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Last Name

Konstantin B Zeldovich PhD

TitleAdjunct Assistant Professor
InstitutionUniversity of Massachusetts Medical School
DepartmentBiochemistry and Molecular Pharmacology
AddressUniversity of Massachusetts Medical School
55 Lake Avenue North
Worcester MA 01655
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    Other Positions
    InstitutionUMMS - School of Medicine
    DepartmentBiochemistry and Molecular Pharmacology

    InstitutionUMMS - Graduate School of Biomedical Sciences
    DepartmentBiochemistry and Molecular Pharmacology

    InstitutionUMMS - Graduate School of Biomedical Sciences
    DepartmentBioinformatics and Computational Biology

    InstitutionUMMS - Graduate School of Biomedical Sciences
    DepartmentTranslational Science

    InstitutionUMMS - Programs, Centers and Institutes
    DepartmentBioinformatics and Integrative Biology

    Collapse Biography 
    Collapse education and training
    Moscow State University, Moscow, , Russian FederationMSPhysics
    Moscow State University, Moscow, , Russian FederationPHDPhysics & Mathematics

    Collapse Overview 
    Collapse overview


    Konstantin Zeldovich graduated from Moscow State University in Russia in 1998 with a M.S. in Physics. In 2001, he received his PhD in physics and mathematics also from Moscow State University. His thesis research, supervised by Prof. Alexei Khokhlov, was focused on the theoretical study of gels and adsorbed layers of charged polymers, or polyelectrolytes. Between 2002 and 2004, Dr. Zeldovich was a postdoctoral fellow at the Institut Curie in Paris, France, where he worked in the area of statistical physics of molecular motors, such as kinesin and myosin in the laboratory of Profs. J.-F. Joanny and J.Prost. Later, from 2004 till August 2008, Dr. Zeldovich was a postdoctoral fellow at the laboratory of Prof. Eugene Shakhnovich at the Department of Chemistry and Chemical Biology, Harvard University. His research there focused on developing novel, physics-inspired models of molecular evolution, as well as protein thermostability and their sequence-structure relationships.

    On September 1, 2008, Dr. Zeldovich was appointed tenure-track assistant professor at the Program in Bioinformatics and Integrative Biology at the University of Massachusetts Medical School. His research deals with molecular evolution, and protein folding, stability, and interactions.

    Physics-based models of molecular evolution

    Earlier, we have proposed a new model of molecular evolution, which considers evolution as a diffusion process in the space of stabilities of the organism’s proteins [Zeldovich, Chen, Shakhnovich, PNAS 2007]. Indeed, when a protein undergoes a mutation, its thermodynamic stability (folding free energy dG) changes by a small amount. In present-day proteins, these changes are normally detrimental, decreasing the stability. However, a small fraction of mutations makes proteins more stable. Looking at each protein, this process can be thought of as a biased diffusion along the coordinate of dG. Now, consider the organism as a whole, containing N proteins in the genome. Exceptional cases aside, all of the essential proteins encoded by the organism’s genome must be stable (dG<0) in order to work properly. Otherwise, the organism may not be viable. A mathematical treatment of this problem leads to a diffusion equation with an absorbing boundary, which allows an exact solution. In agreement with bioinformatics data, the model predicts that organisms with higher mutation rates have shorter genomes (e.g. RNA-based vs DNA-based viruses), organisms living at elevated temperatures (thermophiles) have shorter genomes, and the probability distribution of stability of evolved proteins has a certain shape.

    Future research along these lines includes explicit consideration of the genetic code, intrinsically unstructured proteins, and incorporation of epistasis, where effects of mutation in one gene can be significantly altered by a mutation in another gene.

