2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994

2017

 

1. Yordanov, V., Dimitrov, I., Doytchinova, I. Proteochemometrics and the MHC Binding Prediction. Lett. Drug Des. Discov., 14, 2-9, 2017 [pdf]


2016

 

1. Stavrakov, G., Valcheva, V., Voynikov, Y., Atanasova, M., Peikov, P.,Doytchinova, I. Design, synthesis and antimycobacterial activity of novel theophylline-7-acetic acid derivatives with amino acid moieties. Chem. Biol. Drug Des.,, 87, 335-341, 2016. [pdf]

2. Dimitrov, I., Doytchinova, I. Associations between main food allergens and HLA-DR/DQ polymorphism. Int. Arch. Allergy Immunol., , 169, 33-39, 2016. [pdf]

3. Stavrakov, G., Philipova, I., Zheleva, D., Atanasova, M., Konstantinov, S., Doytchinova, I. Docking-based design of galantamine derivatives with dual-site binding to acetylcholinesterase. Mol. Inf., 35, 278-285, 2016. [pdf]

4. Dimitrov I., Atanasova M., Patronov A., Flower D.R., Doytchinova, I. A cohesive and integrated platform for immunogenicity prediction. Vaccine Design. Methods and Protocols., Volume 2. Thomas S. (Ed.), Methods in Molecular Biology. Springer, 2016, 1404, pp. 761-770. [pdf]


2015

 

1. Atanasova, M., Yordanov, N., Dimitrov, I., Berkov, S., Doytchinova, I. Molecular docking study on galantamine derivatives as cholinesterase inhibitors. Mol. Inf., 34, 394-403, 2015. [pdf]

2. Dimitrov, I., Doytchinova, I. Peptide binding prediction to five most frequent HLA-DQ proteins – a proteochemometric approach. Mol. Inf., 34, 467-476, 2015. [pdf]

3. Atanasova, M., Doytchinova, I. Substrate - inositol transporte interactions: molecular docking study. Lett. Drug Des. Discov., 12, 622-627, 2015. [pdf]

4. Atanasova, M., Stavrakov, G., Philipova, I., Zheleva, D., Yordanov, N., Doytchinova, I. Galantamine derivatives with indole moiety: docking, design, synthesis and acetylcholinesterase activity Bioorg. Med. Chem., 23, 5382-5389, 2015.

5. Zhivkova, Z., Mandova, T., Doytchinova, I. Quantitative structure - pharmacokinetics relationship analysis of basic drugs: volume of distribution. J. Pharm. Pharm. Sci., 18, 515-527, 2015.[pdf]

6. Gevrenova, R., Weng, A., Voutguenne-Nazabadioko, L., Thakur, M.,Doytchinova, I. Quantitative Structure - Activity Relationship study on saponins as cytotoxicity enhancers. Lett. Drug Des. Discov., , 12, 166-171, 2015. [pdf]

7. Zheleva-Dimitrova D. Zh., Balabanova, V., Gevrenova, R., Doichinova, I., Vitkova A. Chemometrics-based Approach in Analysis of Arnicae flos. Phamacogn. Mag., , 11, S538-S544, 2015.[pdf]


2014

 

1. Patronov, A., Salamanova, E., Dimitrov, I., Flower, D. R., Doytchinova, I. Histidine hydrogen bonding in MHC at pH 5 and pH 7 modeled by molecular docking and molecular dynamics simulations. Curr. Comp.-Aid. Drug Des., 10, 41-49, 2014. [pdf]

2. Dimitrov, I., Naneva, L., Bangov, I., Doytchinova, I. Allergenicity prediction by artificial neural networks. J. Chemometr., 28, 282-286, 2014. [pdf]

3. Naneva, L., Dimitrov, I., Bangov, I., Doytchinova, I. Allergenicity prediction by partial least squares-based discriminant analysis. Bulg. Chem. Commun., 46, 389-396, 2014. [pdf]

4. Walshe V., Hattotuwagama C., Doytchinova I. , Flower D.R. A dataset of experimental HLA-B*2705 peptide binding affinities. Dataset Papers in Science, 2014, article ID 914684, 2014. [pdf]

5. Dimitrov, I., Naneva, L., Bangov, I., Doytchinova, I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics, 30(6), 846-851, 2014.[pdf]

