Comparative Molecular Field Analysis Contour Research Articles

Molecular Docking and 3D-QSAR Based Design of Novel Imidazopyridinone Derivatives as Pseudomonas Aeruginosa Thymidylate Kinase Inhibitors

Thymidylate kinase (TMK) is a potential chemotherapeutic target since it is directly involved in the synthesis of deoxythymidine 5'-triphosphate an essential component in DNA replication. Inhibiting the function of TMK blocks DNA synthesis in replicating organisms. We report 3D-QSAR analysis on a series of thymidine mimetics exhibiting potent inhibitory activity against TMK. Molecular docking, Comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) were carried out to determine the requisite 3D structural features required for potent thymidylate kinase inhibitory activity. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the q 2 loo, r 2 ncv and r 2 pred. The models were graphically interpreted using CoMFA and CoMSIA contour maps. The results obtained from this study were used for rational design of potent inhibitors against thymidylate kinase.

CoMFA and docking study of 2,N6-disubstituted 1,2-dihydro-1,3,5-triazine-4,6-diamines as novel PfDHFR enzyme inhibitors for antimalarial activity

A three-dimensional quantitative structure–activity relationship (3D-QSAR) study was performed on 1,3,5-triazine derivatives which were based on Ala16Val+Ser108Thr mutant DHFR inhibitors of Plasmodium falciparum clone (FCR-3). Comparative Molecular Field Analysis (CoMFA) was carried out for designing novel PfDHFR enzyme inhibitors. It is shown that the steric and electrostatic properties by CoMFA contours can be related to the PfDHFR inhibitory activity. Glide-XP of Schrödinger was used for docking of PfDHFR inhibitors into the putative binding sites of the PfDHFR.

Investigations and design of pyridine-2-carboxylic acid thiazol-2-ylamide analogs as methionine aminopeptidase inhibitors using 3D-QSAR and molecular docking

Methionine amino peptidases (MetAPs) are metalloproteases that remove co-translational N-terminal methionine from nascent polypeptide chains. Due to their essential role in protein synthesis, MetAPs are considered as potential targets for antibacterial drugs. In the present work, three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were carried out on a series of pyridine-2-carboxylic acid thiazol-2-ylamide-based MetAP inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The models were developed using 30 training set molecules. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients (q 2) of 0.799 and 0.704 and conventional correlation coefficients (r 2) of 0.989 and 0.954, respectively. These inhibitors were docked into MetAP active site. The CoMFA and CoMSIA field contour maps correlate well with the structural characteristics of the binding pocket of MetAP active site. Using the knowledge of structure–activity relationship and receptor–ligand interactions from 3D-QSAR model and the docked complexes, four new pyridine-2-carboxylic acid thiazol-2-ylamide analogs were designed. These analogs exhibit significantly better predicted activity than the reported molecules. The present work has implications for the development of novel antibiotics as potent MetAP inhibitors.

P56(lck) kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives.

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on 3D-QSAR (3D-quantitative structure activity relationship) studies were carried out on 97 flavonoid derivatives as potent P56(lck) protein tyrosine kinase inhibitors. The best prediction was obtained with CoMFA standard model (q² = 0.838, r² = 0.948) using steric, electrostatic along with CoMSIA standard model (q² = 0.714, r² = 0.921) using steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. Of the 97 molecules a training set of 76 compounds and the predictive ability of the QSAR model were assessed employing a test set of 21 compounds. The resulting CoMFA and CoMSIA contour maps were used to identify the structural features relevant to the biological activity in this series of flavonoid derivatives, based upon which we identified and designed 10 novel molecules that showed superior inhibitory activity against P56(lck) protein which shed new light on effective therapeutic agents against these classes of enzymes.

