I. Doytchinova

发表

Identifiying Human MHC Supertypes Using Bioinformatic Methods

D. Flower, I. Doytchinova, P. Guan, 2004, The Journal of Immunology.

AntiJen: a quantitative immunology database integrating functional, thermodynamic, kinetic, biophysical, and cellular data

Channa K. Hattotuwagama, Shelley L. Hemsley, D. Flower, 2005, Immunome research.

Journal of Proteomics & Bioinformatics

Irini A. Doytchinova, Darren R. Flower, Ivan Dimitrov, 2022 .

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties.

D. Flower, I. Doytchinova, 2007, Vaccine.

Bridging solvent molecules mediate RNase A – Ligand binding

I. Doytchinova, I. Dimitrov, Stefan Ivanov, 2019, PloS one.

Transporter Associated with Antigen Processing Preselection of Peptides Binding to the MHC: A Bioinformatic Evaluation

Shelley L. Hemsley, D. Flower, I. Doytchinova, 2004, The Journal of Immunology.

QSAR and the Prediction of T-Cell Epitopes

D. Flower, I. Doytchinova, 2008 .

Toward the quantitative prediction of T-cell epitopes: coMFA and coMSIA studies of peptides with affinity for the class I MHC molecule HLA-A*0201.

D. Flower, I. Doytchinova, 2001, Journal of medicinal chemistry.

Quantitative approaches to computational vaccinology

D. Flower, I. Doytchinova, 2002, Immunology and cell biology.

Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201.

D. Flower, I. Doytchinova, M. Blythe, 2002, Journal of proteome research.

Physicochemical explanation of peptide binding to HLA‐A*0201 major histocompatibility complex: A three‐dimensional quantitative structure‐activity relationship study

D. Flower, I. Doytchinova, 2002, Proteins.

Peptide binding to the HLA-DRB1 supertype: a proteochemometrics analysis.

D. Flower, I. Doytchinova, I. Dimitrov, 2010, European journal of medicinal chemistry.

Peptide Binding Prediction to Five Most Frequent HLA‐DQ Proteins – a Proteochemometric Approach

I. Doytchinova, I. Dimitrov, 2015, Molecular informatics.

T-cell epitope vaccine design by immunoinformatics

Irini Doytchinova, Atanas Patronov, I. Doytchinova, 2013, Open Biology.

Quantitative online prediction of peptide binding to the major histocompatibility complex.

Channa K. Hattotuwagama, Pingping Guan, Christianna Zygouri, 2004, Journal of molecular graphics & modelling.

In Silico Identification of Supertypes for Class II MHCs1

Irini A. Doytchinova, Darren R. Flower, D. Flower, 2005, The Journal of Immunology.

Coupling In Silico and In Vitro Analysis of Peptide-MHC Binding: A Bioinformatic Approach Enabling Prediction of Superbinding Peptides and Anchorless Epitopes

Darren R Flower, Persephone Borrow, Irini A Doytchinova, 2004, The Journal of Immunology.

MHCPred 2.0

Channa K. Hattotuwagama, Pingping Guan, Irini A. Doytchinova, 2006 .

MHCPred 2.0: an updated quantitative T-cell epitope prediction server.

Channa K. Hattotuwagama, Pingping Guan, Darren R Flower, 2006, Applied bioinformatics.

Using databases and data mining in vaccinology

Channa K. Hattotuwagama, D. Flower, I. Doytchinova, 2007, Expert opinion on drug discovery.

Computer aided selection of candidate vaccine antigens

Matthew N Davies, Darren R Flower, Irini A Doytchinova, 2010, Immunome research.

Quantitative structure--clearance relationships of acidic drugs.

Irini A. Doytchinova, I. Doytchinova, Zvetanka Zhivkova, 2013, Molecular pharmaceutics.

Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone

Darren R Flower, Irini A Doytchinova, Paul D. Taylor, 2003, Journal of biomedicine & biotechnology.

