Tudor I. Oprea - Publications

I. Zamora, T.I. Oprea, G. Cruciani, M. Pastor, A.L. Ungell. Surface descriptors for protein ligand affinity prediction. J.Med. Chem. 46, pp 25-33, 2003.

Abstract:Molecular descriptors calculated by the VolSurf program have been extensively used to model pharmacokinetic properties, e.g., passive permeability through the gastrointestinal tract or through the blood-brain barrier. These descriptors quantify steric, hydrophobic, and hydrogen bond interactions between model compounds and different environments. Since these interactions are the same as those involved in the ligand-receptor binding, VolSurf descriptors could potentially be relevant in modeling this process as well. We obtained a significant model (r(2) = 0.85, q(2) = 0.75) using VolSurf descriptors derived from the ligand, the protein, and the ligand-protein complex for a diverse set of 38 structures previously used in the VALIDATE (ref 23) training set. Furthermore, a statistically significant model (r(2) = 0.94, q(2) = 0.89) was obtained using the same type of descriptors for a homogeneous set of glycogen phosphorylase inhibitors (ref 25). Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery.
Keywords:

T.I. Oprea. On the information content of 2D and 3D descriptors for QSAR. J. Braz. Chem. Soc., 13, pp 811-815, 2002

Abstract:To gain better understanding on the information content of two-dimensional (2D) vs. threedimensional (3D) descriptor systems, we analyzed principal component analysis scores derived from 87 2D descriptors and 798 3D (ALMOND) variables on a set of 5998 compounds of medicinal chemistry interest. The information overlap between ALMOND and 2D-based descriptors, as modeled by the fraction of explained variance (r2) and by seven-groups cross-validation (q2) in a two PLS components model was 40%. Individual component analysis indicates that the first and second principal components from the 2D-descriptors are related to the first and third dimensions from the ALMOND PCA model. The first ALMOND component is explained (61%) by size-related descriptors, whereas the third component is marginally explained (25%) by hydrophobicity-related descriptors. Surprisingly, 2D-based hydrogen-bonding descriptors did not contribute significantly in this analysis. These results do not a priori justify the choice of one methodology over the other, when performing QSAR studies.
Keywords: ALMOND, cheminformatics, chemometrics, QSAR

TI Oprea. Lead Structure searching: Are we looking at the appropriate property? J. Comput.-Aided Mol. Design, 16, pp 325-334, 2002

Abstract:The new drug discovery paradigm is based on high-throughput technologies, both with respect to synthesis and screening. The progression HTS hits --> lead series --> candidate drug --> marketed drug appears to indicate that the probability of reaching launched status is one in a million. This has shifted the focus from good quality candidate drugs to good quality leads. We examined the current trends in lead discovery by comparing MW (molecular weight), LogP (octanol/water partition coefficient, estimated by Kowwin) and LogSw (intrinsic water solubility, estimated by Wskowwin) for the following categories: 62 leads and 75 drugs; compounds in the development phase (I, II, III and launched), as indexed in MDDR; and compounds indexed in medicinal chemistry journals, categorized according to their biological activity. Comparing the distribution of the above properties, the 62 lead structures show the lowest median with respect to MW (smaller) and LogP (less hydrophobic), and the highest median with respect to LogSw (more soluble). By contrast, over 50% of the medicinal chemistry compounds with activities above 1 nanomolar have MW > 425, LogP > 4.25 and LogSw < -4.75, indicating that the reported active compounds are larger, more hydrophobic and less soluble when compared to time-tested quality leads. In the MDDR set, a progressive constraint to reduce MW and LogP, and to increase LogSw, can be observed when examining trends in the developmental sequence: phase I, II, III and launched drugs. These trends indicate that other properties besides binding affinity, e.g., solubility and hydrophobicity, need to be considered when choosing the appropriate leads.
Keywords: database filtering, drug-likeness, drug research, hydrophobicity, lead-likeness, property distribution, rule of 5 test, solubility

Oprea, Tudor I. . Virtual Screening in Lead Discovery: A Viewpoint. Molecules, 7(1), pp. 51-62, 2002.

Abstract: Virtual screening (VS) methods have emerged as an adaptive response to the massive throughput synthesis and screening technologies. Based on the structure-permeability paradigm, the Lipinski rule of five has become a standard property filtering protocol for VS. Three possible VS scenarios with respect to optimising binding affinity and pharmacokinetic properties are discussed. The parsimony principle for selecting candidate leads for further optimisation is advocated.
Keywords: ADME filters, Combinatorial library design, Drug discovery

Oprea, Tudor I.; Zamora, Ismael; Ungell, Anna-Lena. Pharmacokinetically Based Mapping Device for Chemical Space Navigation. Journal of Combinatorial Chemistry, 4, pp. 258-266, 2002.