A systematic quantitative approach to rational drug design and discovery of novel human carbonic anhydrase IX inhibitors

Drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed for a series of carbonic anhydrase IX inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques with the help of SYBYL 7.1 software. The large set of 36 different aromatic/heterocyclic sulfamates carbonic anhydrase (CA, EC 4.2.1.1) inhibitors, such as hCA IX, was chosen for this study. The conventional ligand-based 3D-QSAR studies were performed based on the low energy conformations employing database alignment rule. The ligand-based model gave q2 values 0.802 and 0.829 and r2 values 1.000 and 0.994 for CoMFA and CoMSIA, respectively, and the predictive ability of the model was validated. The predicted r2 values are 0.999 and 0.502 for CoMFA and CoMSIA, respectively. SEA (steric, electrostatic, hydrogen bond acceptor) of CoMSIA has the significant contribution for the model development. The docking of inhibitors into hCA IX active site using Glide XP (Schrödinger) software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps are well in agreement with the structural characteristics of the binding pocket of hCA IX active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved hCA IX inhibitors as leads for various types of metastatic cancers including those of cervical, renal, breast and head and neck origin.

Hologram quantitative structure–activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors

Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure–activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure–activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q2 = 0.802, r2 = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2–5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q2 = 0.748, r2 = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives.

3D-QSAR studies of chromone derivatives as iron-chelating agent

The metal-chelating activity of a series of 48 chromone compounds, evaluated by ferrous (Fe2+) chelating test, were subjected to 3D-QSAR studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best CoMFA model obtained from HF/6-31G* geometry optimization and field fit alignment gave cross-validated r 2 (q 2) = 0.582, non-cross-validated r 2 = 0.975. The best CoMSIA model gave q 2 = 0.617, non-cross-validated r 2 = 0.917. The resulted CoMFA and CoMSIA contour maps proposed the Fe2+-chelating sites of chromone compounds compared with those of quercetin.

Insight into the Structural Requirements of Narlaprevir-Type Inhibitors of NS3/NS4A Protease Based on HQSAR and Molecular Field Analyses

In the life cycle of hepatitis C virus (HCV), NS3/NS4A protease has been proved to play a vital role in the replication of the HCV virus. Narlaprevir and its derivatives, the inhibitors of NS3/NS4A, would be potentially developed as important anti-HCV drugs in the future. In this study, quantitative structure-activity relationship (QSAR) analyses for 190 narlaprevir derivatives were conducted using comparative molecular field analysis (CoMFA), comparative molecular indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) techniques. Both of the best CoMFA and HQSAR models showed statistical significance for the training set and good predictive accuracy for the test set, which strongly manifested the robustness of the CoMFA and HQSAR models. The CoMFA contour maps and the HQSAR contribution maps were both presented. Furthermore, based on the essential factors for ligand binding derived from the QSAR models, sixteen new derivatives were designed and some of them showed higher inhibitory activities confirmed by our models and molecular docking studies. General speaking, this study provides useful suggestions for the design of potential anti-HCV drugs.

Computational Insights into the Inhibition of Inosine 5′‐Monophosphate Dehydrogenase by Mycophenolic Acid Analogs: Three‐Dimensional Quantitative Structure–Activity Relationship and Molecular Docking Studies

Inosine 5'-monophosphate dehydrogenase (IMPDH) is a key enzyme in the de novo synthesis of guanosine nucleotides. It is considered as an important target in the quest for drugs in the immunosuppressive, antiviral, antibacterial, and anticancer therapeutic areas. Herein, we report the 3D-QSAR analyses using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking on mycophenolic acid derivates for the first time. We obtained cross-validated q(2) value of 0.805 for CoMFA and 0.620 for CoMSIA, while the non-cross-validated r(2) values for them were 0.969 and 0.935, respectively. Based on the CoMFA and CoMSIA contour maps and docking analyses, some key structural factors responsible for inhibitory activity were revealed. The results obtained from this study could be used for the rational design of potent inhibitors against IMPDH.

3D-QSAR Study on dihydro-1,3,5-triazines and their spiro derivatives as DHFR inhibitors by comparative molecular field analysis (CoMFA)

A 3D-QSAR/CoMFA was performed for a series of triazine and its spiro derivative based DHFR inhibitors displaying IC50 values ranging from 0.002 to 58.8μM. Analyses resulted in a reliable computational model with the parameters of n=46, r2=0.986, q2=0.724, SE=0.164, F=275.889. It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the DHFR inhibitory activity. The predictive ability of the resultant model was evaluated using a test set comprised of 18 molecules and the results show that the CoMFA model is able to correctly predict the poor inhibitory activities of the compounds in the testing set. This model is a significant guide to trace the features that really matter especially with respect to the design of novel compounds.