Improving in Silico Prediction of Epitope Vaccine Candidates by Union and Intersection of Single Predictors

D. Flower, I. Doytchinova, I. Dimitrov, 2011 .

Thermal effects compensation and associated uncertainty for large magnet assembly precision alignment

I. Doytchinova, P. Shoreb, B. Nicqueverta, 2019 .

Different approaches for determination of the attachment degree of polyethylene glycols to poly(anhydride) nanoparticles

I. Doytchinova, J. Irache, K. Yoncheva, 2010, Drug development and industrial pharmacy.

A Cohesive and Integrated Platform for Immunogenicity Prediction.

D. Flower, I. Doytchinova, I. Dimitrov, 2016, Methods in molecular biology.

Novel camphane-based anti-tuberculosis agents with nanomolar activity.

I. Doytchinova, V. Valcheva, G. Stavrakov, 2013, European journal of medicinal chemistry.

PROTEOCHEMOMETRIC ANALYSIS OF PEPTIDES BINDING TO HUMAN LEUKOCYTE ANTIGEN ( HLA ) PROTEINS FROM LOCUS DP 31

I. Doytchinova, I. Dimitrov, 2018 .

Proteochemometrics for the Prediction of Peptide Binding to Multiple HLA Class II Proteins

D. Flower, I. Doytchinova, I. Dimitrov, 2018 .

2D and 3D QSAR Analysis of Some Valproic Acid Metabolites and Analogues as Anticonvulsant Agents

I. Doytchinova, T. Netzeva, R. Natcheva, 2000, Pharmaceutical Research.

Bone protective effects of purified extract from Ruscus aculeatus on ovariectomy-induced osteoporosis in rats.

I. Doytchinova, G. Marinov, M. Atanasova, 2019, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

Associations between Milk and Egg Allergens and the HLA-DRB1/DQ Polymorphism: A Bioinformatics Approach

I. Doytchinova, I. Dimitrov, 2016, International Archives of Allergy and Immunology.

Bioinformatic Approach for Identifying Parasite and Fungal Candidate Subunit Vaccines

D. Flower, I. Doytchinova, 2008 .

The Amaryllidaceae alkaloids: an untapped source of acetylcholinesterase inhibitors

I. Doytchinova, S. Berkov, M. Atanasova, 2021, Phytochemistry Reviews.

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

Channa K. Hattotuwagama, Pingping Guan, Debra J. Taylor, 2006, J. Chem. Inf. Model..

Suppression of Disease-Associated B Lymphocytes by GAD65 Epitope-Carrying Protein-Engineered Molecules in a Streptozotocin-Induced Mouse Model of Diabetes.

I. Doytchinova, N. Mihaylova, I. Manoylov, 2019, Monoclonal antibodies in immunodiagnosis and immunotherapy.

Protein‐engineered molecules carrying GAD65 epitopes and targeting CD35 selectively down‐modulate disease‐associated human B lymphocytes

I. Doytchinova, N. Mihaylova, I. Manoylov, 2019, Clinical and experimental immunology.

Peptide-based targeted cancer therapeutics: design, synthesis and biological evaluation.

Armen R. Sargsyan, I. Doytchinova, S. Panseri, 2022, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

In silico prediction of cancer immunogens: current state of the art

D. Flower, I. Doytchinova, 2018, BMC Immunology.

Virtual Screening and Hit Selection of Natural Compounds as Acetylcholinesterase Inhibitors

I. Doytchinova, I. Dimitrov, Stefan Ivanov, 2022, Molecules.

Galantamine Derivatives as Acetylcholinesterase Inhibitors: Docking, Design, Synthesis, and Inhibitory Activity

I. Doytchinova, M. Atanasova, G. Stavrakov, 2018 .

Docking‐based Design of Galantamine Derivatives with Dual‐site Binding to Acetylcholinesterase

I. Doytchinova, S. Konstantinov, M. Atanasova, 2016, Molecular informatics.

Design of Multi-Epitope Vaccine against SARS-CoV-2

I. Doytchinova, A. Tchorbanov, 2020 .

Synthesis and antiproliferative activity of benzo[d]isothiazole hydrazones.

I. Doytchinova, R. Loddo, P. la Colla, 2006, European journal of medicinal chemistry.

Toward 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.