Abstract: ChemGPS, the chem. global positioning system, is a tool that combines rules (equiv. to dimensions) and objects (chem. structures) to provide a consistent chem. space map (Oprea, T. I.; Gottfries, J. J. Comb. Chem. 2001, 3, 157-166.). Rules included, initially, general properties such as size, lipophilicity, and hydrogen bond capacity, while objects include "satellites", intentionally placed outside the druglike space, as well as "core" objects, mostly orally available drugs. ChemGPS mols. (objects) were used in conjunction with the VolSurf (http://www.moldiscovery.com) descriptors (rules), which are relevant for ADME (absorption, distribution, metab., and excretion) properties. The combination of ChemGPS and VolSurf, GPSVS, was investigated with respect to the biopharmaceutics classification system, which is recommended by the Food and Drug Administration (FDA) (http://www.fda.gov/cder/OPS/BCSguidance.htm), in particular with respect to permeability and soly. The first GPSVS principal component correlates, with no further training, to passive transcellular permeability, as illustrated for the Caco-2, ghost erythrocyte, and blood-brain barrier datasets, resp. The second GPSVS principal component correlates, without prior training, to soly., as shown for the octanol-water partition and intrinsic soly. datasets, resp. Although derived from principal component anal., the two property axes rotate and form an angle of approx. 43°, thus being no longer orthogonal. GPSVS can be used to map the chem. space with respect to permeability and soly., as recommended by FDA's biopharmaceutics classification system.
Keywords: Computer program, ChemGPS, Combinatorial library, Drug design, Molecular structure-property relationship, Permeability, Pharmacokinetics, Solubility, VolSurf

Tudor I Oprea. Chemical space navigation in lead discovery. Current Opinion in Chemical Biology, 6, pp. 384-389, 2002.

Abstract: The number of new chemical entities has remained rather constant (averaging 37 per year) in the past decade, despite the multiple-fold increase in the number of compounds that are being made and tested. Chemical space requires novel methods that can handle the increasing number of potentially accessible molecules. Neighborhood behavior, as an approach to similarity, and chemical property space navigation are some of the recent advances that are discussed, in the context of lead discovery and appropriate pharmacokinetic properties.
Keywords: ChemGPS, Drug discovery, Lead discovery, Molecular structure-property relationship, Permeability, Pharmacokinetics, Solubility

L. Kurunczi, M. Olah, T. I. Oprea, C. Bologa, Z. Simon. MTD-PLS: A PLS-Based Variant of the MTD Method. 2. Mapping Ligand-Receptor Interactions. Enzymatic Acetic Acid Esters Hydrolysis. Journal of Chemical Information and Computer Science, 42, pp. 841-846, 2002.

Abstract: The PLS variant of the MTD method (T. I. Oprea et al., SAR QSAR Environ. Res. 2001, 12, 75-92) was applied to a series of 25 acetylcholinesterase hydrolysis substrates. Statistically significant MTD-PLS models (q2 between 0.7 and 0.8) are in agreement with previous MTD models, with the advantage that local contributions are understood beyond the occupancy/nonoccupancy interpretation in MTD. A "chem. intuitive" approach further forces MTD-PLS coeffs. to assume only neg. (or zero) values for fragmental vol. descriptors and pos. (or zero) values for fragmental hydrophobicity descriptors. This further separates the various kinds of local interactions at each vertex of the MTD hypermol., making this method suitable for medicinal chem. synthesis planning.
Keywords: Acetylcholinesterase, QSAR (structure-activity relationship), MTD-PLS, 3D-QSAR, , Enzyme-binding;

Oprea, Tudor I. . Rapid estimation of hydrophobicity for virtual combinatorial library analysis. . SAR and QSAR in Environmental Research, 12(1-2), pp. 129-141, 2001.

Abstract: Novel NPH (Nonpolar, Polar, H) descriptors for rapid estn. of hydrophobicity, amenable for filtering extremely large virtual combinatorial libraries (VCL) are proposed, based on atom counts; Pat, the sum of polar atoms (sum of O, N, P and S); NPat, the sum of nonpolar atoms (the sum of carbons and halogens minus Pat); SHDA (the sum of H bond donors and acceptors). In combination with mol. wt., the following related parameters are defined; MWPat (the polar mol. wt.); MWNPat (the nonpolar mol. wt.); and MWSHDA (the H bonding mol. wt.). The NPH descriptors provide moderate-to-good predictive PLS models when external prediction is evaluated against measured log P values (q2 pred > 0.5, n = 7954) or against calcd. log P values (q2 pred > 0.6, n = 18991). Related to hydrophobicity, the NPH descriptors are intended for fast analyses of extremely large VCLs (106 - 1012 compds.), even before the enumeration of reactants into products occurs.
Keywords: Combinatorial library, Correlation analysis, Hydrophobicity, Linear free energy relationship, Molecular weight

Oprea, Tudor I.; Kurunczi, Ludovic; Olah, Marius; Simon, Zeno. MTD-PLS: a PLS-based variant of the MTD method. A 3D-QSAR analysis of receptor affinities for a series of halogenated dibenzoxin and biphenyl derivatives. . SAR QSAR Environ. Res. , 12(1-2), pp. 75-92, 2001.