    Protein Thermostability

    What can one say about a bacterium just by looking at its genome? It turns out that the temperature of the natural environment of the bacterium can be inferred just by looking at the amino acid composition of the bacterium’s proteins [Zeldovich, Berezovsky, Shakhnovich, PLoS Comp Biol 2007]. The sum of the fractions of amino acids IVYWREL in the genome can be used to predict the environmental temperature up to about 10 degree C. A simple model of lattice proteins [Berezovsky, Zeldovich, Shakhnovich, PLoS Comp Biol 2007] suggested that amino acids responsible for high thermostability must come from the opposite ends of the hydrophobicity spectrum, i.e. the magic combination should contain both very hydrophobic and very hydrophilic amino acids. Unfortunately, we are still lacking the microscopic understanding as to why exactly these amino acids are so tightly linked to thermostability.

    One of the research projects of the lab involves extensive Monte-Carlo simulations of proteins under different temperatures, aimed at the precise, quantitative understanding of the mechanisms of protein thermostability evolved in the thermophiles’ inhospitable world.

    Protein Folding in Crowded Environments

    Most of the conventional models of protein folding deal with a single polypeptide chain, sometimes with an explicit consideration of the surrounding water molecules. However, as it is now understood, these conditions are seldom realized in vivo, as the volume fraction of macromolecules inside a living cell can reach 0.2. Thus, collisions and interactions between proteins (all kinds – folded, misfolded, and nascent chains) are the norm, rather than exception. Previous research, both experimental and computation, has shown that putting mechanical constraints on a folding protein may significantly alter its folding kinetics and maybe even the stability of the native state. Also, avoidance of promiscuous interactions in a dense protein environment might have imposed specific evolutionary constraints on protein sequences.

    One of the research projects in the lab includes analytical calculations and computer modeling of protein folding in crowded environments and looking for the possible “crowding-mitigating” signatures in real proteins.

    Collapse Rotation Projects
    Rotation projects: Biophysics of molecular evolution; selection pressure on amino acid composition of the whole proteome; evolution of the genetic code

