NAME: Emil Alexov
eRA COMMONS USER NAME (credential, e.g., agency login): ealexov
POSITION TITLE: Professor of Physics, Clemson University
Sofia University, Bulgaria MS 07/1984 Physics
Sofia University, Bulgaria PhD 01/1991 Physics
RIKEN, Japan Visiting Scientist 04/1995 Protein Science
City College of New York Postdoctoral 08/2000 Molecular Biophysics
Columbia University, New York Senior Scientist 08/2005 Molecular Biophysics
A. Personal Statement
My research focuses on methods and software development, investigations of molecular effects of human nsSNPs(a), and structure-based drug discovery(b). Recently our lab developed several methods for predicting the changes of folding (SAAFEC method) and binding protein-protein (SAAMBE method) and protein-DNA/RNA (SAMPDI method) free energies caused by amino acid mutations, which are closely related to our efforts in Personalized Medicine and the goals of this proposal. Furthermore, we have investigated the mechanistical roles of DNA variants implicated in various human disorders and showed that there is a strong correlation between these mechanistic effects and propensity given mutation to be photogenic(c). Recently we demonstrated that another mechanistic effects, the changes of electrostatic forces, can be used to discriminate pathogenic from benign mutations(d). The abovementioned tools and developments are currently being used to investigate various phenomena in molecular biology and to reveal molecular effects of human genetic disorders and to seek small molecules (potential drugs) that can eliminate disease-causing effects. They will be used in the current project to reveal mechanistic roles of DNA variants linked with high risk of opioid addiction.
a. Kucukkal TG, Petukh M, Li L, Alexov E. (2014). Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins. (2015). Curr Opin Struct Biol. Jun;32:18-24. doi: 10.1016/j.sbi.2015.01.003. Review. PMID: 25658850.
b. Zhang Z, Martiny V, Lagorce D, Ikeguchi Y, Alexov E, Miteva MA. (2014). Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach. PLoS One. 2014 Oct 23;9(10):e110884. doi: 10.1371/journal.pone.0110884. PMID: 25340632.
c. Petukh M, Kucukkal TG, Alexov E. (2015). On human disease-causing amino acid variants: statistical study of sequence and structural patterns. Hum Mutat. 2015 May;36(5):524-534. doi: 10.1002. PMID: 25689729.
d. Li L, Jia Z, Peng Y, Godar S, Getov I, Teng S, Alper J, Alexov E. (2017). Forces and Disease: Electrostatic force differences caused by mutations in kinesin motor domains can distinguish between disease-causing and non-disease-causing mutations. Sci Rep. 2017 Aug 15;7(1):8237. doi: 10.1038. PMID: 28811629
B. Positions and Honors
Positions and Employment
2012 - Professor, Department of Physics, Clemson University
2016 - Professor, Department of Material Sciences, Clemson University
2014 - Faculty Scholar at Clemson School of Health Research
2005-2012 Associate Professor, Department of Physics, Clemson University
2000-2005 Senior Scientist, Howard Hughes Medical Institute and Columbia University, NY
1997-2005 Adjunct Assistant, Professor Bronx Community College, New York
1995-2000 Research Associate, City College of New York
1994-1995 Visiting Scientist, The Institute of Physical and Chemical Research (RIKEN), Japan
1992-1994 Researcher, Bulgarian Academy of Sciences
1991-1992 Assistant Professor, Medical Academy, Bulgaria
1990-1991 Assistant Professor, Sofia University, Bulgaria
Other Experience and Professional Memberships
1995- Member, American Physics Society
1995- Member, Biophysical Society of America
2005- American Chemical Society
2014- Editor-in-chef, Journal of Theoretical and Computational Chemistry
2014- Editor, Frontiers in Molecular Recognition
2014- Associate Editor, International Journal of Molecular Sciences
2012- Associate Editor, Computational and Mathematical Methods in Medicine
2013- Associate Editor, Molecular Based Mathematical Biology
2011-13 Guest Editor, Communications in Computational Physics
2008 Guest Editor, Current Pharmaceutical Biotechnology
2013 Guest Editor, Journal of Molecular Biology
2011 Editorial Board Member, Computational Biology and Chemistry: Advances and Applications
2018 NIH Peer Review Committee: ZRG1 BCMB, ad hoc reviewer
