Our Approach and Our Goals
Computational methods, including molecular dynamics (MD)
simulations and free energy calculations, are increasingly becoming powerful
tools in the fields of protein structure prediction and de novo protein
design. Despite the continuous advancement of experimental methods,
computational tools have proved to be of utmost importance to fill crucial
“gaps”, obtain information that is not accessible from experiments, and lead
to the discovery of novel biomaterials and therapeutics.
Through the development of novel multidisciplinary computational
strategies, combining biophysical-chemistry and engineering principles, our
research aims at:
• Designing novel
biomaterials with advanced applications, and understanding peptide/protein
self-assembly at the atomic and molecular level;
• Elucidating how
compounds or proteins can serve as inhibitors or disassemblers of
peptide/protein amyloid self-assembly associated with amyloid diseases
including diabetes, Alzheimer’s and Parkinson’s and designing novel compounds
or proteins that can serve as therapeutics for amyloid diseases;
biomolecular interactions between small chemical compounds, proteins and RNAs
involved in key biological systems such as bacteria proteins and shedding
light into key biological axes.
Department of Chemical Engineering
Engineering Research Building
225, Jack E. Brown Chemical Engineering
3122 TAMU, College Station, TX 77843
Phanourios Tamamis - Short Bio
Phanourios Tamamis received his B.S. degree in
2006 (excellent; top academic performance) and Ph.D. degree in 2010 from the Physics
Department of the University of Cyprus, and was recognized as the top Cypriot
undergraduate researcher in 2006. During his undergraduate,
graduate and early-postdoctoral studies, he was supervised by Professor
Georgios Archontis, a notable student of Martin Karplus (Nobel Prize in Chemistry,
2013). After finishing his Ph.D. studies, from 2010 until 2012, Phanourios
Tamamis served as a Postdoctoral Fellow at the University of Cyprus and as a
Fulbright Scholar at the University of California at Riverside and Princeton
University, under the co-supervision of Professors Dimitrios Morikis and
Christodoulos A. Floudas. He was recognized as an “Outstanding Young
Researcher” in the 2012 Computational Biophysics to Systems Biology
conference. In 2013, he joined the lab of Professor Christodoulos A. Floudas
at the Chemical and Biological Engineering Department of Princeton University
as a Postdoctoral Research Associate. In 2015, he joined the Chemical
Engineering Department of Texas A&M University as an Assistant Professor.
• Phanourios Tamamis gives a seminar at the Chemical and
Biomolecular Engineering Department of the University of Akron with title: “From
amyloids to amyloid materials: Using computers to understand and design novel
inhibitors and functional materials”.
• Sai Vamshi Jonnalagadda and
Phanourios Tamamis give four presentations at the annual AIChE
meeting, on the computational design of functional amyloid materials, on
amyloid inhibition and sequestration, as well as on the study of modified
RNAs in their interactions with proteins.
a Computational Protocol for the Design of Functional Amyloid Peptide
High-Throughput Screening of Modified RNA Interactions with Proteins
(3) β-Wrapin Proteins
Sequestering Amyloidogenic Proteins: Understanding Their Function and
Designing Novel β-Wrapins with Improved Binding Affinities
Studies on Modeling, Simulating and Designing Amyloid Biomaterials
• Shujun He, joins our lab as a PhD
• Phanourios Tamamis presents our lab’s pioneering computational
protocol for the design of functional amyloid materials in two conferences:
PEPMAT 2018, London, UK, July 16-18, 2018.
Current Challenges in Amyloid Diseases: From
Molecular Mechanisms to the Cell and Clinics,
Ein Bokek, Israel,
September 2-6, 2018.
• Sai Vamshi Jonnalagadda, Asuka
Orr, Kendal Henderson, and Chang-Hyun Choi from Tamamis lab, in collaboration
with several experimental labs including Dr. Mitraki’s and Dr. Jeong’s labs,
published a paper on the first computational design protocol to functionalize
amyloid materials binding to ions. The
paper was accepted in J. Phys. Chem. B
Amyloid materials are gaining
increasing attention as promising materials for applications in numerous
fields. Computational methods have been successfully implemented to
investigate the structures of short amyloid-forming peptides, yet their
application in the design of functional amyloid materials is still elusive.
Here, we developed a computational protocol for the design of functional
amyloid materials capable of binding to an ion of interest. We applied the
protocol in a test case involving the design of amyloid materials with cesium
ion deposition and capture properties. As part of the protocol, we used an
optimization-based design model to introduce mutations at non-β-sheet
residue positions of an amyloid designable scaffold. The designed amino acids
introduced to the scaffold mimic how amino acids bind to cesium ions
according to experimentally resolved structures, and also aim to
energetically stabilize the bound conformation of the pockets. The optimum
designs were computationally validated using a series of simulations and
structural analysis to select the top designed peptides predicted to form
fibrils with cesium ion binding properties for experimental testing.
