Frontiers Section Editor (Bioinformatics and Biophysics) for the Current Drug Targets ISSN: 1873-5592


Section Editor (Bioinformatics in Drug Design and Discovery) for the Current Medicinal Chemistry ISSN: 1875-533X


Section Editor (Combinatorial/Medicinal Chemistry) for the Combinatorial Chemistry & High Throughput Screening ISSN: 1875-5402


Member of the Editorial Board for the Current Bioinformatics ISSN: 2212-392X (Online) ISSN: 1574-8936 (Print)


Member of the Editorial Board for the Organic & Medicinal Chemistry International Journal ISSN: 2474-7610


Section Editor in Chief (Bioinformatics) for Bioengineering International. ISSN 2668-7119




Protein-Ligand Interacions


Molecular Docking


Bioinspired Computing


Computational Systems Biology



Papers Links
Bitencourt-Ferreira G, Rizzotto C, de Azevedo Junior WF. Machine Learning-Based Scoring Functions. Development and Applications With SAnDReS. Curr Med Chem. doi: 10.2174/0929867327666200515101820


BACKGROUND: Background: Analysis of atomic coordinates of protein-ligand complexes can provide three-dimensional data to generate computational models to evaluate binding affinity and thermodynamic state functions. Application of machine learning techniques can create models to assess protein-ligand potential energy and binding affinity. These methods show superior predictive performance when compared with classical scoring functions available in docking programs. Objective: Our purpose here is to review the development and application of the program SAnDReS. We describe the creation of machine learning models to assess the binding affinity of protein-ligand complexes. Method: SAnDReS implements machine learning methods available in the scikit-learn library. This program is available for download at SAnDReS uses crystallographic structures, binding, and thermodynamic data to create targeted scoring functions. Results: Recent applications of the program SAnDReS to drug targets such as Coagulation factor Xa, cyclin-dependent kinases, and HIV-1 protease were able to create targeted scoring functions to predict inhibition of these proteins. These targeted models outperform classical scoring functions. Conclusion: Here, we reviewed the development of machine learning scoring functions to predict binding affinity through the application of the program SAnDReS. Our studies show the superior predictive performance of the SAnDReS-developed models when compared with classical scoring functions available in the programs such as AutoDock4, Molegro Virtual Docker, and AutoDock Vina.

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KEYWORDS: Gibbs free energy.; Machine learning; SAnDReS; binding affinity; cyclin-dependent kinase; protein-ligand interactions.

PMID: 32410551 DOI: 10.2174/0929867327666200515101820

Bitencourt-Ferreira G, da Silva AD, de Azevedo WF Jr. Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets. A Study of Cyclin-Dependent Kinase 2. Curr Med Chem. doi: 10.2174/2213275912666191102162959


BACKGROUND: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the development of drugs intended to modulate cell-cycle progression and control. Such drugs have potential anticancer activities.

Objective: Our goal here is to review recent applications of machine learning methods to predict ligand-binding affinity for protein targets. To assess the predictive performance of classical scoring functions and targeted scoring functions, we focused our analysis on CDK2 structures.

Method: We have experimental structural data for hundreds of binary complexes of CDK2 with different ligands, many of them with inhibition constant information. We investigate here computational methods to calculate the binding affinity of CDK2 through classical scoring functions and machine-learning models.

Results: Analysis of the predictive performance of classical scoring functions available in docking programs such as Molegro Virtual Docker, AutoDock4, and Autodock Vina indicated that these methods failed to predict binding affinity with significant correlation with experimental data. Targeted scoring functions developed through supervised machine learning techniques showed significant correlation with experimental data.

Conclusion: Here, we described the application of supervised machine learning techniques to generate a scoring function to predict binding affinity. Machine learning models showed superior predictive performance when compared with classical scoring functions. Analysis of the computational models obtained through machine learning could capture essential structural features responsible for binding affinity against CDK2.

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KEYWORDS: CDK2; Machine learning; cancer; drug design; kinase; mass-spring system

PMID: 31729287 DOI: 10.2174/2213275912666191102162959

Russo S, de Azevedo WF Jr. Computational Analysis of Dipyrone Metabolite 4-Aminoantipyrine as a Cannabinoid Receptor 1 Agonist. Curr Med Chem. doi: 10.2174/0929867326666190906155339