3D‐QSAR and Molecular Docking Studies on 3‐Anilino‐4‐Arylmaleimide Derivatives as Glycogen Synthase Kinase‐3β Inhibitors

Glycogen synthase kinase-3, a serine/threonine kinase, is a fascinating enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as diabetes mellitus, cancer, chronic inflammation, bipolar disorders, and Alzheimer's disease. It is important to inhibit glycogen synthase kinase-3 selectively, and the net effect of the glycogen synthase kinase-3 inhibitors thus should be target specific, over other phylogenetically related kinases such as CDK-2. In the present work, we have carried out three-dimensional quantitative structure-activity relationship studies on novel class of 3-anilino-4-arylmaleimide derivatives to have improved cellular activity. Docked conformation of the most active molecule in the series, which shows desirable interactions in the receptor, was taken as template for the alignment of the molecules. Statistically significant CoMSIA (r2(cv)=0.614, r2(ncv)=0.948) and comparative molecular field analysis (r2(cv) =0.652, r2(ncv)=0.958) models were generated using 57 molecules in training set. The predictive ability of CoMSIA and comparative molecular field analysis models was determined using a test set of 17 molecules, which gave predictive correlation coefficients (r2(pred)) of 0.87 and 0.82, respectively, indicating good predictive power. Based on the information derived from CoMSIA and comparative molecular field analysis contour maps, we have identified some key features that explain the observed variance in the activity and have been used to design new anilinoarylmaleimide derivatives. The designed molecules showed better binding affinity in terms of estimated docking scores with respect to the already reported systems, hence suggesting that newly designed molecules can be more potent and selective toward glycogen synthase kinase-3β inhibition.

2D and 3D QSAR study on amino nicotinic acid and isonicotinic acid derivatives as potential inhibitors of dihydroorotate dehydrogenase (DHODH)

Dihydroorotate dehydrogenase (DHODH) is a central enzyme of pyrimidine biosynthesis which catalyzes oxidation of dihydroorotate (DHO) to orotate (ORO). DHODH inhibitors are considered as promising targets for the development of antiproliferative, antiparasitic, and immunosuppressive drugs. The best 2D QSAR model for the prediction of human dihydroorotate dehydrogenase (hDHODH) inhibitory activity was obtained by applying MLR giving r2 = 0.834 and q2 = 0.756, PCR giving r2 = 0.833 and q2 = 0.756, and PLS giving r2 = 0.864 and q2 = 0.786. 2D QSAR studies reveal the importance of alignment independent descriptors for predicting hDHODH inhibitory activity. The 3D QSAR study was performed by comparative molecular field analysis (CoMFA) to rationalize the structural requirements responsible for the inhibitory activity of these compounds. The best CoMFA model obtained for the training set was statistically significant with cross-validated coefficients (q2) of 0.630 and conventional coefficients (r2) of 0.949. The CoMFA contour maps suggest some important structural features-like electronegative substituents at biphenyl ring system for strong inhibitory activity. We believe that these results are helpful in design of more potent and selective hDHODH inhibitors.

3D‐QSAR Studies of JNK1 Inhibitors Utilizing Various Alignment Methods

We report our three-dimensional quantitative structure activity relationship (3D-QSAR) studies of the series of anilinopyrimidine derivatives of JNK1 inhibitors. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied using different alignment methods. The ligand-based atom-by-atom matching alignment has produced better values for CoMFA (q(2) = 0.646 and r(2) = 0.983), while in CoMSIA it has achieved only lower statistical values. The pharmacophore-based model has produced (q(2) = 0.568, r(2) = 0.938) and (q(2) = 0.670, r(2) = 0.982) for CoMFA and CoMSIA models, respectively. As the model was based on the receptor-guided alignment, all the compounds were optimized within the receptor, resulting in q(2) = 0.605 and r(2) = 0.944 for CoMFA, and q(2) = 0.587 and r(2) = 0.863 for CoMSIA. Molecular Dynamic simulation studies suggested that the generated models were consistent with the low-energy protein ligand conformation. The CoMFA and CoMSIA contour maps indicated that the substitutions of the electropositive groups in the phenyl ring, and an addition of hydrophobic groups in the pyrimidine ring, are important to enhance the activity of this series. Moreover, the virtual screening analysis against NCI database yields potentials hits, and the results obtained would be useful to synthesize selective and highly potent c-Jun N-terminal kinase 1 analogs.