Channa K. Hattotuwagama, D. Flower, I. Doytchinova, 2007, Methods in molecular biology.

Epitopes Superbinding Peptides and Anchorless Approach Enabling Prediction of Peptide-MHC Binding : A Bioinformatic Coupling In Silico and In Vitro Analysis of Flower

I. Doytchinova, S. Gloster, P. Borrow, 2004 .

A comparative molecular similarity indices (CoMSIA) study of peptide binding to the HLA-A3 superfamily.

D. Flower, I. Doytchinova, P. Guan, 2003, Bioorganic & medicinal chemistry.

Discovery of a Novel Acetylcholinesterase Inhibitor by Fragment-Based Design and Virtual Screening

I. Doytchinova, S. Konstantinov, M. Atanasova, 2021, Molecules.

A Novel Galantamine-Curcumin Hybrid as a Potential Multi-Target Agent against Neurodegenerative Disorders

I. Doytchinova, I. Valkova, M. Atanasova, 2021, Molecules.

Antioxidant Activity of a Novel Acetylcholinesterase Inhibitor: In Vivo and Ex vivo Studies

I. Doytchinova, M. Atanasova, G. Stavrakov, 2020 .

A Galantamine–Curcumin Hybrid Decreases the Cytotoxicity of Amyloid-Beta Peptide on SH-SY5Y Cells

I. Doytchinova, K. Mladenova, J. Doumanov, 2021, International journal of molecular sciences.

Synthesis of some new S-triazine based chalcones and their derivatives as potent antimicrobial agents.

I. Doytchinova, A. Geronikaki, A. Ćirić, 2010, European journal of medicinal chemistry.

Hepato-, neuroprotective effects and QSAR studies on flavoalkaloids and flavonoids from Astragalus monspessulanus

I. Doytchinova, I. Ionkova, I. Krasteva, 2019, Biotechnology & Biotechnological Equipment.

Beneficial effects of the fructus Sophorae extract on experimentally induced osteoporosis in New Zealand white rabbits

I. Doytchinova, M. Atanasova, Rumyana Simeonova, 2021, Acta pharmaceutica.

LC-MS analysis of phenolic compounds and oleraceins in aerial parts of Portulaca oleracea L.

I. Doytchinova, R. Gevrenova, D. Zheleva-Dimitrova, 2019 .

Thiazolyl‐N‐substituted amides: A group of effective anti‐inflammatory agents with potential for local anesthetic properties. Synthesis, biological evaluation, and a QSAR approach

I. Doytchinova, D. Hadjipavlou-Litina, A. Geronikaki, 1999 .

Novel Hits for N-Myristoyltransferase Inhibition Discovered by Docking-Based Screening

I. Doytchinova, M. Atanasova, D. Spassov, 2022, Molecules.

A role of salt bridges in mediating drug potency: A lesson from the N-myristoyltransferase inhibitors

I. Doytchinova, M. Atanasova, D. Spassov, 2023, Frontiers in Molecular Biosciences.

Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors

I. Doytchinova, I. Dimitrov, S. Berkov, 2015, Molecular informatics.

Hydrazones of 1,2-benzisothiazole hydrazides: synthesis, antimicrobial activity and QSAR investigations.

I. Doytchinova, P. Cozzini, P. Vicini, 2002, European journal of medicinal chemistry.

Aminothiazole derivatives with antidegenerative activity on cartilage.

I. Doytchinova, V. Cardile, A. Geronikaki, 2003, Bioorganic & medicinal chemistry.

In-depth characterization of the GOTCAB saponins in seven cultivated Gypsophila L. species (Caryophyllaceae) by liquid chromatography coupled with quadrupole-Orbitrap mass spectrometer

I. Doytchinova, B. Kołodziej, R. Gevrenova, 2019, Biochemical Systematics and Ecology.

Topical anal fissure treatment: placebo-controlled study of mononitrate and trinitrate therapies

I. Doytchinova, D. Kovatchki, K. Yoncheva, 2009, International Journal of Colorectal Disease.

IN SILICO QUANTITATIVE STRUCTURE – PHARMACOKINETIC RELATIONSHIP MODELING ON ACIDIC DRUGS: HALF LIFE

I. Doytchinova, Z. Zhivkova, 2014 .

Effects of Curcumin and Ferulic Acid on the Folding of Amyloid-β Peptide

I. Doytchinova, I. Dimitrov, M. Atanasova, 2021, Molecules.

Synthetic piperine amide analogs with antimycobacterial activity

I. Doytchinova, V. Valcheva, G. Stavrakov, 2018, Chemical biology & drug design.

An Alignment-Independent Platform for Allergenicity Prediction.

