Hierarchic Informational Technology for Effective Molecular Design of Drug Agents From Science to Business Workshop October 2006, Kyiv Victor E. Kuzmin A.V. Bogatsky Phys. – Chem. Institute NAS of Ukraine Odessa

Talk outline 1.Introduction 2.Problem Description & Market Need 3.Solution of Problem 4.The Principle Steps of QSAR 5.Brief HIT4QSAR description 6.The Principle Steps of HIT4QSAR 7.Experimental results 1 – 4 8.The unique and overwhelming HIT4QSAR advantages 9.Advantages of HIT4QSAR Relatively Competitive Approaches and Models 10.The comparative analysis of efficacy of HIT4QSAR 11.Competitive Matrix 12.Stage of development of HIT4QSAR 13.Targeted Market Segment 14.Opportunity for joint work 15.Contact information

3 Proprietary information statement The technology material presented in this talk is available for licensing or joint product development. None of the slides contain any confidential or proprietary information which would prevent patenting the technology.

4 "There are possible compounds, likely drugs, 10 7 known compounds, 10 6 commercially available compounds, 10 6 compounds in corporate databases, 10 4 compounds in drug databases, 10 3 commercial drugs and 10 2 profitable drugs " A. Weininger J. Chem. Inf. Comput. Sci., 37, 138 (1997) Introduction

5 DRUG DISCOVERY Ooms, F. Curr. Med. Chem. 2000, 7, Problem Description & Market Need How to decrease the set of the explored compounds? How to accelerate the drug discovery process? How to reduce financial expenditure?

6 Solution of Problem Software for QSAR CoMFA - Comparative Molecular Field Analysis (Tripos, USA) CoMSiA - Comparative Molecular Similarity Analysis (Tripos, USA) HQSAR - Holographic QSAR (Tripos, USA) EVA - Eigenvalue Analysis (Tripos, USA) CODESSA – Comprehensive Descriptors for Structural and Statistical Analysis (SemiChem, USA) Cerius 2 - QSAR software (Accelrys, USA) EMMA – Effective Modelling of Molecular Activity (MSU, Russia) DRAGON - QSAR software (MU, Italy) HIT4QSAR – Hierarchical Informational Technology for QSAR (PCI NAS, Odessa, Ukraine) Quantitative Structure – Activity Relationship

The Principle Steps of QSAR Training set StructureObs. activity … …… N0.5 Calculation of the structural parameters S1S1 S2S2 S3S3 …SMSM … … …-2.1 … …………… 128…10 QSAR A = f ( S 1,S 2,S 3,…,S M ) Test set StructureObs. activity Pred. activity … ……… Verification of model Prediction StructureObs. activity Pred. activity 1?2.6 2?5.0 3?6.0 … ……… Molecular design Selection of structural parameters promotes the activity Structures of new compounds

8 Brief HIT4QSAR description

The principle steps of HIT4QSAR Training set MoleculesActivity ……… mimi AiAi Simplex representation of molecular structure Weight parameters for atoms Charge Lipofilicity Polarizability Informational Field H-Bond Structure parameters calculation Local parameters (Quantitative of simplexes) m i S i1, S i2, … Fourier transformation Integral parameters m i q i1, q i2, … QSAR A i =f(S i1, S i2, …q i1, q i2, …) Prediction New molecules Predicted activity Statistical characteristics R – correlation coefficient Q – cross-validation coefficient Test set MoleculesActivity ……… mjmj AjAj Selection of molecular fragments that determine the Activity Estimation of contribution to interaction molecule-biological target Molecular Design of New Perspective Compounds with High Activity Hypotheses about mode of of Biological Activity

10 Experimental results 1 ANALYSIS OF THE ANTI-INFLUENZA ACTIVITY (LgTID 50 ) Training set QSAR models R2R2 Q2 Q2 2D D D Statistical characteristics of QSAR models

11 Color-coding of molecular fragments with standpoint of their influence on the activity - enhance the activity - decrease the activity Experimental results 2

12 The relative influence of molecular fragments on value of activity, lgTID 50 Enhance the activity Decrease the activity -CH 2 -CH 2 -NH--CH 2 -COOH-CO-NH Experimental results 3