3D-QSAR and molecular docking studies of 2-pyrimidinecarbonitrile derivatives as inhibitors against falcipain-3

The three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of falcipain-3 inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 42 molecules served to establish the QSAR models. The optimum CoMFA and CoMSIA models obtained for the training set were statistically significant with cross-validated correlation coefficients r(cv)(2) (q(2)) of 0.549 and 0.608, and conventional correlation coefficients (r(2)) of 0.976 and 0.932, respectively. An independent test set of 12 molecules validated the external predictive power of both models with predicted correlation coefficients (r(pred)(2)) for CoMFA and CoMSIA as 0.697 and 0.509, respectively. The docking of inhibitors into falcipain-3 active site using GOLD software revealed the vital interactions and binding conformation of the inhibitors. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of falcipain-3 active site, which suggests that the information rendered by 3D-QSAR models and the docking interactions can provide guidelines for the development of improved falcipain-3 inhibitors.

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q (2)=0.696 and r (2)=0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q (2)=0.711 and r (2)=0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r (2) (pred) values of 0.76 and 0.74, respectively. CoMFA and CoMSIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.

Multi-conformation 3D QSAR study of benzenesulfonyl-pyrazol-ester compounds and their analogs as cathepsin B inhibitors

Cathepsin B has been found being responsible for many human diseases. Inhibitors of cathepsin B, a ubiquitous lysosomal cysteine protease, have been developed as a promising treatment for human diseases resulting from malfunction and over-expression of this enzyme. Through a high throughput screening assay, a set of compounds were found able to inhibit the enzymatic activity of cathepsin B. The binding structures of these active compounds were modeled through docking simulation. Three-dimensional (3D) quantitative structure–activity relationship (QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on the docked structures of the compounds. Strong correlations were obtained for both CoMFA and CoMSIA models with cross-validated correlation coefficients ( q 2) of 0.605 and 0.605 and the regression correlation coefficients ( r 2) of 0.999 and 0.997, respectively. The robustness of these models was further validated using leave-one-out (LOO) method and training-test set method. The activities of eight (8) randomly selected compounds were predicted using models built from training set of compounds with prediction errors of less than 1 unit for most compounds in CoMFA and CoMSIA models. Structural features for compounds with improved activity are suggested based on the analysis of the CoMFA and CoMSIA contour maps and the property map of the protein ligand binding site. These results may help to provide better understanding of the structure–activity relationship of cathepsin B inhibitors and to facilitate lead optimization and novel inhibitor design. The multi-conformation method to build 3D QSAR is very effective approach to obtain satisfactory models with high correlation with experimental results and high prediction power for unknown compounds.

Structural determinants of benzodiazepinedione/peptide-based p53-HDM2 inhibitors using 3D-QSAR, docking and molecular dynamics

As a tumor suppressor, p53 protein regulates the cell cycle and is involved in preventing tumorgenesis. The protein level of p53 is under the tight control of its negative regulator human double minute 2 (HDM(2)) via ubiquitination. Therefore, the design of inhibitors of HDM(2) has attracted much interest of research on developing novel anticancer drugs. Presently, two classes of molecules, i.e., the 1,4-benzodiazepine-2,5-diones (BDPs) and N-Acylpolyamine (NAPA) derivatives were studied by three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling approaches including the comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) as promising p53-HDM(2) inhibitors. Based on both the ligand-based and receptor-guided (docking) alignments, two optimal 3D-QSAR models were obtained with good predictive power of q(2) = 0.41, r(2)(pred) = 0.60 for BDPs, and q(2) = 0.414, r(2)(pred) = 0.69 for NAPA analogs, respectively. By analysis of the model and its related contour maps, it is revealed that the electrostatic interactions contributed much larger to the compound binding affinity than the steric effects. And the contour maps intuitively suggested where to modify the molecular structures in order to improve the binding affinity. In addition, molecular dynamics simulation (MD) study was also carried out on the dataset with purpose of exploring the detailed binding modes of ligand in the HDM(2) binding pocket. Based on the CoMFA contour maps and MD-based docking analyses, some key structural aspects responsible for inhibitory activity of these two classes of compounds were concluded as follows: For BDPs, the R(1) and R(3) regions should have small electronegativity groups; substituents R(2) and R(4) should be larger, and R(3) substituent mainly involves in H-bonds forming. For NAPA derivatives, bulky and electropositive groups in ring B and ring A, small substituent at region P is favorable for the inhibitory activity. The models and related information, we hope, may provide important insight into the inhibitor-p53-HDM(2) interactions and be helpful for facilitating the design of novel potent inhibitors.

