BIA2610 – Statistical Methods Chapter 6 – Continuous Probability Distributions.
Data-Driven Protein Design: A Continuous Statistical Energy ......Data-Driven Protein Design: A...
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COMPUTATIONAL CHEMISTRY BI-WEEKLY SEMINAR SERIES Data-Driven Protein Design: A Continuous Statistical Energy for De Novo Backbone Design with Complete Structure Flexibility SPEAKER: Haiyan Liu, University of Science and Technology of China TIME: 2:00pm-3:00pm, Wednesday, March 21, 2018 VENUE: Room 264, Geography Building, Zhongbei Campus HOST: Fei Xia, East China Normal University ABSTRACT OF THE TALK To a very large extent, the task of designing de novo proteins can be divided into two sub- tasks. One is to identify backbone structures of high designability. The other is to determine amino acid sequences that are compatible with the respective backbones. Previously, we have already developed a statistical energy model, ABACUS, to carry out the subtask of se- quence design. Here we present a statistical energy model to execute the subtask of struc- ture design. The model comprises descriptions of sidechain type-independent peptide local conformation and through-space backbone packing. When amino acid sequences are par- tially or fully determined, the model also integrates descriptions of intra-residue conforma- tions and inter-residue atomic-packing. The various energies have been statistically derived from the database of native protein structures. Further, we use neural network regression to summarize the dependences of such energies on complex conformational coordinates into continuous functions with analytical derivatives. The resulting energy model combined with established molecular simulation techniques, the conformation of de novo backbones to- gether with partially or fully specialized side chains can be sampled and/or optimized with complete structure flexibility. BIOGRAPHY Haiyan Liu graduated from the University of Science and Technology of China, majored in Biology. He received his B.S. degree in 1990 and Ph.D. degree in 1996. Between 1993 and 1995 he was a visiting graduate student in Laboratory of Physical Chemistry, ETH-Zurich. Between 1998 and 2000, he was a Post-doctoral Research Associate in Department of Chemistry, Duke University and Department of Biochemistry and Biophysics, UNC-Chap- el-Hill. Since 2001, he is a Professor in School of Life Sciences, University of Science and Technology of China. His main research interests are methods and applications of protein simulations and protein design.
Transcript of Data-Driven Protein Design: A Continuous Statistical Energy ......Data-Driven Protein Design: A...
COMPUTATIONAL CHEMISTRY BI-WEEKLY SEMINAR SERIES
Data-Driven Protein Design: A Continuous Statistical Energy for
De Novo Backbone Design with Complete Structure Flexibility
SPEAKER: Haiyan Liu, University of Science and Technology of ChinaTIME: 2:00pm-3:00pm, Wednesday, March 21, 2018VENUE: Room 264, Geography Building, Zhongbei CampusHOST: Fei Xia, East China Normal University
ABSTRACT OF THE TALKTo a very large extent, the task of designing de novo proteins can be divided into two sub-tasks. One is to identify backbone structures of high designability. The other is to determine amino acid sequences that are compatible with the respective backbones. Previously, we have already developed a statistical energy model, ABACUS, to carry out the subtask of se-quence design. Here we present a statistical energy model to execute the subtask of struc-ture design. The model comprises descriptions of sidechain type-independent peptide local conformation and through-space backbone packing. When amino acid sequences are par-tially or fully determined, the model also integrates descriptions of intra-residue conforma-tions and inter-residue atomic-packing. The various energies have been statistically derived from the database of native protein structures. Further, we use neural network regression to summarize the dependences of such energies on complex conformational coordinates into continuous functions with analytical derivatives. The resulting energy model combined with established molecular simulation techniques, the conformation of de novo backbones to-gether with partially or fully specialized side chains can be sampled and/or optimized with complete structure flexibility.
BIOGRAPHYHaiyan Liu graduated from the University of Science and Technology of China, majored in Biology. He received his B.S. degree in 1990 and Ph.D. degree in 1996. Between 1993 and 1995 he was a visiting graduate student in Laboratory of Physical Chemistry, ETH-Zurich. Between 1998 and 2000, he was a Post-doctoral Research Associate in Department of Chemistry, Duke University and Department of Biochemistry and Biophysics, UNC-Chap-el-Hill. Since 2001, he is a Professor in School of Life Sciences, University of Science and Technology of China. His main research interests are methods and applications of protein simulations and protein design.