2018 NIH Peer Review Committee: BST IRG, ad hoc reviewer
2018 NIH Peer Review Committee: ZRG1 BST, ad hoc reviewer
2018 NIH Peer Review Committee: ZRG1 SRB-X, ad hoc reviewer
2008-09 NIH Peer Review Committee: ZRG1 BST-Q, ad hoc reviewer
2009 NIH Peer Review Committee: ZRG1 IMST-A, ad hoc reviewer
2010-17 NIH Peer Review Committee: BDMA, ad hoc reviewer
2010 NIH Peer Review Committee: MSFD, ad hoc reviewer
2015 NIH Peer Review Committee: ZGM1 TWD-3, ad hoc reviewer
2010 NSF Peer Review Committee: CDI, ad hoc reviewer
2010 NSF Peer Review Committee, MBC, ad hoc reviewer
2010 Cottrell College Science Award, mail reviewer
2007-08 Irish Research Foundation, Ireland, mail reviewer
2007-12 National Center for Scientific Research (CNRS) ANR-PCV, France, mail reviewer
2011 Meeting organizer, Modeling electrostatics in Molecular Biology, Clemson, SC
2012 Meeting Organizer, Symposium at the Annual ACS meeting, Continuum Solvation Modeling in Biological Systems: Developments and Applications,” Philadelphia, PA
2013 Meeting Organizer, Symposium at the Annual ACS meeting, Electrostatics in Molecular Biophysics: in silico, in vitro and in vivo approaches;” Indianapolis; IN
2014 Meeting Organizer, Symposium at the Annual ACS meeting, Revealing the Role of Water and Solvation in Molecular Biology, San Francisco, CA.
2014 Meeting Organizer, Chair, Gordon Research Conference, Human Single Nucleotide Polymorphisms & Disease, Stonehill College, MA.
2015 Meeting Organizer, Symposium at the Annual ACS meeting, Molecular Biophysics: Revealing the interplay between different forces and effects in biochemical processes,” Boston, MA.
2015 Semester Organizer, MBI: Emphasis Year on Mathematical Molecular Biosciences, Columbus, OH.
2016 Meeting Organizer, Symposium at the Annual ACS meeting, “Revealing the Role of Water in Calculations of Solvation Energy,” Philadelphia, PA.
2017 Meeting Organizer, Symposium at the Annual ACS meeting, “Revealing molecular effects associated with molecular recognition,” Washington, DC.
Honors
2004 Science and Technology Agency Award (STA Fellowship), RIKEN, Japan.
2013 Outstanding Graduate Student Mentor, Clemson University, USA.
2014 Faculty Achievement in the Science, Clemson University, USA.
2018 Alumni Award for Outstanding Achievement in Research, Clemson, USA
C. Contributions to Science
1. Revealing molecular mechanism of human diseases associated with human DNA variants is crucial for developing effective treatments. With this regard we investigated molecular origin of various human disorders and found, both computationally and experimentally, that the corresponding missense mutations affect the biophysical characteristics of the corresponding proteins and protein complexes(a), and the most frequently affected characteristics were found to be protein stability and protein binding(b,c), while the active center of the corresponding proteins was not directly affected. Thus, the inability of the protein to carry its function frequently is a result of alterations of the wild type protein stability and interactions, but these alterations do not necessarily make the protein less stable or weaken protein-protein/protein-DNA binding(d).
a. Zhang Z, Teng S, Wang L, Schwartz CE, Alexov E. (2010). Computational analysis of missense mutations causing Snyder-Robinson syndrome. Hum Mutat.; Sep;31(9):1043-9. PMID: 20556796. PMCID: PMC2932761.
b. Zhang Z, Norris J, Kalscheuer V, Wood T, Wang L, Schwartz C, Alexov E, Van Esch H. A Y328C missense mutation in spermine synthase causes a mild form of Snyder-Robinson syndrome. Hum Mol Genet. 2013 Sep 15;22(18):3789-97. doi: 10.1093/hmg/ddt229. Epub 2013 May 21. PMID: 23696453. PMCID: PMC374864.
c. Witham S, Takano K, Schwartz C, Alexov E.(2011). A missense mutation in CLIC2 associated with intellectual disability is predicted by in silico modeling to affect protein stability and dynamics. Proteins. Aug;79(8):2444-54. PMID: 21630357. PMCID: PMC3132293.
d. Takano K, Liu D, Tarpey P, Gallant E, Lam A, Witham S, Alexov E, Chaubey A, Stevenson RE, Schwartz CE, Board PG, Dulhunty AF. An X-linked channelopathy with cardiomegaly due to a CLIC2 mutation enhancing ryanodine receptor channel activity. Hum Mol Genet. 2012 Oct 15;21(20):4497-507. Epub 2012 Jul 19. PMID: 22814392. PMCID: PMC3459470.
