget start date: 1-JUL-2009
Budget end date: 30-JUN-2010
5P41RR001081-32_5754 (2009): $8911
Matthew P Jacobson, Associate Professor
University Of California San Francisco, 3333 California St., Ste 315, San Francisco, Ca 94143-0962
Abstract: This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. An enormous number of proteins have been sequenced and their structure and function have not been correctly characterized. We use homology modeling, docking and molecular-mechanics generalized Born surface area (MM-GBSA) based method to calculate relative binding energy and rank metabolite ligands. These compounds are subsequently tested in the Gerlt´s lab at UIUC
Keywords: Area; Binding; Binding (Molecular Function); Biomedical Computing; CRISP; Computer Retrieval of Information on Scientific Projects Database; Docking; Funding; Grant; Homology Modeling; Imagery; Informatics; Institution; Investigators; Ligands; Methods; Molecular Interaction; NIH; National Institutes of Health; National Institutes of Health (U.S.); Relative; Relative (related person); Research; Research Personnel; Research Resources; Researchers; Resources; Source; Structure; Surface; Testing; United States National Institutes of Health; Visualization; base; bio-computation; bio-computing; biocomputing; biomedical computation; d-Numb; molecular mechanics; numb protein
Project start date: 2009-07-01
Project end date: 2010-06-30
Budget start date: 1-JUL-2009
Budget end date: 30-JUN-2010
5P41RR001081-32_5761 (2009): $8911
Understanding, Predicting, And Engineering Membrane Permeability
Matthew P Jacobson
Pharmaceutical Chemistryuniversity Of California San Francisco
Grant 1R01GM086602-01 from National Institute Of General Medical Sciences IRG: MSFD
Abstract: The ability of small molecules to enter cells is a critical parameter in development of pharmaceutical agents and tools for chemical biology. Most synthetic compounds enter cells by passive diffusion across the membrane. The goal of this proposal is to increase our understanding of, and ability to predict, passive membrane permeation. The ultimate test of this understanding will be rationally modifying compounds to improve membrane permeation. The work proposed here builds on existing models of membrane permeation, but the model we are developing differs from most in practical use by being more directly based on an understanding of the physics of passive membrane permeation. As such, it is systematically improvable, and has broad applicability. We propose to 1. Implement and test a physics-based model for passive membrane permeability. A first generation of this model has been described in a series of papers by the PI, and has emphasized the role of conformational flexibility and the ability to form internal hydrogen bonds in promoting membrane permeation. We will extend this model to include other critical aspects of the physics, including entropic losses upon membrane insertion and the semi-ordered hydrophobic environment of the membrane interior, comparing to both literature data and new data generated in Aims 2 and 3. 2. Interrogate key aspects of membrane permeation using cyclic peptides, and use this knowledge to design highly permeable cyclic peptides. We propose to use cyclic peptides as a challenging model system for studying passive membrane permeation. The relative synthetic ease of creating cyclic peptides facilitates developing series of compounds that differ in well-defined ways, such as stereochemistry, rigidity, size, hydrophobicity, etc. As in our earlier work, computational predictions will always be made prior to experimental testing, and the results will probe specific aspects of the physics of membrane permeation. 3. Interrogate key aspects of membrane permeation using non-peptidic small molecules, and use this knowledge in practical efforts to optimize the chemical properties of protein inhibitors. One of the collaborative projects involves improving membrane permeability for inhibitors of parasite cysteine proteases, which have typically had poor bioavailability. A central element of this proposal is collaborations with chemists Scott Lokey (UCSC) and Adam Renslo (UCSF) to test and apply the computational models. Tight coupling between computational modeling and experimental testing is central to this proposal, allowing iterative improvement of our physical understanding of passive membrane permeability and computational methods that encapsulate that understanding. Success of this work will enable hypothesis-driven ("engineering") approaches to improving membrane permeability. One important property of drugs is their ability to enter cells, especially for drugs that are taken orally. This proposal is concerned with developing new computer programs that can predict the ability of compounds to enter cells, and experimental testing of these methods. Success of this work has the potential to reduce the time and cost of early-stage drug discovery, such as the proposed project to develop improved drug candidates for "sleeping sickness", a serious parasitic disease common in Africa
Project start date: 2009-02-01
