Computer-aided identification of novel 3,5-substituted rhodanine derivatives with activity against Staphylococcus aureus DNA gyrase

Methicillin resistant Staphylococcus aureus (MRSA) is among the major drug resistant bacteria that persist in both the community and clinical settings due to resistance to commonly used antimicrobials. This continues to fuel the need for novel compounds that are active against this organism. For this purpose we have targeted the type IIA bacterial topoisomerase, DNA gyrase, an essential enzyme involved in bacterial replication, through the ATP-dependent supercoiling of DNA. The virtual screening tool Shape Signatures was applied to screen a large database for agents with shape similar to Novobiocin, a known gyrase B inhibitor. The binding energetics of the top hits from this initial screen were further validated by molecular docking. Compounds with the highest score on available crystal structure of homologous DNA gyrase from Thermus thermophilus were selected. From this initial set of compounds, several rhodanine-substituted derivatives had the highest antimicrobial activity against S. aureus, as determined by minimal inhibitory concentration assays, with Novobiocin as the positive control. Further activity validation of the rhodanine compounds through biochemical assays confirmed their inhibition of both the supercoiling and the ATPase activity of DNA gyrase. Subsequent docking and molecular dynamics on the crystal structure of DNA gyrase from S. aureus when it became available, provides further rationalization of the observed biochemical activity and understanding of the receptor–ligand interactions. A regression model for MIC prediction against S. aureus is generated based on the current molecules studied as well as other rhodanines derivatives found in the literature.     

Piperazine-azole-fluoroquinolone hybrids: Conventional and microwave irradiated synthesis,biological activity screening and molecular docking studies

A series of new 1,2,4-triazole and 1,3,4-oxadiazole derivatives was obtained via several steps sequential reactions of phenyl piperazine. Then, these compounds were converted to the corresponding fluoroquinolone hybrids via one pot three component Mannich reaction. All the reactions were examined under conventional and microwave mediated conditions, and optimum conditions were determined. The effect of different solvents and microwave power on microwave prompted reactions was investigated as well. All the newly synthesized compounds were characterized by FTIR, ¹H NMR, ¹³C NMR and EI MS spectral techniques. The antimicrobial activity, DNA gyrase and Topoisomerase IV inhibition potentials were performed. The results obtained showed that fluoroquinolone hybrids possess good antimicrobial activity. Moreover, Fluoroquinolone-azole-piperazine hybrids synthesized in the present study displayed excellent DNA gyrase inhibition. To unveil the interaction mode of compounds to receptor, a molecular docking study was performed. With an average least binding energy of −9.5 kcal/mol, all compounds were found to have remarkable inhibitory potentials against DNA gyrase (E. coli).     

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using ‘Receptor-Ligand Pharmacophore Generation’ method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r² of 0.996; for the test set, the correlation coefficient r² was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.     

Receptor based 3D-QSAR to identify putative binders of Mycobacterium tuberculosis Enoyl acyl carrier protein reductase

In the current study, the applicability and scope of 3D-QSAR models (CoMFA and CoMSIA) to complement virtual screening using 3D pharmacophore and molecular docking is examined and applied to identify potential hits against Mycobacterium tuberculosis Enoyl acyl carrier protein reductase (MtENR). Initially CoMFA and CoMSIA models were developed using series of structurally related arylamides as MtENR inhibitors. Docking studies were employed to position the inhibitors into MtENR active site to derive receptor based 3D-QSAR models. Both CoMFA and CoMSIA yielded significant cross validated q² values of 0.663 and 0.639 and r² values of 0.989 and 0.963, respectively. The statistically significant models were validated by a test set of eight compounds with predictive r² value of 0.882 and 0.875 for CoMFA and CoMSIA. The contour maps from 3D-QSAR models in combination with docked binding structures help to better interpret the structure activity relationship. Integrated with CoMFA and CoMSIA predictive models structure based (3D-pharmacophore and molecular docking) virtual screening have been employed to explore potential hits against MtENR. A representative set of 20 compounds with high predicted IC₅₀ values were sorted out in the present study.     