Irini Doytchinova, Ivan Dimitrov, I. Doytchinova, 2020, Methods in molecular biology.

AllergenFP: allergenicity prediction by descriptor fingerprints

Irini A. Doytchinova, Ivan Bangov, Ivan Dimitrov, 2014, Bioinform..

BMC Bioinformatics BioMed Central Methodology article VaxiJen: a server for prediction of protective antigens, tumour

Irini A. Doytchinova, Darren R. Flower, D. Flower, 2007 .

AllerTOP - a server for in silico prediction of allergens

Irini A. Doytchinova, Darren R. Flower, Ivan Dimitrov, 2013, BMC Bioinformatics.

EpiTOP - a proteochemometric tool for MHC class II binding prediction

Irini A. Doytchinova, Darren R. Flower, Ivan Dimitrov, 2010, Bioinform..

Class I T-cell epitope prediction: improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding.

Darren R Flower, Irini A Doytchinova, D. Flower, 2006, Molecular immunology.

MHCPred: bringing a quantitative dimension to the online prediction of MHC binding.

Pingping Guan, Christianna Zygouri, Darren R Flower, 2003, Applied bioinformatics.

BULGARIAN ACADEMY OF SCIENCES

I. Doytchinova, A. Tchorbanov, 2020 .

Quantitative Prediction of Peptide Binding to HLA-DP1 Protein

Irini A. Doytchinova, Ivan Dimitrov, Stefan Ivanov, 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Class II MHCs In Silico Identification of Supertypes for

D. Flower, I. Doytchinova, 2013 .

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study

Irini Doytchinova, Darren R Flower, Ivan Dimitrov, 2012, BMC Structural Biology.

HLA‐DP2 binding prediction by molecular dynamics simulations

Peicho Petkov, Irini Doytchinova, Darren R Flower, 2011, Protein science : a publication of the Protein Society.

Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach

Irini Doytchinova, Darren R Flower, Ivan Dimitrov, 2011, BMC Structural Biology.

Identification of Candidate Vaccine Antigens In Silico

Matthew N. Davies, Irini A. Doytchinova, Darren R. Flower, 2012, Immunomic Discovery of Adjuvants and Candidate Subunit Vaccines.

AllerTOP v.2—a server for in silico prediction of allergens

Darren R. Flower, Ivan Dimitrov, Ivan Bangov, 2014, Journal of Molecular Modeling.

Allergenicity prediction by artificial neural networks

Ivan Bangov, Irini Doytchinova, Ivan Dimitrov, 2014 .

Integrating In Silico and In Vitro Analysis of Peptide Binding Affinity to HLA-Cw*0102: A Bioinformatic Approach to the Prediction of New Epitopes

Channa K. Hattotuwagama, Irini A. Doytchinova, Darren R. Flower, 2009, PloS one.

MHCPred: a server for quantitative prediction of peptide-MHC binding

Pingping Guan, Irini A. Doytchinova, Darren R. Flower, 2003, Nucleic Acids Res..

Predicting Immunogenicity Risk in Biopharmaceuticals

Irini A. Doytchinova, Ivan Dimitrov, Nikolet Doneva, 2021, Symmetry.

Novel Arylsulfonylhydrazones as Breast Anticancer Agents Discovered by Quantitative Structure-Activity Relationships

I. Doytchinova, N. Vassilev, Z. Zhivkova, 2023, Molecules.

EpiJen: a server for multistep T cell epitope prediction

Pingping Guan, Irini A. Doytchinova, Darren R. Flower, 2006, BMC Bioinformatics.