Abstract: MTD-PLS, the Partial Least Squares (PLS) variant of the Min. Topol. Difference (MTD) method is described. In MTD-PLS, mols. are characterized not only by the occupancy or nonoccupancy of the hypermol. vertices (as in classical MTD), but also by addnl. descriptors for each vertex: fragmental van der Waals vols., fragmental hydrophobicities, partial at. charges, etc. This method was applied to a series of 73 polyhalogenated derivs. of dibenzo-p-dioxine, dibenzofuran and biphenyl (induction of aryl hydrocarbon hydrolase and affinities to rat cytosolic receptor), previously studied by MTD. The sepn. of steric, hydrophobic, and electrostatic effects was achieved re-translating from the latent variable space into a linear combination of the initial structural variables. The MTD-PLS method yields more detailed results compared to classical MTD, indicating the importance of electrostatic effects at some substituent positions.
Keywords: QSAR (structure-activity relationship), MTD-PLS, 3D-QSAR, halogenated dibenzoxin and biphenyl derivs., receptor-binding;

Nilsson, Jonas W.; Thorstensson, Fredrik; Kvarnstroem, Ingemar; Oprea, Tudor I.; Samuelsson, Bertil; Nilsson, Ingemar. . Solid-phase synthesis of libraries generated from a 4-phenyl-2-carboxy-piperazine scaffold. . Journal of Combinatorial Chemistry, 3(6), pp. 546-553, 2001.

Abstract: Strategies for finding novel structures of therapeutic interest are discussed. The rationale for the selection of the two scaffolds N-4-(m-aminophenyl)-piperazine-2-carboxylic acid (I) and N-4-(o-aminophenyl)-piperazine-2-carboxylic (II) is described. The synthesis of the appropriate precursors to scaffold I and II and their use in solid-phase chem. are described. A 160-member library was produced combining these novel piperazine scaffolds with eight sulfonyl chlorides/acid chlorides and 10 amines. The compd. library prepd. was analyzed using LC-MS, showing the expected base peak in all wells at an av. purity of 82%.
Keywords: Combinatorial chemistry, Solid-phase synthesis, Lead-like library, Phenylcarboxypiperazine scaffold

Oprea, Tudor I.; Davis, Andrew M.; Teague, Simon J.; Leeson, Paul D. . Is There a Difference between Leads and Drugs? A Historical Perspective. . Journal of Chemical Information and Computer Sciences, 41(5), pp. 1308-1315, 2001.

Abstract: To be considered for further development, lead structures should display the following properties: (1) simple chem. features, amenable for chem. optimization; (2) membership to an established SAR series; (3) favorable patent situation; and (4) good absorption, distribution, metab., and excretion (ADME) properties. There are two distinct categories of leads: those that lack any therapeutic use (i.e., "pure" leads), and those that are marketed drugs themselves but have been altered to yield novel drugs. We have previously analyzed the design of leadlike combinatorial libraries starting from 18 lead and drug pairs of structures (S. J. Teague et al. Angew. Chem., Int. Ed. Engl. 1999, 38, 3743-3748). Here, we report results based on an extended dataset of 96 lead-drug pairs, of which 62 are lead structures that are not marketed as drugs, and 75 are drugs that are not presumably used as leads. We examd. the following properties: MW (mol. wt.), CMR (the calcd. mol. refractivity), RNG (the no. of rings), RTB (the no. of rotatable bonds), the no. of hydrogen bond donors (HDO) and acceptors (HAC), the calcd. logarithm of the n-octanol/water partition (CLogP), the calcd. logarithm of the distribution coeff. at pH 7.4 (LogD74), the Daylight-fingerprint druglike score (DFPS), and the property and pharmacophore features score (PPFS). The following differences were obsd. between the medians of drugs and leads: DMW = 69; DCMR = 1.8; DRNG = DHAC =1; DRTB = 2; DCLogP = 0.43; DLogD74 = 0.97; DHDO = 0; DDFPS = 0.15; DPPFS = 0.12. Lead structures exhibit, on the av., less mol. complexity (less MW, less no. of rings and rotatable bonds), are less hydrophobic (lower CLogP and LogD74), and less druglike (lower druglike scores). These findings indicate that the process of optimizing a lead into a drug results in more complex structures. This information should be used in the design of novel combinatorial libraries that are aimed at lead discovery.
Keywords: Combinatorial library, Drug design, Hydrogen bond, Hydrophobicity, Leadlike, Partition, Pharmacophores, Structure-activity relationship

Olsson, Thomas; Oprea, Tudor I. . Cheminformatics: a tool for decision-makers in drug discovery. . Curr. Opin. Drug Discovery Dev. , 4(3), pp. 308-313, 2001.

Abstract: A review with 68 refs. Cheminformatics is a tool that aims at facilitating the decision-making process across various preclin. stages of drug discovery. Access to biol. and chem. data, but not the data themselves, is an integral part of cheminformatics. Emerging tools that allow storage of, and access to, chem., structural-chem. and biol. information are only now beginning to reach maturity. Recent advances in cheminformatics include virtual library anal. without enumeration and novel methods to investigate global chem. similarity and diversity voids. The most important task for cheminformatics is to constantly re-evaluate itself and its utility in the area of drug discovery, to provide probabilistic, rather than categorical predictions.
Keywords: Databases (chem.; cheminformatics as a tool for decision-makers in drug discovery), Combinatorial library, Drug design (cheminformatics as a tool for decision-makers in drug discovery), Chemistry (computational; cheminformatics as a tool for decision-makers in drug discovery)

Oprea, Tudor I.; Gottfries, Johan. . Chemography: The Art of Navigating in Chemical Space. . Journal of Combinatorial Chemistry, 3(2), pp. 157-166, 2001.