Quinoline Hydrazone Derivatives as New Antibacterials against Multidrug Resistant Strains

To develop novel antimicrobial agents a series of 2(4)-hydrazone derivatives of quinoline were designed, synthesized and tested. QSAR models of the antibacterial activity of quinoline derivatives were developed by the OCHEM web platform using different machine learning methods. A virtual set of quinoline derivatives was verified with a previously published classification model of anti-E. coli activity and screened using the regression model of anti-S. aureus activity. Selected and synthesized 2(4)-hydrazone derivatives of quinoline exhibited antibacterial activity against the standard and antibiotic-resistant S. aureus and E. coli strains in the range from 15 to 30 mm by the diameter of growth inhibition zones. Molecular docking showed the complex formation of the studied compounds into the catalytic domain of dihydrofolate reductase with an estimated binding affinity from −8.4 to −9.4 kcal/mol.     

3D-QSAR pharmacophore modelling,virtual screening and docking studies for lead discovery of a novel scaffold for VEGFR 2 inhibitors: Design,synthesis and biological evaluation

A series of novel 6,7-dihydro-5H-cyclopenta[d]pyrimidine derivatives was successfully designed, synthesized and evaluated as a new chemical scaffold with vascular endothelial growth factor receptor (VEGFR 2) inhibitory activity. Compounds 6c and 6b showed enzyme inhibition of 97% and 87% at 10 µM, respectively, and exhibited potent dose-related VEGFR 2 inhibition with IC₅₀ values of 0.85 µM and 2.26 µM, respectively. The design of the 6,7-dihydro-5H-cyclopenta[d]pyrimidine scaffold was implemented via consecutive molecular modelling protocols prior to the synthesis and biological evaluation of the derivatives. First, sorafenib was docked in the binding site of VEGFR 2 to study its binding orientation and affinity, followed by the generation of a valid 3D QSAR pharmacophore model for use in the virtual screening of different 3D databases. Structures with promising pharmacophore-based virtual screening results were refined using molecular docking studies in the binding site of VEGFR 2. A novel scaffold was designed by incorporating the results of the pharmacophore model generation and molecular docking studies. The new scaffold showed hydrophobic interactions with the kinase front pocket that may be attributed to increasing residence time in VEGFR 2, which is a key success factor for ligand optimization in drug discovery. Different derivatives of the novel scaffold were validated using docking studies and pharmacophore mapping, where they exhibited promising results as VEGFR 2 inhibitors to be synthesized and biologically evaluated. 6,7-dihydro-5H-cyclopenta[d]pyrimidine is a new scaffold that can be further optimized for the synthesis of promising VEGFR 2 inhibitors.     

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.     

2D- and 3D-QSAR modelling,molecular docking and in vitro evaluation studies on 18β-glycyrrhetinic acid derivatives against triple-negative breast cancer cell line

Abstract

Triple-negative breast cancers (TNBCs) are one of the most aggressive and complex forms of cancers in women. TNBCs are commonly known for their complex heterogeneity and poor prognosis. The present work aimed to develop a predictive 2D and 3D quantitative structure–activity relationship (QSAR) models against metastatic TNBC cell line. The 2D-QSAR was based on multiple linear regression analysis and validated by Leave-One-Out (LOO) and external test set prediction approach. QSAR model presented regression coefficient values for training set (r²), LOO-based internal regression (q²) and external test set regression (pred_r²) which are 0.84, 0.82 and 0.75, respectively. Five properties, Epsilon4 (electronegativity), ChiV3cluster (valence molecular connectivity index), chi3chain (retention index for three-membered ring), TNN5 (nitrogen atoms separated through 5 bond distance) and nitrogen counts, were identified as important structural features responsible for anticancer activity of MDA-MB-231 inhibitors. Five novel derivatives of glycyrrhetinic acid (GA) named GA-1, GA-2, GA-3, GA-4 and GA-5 were semi-synthesised and screened through the QSAR model. Further, in vitro activities of the derivatives were analysed against human TNBC cell line, MDA-MB-231. The result showed that GA-1 exhibits improved cytotoxic activity to that of parent compound (GA). Further, atomic property field (APF)-based 3D-QSAR and scoring recognise C-30 carboxylic group of GA-1 as major influential factor for its anticancer activity. The significance of C-30 carboxylic group in GA derivatives was also confirmed by molecular docking study against cancer target glyoxalase-I. Finally, the oral bioavailability and toxicity of GA-1 were assessed by computational ADMET studies.

Communicated by Ramaswamy H. Sarma     

In silico design of potent EGFR kinase inhibitors using combinatorial libraries

This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set approaches. The partial least squares model showed some interesting results in terms of internal and external predictability against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860 compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399) showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were finally reported.     