6. Petkova, Z., Valcheva, V., Momekov, G., Petrov, P., Dimitrov, V., Doytchinova, I., Stavrakov, G., Stoyanova, M. Antimycobacterial activity of chiral aminoalcohols with camphane scaffold. Eur. J. Med. Chem., 81, 150-157, 2014.[pdf]

7. Stavrakov, G., Valcheva, V., Philipova, I., Doytchinova, I. Design of novel camphene-based derivatives with antimycobacterial activity. J. Mol. Graph. Model., 51, 7-12, 2014.[pdf]

8. Dimitrov, I., Bangov, I., Flower, D.R., Doytchinova, I. AllerTOP v.2 - a server for in silico prediction of allergens. J. Mol. Model., 20, 2278, 2014. [pdf]

9. Zhivkova, Z., Doytchinova, I. In Silico Quantitative Structure - Pharmacokinetic Relationship Modeling on Acidic Drugs: Half life. Int. J. Pharm. Pharm. Sci., 6, 283-289, 2014. [pdf]

10. Gevrenova, R., Weng, A., Voutguenne-Nazabadioko, L., Thakur, M., Doytchinova, I. Quantitative Structure - Activity Relationship study on saponins as cytotoxicity enhancers. Lett. Drug Des. Discov., 12, 166-171, 2014. [pdf]

 

2013

 

1. Patronov, A., I.A. Doytchinova: T-cell epitope vaccine design by immunoinformatics. Open Biology, 3, 120139, 2013.[pdf]

2. Dimitrov I., Flower D. R., Doytchinova I. AllerTOP - a server for in silico prediction of allergens. BMC Bioinformatics, 14 (Suppl.6), S4, 2013.[pdf]

3. Gevrenova, R., Badjakov, I., Nikolova, M., Doytchinova, I. Phenolic derivatives in raspberry (Rubus L.) germplasm collection in Bulgaria. Biochem. Syst. Ecol., 50, 419-427, 2013.[pdf]

4. Zhivkova, Z., Doytchinova, I. Quantitative structure - clearance relationships of acidic drugs. Mol. Pharmaceutics, 10(10), 3758-3768, 2013.[pdf]

5. Atanasova, M., Patronov, A., Dimitrov, I., Flower, D. R., I.A. Doytchinova EpiDOCK - a molecular docking-based tool for MHC class II binding prediction. Protein Eng. Des. Sel., 26, 631-634, 2013. [pdf]

6. Stavrakov, G., Valcheva, V., Philipova, I., Doytchinova, I. Novel camphene-based anti-tuberculosis agents with nanomolar activity. Eur. J. Med. Chem., 70, 372-379, 2013. [pdf]

7. Ivanov, S., Dimitrov, I., Doytchinova, I. Quantitative prediction of peptide binding to HLA-DP1 protein. IEEE Trans. Comp. Biol. Bioinf., 10, 811-815, 2013. [pdf]

 

2012

 

1. Zhivkova, Z., Doytchinova, I. Prediction of steady-state volume of distribution of acidic drugs by quantitative structure - pharmacokinetics relationships. J. Pharm. Sci., 101(3), 1253-1266, 2012 [pdf].

2. Valkova I., Zlatkov A., Krystyna Nedza K., Doytchinova I. Synthesis, 5-HT1A and 5-HT2A receptor affinity and QSAR study of 1-benzhydryl-piperazine derivatives with xanthine moiety at N4. Med. Chem. Res., 21(4), 477-486, 2012 [pdf].

3. Zhivkova, Z., Doytchinova, I. Quantitative structure - plasma protein binding relationships of acidic drugs. J. Pharm. Sci., 101(12), 4627-4641, 2012 [pdf].

4. Patronov, A., Dimitrov, I.Flower, D. R., Doytchinova, I. Peptide binding to HLA-DP2 proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study. BMC Struct. Biol., 12, 20, 2012 [pdf].

5. Yoncheva, K. Doytchinova, I., Tankova, L. Preparation and evaluation of isosorbide mononitrate hydrogels for topical fissure treatment. Curr. Drug Delivery, 9, 452-458, 2012.

 

2011

 

1. Bakalova A., Varbanov H., Buyukliev R., Momekov G., Ivanov D., Doytchinova I. Platinum complexes with 5-methyl-5(4-pyridyl)hydantoin and its 3-methyl derivatives: Synthesis and cytotoxic activity – quantitative structure – activity relationships. Arch. Pharm. Chem. Life Sci., 344(4), 209-216, 2011 [pdf].