Experiments verified the amyloid-forming properties of the selected top
designed peptides, as well as the cesium ion deposition and capture
properties by the amyloid materials formed. This study demonstrates the
first, to the best of our knowledge, computational design protocol to
functionalize amyloid materials and suggests that its further advancement can
lead to novel highly promising functional amyloid materials of the future.
Previous Key Stories from 2018
• Sai Vamshi Jonnalagadda, Asuka Orr
and Joseph Jakubowski from Tamamis lab, in collaboration with Dr. Mitraki’s
lab and several other labs in Europe published paper on a novel amyloid
designable scaffold and potential inhibitor inspired by GAIIG of amyloid beta
and the HIV-1 V3 loop.
Previous Key Stories from 2017
Graduate students Vamshi Jonnalagadda and Asuka Orr gave three presentations at the AIChE meeting in Minneapolis.
• A new Ph.D. student, Joseph Jakubowski, joined Tamamis lab.
• Tamamis lab received a Seed
Grant for Water Research from the Texas A&M
Engineering Experiment Station.
4th year Ph.D.
3rd year Ph.D. student
year Ph.D. student
1st year Ph.D.
4th Year Undergrad.
3rd Year Undergrad.
Xue Le Lim
Our Current Research
Engineering novel peptide self-assembled
bio-nanomaterials with promising applications in biomedicine, energy and
methods possess the capacity to provide atomic-level insights into the
β-sheet structural organization of amyloid-forming self-assembled
peptides, and peptide-based nanostructures. Our research aims at exploiting
the self-assembly properties of β-sheet or α-helical
peptides/proteins to engineer novel peptide self-assembled biological
nanomaterials with promising applications in biomedicine, energy and
Designing inhibitors of amyloid formation as
potential therapeutics of amyloid diseases
Amyloid deposition in human tissue is
associated with a number of diseases including all common dementias and
diabetes. A critical initial step to prevent amyloid fibril formation is to
delineate the self-assembly properties and provide insights into the
structure of amyloid fibrils of the associated peptide or protein in each
disease. Our research aims at (i) elucidating the
amyloid structures formed by amyloidogenic peptides and proteins,
and (ii) designing protein and non-proteins-based inhibitors
or disassemblers of amyloid formation, as potential therapeutics for
amyloid diseases, including Alzheimer’s, Parkinson’s and diabetes
biomolecular complex structures of small-molecule ligand
: protein and RNA : proteins complexes, shedding light into key
biological axes and discovering novel potential therapeutics.
Understanding the binding of small ligands
to proteins or RNAs to proteins is of significant importance, as such
interactions play a key role in living organisms’ biological processes. Our
research aims to develop novel computational protocols investigating the
molecular recognition of proteins (e.g., in bacteria proteins) by
small-molecule ligands or RNAs. We emphasize on developing novel
computational tools to elucidate the structures and interactions formed
between small-molecule ligands and proteins or between chemically modified
RNAs and proteins.
and Book Chapters
Publications from Tamamis lab
1. Jonnalagadda SVR,
Kokotidou C, Orr AA, Fotopoulou E, Henderson KJ,
Choi CH, Lim WT, Choi SJ, Jeong HK, Mitraki A, Tamamis P. Computational Design of Functional Amyloid Materials
with Cesium Binding, Deposition and Capture
Properties. J Phys Chem B. 2018, 122, 7555-7568.
2. Keasar C. et
al. An analysis and evaluation of the WeFold
collaborative for protein structure prediction and its pipelines in CASP11
and CASP12. Scientific Reports 2018, 8, 9939.
3. Mohan RR, Wilson M, Gorham RD Jr, Harrison RES,
Morikis VA, Kieslich CA, Orr AA, Coley AV, Tamamis P, Morikis D. Virtual
Screening of Chemical Compounds for Discovery of Complement C3 Ligands. ACS
Omega, 2018, 3, 6427–6438.
Kokotidou C, Jonnalagadda SVR, Orr AA, Seoane-Blanco M, Apostolidou CP, van
Raaij MJ, Kotzabasaki M, Chatzoudis A, Jakubowski JM, Mossou E, Forsyth VT,
Mitchell EP, Bowler MW, Llamas-Saiz AL, Tamamis P, Mitraki A. A Novel Amyloid Designable Scaffold and
Potential Inhibitor Inspired by GAIIG of Amyloid Beta and the HIV-1 V3
loop. FEBS Lett. 2018. 592, 1777–1788
Jin UH, Park H,
Li X, Davidson LA, Allred C, Patil B, Jayaprakasha G, Orr AA, Mao L,
Chapkin RS, Jayaraman A, Tamamis P, Safe S. Structure-Dependent
Modulation of Aryl Hydrocarbon Receptor-Mediated Activities by Flavones. Toxicological
Sciences, 2018,164: 205-217.