On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity

Farnesoid X receptor (FXR) is a nuclear receptor related to lipid and glucose homeostasis and is considered an important molecular target to treatment of metabolic diseases as diabetes, dyslipidemia, and liver cancer. Nowadays, there are several FXR agonists reported in the literature and some of it in clinical trials for liver disorders. Herein, a compound series was employed to generate QSAR models to better understand the structural basis for FXR activation by anthranilic acid derivatives (AADs). Furthermore, here we evaluate the inclusion of the standard deviation (SD) of EC₅₀ values in QSAR models quality. Comparison between the use of experimental variance plus average values in model construction with the standard method of model generation that considers only the average values was performed. 2D and 3D QSAR models based on the AAD data set including SD values showed similar molecular interpretation maps and quality (Q²_LOO, Q²_(F2), and Q²_(F3)), when compared to models based only on average values. SD-based models revealed more accurate predictions for the set of test compounds, with lower mean absolute error indices as well as more residuals near zero. Additionally, the visual interpretation of different QSAR approaches agrees with experimental data, highlighting key elements for understanding the biological activity of AADs. The approach using standard deviation values may offer new possibilities for generating more accurate QSAR models based on available experimental data.     

Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer

Aromatase, catalyzing final step of estrogen biosynthesis, is considered a key target for the development of drug against estrogen-dependent breast cancer (EDBC). Identification and development of naturally occurring compounds, such as flavonoids, as drugs against EDBC is in demand due to their lesser toxicity when compared to those of synthetic ones. Thus, a three-dimensional quantitative structure–activity relationship, using comparative molecular field analysis (CoMFA) was done on a series of 45 flavonoids against human aromatase. A significant cross-validated correlation coefficient (q²) of 0.827 was obtained. The best predictive CoMFA model explaining the biological activity of the training and test sets with correlation coefficient values (r²) of 0.916 and 0.710, respectively, when used for virtual screening of a flavanoids database following molecular docking revealed a flavanone namely, 7-hydroxyflavanone beta-D-glucopyranoside showing highest predicted activity of 1.09?μM. In comparison to a well-established inhibitor of aromatase, namely 7-hydroxyflavanone (IC₅₀: 3.8?μM), the derivative identified in the present study, namely 7-hydroxyflavanone beta-D-glucopyranoside exhibited about 3.5 folds higher inhibitory activity against aromatase. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 25 ns MD simulation analysis revealed high stability and effective binding of 7-hydroxyflavanone beta-D-glucopyranoside within the active site of aromatase. To the best of our knowledge, this is the first report of CoMFA-based QSAR model for virtual screening of flavonoids as inhibitors of aromatase.     

QSAR and docking studies of anthraquinone derivatives by similarity cluster prediction

Forty anthraquinone derivatives have been downloaded from PubChem database and investigated in a quantitative structure-activity relationships (QSAR) study. The models describing log P and LD50 of this set were built up on the hypermolecule scheme that mimics the investigated receptor space; the models were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using similarity clusters. Molecular docking approach using Lamarckian Genetic Algorithm was made on this class of anthraquinones with respect to 3Q3B receptor. The best scored molecules in the docking assay were used as leaders in the similarity clustering procedure. It is demonstrated that the LD50 data of this set of anthraquinones are related to the binding energies of anthraquinone ligands to the 3Q3B receptor.     

Design,synthesis and biological evaluation of 4,5-dibromo-N-(thiazol-2-yl)-1H-pyrrole-2-carboxamide derivatives as novel DNA gyrase inhibitors

Development of novel DNA gyrase B inhibitors is an important field of antibacterial drug discovery whose aim is to introduce a more effective representative of this mechanistic class into the clinic. In the present study, two new series of Escherichia coli DNA gyrase inhibitors bearing the 4,5-dibromopyrrolamide moiety have been designed and synthesized. 4,5,6,7-Tetrahydrobenzo[1,2-d]thiazole-2,6-diamine derivatives inhibited E. coli DNA gyrase in the submicromolar to low micromolar range (IC₅₀ values between 0.891 and 10.4 μM). Their “ring-opened” analogues, based on the 2-(2-aminothiazol-4-yl)acetic acid scaffold, displayed weaker DNA gyrase inhibition with IC₅₀ values between 15.9 and 169 μM. Molecular docking experiments were conducted to study the binding modes of inhibitors.     