2. The observation that disease-causing mutations frequently do not affect the active site of the corresponding protein suggests plausible strategy of mitigating disease-causing effects, namely to restore the wild type stability and binding affinity. In the past we were investigating the possibility of restoring wild type folding free energy of spermine synthase mutant, G56S (causing Snyder-Robinson syndrome), by small molecule binding to the mutant(a,b). We demonstrated, both computationally and experimentally, that selected small molecules upon their binding to malfunctioning G56S mutant increase the binding affinity of the mutant and thus facilitates homo-dimer formation, which resulted in increased activity. This is also reported as an intellectual property(c).
a. Zhang Z, Witham S, Petukh M, Moroy G, Miteva M, Ikeguchi Y, Alexov E. (2013). A rational free energy based approach to understanding and targeting disease-causing missense mutations. J Am Med Inform Assoc. Jul-Aug;20(4):643-51. PMID: 234085. PMCID: PMC3721167.
b. Zhang Z, Martiny V, Lagorce D, Ikeguchi Y, Alexov E, Miteva MA. Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach. PLoS One. 2014 Oct 23;9(10):e110884. doi: 10.1371/journal.pone.0110884. PMID:
25340632. PMCID: PMC4207787.
c. Intellectual property (IP). Tech ID: 2014-009; Physics-based approach to understanding and targeting disease-causing mutations; Grant support: LM009748, National Institutes of Health; PI; E Alexov; Disclosure date: 2013-12-04.
3. The modeling of electrostatic potential and computing electrostatic energies is a key problem in molecular biophysics since all biological macromolecules (and nanoparticles) are made of atoms carrying partial changes and are situated at Angstrom distances. However, this modeling is not trivial because of large number of atoms (both solute and water) and irregular shape of biological objects. One of the first software capable of accurate modeling the electrostatic potential in systems made of biological macromolecules and water was DelPhi, originally developed in Barry Honig lab in 1988. Since 2010, the PI lab has been responsible for maintaining and developing DelPhi. With the support of the previous funding period, DelPhi has been completely rewritten into object-oriented C++ code, which is distributed free of charge for academic users. The code was extensively tested and shown to be performing very well in terms of accuracy and speed of calculations(a). Furthermore, we have developed a parallelized version of DelPhi which is more than 40 time faster than sequential one and is very suitable for handling calculations of objects with large dimensions(b,c). The algorithms for this parallelization are also secured as intellectual property (IP)(d). The new DelPhi C++ code, which allows for the easy expansion of DelPhi capability, is very well documented, has several new features and comes with a developer’s manual. We expect that updated DelPhi package will further enable computational community to study the role of electrostatics in various molecular biology phenomena including large systems and nano-objects.
a. Li L, Li C, Sarkar S, Zhang J, Witham S, Zhang Z, Wang L, Smith N, Petukh M, Alexov E. (2012). DelPhi: a comprehensive suite for DelPhi software and associated resources. BMC Biophys. May 14;5:9. PMID: 22583952. PMCID: PMC3463482
b. Li C, Li L, Zhang J, Alexov E. (2012). Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi. J Comput Chem. Sep 15;33(24):1960-6. PMID: 22674480. PMCID: PMC3412928.
c. Li C, Petukh M, Li L, Alexov E. (2013). Continuous development of schemes for parallel computing of the electrostatics in biological systems: implementation in DelPhi. J Comput Chem. Aug 15;34(22):1949-60. PMID: 23733490. PMCID: PMC3707979.
d. Intellectual Property (IP). Tech ID: 2013-018; IR: 1626401-12-0015; Algorithms and Computer Code for Parallel Computing of Electrostatics in Systems Made of Biological Macromolecules and Objects; Grant support: GM093937, National Institutes of Health; PI; E Alexov; Disclosure date: 2012-08-13
4. In addition to the contributions described above, we implemented a smooth Gaussian-based dielectric function in DelPhi.(a) This implementation addresses a major question of modeling electrostatics in molecular biology since biological macromolecules, rather than being static structures, constantly undergo conformational changes. To account for such flexibility in the modeling of electrostatic potential, the macromolecule should be treated as an inhomogeneous dielectric medium, and the transition between the solute and water phase should be a smooth dielectric function since properties of the water at the surface of the solute differ from the properties of bulk water. Our approach outperformed the standard homogeneous dielectric approach in terms of matching experimentally measured pKa’s(a) and small molecule solvation energies(b). In addition, the solvation energy calculations with smooth Gaussian-based dielectric function were shown to be less grid sensitive than the standard model(c). This implementation is also registered as IP(d).