6. Orr AA, Shaykhalishahi H, Mirecka EA,
Jonnalagadda SVR, Hoyer W, Tamamis P*. Elucidating the Multi-Targeted Anti-Amyloid Activity and Enhanced
Islet Amyloid Polypeptide Binding of β-wrapins. Computers &
Chemical Engineering, 2018. https://doi.org/10.1016/j.compchemeng.2018.02.013
AA, Jayaraman A, Tamamis P*. Molecular Modeling of Chemoreceptor:
Ligand Interactions. Methods in Molecular Biology, 2018, 1729:353-372.
AA, Gonzalez-Rivera JC, Wilson M, Bhikha PR, Wang D, Contreras LM, Tamamis
P*. A high-throughput and rapid computational method for screening of
RNA post-transcriptional modifications that can be recognized by target
proteins. Methods, 2018, https://doi.org/10.1016/j.ymeth.2018.01.015
9. Jonnalagadda SVR, Ornithopoulou E, Orr AA, Mossou E, Forsyth E, Mitchell EP, Bowler MW, Mitraki A,
Tamamis P*. Computational Design of Amyloid Self-Assembling Peptides
Bearing Aromatic Residues and the Cell Adhesive Motif Arg-Gly-Asp. Molecular Systems Design & Engineering,
2017, 2(3): 321-335.
AA, Wördehoff MM. Hoyer W, Tamamis P*.
Uncovering the Binding and Specificity of β-Wrapins for Amyloid-β
and α-Synuclein. Journal of Physical Chemistry B, 2016, 120 (50):
11. Deidda G,
Jonnalagadda SVR, Spies JW, Ranella A, Mossou E,
Forsyth VT, Mitchell EP, Bowler MW, Tamamis P*, Mitraki A. Self-assembled amyloid peptides with Arg-Gly-Asp (RGD) motifs as
scaffolds for tissue engineering. ACS Biomaterials Science &
Engineering, 2017, 3(7): 1404–1416.
G. Deidda and S.V.R.
Jonnalagadda were equally contributing first authors
Y, Jin UH, Davidson LA, Chapkin
RS, Jayaraman A, Tamamis P, Orr A, Allred C, Denison MS, Soshilov A, Weaver E, Safe S. Microbial-Derived
1,4-Dihydroxy-2-naphthoic Acid and Related Compounds as Aryl Hydrocarbon
Receptor Agonists/Antagonists: Structure-Activity Relationships and
Receptor Modeling. Toxicological Sciences, 2017, 155 (2): 458-473.
13. Khoury GA, Smadbeck
J, Kieslich CA, Koskosidis
AJ, Guzman YA, Tamamis P*, Floudas CA. Princeton_TIGRESS
2.0: High refinement consistency and net gains through support vector
machines and molecular dynamics in double-blind predictions during the
CASP11 experiment. Proteins 2017, 85(6):1078-1098.
14. Kieslich CA, Tamamis P, Guzman YA,
Onel M, Floudas CA. Highly Accurate
Structure-Based Prediction of HIV-1 Coreceptor
Usage Suggests Intermolecular Interactions Driving Tropism. PLoS One. 2016, 11(2): e0148974.
Publications from Dr. Tamamis’
graduate and postgraduate studies
RD Jr, Forest DL, Khoury GA, Beecher CN, Tamamis
P, Archontis G, Larive CK, Floudas C A, Radeke M J, Johnson LV, Morikis D. New compstatin peptides
containing N-terminal extensions and non-natural amino acids exhibit potent
complement inhibition and improved solubility characteristics. Journal of
Medicinal Chemistry, 2015, 58(2): 814-826.
P, Floudas CA. Elucidating a Key
Anti-HIV-1 and Cancer-Associated Axis: The Structure of CCL5 (Rantes) in Complex with CCR5. Scientific Reports, 2014,
P, Floudas CA. Elucidating a Key
Component of Cancer Metastasis: CXCL12 (SDF-1α) Binding to CXCR4.
Journal of Chemical Information and Modeling, 2014, 54 (4): 1174-1188.
P, Floudas CA. Molecular
Recognition of CCR5 by an HIV-1 gp120 V3 Loop. PLoS
ONE 2014, 9 (4): e95767.