3D QSAR,pharmacophore and molecular docking studies of known inhibitors and designing of novel inhibitors for M18 aspartyl aminopeptidase of <Emphasis Type="Italic">Plasmodium falciparum</Emphasis>

Background

The Plasmodium falciparum M18 Aspartyl Aminopeptidase (PfM18AAP) is only aspartyl aminopeptidase which is found in the genome of P. falciparum and is essential for its survival. The PfM18AAP enzyme performs various functions in the parasite and the erythrocytic host such as hemoglobin digestion, erythrocyte invasion, parasite growth and parasite escape from the host cell. It is a valid target to develop antimalarial drugs. In the present work, we employed 3D QSAR modeling, pharmacophore modeling, and molecular docking to identify novel potent inhibitors that bind with M18AAP of P. falciparum.

Results

The PLSR QSAR model showed highest value for correlation coefficient r² (88 %) and predictive correlation coefficient (pred_r2) =0.6101 for external test set among all QSAR models. The pharmacophore modeling identified DHRR (one hydrogen donor, one hydrophobic group, and two aromatic rings) as an essential feature of PfM18AAP inhibitors. The combined approach of 3D QSAR, pharmacophore, and structure-based molecular docking yielded 10 novel PfM18AAP inhibitors from ChEMBL antimalarial library, 2 novel inhibitors from each derivative of quinine, chloroquine, 8-aminoquinoline and 10 novel inhibitors from WHO antimalarial drugs. Additionally, high throughput virtual screening identified top 10 compounds as antimalarial leads showing G-scores -12.50 to -10.45 (in kcal/mol), compared with control compounds(G-scores -7.80 to -4.70) which are known antimalarial M18AAP inhibitors (AID743024). This result indicates these novel compounds have the best binding affinity for PfM18AAP.

Conclusion

The 3D QSAR models of PfM18AAP inhibitors provided useful information about the structural characteristics of inhibitors which are contributors of the inhibitory potency. Interestingly, In this studies, we extrapolate that the derivatives of quinine, chloroquine, and 8-aminoquinoline, for which there is no specific target has been identified till date, might show the antimalarial effect by interacting with PfM18AAP.

     

Refined homology model of cytochrome bcc complex B subunit for virtual screening of potential anti-tuberculosis agents

Abstract

Cytochrome bcc complex is important for ATP synthesis and cellular activity, as a crucial step in the terminal reduction of oxygen in aerobic electron transport chains. The b subunit of cytochrome bcc complex (QcrB) has been reported as a promising anti-tuberculosis target, with many novel anti-tuberculosis scaffolds reported. However, the 3D structure of mycobacterium tuberculosis (M. tuberculosis) QcrB has not been released, making it hard to understand the interactions between QcrB and its inhibitors as well as to develop novel anti-tuberculosis scaffolds. Herein we built the optimal homology model of M. tuberculosis QcrB using the M. smegmatis QcrB structure as template, which was refined through all-atom molecular dynamics simulation. Then, the binding modes of known inhibitors were predicted through molecular docking method, along with molecular dynamics simulation and binding free energy calculation to verify the accuracy of docking results and stability of the protein-inhibitor complexes. The informative key residues within QcrB site enabled us to perform structure-based virtual library screening to obtain potential M. tuberculosis QcrB inhibitors, which were validated through molecular dynamics simulation and MM-GBSA calculation and analyzed through pharmacokinetic properties prediction. Our research would provide a deeper insight into the interactions between M. tuberculosis QcrB and its inhibitors, which boosts to develop novel therapy against tuberculosis.

Communicated by Ramaswamy H. Sarma     

Mycobacterium fluoroquinolone resistance protein B,a novel small GTPase,is involved in the regulation of DNA gyrase and drug resistance

DNA gyrase plays a vital role in resolving DNA topological problems and is the target of antibiotics such as fluoroquinolones. Mycobacterium fluoroquinolone resistance protein A (MfpA) from Mycobacterium smegmatis is a newly identified DNA gyrase inhibitor that is believed to confer intrinsic resistance to fluoroquinolones. However, MfpA does not prevent drug-induced inhibition of DNA gyrase in vitro, implying the involvement of other as yet unknown factors. Here, we have identified a new factor, named Mycobacterium fluoroquinolone resistance protein B (MfpB), which is involved in the protection of DNA gyrase against drugs both in vivo and in vitro. Genetic results suggest that MfpB is necessary for MfpA protection of DNA gyrase against drugs in vivo; an mfpB knockout mutant showed greater susceptibility to ciprofloxacin than the wild-type, whereas a strain overexpressing MfpA and MfpB showed higher loss of susceptibility. Further biochemical characterization indicated that MfpB is a small GTPase and its GTP bound form interacts directly with MfpA and influences its interaction with DNA gyrase. Mutations in MfpB that decrease its GTPase activity disrupt its protective efficacy. Our studies suggest that MfpB, a small GTPase, is required for MfpA-conferred protection of DNA gyrase.     