2. Atanasova, M., Dimitrov, I., Flower, D. R., Doytchinova, I. MHC class II binding prediction by molecular docking. Mol. Informatics, 30(4), 368-375, 2011 [pdf].

3. Dimitrov I., Flower D. R., Doytchinova I. Improving in silico prediction of epitope vaccine candidates by union and intersection of single predictors. World J. Vaccines, 1(2), 15-22, 2011 [pdf].

4. Patronov, A., Dimitrov, I., Flower, D. R., Doytchinova, I. Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach. BMC Struct. Biol., 11:32, 2011 [pdf].

5. Doytchinova, I., Petkov, P., Dimitrov, I., Atanasova, M., Flower, D. R. HLA-DP2 binding prediction by molecular dynamics simulations. Protein Sci., 20(11), 1918-1928, 2011 [pdf].

 

 

2010

 

1. Dimitrov, I. , P. Garnev, D. R. Flower, I. Doytchinova: Peptide binding to the HLA-DRB1 sypertype: A proteochemometric analysis, Eur. J. Med. Chem., 45(1), 236-243, 2010 [pdf].

2. Solankee, A., K. Kapadia, A. Ćirić, M. Soković, I. Doytchinova, A. Geronikaki: Synthesis of some new S-triazine based chalcones and their derivatives as potent antimicrobial agents, Eur. J. Med. Chem., 45(2), 510-518, 2010 [pdf].

3. Yoncheva, K.,I. Doytchinova, J. M. Irache: Different approaches for determination of the attachment degree of polyethylene glycols to poly(anhydride) nanoparticles, Drug Develop. Ind. Pharm., 36(6), 676-680, 2010 [pdf]

4. Dimitrov, I., P. Garnev, D. R. Flower, I. Doytchinova: MHC clas binding prediction - a little help from a friend. J. Biomed. Biotech., 2010, article ID 705821, 2010 [pdf].

5. Dimitrov, I., P. Garnev, D. R. Flower, I. Doytchinova: EpiTOP - a proteochemometric tool for MHC class II binding prediction. Bioinformatics, 26(16), 2066-2068, 2010 [pdf].

6. D.R. Flower, I.K. Macdonald, K. Ramakrishnan, M.N. Davies, I.A. Doytchinova: Computer-aided selection of candidate vaccine antigens. Immunome Res., 6(Suppl. 2), S1, 2010 [pdf]

 

2009

 

1. Tankova, L., K. Yoncheva, D. Kovatchki, I. Doytchinova: Topical and fissure treatment: placebo-controlled study of mononitrate and trinitrate therapies.  Int J. Colorectal Dis., 24(1), 461-464, 2009.

2. Walshe, V. A., Hattotuwagama, C. K., Doytchinova, I., Wong, M., Macdonald, I. K., Mulder, A., Claas, F. H. J., Pellegrino, P., Turner, J., Williams, I., Turnbull, E. L., Borrow, P., Flower, D. R. Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: A bioinformatic approach to the prediction of new epitopes. PLoS ONE, 4(11), e8095, 2009. [pdf]

 

2008

 

1. Doytchinova, I.A., D.R. Flower: Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines.  The Open Vaccine Journal, 1(1), 22-26, 2008. [pdf]

2. Doytchinova, I.A., D.R. Flower: QSAR and the prediction of T-cell epitopes. Current Proteomics, 5(2), 73-95, 2008. [pdf]

 

2007

 

1. Doytchinova, I.A., D.R. Flower: Predicting T cell epitopes using multivariate statistics: Comparison of discriminant analysis and multiple linear regression. J. Chem. Inf. Model., 47(1), 234-238, 2007. [pdf]

2. Davies, M. N., P. Guan, M.J. Blythe, J. Salomon, C.P. Toselan, C. Hattotuwagama, V. Walshe, I.A. Doytchinova, D.R. Flower: Using databases and data mining in vaccinology. Expert Opin. Drug Discov., 2(1), 19-35, 2007. [pdf]

3. Hattotuwagama, C.K., P. Guan, M. Davies, D.J. Taylor, V. Walshe, S.L. Hemsley, C. Toseland, I.A. Doytchinova, P. Borrow, D.R. Flower: Empirical, AI, and QSAR Approaches to Peptide – MHC Binding Prediction. In: In silico Immunology. (Eds. D.R. Flower, J. Timmis), Springer, New York, 139-176, 2007.