BACKGROUND: Cannabinoid receptor 1 has its crystallographic structure available in complex with agonists and inverse agonists, which paved the way to establish an understanding of the structural basis of interactions with ligands. Dipyrone is a prodrug with analgesic capabilities and which is widely used in some countries. Recently it was shown some evidence of a dipyrone metabolite acting over the Cannabinoid Receptor 1. OBJECTIVE: Our goal here is to explore the dipyrone metabolite 4-aminoantipyrine as a Cannabinoid Receptor 1 agonist, reviewing dipyrone characteristics, and investigating the structural basis for its interaction with Cannabinoid Receptor 1. METHOD: We reviewed here recent functional studies related to the dipyrone metabolite focusing on its action as a Cannabinoid Receptor 1 agonist. We also analyzed protein-ligand interactions for this complex obtained through docking simulations against the crystallographic structure of the Cannabinoid Receptor 1. RESULTS: Analysis of the crystallographic structure and docking simulations revealed that most of the interactions present in the docked pose were also present in the crystallographic structure of Cannabinoid Receptor 1 and agonist. CONCLUSION: Analysis of the complex of 4-aminoantipyrine and Cannabinoid Receptor 1 revealed the pivotal role played by residues Phe 170, Phe 174, Phe 177, Phe 189, Leu 193, Val 196, and Phe 379, besides the conserved hydrogen bond at Ser 383. The mechanistic analysis and the present computational study suggest that the dipyrone metabolite 4-aminoantipyrine interacts with Cannabinoid Receptor 1.

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KEYWORDS: 4-aminoantipyrine; cannabinoid receptor 1; dipyrone; docking; metamizole; molecular interactions

PMID: 31490743 DOI: 10.2174/0929867326666190906155339

de Ávila MB, Bitencourt-Ferreira G, de Azevedo Jr. WF. Structural Basis for Inhibition of Enoyl-[Acyl Carrier Protein] Reductase (InhA) from Mycobacterium tuberculosis. Curr Med Chem. 2020; 27(5): 745–759. doi: 10.2174/0929867326666181203125229


BACKGROUND: The enzyme trans-enoyl-[acyl carrier protein] reductase (InhA) is a central protein for the development of antitubercular drugs. This enzyme is the target for the pro-drug isoniazid, which is catalyzed by the enzyme catalase-peroxidase (KatG) to become active. OBJECTIVE: Our goal here is to review the studies on InhA, starting with general aspects and focusing on the recent structural studies, with emphasis on the crystallographic structures of complexes involving InhA and inhibitors. METHOD: We start with a literature review, and then we describe recent studies on InhA crystallographic structures. We use this structural information to depict protein-ligand interactions. We also analyze the structural basis for inhibition of InhA. Furthermore, we describe the application of computational methods to predict binding affinity based on the crystallographic position of the ligands. RESULTS: Analysis of the structures in complex with inhibitors revealed the critical residues responsible for the specificity against InhA. Most of the intermolecular interactions involve the hydrophobic residues with two exceptions, the residues Ser 94 and Tyr 158. Examination of the interactions has shown that many of the key residues for inhibitor binding were found in mutations of the InhA gene in the isoniazid-resistant Mycobacterium tuberculosis. Computational prediction of the binding affinity for InhA has indicated a moderate uphill relationship with experimental values. CONCLUSION: Analysis of the structures involving InhA inhibitors shows that small modifications on these molecules could modulate their inhibition, which may be used to design novel antitubercular drugs specific for multidrug-resistant strains.

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KEYWORDS: Crystal Structure; Drug Design.; Enoyl-[Acyl Carrier Protein] Reductase; Protein-Ligand Interactions

PMID: 30501592 DOI: 10.2174/0929867326666181203125229

Russo S, De Azevedo WF. Advances in the Understanding of the Cannabinoid Receptor 1 - Focusing on the Inverse Agonists Interactions. Curr Med Chem. 2019; 26(10): 1908–1919.


BACKGROUND: Cannabinoid Receptor 1 (CB1) is a membrane protein prevalent in the central nervous system, whose crystallographic structure has recently been solved. Studies will be needed to investigate CB1 complexes with its ligands and its role in the development of new drugs. OBJECTIVE: Our goal here is to review the studies on CB1, starting with general aspects and focusing on the recent structural studies, with emphasis on the inverse agonists bound structures. METHOD: We start with a literature review, and then we describe recent studies on CB 1 crystallographic structure and docking simulations. We use this structural information to depict protein-ligand interactions. We also describe the molecular docking method to obtain complex structures of CB 1 with inverse agonists. RESULTS: Analysis of the crystallographic structure and docking results revealed the residues responsible for the specificity of the inverse agonists for CB 1. Most of the intermolecular interactions involve hydrophobic residues, with the participation of the residues Phe 170 and Leu 359 in all complex structures investigated in the present study. For the complexes with otenabant and taranabant, we observed intermolecular hydrogen bonds involving residues His 178 (otenabant) and Thr 197 and Ser 383 (taranabant). CONCLUSION: Analysis of the structures involving inverse agonists and CB 1 revealed the pivotal role played by residues Phe 170 and Leu 359 in their interactions and the strong intermolecular hydrogen bonds highlighting the importance of the exploration of intermolecular interactions in the development of novel inverse agonists.