Abstract: Combinatorial chem. needs focused mol. diversity applied to the drug-like chem. space (drugspace). A drugspace map can be obtained by systematically applying the same conventions when examg. the chem. space, in a manner similar to the Mercator convention in geog.: Rules are equiv. to dimensions (e.g., longitude and latitude), while structures are equiv. to objects (e.g., cities and countries). Selected rules include size, lipophilicity, polarizability, charge, flexibility, rigidity, and hydrogen bond capacity. For these, extreme values were set, e.g., max. mol. wt. 1500, calcd. neg. logarithm of the octanol/water partition between -10 and 20, and up to 30 nonterminal rotatable bonds. Only S, N, O, P, and halogens were considered as elements besides C and H. Selected objects include a set of "satellite" structures and a set of representative drugs ("core" structures). Satellites, intentionally placed outside drugspace, have extreme values in one or several of the desired properties, while contg. druglike chem. fragments. ChemGPS (chem. global positioning system) is a tool that combines these predefined rules and objects to provide a global drugspace map. The ChemGPS drugspace map coordinates are t-scores extd. via principal component anal. (PCA) from 72 descriptors that evaluate the above-mentioned rules on a total set of 423 satellite and core structures. Global ChemGPS scores describe well the latent structures extd. with PCA for a set of 8599 monocarboxylates, a set of 45 heteroarom. compds., and for 87 a-amino acids. ChemGPS positions novel structures in drugspace via PCA-score prediction, providing a unique mapping device for the druglike chem. space. ChemGPS scores are comparable across a large no. of chems. and do not change as new structures are predicted, making this tool a well-suited ref. system for comparing multiple libraries and for keeping track of previously explored regions of the chem. space.
Keywords: Computer program, ChemGPS, Combinatorial library, Drug design, Hydrogen bond, Lipophilicity, Molecular structure-property relationship, Polarizability

Oprea, Tudor I.; Gottfries, Johan. ChemGPS: A chemical space navigation tool. In Hoeltje, Hans-Dieter; Sippl, Wolfgang (eds.), Rational Approaches to Drug Design, Proceedings of the 13th European Symposium on Quantitative Structure-Activity Relationships, pp. 437-446. Prous Science, Barcelona, Spain, 2001.

Abstract: A global method was recently proposed for chem. information management based on chemog. and GPS, the Navstar Global positioning System, a 24-satellites network in Earth orbit that provides precise positioning everywhere on the planet. Novel compds. are positioned in the ChemGPS system by predicting the nine-dimensional PCA scores, based on the previously defined model. The resulting coordinate system is similar across large nos. of chems., as it is obtained via external predictions based on the same, consistent, ref. system. This nine-dimensional score does not change with new structures, which in turn provides a global mapping device for the drug-like chem. space. ChemGPS captures the global aspects of chem. space and it has the ability to provide a common ref. for all compds. studied so far, and can be further re-directed towards a group of desired properties, such as pharmacokinetics.
Keywords: Computer program, ChemGPS, Combinatorial library, Drug design, Molecular structure-property relationship

Zamora, Ismael; Oprea, Tudor I.; Ungell, Anna-Lena. Prediction of oral drug permeability. Rational Approaches to Drug Design, Proceedings of the 13th European Symposium on Quantitative Structure-Activity Relationships, pp. 271-280, 2001.

Abstract: No high quality QSAR model was achievable for oral availability because this physiol. process is multifactorial and difficult to describe using linear models. A strategy was proposed to break down the complexity of oral availability into simpler, more fundamental processes. For the permeability process, a model based on 20 compds. and Caco-2 measurements is presented. The ghost erhytrocytes diffusion rate, as measured by NMR for 12 compds., that is believed to represent passive diffusion through a membrane, was successfully modeled using VolSurf. Two models to predict and explain the inhibition of cephalexine uptake that represents a measure of the dipeptide carrier system were developed and shown. From this 3D quant. structure absorption relationship, a pharmacophoric model can be achieved. The applicability of this model to predict active transport via the peptide carrier in general is limited, since the present study data set is too homogeneous. However, it suggests that modeling of active transport is possible, indicating possible new applications of mol. modeling in drug discovery.
Keywords: Computer program; Molecular Structure-Property Relationships; Oral drug delivery permeability model

Mracec, Maria; Oprea, Tudor I.; Mracec, Mircea. Correlation between experimental electron affinities for aromatic derivatives and the values calculated with semiempirical MO methods. . Revue Roumaine de Chimie, 45(10), pp. 949-954, 2000.