Statistical molecular design of a focused salicylidene acylhydrazide library and multivariate QSAR of inhibition of type III secretion in the Gram-negative bacterium Yersinia

A combined application of statistical molecular design (SMD), quantitative structure–activity relationship (QSAR) modeling and prediction of new active compounds was effectively used to develop salicylidene acylhydrazides as inhibitors of type III secretion (T3S) in the Gram-negative pathogen Yersinia pseudotuberculosis. SMD and subsequent synthesis furnished 50 salicylidene acylhydrazides in high purity. Based on data from biological evaluation in T3S linked assays 18 compounds were classified as active and 25 compounds showed a dose-dependent inhibition. The 25 compounds were used to compute two multivariate QSAR models and two multivariate discriminant analysis models were computed from both active and inactive compounds. Three of the models were used to predict 4416 virtual compounds in consensus and eight new compounds were selected as an external test set. Synthesis and biological evaluation of the test set in Y. pseudotuberculosis and the intracellular pathogen Chlamydia trachomatis validated the models. Y. pseudotuberculosis and C. trachomatis cell-based infection models showed that compounds identified in this study are selective and non-toxic inhibitors of T3S dependent virulence.     

Virtual screening of small molecules databases for discovery of novel PARP-1 inhibitors: combination of in silico and in vitro studies

Poly(ADP-ribose) polymerase-1 (PARP-1) enzyme has critical roles in DNA replication repair and recombination. Thus, PARP-1 inhibitors play an important role in the cancer therapy. In the current study, we have performed combination of in silico and in vitro studies in order to discover novel inhibitors against PARP-1 target. Structure-based virtual screening was carried out for an available small molecules database. A total of 257,951 ligands from Otava database were screened at the binding pocket of PARP-1 using high-throughput virtual screening techniques. Filtered structures based on predicted binding energy results were then used in more sophisticated molecular docking simulations (i.e. Glide/standard precision, Glide/XP, induced fit docking – IFD, and quantum mechanics polarized ligand docking – QPLD). Potential high binding affinity compounds that are predicted by molecular simulations were then tested by in vitro methods. Computationally proposed compounds as PARP-1 inhibitors (Otava Compound Codes: 7111620047 and 7119980926) were confirmed by in vitro studies. In vitro results showed that compounds 7111620047 and 7119980926 have IC₅₀ values of 0.56 and 63 μM against PARP-1 target, respectively. The molecular mechanism analysis, free energy perturbation calculations using long multiple molecular dynamics simulations for the discovered compounds which showed high binding affinity against PARP-1 enzyme, as well as structure-based pharmacophore development (E-pharmacophore) studies were also studied.     

Comparative QSAR studies on peptide deformylase inhibitors

Comparative quantitative structure–activity relationship (QSAR) analyses of peptide deformylase (PDF) inhibitors were performed with a series of previously published (British Biotech Pharmaceuticals, Oxford, UK) reverse hydroxamate derivatives having antibacterial activity against Escherichia coli PDF, using 2D and 3D QSAR methods, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR). Statistically reliable models with good predictive power were generated from all three methods (CoMFA r ² = 0.957, q ² = 0.569; CoMSIA r ² = 0.924, q ² = 0.520; HQSAR r ² = 0.860, q ² = 0.578). The predictive capability of these models was validated by a set of compounds that were not included in the training set. The models based on CoMFA and CoMSIA gave satisfactory predictive r ² values of 0.687 and 0.505, respectively. The model derived from the HQSAR method showed a low predictability of 0.178 for the test set. In this study, 3D prediction models showed better predictive power than 2D models for the test set. This might be because 3D information is more important in the case of datasets containing compounds with similar skeletons. Superimposition of CoMFA contour maps in the active site of the PDF crystal structure showed a meaningful correlation between receptor–ligand binding and biological activity. The final QSAR models, along with information gathered from 3D contour and 2D contribution maps, could be useful for the design of novel active inhibitors of PDF. Figure Superimposition of comparative molecular field analysis (CoMFA) contour plot in the active site of peptide deformylase (PDF)