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KEYWORDS: Cannabinoid receptor; docking; drug design; inverse agonist.

PMID: 29667549 DOI: 10.2174/0929867325666180417165247

Volkart PA, Bitencourt-Ferreira G, Souto AA, de Azevedo WF. Cyclin-Dependent Kinase 2 in Cellular Senescence and Cancer. A Structural and Functional Review. Curr Drug Targets. 2019;20(7): 716–726.


BACKGROUND: Cyclin-dependent kinase 2 (CDK2) has been studied due to its role in the cell-cycle progression. The elucidation of the CDK2 structure paved the way to investigate the molecular basis for inhibition of this enzyme, with the coordinated efforts combining crystallography with functional studies. OBJECTIVE: Our goal here is to review recent functional and structural studies directed to understanding the role of CDK2 in cancer and senescence. METHOD: There are over four hundreds of crystallographic structures available for CDK2, many of them with binding affinity information. We use this abundance of data to analyze the essential features responsible for the inhibition of CDK2 and its function in cancer and senescence. RESULTS: The structural and affinity data available CDK2 makes possible to have a clear view of the vital CDK2 residues involved in molecular recognition. A detailed description of the structural basis for ligand binding is of pivotal importance in the design of CDK2 inhibitors. Our analysis shows the relevance of the residues Leu 83 and Asp 86 for binding affinity. The recent findings revealing the participation of CDK2 inhibition on senescence opens the possibility to explore the richness of structural and affinity data to start a new age the development of CDK2 inhibitors, now targeting on cellular senescence. CONCLUSION: Here we analyzed structural information for CDK2 in complex with inhibitors and mapped the molecular aspects behind the strongest CDK2 inhibitors for which structures and ligand-binding affinity data were available. From this analysis, we identified the significant intermolecular interactions responsible for binding affinity. This knowledge may guide the future development of CDK2 inhibitors targeting cancer and cellular senescence.

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KEYWORDS: CDK2; Cyclin; cancer. ; cellular senescence; drug design; protein-ligand interactions

de Azevedo WF. Meet Our Editorial Board Member. Author(s): Walter Filgueira de Azevedo. Curr Bioinform. 2017; 12(5):385–386.
Heck GS, Pintro VO, Pereira RR, de Ávila MB, Levin NMB, de Azevedo WF. Supervised Machine Learning Methods Applied to Predict Ligand-Binding Affinity. Curr Med Chem. 2017; 24(23): 2459–2470.


BACKGROUND: Calculation of ligand-binding affinity is an open problem in computational medicinal chemistry. The ability to computationally predict affinities has a beneficial impact in the early stages of drug development, since it allows a mathematical model to assess protein-ligand interactions. Due to the availability of structural and binding information, machine learning methods have been applied to generate scoring functions with good predictive power. OBJECTIVE: Our goal here is to review recent developments in the application of machine learning methods to predict ligand-binding affinity. METHOD: We focus our review on the application of computational methods to predict binding affinity for protein targets. In addition, we also describe the major available databases for experimental binding constants and protein structures. Furthermore, we explain the most successful methods to evaluate the predictive power of scoring functions. RESULTS: Association of structural information with ligand-binding affinity makes it possible to generate scoring functions targeted to a specific biological system. Through regression analysis, this data can be used as a base to generate mathematical models to predict ligandbinding affinities, such as inhibition constant, dissociation constant and binding energy. CONCLUSION: Experimental biophysical techniques were able to determine the structures of over 120,000 macromolecules. Considering also the evolution of binding affinity information, we may say that we have a promising scenario for development of scoring functions, making use of machine learning techniques. Recent developments in this area indicate that building scoring functions targeted to the biological systems of interest shows superior predictive performance, when compared with other approaches.

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KEYWORDS: Machine learning; binding affinity; drug; enzyme; ligand-binding affinity; medicinal chemistry; regression

PMID: 28641555 DOI: 10.2174/0929867324666170623092503

Levin NM, Pintro VO, de Ávila MB, de Mattos BB, De Azevedo WF Jr. Understanding the Structural Basis for Inhibition of Cyclin-Dependent Kinases. New Pieces in the Molecular Puzzle. Curr Drug Targets. 2017; 18(9): 1104–1111.