Project end date: 2013-01-31
Matthew P Jacobson, Associate Professor
University Of California San Francisco, 3333 California St., Ste 315, San Francisco, Ca 94143-0962
Abstract: PROJECT 5 - Net (PETERLIN AND ALBER. PROJECT LEADERS! Nef (negative factor) is a misnamed, accessory activator of HIV-1, HIV-2, and SIV that is essential for high-level viremia and progression to AIDS in infected patients. Nef is myristylated at its N-terminus and binds cholesterol via its C-terminal cholesterol recognition motif (CRM). These signals target Nef to lipid rafts (LRs) in cellular membranes. This project aims to characterize Nef interactions with partner proteins that are mobilized in two crucial processes¿host-cell activation and receptor endocytosis. These studies will test the hypotheses that much of the surface of Nef contacts host proteins, and these interactions not only bring together functional partners but also activate targets through allosteric conformational changes. The identification of surfaces of Nef that mediate multiple host interactions will provide new information about how to simultaneously target more than one Nef function with new Pharmaceuticals. Nef assembles a signalosome early in the viral life cycle that activates infected immune cells, stimulating viral replication. The signalosome consists of six proteins including the Nef scaffold. It is not known if Nef simply brings together the host components of the signalosome or also activates these factors through allosteric interactions. Nef also mediates remodeling of the host cell surface by promoting internalization of cellular receptors, such as CD4, MHC class I, and T cell antigen receptor. To mediate endocytosis, Nef bridges the receptors in ternary complexes with armadillo repeat (ARM-repeat) containing proteins such as adaptor protein (AP) complexes, ¿COP, and the catalytic subunit (V1H) of the vacuolar ATPase (V-ATPase). The mechanisms of these essential bridging functions are unknown and the cooperativity of Nef binding has not been characterized. Monomeric and dimeric structures of Nef have been solved by NMR and crystallography, but except for small complexes between the proline-rich sequence of Nef and SH3 domains, little information is available about Nef bound to host proteins
Keywords: AIDS; AIDS Virus; ARM Domain; Acquired Immune Deficiency; Acquired Immune Deficiency Syndrome; Acquired Immuno-Deficiency Syndrome; Acquired Immunodeficiency Syndrome; Adaptor Protein; Adaptor Signaling Protein; Armadillo Repeat; Armadillo/Beta-Catenin-Like Repeat; Beta-Catenin Binding Repeat; Beta-Catenin-Binding Domain; Beta-Catenin-Like Repeat; Binding; Binding (Molecular Function); C-terminal; CDC42; CDC42 gene; CDC42Hs; Catalytic Core; Catalytic Domain; Catalytic Region; Catalytic Site; Catalytic Subunit; Cell Communication and Signaling; Cell Signaling; Cell surface; Cells; Cellular Membrane; Cholest-5-en-3-ol (3beta)-; Cholesterol; Complex; Crystallographies; Crystallography; Cytoplasmic Domain; Cytoplasmic Tail; Endocytosis; G25K; Genes, Class I; Genes, MHC Class I; HIV-1; HIV-2; HIV-I; HIV-II; HIV1; HIV2; HTLV-IV; Host Factor; Host Factor Protein; Human T-Lymphotropic Virus Type IV; Human immunodeficiency virus 1; Human immunodeficiency virus 2; Immune; Immunodeficiency Virus Type 1, Human; Immunodeficiency Virus Type 2, Human; Immunologic Deficiency Syndrome, Acquired; Integration Host Factors; Intracellular Communication and Signaling; L-Proline; LAV-2; Life Cycle; Life Cycle Stages; Lipid Rafts, Cell Membrane; MHC Class I; MHC Class I Genes; MHC Receptor; Major Histocompatibility Complex Receptor; Mediating; Membrane Microdomains; Molecular Interaction; Patients; Pharmaceutical Agent; Pharmaceuticals; Pharmacologic Substance; Pharmacological Substance; Proline; Proteins; Reaction; Reading; Receptor Activation; Receptor Protein; Receptors, Antigen, T-Cell; SH3 Domains; SIV; SRC Homology Region 3 Domain; Signal Transduction; Signal Transduction Systems; Signaling; Simian Immunodeficiency Viruses; Sphingolipid Microdomains; Sphingolipid-Cholesterol Rafts; Structure; Surface; T-Cell Receptor; Testing; V-ATPase; V-type ATPase; Viral; Viremia; biological signal transduction; gene product; human T cell leukemia virus III; human T lymphotropic virus III; life course; lipid raft; protein complex; receptor; receptor mediated endocytosis; scaffold; scaffolding; vacuolar ATPase; vacuolar H+-ATPase; vacuolar membrane H(+)-ATPase; viraemia; viral sepsis; virusemia
Budget start date: 1-AUG-2010
Budget end date: 31-JUL-2011
5P50GM082250-04_0003 (2010): $71048
5P50GM082250-03_0003 (2009): $73250
NEW PHYSICS-BASED APPROACHES TO PREDICTIVE PROTEIN MODELING
Matthew P Jacobson
University Of California San Francisco 3333 California St., Ste 315 San Francisco, Ca 941430962
Grant 5P41RR001081-270184 from National Center For Research Resources IRG: ZRG1
Keywords: biomedical resource, chemical model, computational biology, computer center, physics, protein, bioinformatics
Project start date: 2004-07-01
Project end date: 2005-06-30
Sponsored Links Excellgen http://Excellgen.com