K, Kassinopoulos M, Mastrogiannis
E, Forsyth VT, Mitchell EP, Mitraki A, Archontis G. Self-Assembly of an
Aspartate-Rich Sequence from the Adenovirus Fibre
Shaft: Insights from Molecular Dynamics Simulations and Experiments.
Journal of Physical Chemistry B, 2014, 118 (7): 1765-1774.
20. Khoury GA, Smadbeck
J, Tamamis P, Vandris AC, Kieslich CA, Floudas CA Forcefield_NCAA:
Ab Initio Charge Parameters to Aid in the Discovery and Design of Therapeutic
Proteins and Peptides with Unnatural Amino Acids and Their Application to
Complement Inhibitors of the Compstatin Family. ACS Synthetic Biology,
2014, 3(12): 855–869.
21. Khoury GA, Tamamis P, Pinnaduwage N, Smadbeck J, Kieslich CA, Floudas CA. Princeton_TIGRESS:
Protein geometry refinement using simulations and support vector machines.
Proteins, 2014, 82 (5): 794-814.
E, Archontis G, Mitraki A.
Combination of Theoretical and Experimental Approaches for the Design and
Study of Fibril-forming Peptides. In Protein Design: Methods and
Applications. Methods in Molecular Biology, 2014, 1216: 53-70.
CA, Nikiforovich GV, Woodruff TM, Morikis D,
Archontis G. Insights into the Mechanism of C5aR Inhibition by PMX53 via
Implicit Solvent Molecular Dynamics Simulations and Docking. BMC
Biophysics, 2014, 7: 5.
RD Jr, Forest DL, Tamamis P, López de
Victoria A, Kraszni M, Kieslich CA,
Banna CD, Bellows-Peterson ML, Larive CK, Floudas CA, Archontis G, Johnson LV, Morikis
D. Novel compstatin family peptides inhibit complement activation by drusen-like deposits in human retinal pigmented
epithelial cell cultures. Experimental Eye Research, 2013, 116: 96-108.
P, Floudas CA. Molecular
Recognition of CXCR4 by a Dual Tropic HIV-1 gp120 V3 Loop. Biophysical
Journal, 2013, 105 (6): 1502-1514.
de Victoria, A, Tamamis P, Kieslich, CA,
Morikis, D. Insights into the Structure, Correlated Motions, and
Electrostatic Properties of two HIV-1 gp120 V3 loops. PLoS
ONE 2012, 7 (11): e49925.
27. Kieslich CA, Tamamis P, Gorham RD
Jr, Lopez de Victoria A, Sausman N, Archontis G,
Morikis D. Exploring protein-protein and protein-ligand interactions in the
immune system using molecular dynamics and continuum electrostatics.
Current Physical Chemistry 2012, 2 (4): 324-343.
P, Lopez de Victoria A, Gorham RD,
Bellows-Peterson ML, Pierou P, Floudas CA,
Morikis D, Archontis G. Molecular Dynamics in Drug Design: New Generations
of Compstatin Analogs. Chemical Biology & Drug Design 2012, 79 (5):
P, Mytidou C, Floudas CA, Morikis D, Archontis G.
Design of a modified mouse protein with ligand binding properties of its
human analog by molecular dynamics simulations: The case of C3 inhibition
by compstatin. Proteins, 2011, 79 (11): 3166-3179.
30. Pieridou G, Avgousti-Menelaou
C, Tamamis P, Archontis G, Hayes SC. UV Resonance Raman Study of
TTR(105-115) Structural Evolution as a Function of Temperature. Journal of
Physical Chemistry B, 2011, 115 (14): 4088-4098.
31. Tamamis P, Archontis G.
Amyloid-like Self-Assembly of a Dodecapeptide
Sequence from the Adenovirus Fiber Shaft: Perspectives from Molecular
Dynamics Simulations. Journal of Non-Crystalline Solids, 2011, 357 (2):
P, Morikis D, Floudas CA,
Archontis G. Species specificity of the complement inhibitor compstatin
investigated by all-atom molecular dynamics simulations. Proteins, 2010, 78
E, Mitraki A, Archontis G. Amyloid-like Self-Assembly of Peptide Sequences
from the Adenovirus Fiber Shaft: Insights from Molecular Dynamics
Simulations. Journal of Physical Chemistry B, 2009, 113 (47): 15639-15647.
L, Reches M, Marshall K, Sikorski P, Serpell L, Gazit E, Archontis
G. Self-Assembly of Phenylalanine Oligopeptides: Insights from Experiments
and Simulations. Biophysical Journal, 2009, 96 (12): 5020-5029.