Drug Design—Past, Present, Future

I. Doytchinova, 2022, Molecules.

JenPep: a database of quantitative functional peptide data for immunology

Irini A. Doytchinova, Darren R. Flower, Martin J. Blythe, 2002, Bioinform..

JenPep: A Novel Computational Information Resource for Immunobiology and Vaccinology

Irini A. Doytchinova, Darren R. Flower, Christianna Zygouri, 2003, J. Chem. Inf. Comput. Sci..

Quantitative structure-activity relationships and the prediction of MHC supermotifs.

Pingping Guan, Darren R Flower, Irini A Doytchinova, 2004, Methods.

Immunoinformatics and the prediction of immunogenicity.

Darren R Flower, Irini A Doytchinova, D. Flower, 2002, Applied bioinformatics.

MHC : A Bioinformatic Evaluation toProcessing Preselection of Peptides Binding Transporter Associated with Antigen

Shelley L. Hemsley, I. Doytchinova, 2004 .

The HLA-A2-supermotif: a QSAR definition.

Irini Doytchinova, Darren Flower, D. Flower, 2003, Organic & biomolecular chemistry.

HLA-A3 supermotif defined by quantitative structure-activity relationship analysis.

Pingping Guan, Darren R Flower, Irini A Doytchinova, 2003, Protein engineering.

MHC Class II Binding Prediction by Molecular Docking

D R Flower, I Dimitrov, D. Flower, 2011, Molecular informatics.

MHC Class II Binding Prediction—A Little Help from a Friend

Darren R. Flower, Irini Doytchinova, Ivan Dimitrov, 2010, Journal of biomedicine & biotechnology.

New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

Channa K. Hattotuwagama, Pingping Guan, Darren R Flower, 2004, Organic & biomolecular chemistry.

Computational vaccinology: quantitative approaches.

Pingping Guan, Debra J. Taylor, Peter V Coveney, 2003, Novartis Foundation symposium.

A Dataset of Experimental HLA-B*2705 Peptide Binding Affinities

Channa K. Hattotuwagama, Irini A. Doytchinova, Darren R. Flower, 2014 .

In Silico QSAR-Based Predictions of Class I and Class II MHC Epitopes

Channa K. Hattotuwagama, Pingping Guan, Irini A. Doytchinova, 2008 .

Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for human histocompatibility complex HLA-A0201.

Pingping Guan, Darren R Flower, Persephone Borrow, 2005, Journal of medicinal chemistry.

In Silico Prediction of Peptide Binding Affinity to Class I Mouse Major Histocompatibility Complexes: A Comparative Molecular Similarity Index Analysis (CoMSIA) Study

Channa K. Hattotuwagama, Irini A. Doytchinova, Darren R. Flower, 2005, J. Chem. Inf. Model..

Towards the chemometric dissection of peptide – HLA-A*0201 binding affinity: comparison of local and global QSAR models

Irini A. Doytchinova, Darren R. Flower, Valerie Walshe, 2005, J. Comput. Aided Mol. Des..

Towards the in silico identification of class II restricted T-cell epitopes: a partial least squares iterative self-consistent algorithm for affinity prediction

Irini A. Doytchinova, Darren R. Flower, D. Flower, 2003, Bioinform..

A Comparative Molecular Similarity Index Analysis (CoMSIA) study identifies an HLA-A2 binding supermotif

Irini A. Doytchinova, Darren R. Flower, D. Flower, 2002, J. Comput. Aided Mol. Des..

The classification of HLA supertypes by GRID/CPCA and hierarchical clustering methods.

Pingping Guan, Darren R Flower, Irini A Doytchinova, 2007, Methods in molecular biology.

Quantitative Structure - Pharmacokinetics Relationships Analysis of Basic Drugs: Volume of Distribution.