SAR studies of 4-pyridyl heterocyclic anilines that selectively induce autophagic cell death in von Hippel-Lindau-deficient renal cell carcinoma cells

We recently identified a class of pyridyl aniline thiazoles (PAT) that displayed selective cytotoxicity for von Hippel-Lindau (VHL) deficient renal cell carcinoma (RCC) cells in vitro and in vivo. Structure–activity relationship (SAR) studies were used to develop a comparative molecular field analysis (CoMFA) model that related VHL-selective potency to the three-dimensional arrangement of chemical features of the chemotype. We now report the further molecular alignment-guided exploration of the chemotype to discover potent and selective PAT analogues. The contribution of the central thiazole ring was explored using a series of five- and six-membered ring heterocyclic replacements to vary the electronic and steric interactions in the central unit. We also explored a positive steric CoMFA contour adjacent to the pyridyl ring using Pd-catalysed cross-coupling Suzuki–Miyaura, Sonogashira and nucleophilic displacement reactions to prepare of a series of aryl-, alkynyl-, alkoxy- and alkylamino-substituted pyridines, respectively. In vitro potency and selectivity were determined using paired RCC cell lines: the VHL-null cell line RCC4 and the VHL-positive cell line RCC4-VHL. Active analogues selectively induced autophagy in RCC4 cells. We have used the new SAR data to further develop the CoMFA model, and compared this to a 2D-QSAR method. Our progress towards realising the therapeutic potential of this chemotype as a targeted cytotoxic therapy for the treatment of RCC by exploiting the absence of the VHL tumour suppressor gene is reported.

Predicting anti-cancer activity of quinoline derivatives: CoMFA and CoMSIA approach

The 3D quantitative structure-activity relationships of 31 quinoline nuclei containing compounds and their biological activity have been investigated to establish various models. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies resulted in reliable and significant computational models. The obtained CoMFA model showed high predictive ability with q2 = 0.592, r2 = 0.966 and standard error of estimation (SEE) = 0.167, explaining majority of the variance in the data with two principal components. Predictions obtained with CoMSIA steric, electrostatic, hydrophobic, hydrogen-bond acceptor and donor fields (q2 = 0.533, r2 = 0.985) showed high prediction ability with minimum SEE (0.111) and four principal components. The information obtained from the CoMFA and CoMSIA contour maps can be utilized for the design and development of topoisomerase-II inhibitors for synthesis.

Comparative Molecular Field Analysis of a Series of Inhibitors of HIV-1 Protease

Several protease inhibitors have reached the world market in the last fifteen years, dramatically improving the quality of life and life expectancy of millions of HIV-infected patients. In spite of the tremendous research efforts in this area, resistant HIV-1 variants are constantly decreasing the ability of the drugs to efficiently inhibit the enzyme. As a consequence, inhibitors with novel frameworks are necessary to circumvent resistance to chemotherapy. In the present work, we have created 3D QSAR models for a series of 82 HIV-1 protease inhibitors employing the comparative molecular field analysis (CoMFA) method. Significant correlation coefficients were obtained (q(2) = 0.82 and r(2) = 0.97), indicating the internal consistency of the best model, which was then used to evaluate an external test set containing 17 compounds. The predicted values were in good agreement with the experimental results, showing the robustness of the model and its substantial predictive power for untested compounds. The final QSAR model and the information gathered from the CoMFA contour maps should be useful for the design of novel anti-HIV agents with improved potency.