Alexis Ivanov

Prof. Alexis Ivanov


Research Focus & Metrics

Academic Career Length

52Years (1975-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2013 in Analytica Chimica Acta
Verified
Journal Article
Closed access
OGOksana Gnedenko
Oksana Gnedenko
YMYuri Mezentsev
Yuri Mezentsev
AMAndrey A. Molnar
Andrey A. Molnar
ALAndrey V. Lisitsa
Andrey V. Lisitsa
AIAlexis Ivanov
Alexis Ivanov
AAAlexander I. Archakov
Alexander I. Archakov

1 November 2002 in Journal of Molecular Recognition
Verified
Journal Article
Closed access
PDF file
AVAlexander Vladimirovich Veselovsky
Alexander Vladimirovich Veselovsky
YIYu. D. Ivanov
Yu. D. Ivanov
AIAlexis Ivanov
Alexis Ivanov
AAA. I. Archakov
A. I. Archakov
PLP. Lewi
P. Lewi
PJP. Janssen
P. Janssen

1 March 2010 in Biosensors and Bioelectronics
Verified
Journal Article
Closed access
ESElena Suprun
Elena Suprun
TBTatiana Bulko
Tatiana Bulko
ALAlexander Lisitsa
Alexander Lisitsa
OGOksana Gnedenko
Oksana Gnedenko
AIAlexis Ivanov
Alexis Ivanov
AAAlexander Archakov
Alexander Archakov

1 March 2003 in Current Drug Targets - Infectious Disorders
Verified
Journal Article
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AVAlexander Vladimirovich Veselovsky
Alexander Vladimirovich Veselovsky
AIAlexis Ivanov
Alexis Ivanov
Modern strategies of computer-aided drug design (CADD) are reviewed. The task of CADD in the pipeline of drug discovery is accelerating of finding the new lead compounds and their structure optimization for the following pharmacological tests. The main directions in CADD are based on the availability of the experimentally determined three-dimensional structure of the target macromolecule. If spatial structure is known the methods of structure-based drug design are used. In the opposite case the indirect methods of CADD based on the structures of known ligands (ligand-based drug design) are used. The interrelationship between the main directions of CADD is reviewed. The main CADD approaches of molecule de novo design and database mining are described. They include methods of molecular docking, de novo design, design of pharmacophore and quantity structure-activity relationship models. New ways and perspectives of CADD are discussed.

22 August 2011 in The FASEB Journal
Verified
Journal Article
Open access
PDF file
AGAlexander Gabibov
Alexander Gabibov
ABAlexey A. Belogurov
Alexey A. Belogurov
YLYakov A. Lomakin
Yakov A. Lomakin
MZMaria Yu Zakharova
Maria Yu Zakharova
MAMarat E. Avakyan
Marat E. Avakyan
NTNina V. Tikunova
Nina V. Tikunova
Multiple sclerosis (MS) is a widespread neurodegenerative autoimmune disease with unknown etiology. It is increasingly evident that, together with pathogenic T cells, autoreactive B cells are among the major players in MS development. The analysis of myelin neuroantigen‐specific antibody repertoires and their possible cross‐reactivity against environmental antigens, including viral proteins, could shed light on the mechanism of MS induction and progression. A phage display library of single‐chain variable fragments (scFvs) was constructed from blood lymphocytes of patienst with MS as a potential source of representative MS autoantibodies. Structural alignment of 13 clones selected toward myelin basic protein (MBP), one of the major myelin antigens, showed high homology within variable regions with cerebrospinal fluid MS‐associated antibodies as well as with antibodies toward Epstein‐Barr latent membrane protein 1 (LMP1). Three scFv clones showed pronounced specificity to MBP fragments 65–92 and 130–156, similar to the serum MS antibodies. One of these clones, designated E2, in both scFv and full‐size human antibody constructs, was shown to react with both MBP and LMP1 proteins in vitro , suggesting natural cross‐reactivity. Thus, antibodies induced against LMP1 during Epstein‐Barr virus infection might act as inflammatory trigger by reacting with MBP, suggesting molecular mimicry in the mechanism of MS pathogenesis.—Gabibov, A. G., Belogurov, A. A., Jr. Lomakin, Y. A., Zakharova, M. Y., Avakyan, M. E., Dubrovskaya, V. V., Smirnov, I. V., Ivanov, A. S., Molnar, A. A., Gurtsevitch, V. E., Diduk, S. V., Smirnova, K. V., Avalle, B., Sharanova, S. N., Tramontano, A., Friboulet, A., Boyko, A. N., Ponomarenko, N. A., Tikunova, N. V. Combinatorial antibody library from multiple sclerosis patients reveals antibodies that cross‐react with myelin basic protein and EBV antigen. FASEB J. 25, 4211–4221 (2011). www.fasebj.org

25 February 2011 in Molecular BioSystems
Verified
Journal Article
Closed access
PDF file
SKSergey A. Kozin
Sergey A. Kozin
YMYuri Mezentsev
Yuri Mezentsev
AKAlexandra A Kulikova
Alexandra A Kulikova
MIMaria I Indeykina
Maria I Indeykina
AGAndrey V. Golovin
Andrey V. Golovin
AMAlexander Makarov
Alexander Makarov
Analysis of complex formation between amyloid-β fragments using surface plasmon resonance biosensing and electrospray mass spectrometry reveals that region 11–14 mediates zinc-induced dimerization of amyloid-β and may serve as a potential drug target for preventing development and progression of Alzheimer's disease.