Abstract: Linear regressions of exptl. electron affinities, EA, and their values calcd. by semiempirical MO methods (CNDO, INDO, ZINDO/1, MNDO, AM1, PM3) were obtained for three classes of arom. derivs., ring-substituted nitrobenzenes, substituted 1,4-benzo-, naphtho- and anthraquinones and polycondensed arom. hydrocarbons. The most closed values to the exptl. EAs are obtained by the AM1 method which gives also a good correlation coeff. r = 0.97 and std. error of est. s = 0.12. The ZINDO/1 method gives a slightly better correlation coeff., r = 0.98, but s = 0.30 and the calcd. EA values are neg. and far from the exptl. ones.
Keywords: Quantum mechanics; Semiempirical calculations; Aromatic derivatives

Oprea, T. I.; Gottfries, J.; Sherbukhin, V.; Svensson, P.; Kuhler, T. C. . Chemical information management in drug discovery: optimizing the computational and combinatorial chemistry interfaces. . J. Mol. Graphics Modell. , 18(4/5), pp. 512-524, 2000.

Abstract: Structure-property relationships, central to many of today's drug discovery strategies, are not straightforward to deal with when trying to predict drug efficacy, i.e., the combined outcome of target affinity, pharmacodynamic behavior, pharmacokinetic properties, and metabolic fate. In this article, we discuss the handling of chem. property information in reagents-for-synthesis selection, enumeration, and virtual library construction. We describe the use of diversity assessment and/or exptl. design in selection of compd.-libraries-to-be-synthesized. Our overall objective was to identify good-quality drug candidates through reliable structure-activity relationship data, with the min. no. of compds. synthesized and tested. Chem. filters, property filters, scoring functions, and utilization of interactive visualization tools are discussed. The concept of chem. diversity and aspects of chem. space navigation employing a proprietary tool, Chem. Global Positioning System (ChemGPS), for mapping the drug-related chem. space are examd. Guidelines and workflow recommendations for the practicing medicinal chemist are proposed.
Keywords: Combinatorial chemistry, ChemGPS, Computer application, Drug design, Information systems, Hydrogen bond, Lipophilicity, Optimization, QSAR

Oprea, Tudor I. . Property distribution of drug-related chemical databases. . J. Comput. -Aided Mol. Des. , 14(3), pp. 251-264, 2000.

Abstract: The process of compd. selection and prioritization is crucial for both combinatorial chem. (CBC) and high throughput screening (HTS). Compd. libraries have to be screened for unwanted chem. structures, as well as for unwanted chem. properties. Property extrema can be eliminated by using property filters, in accordance with their actual distribution. Property distribution was examd. in the following compd. databases: MACCS-II Drug Data Report (MDDR), Current Patents Fast-alert, Comprehensive Medicinal Chem., Physician Desk Ref., New Chem. Entities, and the Available Chem. Directory (ACD). The ACDF and MDDRF subsets were created by removing reactive functionalities from the ACD and MDDR databases, resp. The ACDF subset was further filtered by keeping only mols. with a "drug-like" score below 0.8. The following properties were examd.: mol. wt. (MW), the calcd. octanol/water partition coeff. (CLOGP), the no. of rotatable (RTB) and rigid bonds (RGB), the no. of rings (RNG), and the no. of hydrogen bond donors (HDO) and acceptors (HAC). Of these, MW and CLOGP follow a Gaussian distribution, whereas all other descriptors have an asym. (truncated Gaussian) distribution. Four out of five compds. in ACDF and MDDRF pass the "rule of 5" test, a probability scheme that ests. oral absorption proposed by Lipinski et al. Because property distributions of HDO, HAC, MW and CLOGP (used in the "rule of 5" test) do not differ significantly between these datasets, the "rule of 5" does not distinguish "drugs" from "nondrugs". Therefore, Pareto analyses were performed to examine skewed distributions in all compd. collections. Seventy percent of the "drug-like" compds. were found between the following limits: 0 <= HDO <= 2, 2 <= HAC <= 9, 2 <= RTB <= 8, and 1 <= RNG <= 4, resp. The no. of launched drugs in MDDR having 0 <= HDO <= 2 is 4.8 times higher than the no. of drugs having 3 <= HDO <= 5. Skewed distributions can be exploited to focus on the "drug-like space": 62.68% of ACDF ("nondrug-like") compds. have 0 <= RNG <= 2, and RGB <= 17, while 28.88% of ACDF compds. have 3 <= RNG <= 13, and 18 <= RGB <= 56. By contrast, 61.22% of MDDRF compds. have RNG =< 3, and RGB =< 18, and only 24.73% of MDDRF compds. have 0 <= RNG <= 2 rings, and RGB <= 17. The probability of identifying "drug-like" structures increases with mol. complexity.
Keywords: Combinatorial chemistry, Computer application, Databases, Drug design, Drugs, Hydrogen bond, Molecular weight, Partition, QSAR, Structure-activity relationship

Oprea, T. I.; Gottfries, J. . Toward minimalistic modeling of oral drug absorption. . Journal of Molecular Graphics & Modelling, 17(5/6), pp. 261-274, 1999.