4. Guan, P., I.A. Doytchinova, D.R. Flower: Identifying Major Histocompatibility Complex Supertypes. In: In silico Immunology. (Eds. D.R. Flower, J. Timmis), Springer, New York, 197-234, 2007.

5. Guan, P., I.A. Doytchinova, D.R. Flower: The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods. In: Immunoinformatics: Predicting Immunogenicity In Silico, Series: Methods in Molecular Biology, Vol. 409, (Ed. D.R. Flower), 143-154, 2007.

6. Hattotuwagama, C., I.A. Doytchinova, D.R. Flower: Towards the Prediction of Class I and II Mouse Major Histocompatibility Complex Peptide Binding Affinity: In Silico Bioinformatic Step by Step Guide Using Quantitative Structure-Activity Relationships. In: Immunoinformatics: Predicting Immunogenicity In Silico, Series: Methods in Molecular Biology, Vol. 409, (Ed. D.R. Flower), 227-245, 2007.

7. Hattotuwagama, C.K., P. Guan, I.A. Doytchinova, D.R. Flower: In Silico QSAR-Based Predictions of Class I and Class II MHC Epitopes. In: Immunoinformatics (Eds. C. Schoenbach, S. Ranganathan, V. Brusic), Sprinder Science+Business Media, LLC, New York , 63 – 89, 2007.

8. Doytchinova, I.A., D.R. Flower: Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties. Vaccine, 25(5), 856-866, 2007. [pdf]

9. Doytchinova, I.A., D.R. Flower: VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines.  BMC Bioinformatics, 8, 4, http://www.biomedcentral.com/1471-2105/8/4, 2007.

10. Slavov, S., M. Atanasova, B. Galabov: QSAR analysis of the anticancer activity of 2,5-disubstituted 9-aza-anthrapyrazoles, QSAR & Comb. Chem., 26(2), 173-181, 2007.

11. Atanasova, M., Ilieva, S., Galabov, B.: QSAR analysis of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines with anticancer activity, Eur. J. Med. Chem., 42(9), 1184-1192, 2007.

 

2006

 

1.  Vicini, P., M. Incerti, I. A. Doytchinova, P. La Colla, B. Busonera, R. Loddo. Synthesis and antiproliferative activity of benzo[d]isothiazole hydrazones. Eur. J. Med. Chem., 2006, 41, 624-632. [pdf]

2.  Hattotuwagama, C.K., C.P. Toseland, P. Guan, D.J. Taylor, S.L. Hemsley, I.A. Doytchinova, D.R. Flower: Toward Prediction of Class II Mouse Major Histocompatibility Complex Peptide Binding Affinity: In Silico bioinformatic Evaluation Using Partial Least Squares, a Robust Multivariate Statistical Technique. J. Chem. Inf. Model., 46(3), 1491-1502, 2006. [pdf]

3.  Guan, P., I. Doytchinova, C. Hattotuwagama, D.R. Flower: MHCPred 2.0, an updated quantitative T cell epitope prediction server. Appl. Bioinformatics, 5(1), 55-61, 2006. [pdf]

4.  Doytchinova, I.A., D.R. Flower: Class I T cell epitope prediction: improvements using a combination of Proteasome cleavage, TAP affinity, and MHC binding. Mol. Immun., 43(13), 2037-2044, 2006. [pdf]

5.  Doytchinova, I.A., P. Guan, D.R. Flower: EpiJen: a server for multi-step T cell epitope prediction. BMC Bioinformatics, 7, 131, http://www.biomedcentral.com/ 1471-2105/7/131, 2006.