13 Molecular design of structures with potentially high anti-influenza activity

14 The relative influence of some physical and chemical factors into the activity estimated from the HIT4QSAR models Experimental results 4

15 The unique and overwhelming HIT4QSAR advantages are: simplex representation of molecular structure (SiRMS), Fourier transformation of structure parameters spectrum, characteristics of molecular informational field – all of them is providing universality, diversity and flexibility of description for compounds of different structural types; HIT4QSAR that depending on the concrete aims of research allows to construct the optimal strategy of QSAR models generation, avoiding at the same time the superfluous complication that doesn't results in the adequacy increase. on the every stage of HIT4QSAR usage we can determine the molecular structure features that are important for the studied activity, and exclude the rest. It shows unambiguously the limits of expedient QSAR models complication and allows not to waste superfluous resources for needless calculations.

16 Unlike HIT4QSAR, a majority of descriptors in CODESSA, EMMA, DRAGON have interpretation difficulties and little suitable for molecular design. These approaches are applicable, mainly, for an activity prediction. HIT4QSAR does not have the restrictions of such well-known and widely used approaches as CoMFA (Comparative Molecular Field Analysis), CoMSIA, and HASL, usage of the lasts is limited in the structurally homogeneous set of molecules and only one conformer. HIT4QSAR has not the HQSAR restrictions (only topological representation of molecular structure) and lacks (ambiguity of descriptors formation when procedure of hashing of molecular holograms is realized). Besides, on the contrary to HQSAR, in SiRMS, different physical and chemical properties of atoms (charge, lipophilicity, etc.) can be taken into account. Advantages of HIT4QSAR Relatively Competitive Approaches and Models (CoMFA, CoMSiA, HASL, CODESSA, EMMA, DRAGON, HQSAR)

17 Angiotensin Converting Enzyme (ACE) inhibitors Work set – 76 compounds Test set – 38 The comparative analysis of efficacy of HIT4QSAR Q2Q2 R2R2 Results from Sutherland J.J.; OBrien L.A.; Weaver D.F. A Comparison of Methods for Modeling Quantitative StructureActivity Relationships. J. Med. Chem. 2004, 47, CoMFA - Comparative Molecular Field Analysis CoMSiA - Comparative Molecular Similarity Indices Analysis EVA - Eigenvalue Analysis HQSAR - Holographic QSAR Cerius2 - QSAR software Our models are more adequately and have more high statistical rates. HIT4QSAR on Base Simplex Representation of Molecular Structure

18 Competitive Matrix

19 Stage of development of HIT4QSAR Here are presented high activity compounds, which was designed by means of developed HIT4QSAR HIT4QSAR is realized as software, tested, available for demonstration, field testing was carried out.

20 Targeted Market Segment The developed HIT4QSAR allows to decide any tasks structure – property. On the basis of this technology, carry out of molecular design of various compounds is possible with the complex of useful properties. We have experience of molecular design of perspective drugs (antiviral, antitumor, psychotropic, antimicrobial, anti-inflammation, etc), pesticides, optical materials, complexones, food supplements, quenching agents, etc. The results of the use of our technology can be interesting and useful for all, who carry out development of new drugs, materials, reagents, etc. Potential consumers of HIT4QSAR are pharmaceutical companies and developers of software for QSAR. Cost of project that related to the prediction and design of new drugs, substances and materials depends on the amount of concrete tasks, presence and content of information for the construction of training set, special requirements to the results. Rough estimate – $ for: test set compounds, level of modeling - 2D, term of contract - 1 month

21 Opportunity for joint work We seek a potential clients, which need the results of the use of our technology. We are ready to vend the service – structure optimization, molecular design, prediction of new compounds with complex of demand properties – by means of HIT4QSAR. We are ready for collaboration with colleagues – chemists- synthesist and specialists of investigation different properties of substances (biologist, virologists, pharmacologist, etc) for carry out joint projects.

Contact information Doctor of chemical science Victor E. Kuzmin Head of laboratory on theoretical chemistry A.V. Bogatsky Phys. – Chem. Institute NAS of Ukraine, Odessa Thank you for attention