Abstract: Poor intestinal permeability of drugs constitutes a major bottleneck in the successful development of candidate drugs. Fast computational tools to help in designing compds. with increased probability of oral absorption are required, since both medicinal and combinatorial chemists are under pressure to consider increasing nos. of virtual and existing compds. The QSAR paradigm for drug absorption is expressed as a function of mol. size, hydrogen-bonding capacity, and lipophilicity. A nonlinear PLS model that can be achieved with minimal computational efforts is described. The QSAR model correlates human intestinal absorption (%HIA) data, and apparent Caco-2 cell permeability data, to parameters calcd. from mol. structures. Two properties were found to be relevant for absorption predictions, namely H-bonding capacity, and hydrophobic transferability. The parsimony principle was applied in several aspects: single conformers were used to compute mol. surface areas; the definitions of "polar" and "nonpolar" surfaces were done in a simplistic fashion; simple and fast 2D descriptors were used to est. other properties; the 1 PLS component model was selected. These choices result in a minimalistic model for oral absorption. The use of both %HIA and Caco-2 permeability data was found to stabilize and improve the model. This QSAR model can serve as a simple, quant. extension of the "rule of five" scheme, in a manner that can prove beneficial to the drug discovery process.
Keywords: Biological Simulation and Modeling, Combinatorial chemistry, Drug delivery systems, Drug design, Hydrophilicity, Hydrophobicity, Intestine, Oral drug absorption, Permeability, Pharmacokinetics, QSAR (structure-activity relationship)

Teague, Simon J.; Davis, Andrew M.; Leeson, Paul D.; Oprea, Tudor I. . The design of leadlike combinatorial libraries. . Angew. Chem., Int. Ed. , 38(24), pp. 3743-3748, 1999.

Abstract: A review with 26 refs. The authors proposed that the properties required of library compds. intended to provide leads suitable for further optimization may be rather different. The selection of leadlike compds. for further optimization eases the pressure on subsequent and more labor-intensive parts of drug discovery process.
Keywords: Combinatorial library, Drug Design, Drug Discovery, Drug screening, High-throughput screening, HTS, QSAR, Structure-activity relationship

Sulea, Traian; Kurunczi, Ludovic; Oprea, Tudor I.; Simon, Zeno. . MTD-ADJ: a multiconformational minimal topologic difference for determining bioactive conformers using adjusted biological activities. . J. Comput. -Aided Mol. Des. , 12(2), pp. 133-146, 1998.

Abstract: The active conformation is part of a conformational mixt. with exptl. activity Yexp, and is used in QSAR studies to ext. more information regarding the ligand-receptor interaction. To reflect the relative amt. (a) of the active conformation, we adjust Yexp: Yadj = Yexp - log a. We establish a quant. structure-activity relationship (QSAR) between Yadj and 3D conformational characteristics for the acetylcholinesterase (AChE) hydrolysis rates of 25 acetic esters. The 3D-QSAR model was obtained using the adjusted multiconformational minimal steric/topol. difference (MTD-ADJ) method, optimizing the receptor map based on Yadj for each conformer. Yadj was updated during each step of the optimization process. a And Yadj are based on the Boltzmann distribution calcd. using AM1 (MOPAC 6.0) relative energies of the COSMIC 90 derived conformers. The MTD-ADJ results are: (i) the 3D-QSAR models obtained by this procedure have significant statistical parameters and are similar to the unadjusted (MTD-MC, using Yexp) models; (ii) the selected bioactive conformations are extended, occupy cavity vertices and, for the same structures, have the same MTD value; and (iii) the optimized conformational map of the neutral ligands obtained from the MTD-ADJ model fits well in the active site of the crystallog. structure of AChE (from Torpedo californica). We propose a neutral ligands binding site model for AChE. Our results show that MTD-ADJ, which can be implemented in any 3D-QSAR method, is capable of providing addnl. information regarding the active conformations, and can be used to gain further insight into the ligand-receptor models for which no structural data are available.
Keywords: Acetylcholinesterase, Conformation (ligand), Molecular association, MTD-ADJ, QSAR (structure-activity relationship), Receptor-binding

Oprea, Tudor I.; Marshall, Garland R. Receptor-based prediction of binding affinities. . Perspect. Drug Discovery Des. , 9-11, pp. 35-61, 1998.

Abstract: A review with 76 refs. is given on methods that use the receptor's 3-dimensional structure to derive the scoring function for predicting binding affinities including general comments on scoring functions, the LUDI scoring function, the Wallqvist scoring function, the Verkhivker scoring function, VALIDATE, the Jain scoring function, the HTS approach, and prospects of scoring functions. Enzymes as examples are given.
Keywords: Conformation (ligand), Conformation (protein), Molecular association, QSAR (structure-activity relationship), Receptor-binding, Scoring functions

Oprea, Tudor I.; Hummer, Gerhard; Garcia, Angel E. . Identification of a functional water channel in cytochrome P450 enzymes. . Proc. Natl. Acad. Sci. U. S. A. , 94(6), pp. 2133-2138, 1997.