6.  Doytchinova, I.A., D.R. Flower: Modeling the peptide – T cell receptor interaction by the Comparative Molecular Similarity Indices Analysis – Soft Independent Modeling of Class Analogy technique. J. Med. Chem., 49(7), 2193-2199, 2006. [pdf]

 

2005

 

1. Doytchinova, I.A., D.R. Flower: In silico identification of supertypes for Class II Major Histocompatibility Complexes. J. Immunol., 174(11), 7085-7095, 2005. [pdf]

2. Doytchinova, I.A., V. Walshe, P. Borrow, D.R. Flower: Towards the chemometric dissection of peptide-HLA-A*0201 binding affinity: comparison of local and global QSAR models. J. Comput. Aid. Mol. Des., 19(3), 203-212, 2005. [pdf]

3. Hattotuwagama, C.K., I.A. Doytchinova, D.R. Flower: In Silico prediction of peptide binding affinity to class I mouse major histocompatibility complexes: A Comparative Molecular Similarity Index Analysis (CoMSIA) study. J. Chem. Inf. Model., 45(5), 1415-1426, 2005. [pdf]

4. Guan, P., I.A. Doytchinova, V.A. Walshe, P. Borrow, D.R. Flower: Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for HLA-A*0201. J. Med. Chem., 48(23), 7418-7425, 2005. [pdf]

5. Toseland C.P., D.J. Taylor, H. McSparron, S.L. Hemsley, M.J. Blythe, K. Paine, I.A. Doytchinova, P. Guan, C.K. Hattotuwagama, D.R. Flower: AntiJen: a quantitative immunology database integrating functional, thermodynamic, kinetic, biophysical and cellular data. Immunome Res., 1: 4. http://www.immunone-research.com/content/ 1/1/4, 2005. [pdf]

6. Guan, P., M. Davies, D.J. Taylor , S. Wan, H. McSparron, S.L. Hemsley, C. Toseland, M.J. Blythe, P.D. Taylor, V. Walshe, C.K. Hattotuwagama, I.A. Doytchinova, P.V. Coveney, P. Borrow, D.R..Flower: Computational Chemistry, Informatics, and the Discovery of Vaccines. Current Computer-Aided Drug Design, 1(4), 377-398, 2005.

 

2004

 

1. Doytchinova, I.A., P. Guan, D. R. Flower. Identifiying human MHC supertypes using bioinformatic methods. J. Immunol., 172(7), 4314 4323, 2004. [pdf]

2. Hattotuwagama, C.K., P. Guan, I.A. Doytchinova, C. Zygouri, D.R. Flower: Quantitative online prediction of peptide binding to the major histocompatibility complex. J. Mol. Graph. Model., 22(3), 195-207, 2004. [pdf]

3. Doytchinova, I.A., V.A. Walshe, N.A. Jones, S.E. Gloster, P. Borrow, D.R. Flower: Coupling in silico and in vitro analysis of peptide–MHC binding: A bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes. J. Immunol., 172(12), 7495-7502, 2004. [pdf]

4. Doytchinova, I.A., S. Hemsley, D.R. Flower: Transporter associated with antigen processing preselection of peptides binding to the MHC: A Bioinformatic evaluation. J. Immunol., 173(11), 6813-6819, 2004. [pdf]

5. Hattotuwagama, C.K., P. Guan, I.A. Doytchinova, D.R. Flower: New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity. Org. Biomol. 
Chem., 2(22), 3274-3283, 2004. [pdf] 

6.Doytchinova, I.A., P. Guan, D.R. Flower: Quantitative structure – activity relationships and the prediction of MHC supermotifs. Methods, 34(4), 444-453, 2004. [pdf]

7. Valkova, I., Vračko, M., Basak, S.C., Modeling of structure-mutagenicity relationships: Counter propagation neural network approach using calculated structural descriptors  Analytica Chimica Acta 509 (2), 179-186, 2004

 

2003

 

1. Panico A.M., A. Geronikaki, R. Mgonzo, V. Cardile, B. Gentile, I. Doytchinova. Aminothiazole derivatives with antidegenerative activity on cartilage. Bioorg. & Med. Chem., 11, 2003, 13, 2983 – 2989.