I. Doytchinova, Z. Zhivkova, T. Mandova, 2015, Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques.

Curcumin Inhibits the Primary Nucleation of Amyloid-Beta Peptide: A Molecular Dynamics Study

I. Doytchinova, I. Dimitrov, M. Atanasova, 2020, Biomolecules.

Galantamine-Curcumin Hybrids as Dual-Site Binding Acetylcholinesterase Inhibitors

I. Doytchinova, Z. Zhivkova, S. Konstantinov, 2020, Molecules.

Design, Synthesis, and Antimycobacterial Activity of Novel Theophylline‐7‐Acetic Acid Derivatives With Amino Acid Moieties

I. Doytchinova, S. Konstantinov, M. Atanasova, 2016, Chemical biology & drug design.

Design of novel camphane-based derivatives with antimycobacterial activity.

I. Doytchinova, V. Valcheva, G. Stavrakov, 2014, Journal of molecular graphics & modelling.

Quantitative structure--plasma protein binding relationships of acidic drugs.

Irini Doytchinova, I. Doytchinova, Zvetanka Zhivkova, 2012, Journal of pharmaceutical sciences.

Prediction of steady-state volume of distribution of acidic drugs by quantitative structure-pharmacokinetics relationships.

Irini Doytchinova, I. Doytchinova, Zvetanka Zhivkova, 2012, Journal of pharmaceutical sciences.

Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database

Irini Doytchinova, Ivan Dimitrov, Irena Philipova, 2018, Journal of enzyme inhibition and medicinal chemistry.

Docking‐based design and synthesis of galantamine–camphane hybrids as inhibitors of acetylcholinesterase

I. Doytchinova, I. Valkova, S. Konstantinov, 2017, Chemical biology & drug design.

Galantamine derivatives with indole moiety: Docking, design, synthesis and acetylcholinesterase inhibitory activity.

I. Doytchinova, M. Atanasova, G. Stavrakov, 2015, Bioorganic & medicinal chemistry.

In Silico Identification of the B-Cell and T-Cell Epitopes of the Antigenic Proteins of Staphylococcus aureus for Potential Vaccines.

I. Doytchinova, S. Thomas, 2021, Methods in molecular biology.

Cellular polyamines condense hyperphosphorylated Tau, triggering Alzheimer’s disease

I. Doytchinova, I. Dimitrov, M. Atanasova, 2020, Scientific Reports.

MILK ALLERGY IN HLA-DRB1*14:19/14:21 PAEDIATRIC PATIENTS: A BIOINFORMATICS APPROACH Table 1. Number of peptide fragments and peptide binders/non-binders to HLA-DRB1*14:19 and *14:21before and after digestion

I. Doytchinova, I. Dimitrov, T. Kadiyska, 2018 .

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique.

D. Flower, I. Doytchinova, 2006, Journal of medicinal chemistry.

Empirical, AI, and QSAR Approaches to Peptide-MHC Binding Prediction

Channa K. Hattotuwagama, Pingping Guan, Matthew N. Davies, 2007 .

Adenosine A 2A receptor agonists: CoMFA-based selection of the most predictive conformation

I. Doytchinova, I. Valkova, I Doytchinova, 2002, SAR and QSAR in environmental research.

Antimycobacterial activity of chiral aminoalcohols with camphane scaffold.

I. Doytchinova, M. Stoyanova, V. Valcheva, 2014, European journal of medicinal chemistry.

Predicting Class I Major Histocompatibility Complex (MHC) Binders Using Multivariate Statistics: Comparison of Discriminant Analysis and Multiple Linear Regression

Irini A. Doytchinova, Darren R. Flower, D. Flower, 2007, J. Chem. Inf. Model..

Cellular polyamines condense hyperphosphorylated Tau, triggering Alzheimer’s disease

I. Doytchinova, I. Dimitrov, M. Atanasova, 2020, Scientific Reports.

preDQ – a software tool for peptide binding prediction to HLA‐DQ2 and HLA‐DQ8

I. Doytchinova, I. Dimitrov, M. Atanasova, 2023, EFSA Supporting Publications.

Bacterial Immunogenicity Prediction by Machine Learning Methods

Irini Doytchinova, Ivan Dimitrov, Nevena Zaharieva, 2020, Vaccines.