Abstract: Cytochrome P 450 enzymes are monooxygenases that contain a functional heme b group linked to a conserved cysteine with a thiolate bond. In the native state, the central iron atom is hexacoordinated with a covalently bound water mol. The exclusion of solvent mols. from the active site is essential for efficient enzymic function. Upon substrate binding, water has to be displaced from the active site to prevent electron uncoupling that results in hydrogen peroxide or water. In contrast to typical hemoproteins, the protein surface is not directly accessible from the heme of cytochromes P 450. We postulate a two-state model in which a conserved arginine, stabilizing the heme propionate in all known cytochrome P 450 crystal structures, changes from the initial, stable side-chain conformation to another rotamer (metastable). In this new state, a functional water channel (aqueduct) is formed from the active site to a water cluster located on the thiolate side of the heme, close to the protein surface. This water cluster communicates with the surface in the closed state and is partly replaced by the flipping arginine side chain in the open state, allowing water mols. to exit to the surface or to reaccess the active site. This two-state model suggests the presence of an exit pathway for water between the active site and the protein surface.
Keywords: Active sites (enzyme), Aromatase, Cytochrome P450, Conformation (protein), Hydration (chemical), X-ray structure analysis

Sulea, Traian; Oprea, Tudor Ionel; Muresan, Sorel; Chan, Shek Ling. A different method for steric field evaluation in CoMFA improves model robustness. . J. Chem. Inf. Comput. Sci. , 37(6), pp. 1162-1170, 1997.

Abstract: The all-grid probe Lennard-Jones 6-12 potential, typically used as steric descriptor in CoMFA, has been replaced by the vols. of van der Waals envelopes intersections between the probe-atom and the ligand mols. under investigation. The intersection vols. present a smoother distance dependence that overcomes the problems arising from formulation of a precise alignment and docking into the 3D lattice. A CoMFA-type application on a set of 78 steroid aromatase inhibitors with different grid and probe-atom characteristics suggests an improved model robustness for the new steric field in comparison with the classical 6-12 potential. Predefined cut-off and "min. sigma" values are not required. Systematic variation of the 3D lattice position leads to lower variations of cross-validated r-squared (q2LOO) at all levels of model complexity, which can be reduced with exclusion of some "interior" points. The relative simplicity and inexpensive computational demands make this steric field a promising alternative for routine CoMFA-based 3D-QSAR analyses.
Keywords: CoMFA, Conformation (ligand), Model predictivity, Molecular association, Physicochemical simulation, QSAR (structure-activity relationship), Receptor-binding, Steric field evaluation

Oprea, Tudor Ionel; Kurunczi, Ludovic; Timofei, Simona. QSAR studies of disperse azo dyes. Towards the negation of the pharmacophore theory of dye-fiber interaction?. Dyes Pigm. , 33(1), pp. 41-64, 1997.

Abstract: Twenty-seven disperse azo dyes were analyzed using Quant. Structure-Activity Relationship (QSAR) methods by correlating variations in the chem. structure with -<delta><mu>°, the affinity to cellulose fiber. Classical QSAR results, r2 of 0.32 for CLogP (the calcd. octanol-water partition coeff.) and r2 of 0.924 for MTD (min. topol. difference), suggest that steric, but not hydrophobic, effects are important. For Comparative Mol. Field Anal. (CoMFA), a 3-dimensional QSAR (3D-QSAR) method, r2 was 0.925, while q2 (cross-validated r2) was 0.776 for 2 PCs (principal components). CoMFA results imply that the pharmacophore theory of dye-fiber interaction holds true. However, CoMFA was insensitive to the alignment rules. PCA (Principal Component Anal.) shows that PC1 is related to chem. substituents, whereas PC2 is related to mol. length (l). The correlation between -<delta><mu>° and l (a 1D descriptor) is similar to the CoMFA results. The validity of the pharmacophore theory of dye-fiber interaction is questioned, illustrated by a case of overfitting in QSAR. Features that could improve disperse azo dye binding to cellulose are proposed.
Keywords: Biological Simulation and Modeling, Cellulose fibers, CoMFA, Disperse dyes, Dye-Fiber interaction, MTD, Pharmacophore theory, QSAR (Structure-Activity relationships)

Tung, C. -S.; Oprea, T. I.; Hummer, G.; Garcia, A. E. . Three-dimensional model of a selective theophylline-binding RNA molecule. . J. Mol. Recognit. , 9(4), pp. 275-286, 1996.

Abstract: A three-dimensional (3D) model for an RNA mol. that selectively binds theophylline but not caffeine is proposed. This RNA, which was found using SELEX (Jension et al., 1994), is 10 000 times more specific for theophylline (KD = 320 nM) than for caffeine (KD = 3.5 mM), although the two ligands are identical except for a Me group substituted at N7 (present only in caffeine). The binding affinity for ten xanthine-based ligands was used to derive a comparative mol. field anal. model (R2 = 0.93 for three components, with cross-validated R2 of 0.73), using the SYBYL and GOLPE programs. A pharmacophoric map was generated to locate steric and electrostatic interactions between theophylline and the RNA binding site. This information was used to identify putative functional groups of the binding pocket and to generate distance constraints. On the basis of a model for the secondary structure (Jenison et al., 1994), the 3D structure of this RNA was then generated using the following method: each helical region of the RNA mol. was treated as a rigid body; single-stranded loops with specific end-to-end distances were generated. The structures of RNA-xanthine complexes were studied using a modified Monte Carlo algorithm. The detailed structure of an RNA-ligand complex model, as well as possible explanations for the theophylline selectivity are discussed.
Keywords: Algorithm, Computer application, GOLPE, Monte Carlo, QSAR (Structure-activity relationship), RNA-binding, SELEX, Steric effects, Theophylline

Waller, Chris L.; Oprea, Tudor I.; Chae, Kun; Park, Hee-Kyoung; Korach, Kenneth S.; Laws, Susan C.; Wiese, Thomas E.; Kelce, William R.; Gray, L. Earl Jr. Ligand-Based Identification of Environmental Estrogens. . Chem. Res. Toxicol. , 9(8), pp. 1240-1248, 1996.