2. Guan P., I.A. Doytchinova, D.R. Flower: HLA-A3-supermotif defined by quantitative structure-activity relationship analysis. Protein Eng., 16(1), 11-18, 2003. [pdf]

3. Guan, P., I.A. Doytchinova, C.Zygouri, D.R. Flower: MHCPred: bringing a  quantitative dimension to the online prediction of MHC binding. Appl. Bioinformatics, 2(1), 63-66, 2003. [pdf]

4. Guan, P., I.A. Doytchinova, C.Zygouri, D.R. Flower: MHCPred: a server for quantitative prediction of peptide-MHC binding. Nucleic Acids Res., 31(13), 3621-3624, 2003. [pdf]

5. Guan, P., I.A. Doytchinova, D.R. Flower: A Comparative Molecular Similarity Indices (CoMSIA) study of peptides binding to the HLA-A3 superfamily. Bioorgan. Med. Chem., 11(10), 2307-2311, 2003. [pdf]

6. Doytchinova, I.A., D.R. Flower: The HLA-A2-supermotif: A QSAR definition. Org. Biomol. Chem., 1(15), 2648-2654, 2003. [pdf]

7. McSparron, H., M.J. Blythe, C. Zygouri, I.A. Doytchinova, D.R. Flower: JenPep: A Novel Computational Information Resource for Immunobiology and Vaccinology. J. Chem. Inf. Comp. Sci., 43(4), 1276 – 1287, 2003. [pdf]

8. Doytchinova, I.A., D.R. Flower: Towards the in silico identification of class II restricted T cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction. Bioinformatics, 19(17), 2263 – 2270, 2003. [pdf]

9. Doytchinova, I.A., P. Taylor, D.R. Flower: Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone. J. Biomed. Biotechnol., 2003(5), 267 – 290, 2003. [pdf]

10. Flower, D.R., H. McSparron, M.J. Blythe, C. Zygouri, D. Taylor, P. Guan, S. Wan, P. Coveney, V. Walshe, P. Borrow, I.A. Doytchinova: Computational vaccinology: quantitative approaches. In: Immunoinformatics: Bioinformatic Strategies for Better Understanding of Immune Function, (Eds. G. Bock, J. Goode), Wiley J. & Sons Ltd., Chichester, 102-120, 2003.

 

2002

 

1. Doytchinova, I., I. Valkova, R. Natcheva. Adenosine A2A receptor agonists: CoMFA – based selection of the most predictive conformation. SAR QSAR Environ. Res., 13, 2002, 2, 227-235.

2. Vicini P., F. Zani, P. Cozzini, I. Doytchinova. Hydrazones of 1,2-benzisothiazole hydrazides: synthesis, antimicrobial activity and QSAR investigations. Eur. J. Med. Chem., 37, 2002, 553-564.

3. Blythe, M.J., I.A. Doytchinova, D.R. Flower: JenPep: a database of quantitative functional peptide data for immunology. Bioinformatics, 18(3), 434-439, 2002. [pdf]

4. Doytchinova, I.A., M.J. Blythe, D.R. Flower: Additive Method for the Prediction of Protein-Peptide Binding Affinity. Application to the MHC Class I Molecule HLA-A*0201. J. Proteome Res., 1(3), 263-272, 2002. [pdf]

5. Doytchinova, I.A., D.R. Flower: Physicochemical explanation of peptide binding to HLA-A*0201 major histocompatibility complex: A three-dimensional quantitative structure-activity relationship study. PROTEINS, 48(3), 505-518, 2002. [pdf]

6. Doytchinova, I.A., D.R. Flower: A Comparative Molecular Similarity Index Analysis (CoMSIA) study identifies an HLA-A2 binding supermotif. J. Comput. Aid. Mol. Des., 16(8-9), 535-544, 2002. [pdf]

7. Doytchinova I.A., D.R. Flower: Quantitative approaches to computational vaccinology. Immunol. Cell Biol., 80(3), 270-279, 2002. [pdf]

8. Flower, D.R., I.A. Doytchinova: Immunoinformatics and the prediction of immunogenicity. Appl. Bioinformatics, 1(4), 167-176, 2002. [pdf]

9. Flower, D.R., I.A. Doytchinova, K. Paine, P. Taylor, M.J. Blythe, D. Lamponi, C. Zygouri, P. Guan, H. McSparron, H. Kirkbride: Computational Vaccine Design. In: Drug Design: Cutting Edge Approaches, (Ed. D.R. Flower), RSC publications, Cambridge, 136-180, 2002.

10. Aptula, A.O., Netzeva, T.I., Valkova, I.V., Cronin, M.T.D., Schultz, T.W., Kühne, R., Schüürmann, G,. Multivariate discrimination between modes of toxic action of phenols  Quantitative Structure-Activity Relationships 21 (1), 12-22, 2002.