    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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    1. Chan YH, Venev SV, Zeldovich KB, Matthews CR. Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints. Nat Commun. 2017 Mar 06; 8:14614. PMID: 28262665.
      View in: PubMed
    2. Prachanronarong KL, Özen A, Thayer KM, Yilmaz LS, Zeldovich KB, Bolon DN, Kowalik TF, Jensen JD, Finberg RW, Wang JP, Kurt-Yilmaz N, Schiffer CA. Molecular Basis for Differential Patterns of Drug Resistance in Influenza N1 and N2 Neuraminidase. J Chem Theory Comput. 2016 Dec 13; 12(12):6098-6108. PMID: 27951676.
      View in: PubMed
    3. Bank C, Renzette N, Liu P, Matuszewski S, Shim H, Foll M, Bolon DN, Zeldovich KB, Kowalik TF, Finberg RW, Wang JP, Jensen JD. An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy. Evolution. 2016 Nov; 70(11):2470-2484. PMID: 27566611.
      View in: PubMed
    4. Jiang L, Liu P, Bank C, Renzette N, Prachanronarong K, Yilmaz LS, Caffrey DR, Zeldovich KB, Schiffer CA, Kowalik TF, Jensen JD, Finberg RW, Wang JP, Bolon DN. A Balance between Inhibitor Binding and Substrate Processing Confers Influenza Drug Resistance. J Mol Biol. 2016 Feb 13; 428(3):538-53. PMID: 26656922.
      View in: PubMed
    5. Venev SV, Zeldovich KB. Massively parallel sampling of lattice proteins reveals foundations of thermal adaptation. J Chem Phys. 2015 Aug 7; 143(5):055101. PMID: 26254668.
      View in: PubMed
    6. Zeldovich KB, Liu P, Renzette N, Foll M, Pham ST, Venev SV, Gallagher GR, Bolon DN, Kurt-Jones EA, Jensen JD, Caffrey DR, Schiffer CA, Kowalik TF, Wang JP, Finberg RW. Positive Selection Drives Preferred Segment Combinations during Influenza Virus Reassortment. Mol Biol Evol. 2015 Jun; 32(6):1519-32. PMID: 25713211.
      View in: PubMed
    7. Foll M, Poh YP, Renzette N, Ferrer-Admetlla A, Bank C, Shim H, Malaspinas AS, Ewing G, Liu P, Wegmann D, Caffrey DR, Zeldovich KB, Bolon DN, Wang JP, Kowalik TF, Schiffer CA, Finberg RW, Jensen JD. Influenza virus drug resistance: a time-sampled population genetics perspective. PLoS Genet. 2014 Feb; 10(2):e1004185. PMID: 24586206.
      View in: PubMed
    8. Renzette N, Caffrey DR, Zeldovich KB, Liu P, Gallagher GR, Aiello D, Porter AJ, Kurt-Jones EA, Bolon DN, Poh YP, Jensen JD, Schiffer CA, Kowalik TF, Finberg RW, Wang JP. Evolution of the influenza A virus genome during development of oseltamivir resistance in vitro. J Virol. 2014 Jan; 88(1):272-81. PMID: 24155392.
      View in: PubMed
    9. Jiang L, Mishra P, Hietpas RT, Zeldovich KB, Bolon DN. Latent effects of Hsp90 mutants revealed at reduced expression levels. PLoS Genet. 2013 Jun; 9(6):e1003600. PMID: 23825969.
      View in: PubMed
    10. Venev SV, Zeldovich KB. Segment self-repulsion is the major driving force of influenza genome packaging. Phys Rev Lett. 2013 Mar 1; 110(9):098104. PMID: 23496749.
      View in: PubMed
    11. Roscoe BP, Thayer KM, Zeldovich KB, Fushman D, Bolon DN. Analyses of the effects of all ubiquitin point mutants on yeast growth rate. J Mol Biol. 2013 Apr 26; 425(8):1363-77. PMID: 23376099.
      View in: PubMed
    12. Zeldovich KB, Shakhnovich EI. Understanding protein evolution: from protein physics to Darwinian selection. Annu Rev Phys Chem. 2008; 59:105-27. PMID: 17937598.
      View in: PubMed
    13. Zeldovich KB, Chen P, Shakhnovich EI. Protein stability imposes limits on organism complexity and speed of molecular evolution. Proc Natl Acad Sci U S A. 2007 Oct 9; 104(41):16152-7. PMID: 17913881.
      View in: PubMed
    14. Zeldovich KB, Chen P, Shakhnovich BE, Shakhnovich EI. A first-principles model of early evolution: emergence of gene families, species, and preferred protein folds. PLoS Comput Biol. 2007 Jul; 3(7):e139. PMID: 17630830.
      View in: PubMed
    15. Wallin S, Zeldovich KB, Shakhnovich EI. The folding mechanics of a knotted protein. J Mol Biol. 2007 May 4; 368(3):884-93. PMID: 17368671.
      View in: PubMed
    16. Berezovsky IN, Zeldovich KB, Shakhnovich EI. Positive and negative design in stability and thermal adaptation of natural proteins. PLoS Comput Biol. 2007 Mar 23; 3(3):e52. PMID: 17381236.
      View in: PubMed
    17. Zeldovich KB, Berezovsky IN, Shakhnovich EI. Protein and DNA sequence determinants of thermophilic adaptation. PLoS Comput Biol. 2007 Jan 12; 3(1):e5. PMID: 17222055.
      View in: PubMed
    18. Zeldovich KB, Berezovsky IN, Shakhnovich EI. Physical origins of protein superfamilies. J Mol Biol. 2006 Apr 7; 357(4):1335-43. PMID: 16483605.
      View in: PubMed
    19. Minc N, Bokov P, Zeldovich KB, Fütterer C, Viovy JL, Dorfman KD. Motion of single long DNA molecules through arrays of magnetic columns. Electrophoresis. 2005 Jan; 26(2):362-75. PMID: 15657884.
      View in: PubMed
    20. Leduc C, Campàs O, Zeldovich KB, Roux A, Jolimaitre P, Bourel-Bonnet L, Goud B, Joanny JF, Bassereau P, Prost J. Cooperative extraction of membrane nanotubes by molecular motors. Proc Natl Acad Sci U S A. 2004 Dec 7; 101(49):17096-101. PMID: 15569933.
      View in: PubMed
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