Abstract: Comparative mol. field anal. (CoMFA), a three-dimensional quant. structure-activity relation (3D-QSAR) paradigm, was used to examine the estrogen receptor (ER) binding affinities of a series of structurally diverse natural, synthetic, and environmental chems. of interest. The CoMFA/3D-QSAR model is statistically robust and internally consistent, and successfully illustrates that the overall steric and electrostatic properties of structurally diverse ligands for the estrogen receptor are both necessary and sufficient to describe the binding affinity. The ability of the model to accurately predict the ER binding affinity of an external test set of mols. suggests that structure-based 3D-QSAR models may be used to supplement the process of endocrine disrupter identification through prioritization of novel compds. for bioassay. The general application of this 3D-QSAR model within a toxicol. framework is, at present, limited only by the quantity and quality of biol. data for relevant biomarkers of toxicity and hormonal responsiveness.
Keywords: Biological Simulation and Modeling, CoMFA, Conformation (ligand), Endocrine disruptors, Environmental estrogens, Estrogen receptor, QSAR (Structure-Activity relationships), Receptor-binding, Toxicity

Oprea, Tudor I.; Garcia, Angel E. . Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors. . J. Comput. -Aided Mol. Des. , 10(3), pp. 186-200, 1996.

Abstract: Inhibition of aromatase, a cytochrome P 450 that converts androgens to estrogens, is relevant in the therapeutic control of breast cancer. We investigate this inhibition using a three-dimensional quant. structure-activity relationship (3D QSAR) method known as Comparative Mol. Field Anal., CoMFA [Cramer III, R.D. et al., J. Am. Chem. Soc., 110 (1988) 5959]. We analyzed the data for 50 steroid inhibitors [Numazawa, M. et al., J. Med. Chem., 37 (1994) 2198, and refs. cited therein] assayed against androstenedione on human placental microsomes. An initial CoMFA resulted in a three-component model for log(1/K1), with an explained variance r2 of 0.85, and a cross-validated q2 of 0.673. Chemometric studies were performed using GOLPE [Baroni, M. et al., Quant. Struct.-Act. Relatsh., 12(1993Z)9]. The CoMFA/GOLPE model is discussed in terms of robustness, predictivity, explanatory power and simplicity. After randomized exclusion of 25 or 10 compds. (repeated 25 times), the q2 for one component was 0.62 and 0.61, resp., while r2 was 0.674. We demonstrate that the predictive r2 based on the index gives a more accurate est. of external predictivity. Using CoMFA, the obsd. differences in aromatase inhibition among C6-substituted steroids are rationalized at the at. level. The CoMFA fields are consistent with known, potent inhibitors of aromatase, not included in the model. When positioned in the same alignment, these compds. have distinct features that overlap with the steric and electrostatic fields obtained in the CoMFA model. The presence of two hydrophobic binding pockets near the aromatase active site is discussed: a steric bulk tolerant one, common for C4, C6-alpha and C7-alpha substituents, and a smaller one at the C6-beta region.
Keywords: Anti-cancer compounds, Aromatase, CoMFA, QSAR (structure-activity relationships), Steroids,

Head, Richard D.; Smythe, Mark L.; Oprea, Tudor I.; Waller, Chris L.; Green, Stuart M.; Marshall, Garland R. VALIDATE: A New Method for the Receptor-Based Prediction of Binding Affinities of Novel Ligands. . J. Am. Chem. Soc. , 118(16), pp. 3959-3969, 1996.

Abstract: VALIDATE is a hybrid approach to predict the binding affinity of novel ligands for receptors of known three-dimensional structure. This approach calcs. physicochem. properties of the ligand and the receptor-ligand complex to est. the free energy of binding. The enthalpy of binding is calcd. by mol. mechanics while properties such as complementary hydrophobic surface area are used to est. the entropy of binding through heuristics. A diverse training set of 51 cryst. complexes was assembled, and their relevant physicochem. properties were computed. These properties were analyzed by partial least squares (PLS) statistics, or neural network anal. (SONNIC), to generate models for the general prediction of the affinity of ligands with receptors of known three-dimensional structure. The ability of the model to predict the affinity of novel complexes not included in the training set was demonstrated with three independent test sets: 14 complexes of known three-dimensional structure including 3 DNA complexes, a class of compd. not included in the training set, 13 HIV protease inhibitors fit to HIV-1 protease, and 11 thermolysin inhibitors fit to thermolysin.
Keywords: Conformation (ligand), Conformation (receptor), Hydrophobicity, Molecular association, QSAR (Structure-Activity Relationships), Receptor-binding, Scoring functions