11. Mitcheva, M., Vitcheva, V., Manolov, I., Valkova, I., Effects of two newly synthesized 4-hydroxycoumarin derivatives (4-OHC) on isolated rat hepatocytes   Methods and Findings in Experimental and Clinical Pharmacology 24 (6), 345-349, 2002.

12. Cronin, M.T.D., Aptula, A.O., Duffy, J.C., Netzeva, T.I., Rowe, P.H., Valkova, I.V., Schultz, T.W., Comparative assessment of methods to develop QSARs for the prediction of the toxicity of phenols to Tetrahymena pyriformis,  Chemosphere 49 (10), 1201-1221, 2002.

 

2001

 

1. Doytchinova, I. CoMFA-Based Comparison of Two Models for Binding Site on Adenosine A1 receptors. J. Comput.-Aid. Mol. Des., 15, 2001, 1, 29-39.

2. Doytchinova, I., D.R.Flower. Towards the quantitative prediction of T-cell epitopes: CoMFA and CoMSIA studies of peptides with affinity to class I MHC molecule HLA-A*0201. J. Med. Chem., 44, 2001, 3572-3581. [pdf]

3. Doytchinova, I., I. Valkova, R. Natcheva. CoMFA Study on Adenosine A2A Receptor Agonists. Quant. Struct. – Act. Relat., 20, 2001, 2, 124-129.

 

2000

 

1. Netzeva, T., I. Doytchinova, R. Natcheva. 2D and 3D QSAR analysis of some valproic acid metabolites and analogues as anticonvulsant agents. Pharmaceut. Res., 17, 2000, 6, 727-732.

2. Dimitrova, B., I. Doytchinova, M. Zlatkova. Reversed-phase high-performance liquid chromatography for evaluating the distribution behavior of pharmaceutical substances in suppository base Witepsol H15-phosphate buffer system. J. Pharmaceut. Biomed. Anal., 23, 2000, 955-964.

 

 

1999

 

1.     Heun, G., N.Lambov, A.Zlatkov, P.Peikov, I.Doytchinova, K.Gesheva. Biodegradable cross-linked prodrug of the bronchial dilator Vephylline: II. Kinetics and quantum chemical studies on the release mechanism. J. Control. Release, 58, 1999, 189-194.

2.     Hadjipavlou-Litina, D., A. Geronikaki, R. Mgonzo, I. Doytchinova. Thiazolyl-N-substituted amides: a group of effective anti inflammatory agents with potential for local anaesthetic properties. Synthesis, biological evaluation and a QSAR approach. Drug Develop. Res., 48, 1999, 53-60.

3.     Netzeva, T., R. Natcheva, I. Doytchinova. A QSAR Study of Some Ethers of Dihydroartemisinin as Antimalarial Agents. Pharmacia, Sofia, 46, 1999, 1, 5-10.

 

1998

 

1.     Doytchinova, I. , S.Petrova. “N6-N7” - a Modification of the “N6-C8” Model for the Binding Site on Adenosine A1 Receptors with Improved Steric and Electrostatic Fit. Med.Chem.Res., 8, 1998, 3, 143-152.

2.     Netzeva, T., R.Natcheva, I.Doytchinova, I.Lesigiarska, D.Mihailova. Theoretical investigation of the chemical structure and QSAR-analysis of a series of 9-substituted artemisinin derivatives. Archives of the Balkan Medical Union , 33, 1998, 4, 189-198.

 

 

1997

 

1.     Doytchinova, I. , R.Natcheva. QSAR-Study on a Series of 1,4-disubstituted Piperazines with Analgesic Activity. Acta Pharm., 47, 1997, 3, 189-195.

 

1995

 

1.     Дойчинова, И., Р. Начева, Д. Михайлова. QSAR анализ на серия новосинтезирани производни на ксантина. Фармация, София, 43, 1995, 1, 8-12.

2.     Дойчинова, И., Р. Начева, Д. Михайлова. QSAR анализ на серия 3-пропилксантини с бронходилатиращо действие. Фармация, София, 43, 1995, 5-6, 30-36.

 

1994

 

1.     Doichinova, I.A., R.N.Natcheva, D.N.Mihailova. QSAR-Studies of 8-Substituted Xanthines as Adenosine Receptors Antagonists. Eur. J. Med. Chem., 29, 1994, 2, 133-138.