In silico prediction of cancer immunogens: current state of the art

D. Flower, I. Doytchinova, 2018, BMC Immunology.

Design, Synthesis and Cytotoxic Activity of Novel Salicylaldehyde Hydrazones against Leukemia and Breast Cancer

I. Doytchinova, Z. Zhivkova, B. Nikolova-Mladenova, 2023, International journal of molecular sciences.

VaxiJen Dataset of Bacterial Immunogens: An Update.

Irini Doytchinova, Darren R Flower, Ivan Dimitrov, 2019, Current computer-aided drug design.

Synthesis, 5-HT1A and 5-HT2A receptor affinity and QSAR study of 1-benzhydryl-piperazine derivatives with xanthine moiety at N4

I. Doytchinova, I. Valkova, A. Zlatkov, 2012, Medicinal Chemistry Research.

Platinum Complexes with 5‐Methyl‐5(4‐pyridyl)hydantoin and Its 3‐Methyl Derivatives: Synthesis and Cytotoxic Activity – Quantitative Structure‐Activity Relationships

I. Doytchinova, H. Varbanov, D. Ivanov, 2011, Archiv der Pharmazie.

Proteochemometrics-Based Prediction of Peptide Binding to HLA-DP Proteins

Irini Doytchinova, Ivan Dimitrov, Ventsislav Yordanov, 2017, J. Chem. Inf. Model..

EpiDOCK: a molecular docking-based tool for MHC class II binding prediction.

Irini Doytchinova, Darren R Flower, Ivan Dimitrov, 2013, Protein engineering, design & selection : PEDS.

Thiazole derivatives as dual inhibitors of deoxyribonuclease I and 5-lipoxygenase: A promising scaffold for the development of neuroprotective drugs.

H. Stark, I. Doytchinova, D. Steinhilber, 2023, Chemico-biological interactions.

Inhibitor Trapping in N-Myristoyltransferases as a Mechanism for Drug Potency

I. Doytchinova, M. Atanasova, D. Spassov, 2023, International journal of molecular sciences.

Ex Vivo Antioxidant and Cholinesterase Inhibiting Effects of a Novel Galantamine–Curcumin Hybrid on Scopolamine-Induced Neurotoxicity in Mice

I. Doytchinova, M. Atanasova, Rumyana Simeonova, 2022, International Journal of Molecular Sciences.

Biochemical Studies on a Novel Potent Acetylcholinesterase Inhibitor with Dualsite Binding for Treatment of Alzheimer’s Disease

I. Doytchinova, I. Valkova, V. Vitcheva, 2021 .

In Vivo Studies on Novel Potent Acetylcholinesterase Inhibitors with Dual-site Binding for Treatment of Alzheimer’s Disease

I. Doytchinova, I. Valkova, V. Vitcheva, 2021 .

Selective Silencing of Disease-Associated B Lymphocytes from Hashimoto’s Thyroiditis Patients by Chimeric Protein Molecules

I. Doytchinova, N. Mihaylova, I. Manoylov, 2022, International journal of molecular sciences.

AllergenFP: allergenicity prediction by descriptor fingerprints

I. Doytchinova, I. Dimitrov, I. Bangov, 2014, Bioinform..

Using databases and data mining in vaccinology

Channa K. Hattotuwagama, D. Flower, I. Doytchinova, 2007, Expert opinion on drug discovery.

Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for human histocompatibility complex HLA-A0201.

D. Flower, I. Doytchinova, P. Guan, 2005, Journal of medicinal chemistry.

Immunoinformatic Analysis of Human Thyroglobulin

I. Doytchinova, A. Tchorbanov, S. Ivanov, 2020 .

EpiDOCK: a molecular docking-based tool for MHC class II binding prediction.

D. Flower, I. Doytchinova, I. Dimitrov, 2013, Protein engineering, design & selection : PEDS.

Docking‐based design and synthesis of galantamine–camphane hybrids as inhibitors of acetylcholinesterase

I. Doytchinova, I. Valkova, S. Konstantinov, 2017, Chemical biology & drug design.

In Silico Immunology

Channa K. Hattotuwagama, Debra J. Taylor, Shelley L. Hemsley, 2007 .