a. Pahari S, Sun L, Basu S, Alexov E (2018), DelPhiPKa: Including salt in the calculations and enabling polar residues to titrate, Proteins. 86(12):1277-1283, PMID 30252159 PMCID: PMC6294708.
b. Li L, Li C, Zhang Z, Alexov E. (2013). On the Dielectric "Constant" of Proteins: Smooth Dielectric Function for Macromolecular Modeling and Its Implementation in DelPhi. J Chem Theory Comput. Apr 9;9(4):2126-2136. PMID: 23585741. PMCID: PMC4092036.
c. Li L, Li C, Alexov E.(2014). On the Modeling of Polar Component of Solvation Energy using Smooth Gaussian-Based Dielectric Function. J Theor Comput Chem. May;13(3). PMID: 25018579. PMCID: PMC4092036.
d. IP. Tech ID: 2013-021 1; IR: 626401-12-0017; Gaussian Dielectric Function in DelPhi; Grant Sponsor: GM093937, National Institutes of Health; PI: E. Alexov; Disclosure date: 2012-08-14
5. Furthermore, we developed a stand-alone software, the Protein Nano Object Integrator (ProNOI), to generate atomic-style geometrical objects as cone, cylinder, sphere and parallelepiped(a). ProNOI is an easy-to-use tool that allows the user to generate various nano-objects along with proteins, DNAs and RNAs, and to manipulate their positions, dimensions, atomic charges and the dielectric constant. The generated files can be visualized with any existing visualization program in molecular biology (such as VMD and Chimera) and subjected to various modeling software. Last year, we further upgraded the ProNOI to allow the 3D modeling of photographs, specifically cryo-electron microscope images. This development, which is an essential component of this planned research, will pioneer the modeling of cellular organelles and large macromolecular and nano-objects. The development is also registered as an IP(b). We also developed the MEMPOT algorithm(c), which is a new method for modeling the electrostatic potential in large biological membranes and continued exploring large macromolecular assemblages(d).
a. Smith N, Campbell B, Li L, Li C, Alexov E. (2012). Protein Nano-Object Integrator (ProNOI) for generating atomic style objects for molecular modeling. BMC Struct Biol. Dec 5;12:31. PMID: 23217202. PMCID: PMC3532097.
b. IP; Tech ID: 2013-020 1; IR: 626401-12-0016; ProNOI software ; Grant Sponsor: GM093937, National Institutes of Health; PI: E. Alexov; Disclosure date: 2012-08-14.
c. Dias RP, Li L, Soares TA, Alexov E. (2014). Modeling the electrostatic potential of asymmetric lipopolysaccharide membranes: the MEMPOT algorithm implemented in DelPhi. J Comput Chem. Jul 15;35(19):1418-29. PMID: 24799021. PMCID: PMC4057312.
d. Tajielyato N, Li L, Peng Y, Alper J, Alexov E, E-hooks provide guidance and a soft landing for the microtubule binding domain of dynein. Sci Rep. 2018 Sep 5;8(1):13266, PMID: 30185874 PMCID: PMC6125590.
Complete List of Published Work in MyBibliography (more than 160 peer-reviewed papers):
http://www.ncbi.nlm.nih.gov/myncbi/browse/collection/44998670/?sort=date&direction=descending
D. Additional Information: Research Support and/or Scholastic Performance
Ongoing Research support
R01 GM093937 Alexov (PI) 04/01/2016–03/31/2020
New generation DelPhi: large objects and beyond electrostatics
This grant supports the maintenance and further development of DelPhi, a popular software package for modeling electrostatic potential and energies in systems composed of biological macromolecules and geometrical shapes.
Role: PI
1R01GM125639-01 Yu (PI) 01/23/2018 – 12/31/2022
NIH/NIGMS
Quantifying molecular consequences of human missense variants with large-scale interactome perturbation studies
This grant supports development of methods and computer code to predict effects of mutations on protein-protein binding free energy.
Role: Co-PI
NSF Zhao (PI) 8/15/2018 – 7/31/2021
NSF DMS/Mathematical Biology
Collaborative Research: A Regularized Poisson Boltzmann Model for Fast Computation of the Ensemble Average Polar Solvation Energy
The major goal of this project is to develop supper Gaussian approach to compute solvation energy of biomolecules
Role: Co-PI
NIH Yao (PI) 09/15/18 - 07/31/2023
SC COBRE for Musculoskeletal Health Translational Research
Role: Member