BACKGROUND: Cyclin-dependent kinases (CDKs) comprise an important protein family for development of drugs, mostly aimed for use in treatment of cancer but there is also potential for development of drugs for neurodegenerative diseases and diabetes. Since the early 1990s, structural studies have been carried out on CDKs, in order to determine the structural basis for inhibition of this protein target. OBJECTIVE: Our goal here is to review recent structural studies focused on CDKs. We concentrate on latest developments in the understanding of the structural basis for inhibition of CDKs, relating structures and ligand-binding information. METHOD: Protein crystallography has been successfully applied to elucidate over 400 CDK structures. Most of these structures are complexed with inhibitors. We use this richness of structural information to describe the major structural features determining the inhibition of this enzyme. RESULTS: Structures of CDK1, 2, 4-9, 12 13, and 16 have been elucidated. Analysis of these structures in complex with a wide range of different competitive inhibitors, strongly indicate some common features that can be used to guide the development of CDK inhibitors, such as a pattern of hydrogen bonding and the presence of halogen atoms in the ligand structure. CONCLUSION: Nowadays we have structural information for hundreds of CDKs. Combining the structural and functional information we may say that a pattern of intermolecular hydrogen bonds is of pivotal importance for inhibitor specificity. In addition, machine learning techniques have shown improvements in predicting binding affinity for CDKs. Copyright© Bentham Science Publishers; For any queries, please email at

KEYWORDS: Cyclin-dependent kinase; binding affinity; drug design; inhibitors; machine learning; neurodegenerative disease

PMID: 27848884 DOI: 10.2174/1389450118666161116130155

de Azevedo Jr. WF. Opinion Paper: Targeting Multiple Cyclin-Dependent Kinases (CDKs): A New Strategy for Molecular Docking Studies. Curr Drug Targets. 2016;17(1):2.
Coracini JD, de Azevedo WF Jr. Shikimate kinase, a protein target for drug design. Curr Med Chem. 2014; 21(5):592–604.


ATP: shikimate 3-phosphotransferase catalyzes the fifth chemical reaction of shikimate pathway. This metabolic route is responsible for the production of chorismate, a precursor of aromatic amino acids. This especially interesting enzymatic step is indispensable for the survival of the etiological agent of tuberculosis and not found in animals. Therefore the enzyme ATP: shikimate 3-phosphotransferase has been classified as a target for chemotherapeutic development of antitubercular drugs. The ATP:shikimate 3-phosphotransferase has also the denomination of shikimate kinase. This review highlights the available crystallographic studies of shikimate kinases that have been used to identify structural features for ligand-biding affinity. We also describe molecular docking studies focused on shikimate kinase. These computational studies were performed in order to identify the new generation of antitubercular drugs and several potential inhibitors have been described. In addition, a structural comparison of shikimate kinase ATP-binding pocket with human cyclin-dependent kinase 2 (CDK2) is described. This analysis shows the structural similarities between both enzymes, and the potential beneficial aspects of abundant structural studies of CDK2 and their inhibitors to bring further understanding of the ligand-binding specificity for shikimate kinase.

Lombardi FR, Anazetti MC, Santos GC, Polizelli PP, Olivieri JR, de Azevedo WF, Bonilla-Rodriguez GO. Oxygen Binding Properties and Tetrameric Stability of Hemoglobins From the Snakes Crotalus Durissus Terrificus and Liophis Miliaris (Chapter 1). Frontiers in Protein and Peptide Sciences. 2014; 1, 3–30.


Hemoglobins (Hbs) from the South American snake Liophis miliaris undergo a reversible oxygen-linked dissociation phenomenon α2β2 + 4O2 ↔ 2αβ(O2), due to substituted glutamate residues (43β and 101β) at the α1β2- interface, according to Matsuura et al., 1989. This work reports the oxygen-binding properties and analysis of tetrameric stability from the major hemoglobins of two snakes: a terrestrial species (Crotalus durissus terrificus), and a semiaquatic one, L. miliaris. The major hemoglobins from both species were analyzed by classic functional experimental approaches and other analytical techniques: dimer-tetramer association constant by analytical gel filtration chromatography and small angle x-ray scattering (SAXS). In addition, we performed molecular modeling of the hemoglobin from L. miliaris. The functional results display cooperative oxygen binding, alkaline Bohr Effect, and conformational transitions, a behavior which is compatible with tetrameric Hbs. Also, the estimated dimer-tetramer association constant 4K2, radius of gyration, and maximum dimension exhibit similar compatibility. A molecular modeling of the structure of L. miliaris Hb, on the other hand, allows us to conclude that the residues Glu43β(CD2) and Glu101β(G3) are not essential in the maintenance of the tetrameric form, supporting our findings and allowing us to rule out the hypothesis proposed in the literature for the Hb of Liophis miliaris and other species of snakes. Therefore, the results reported in the paper suggest that the major Hbs of Liophis miliaris and Crotalus durissus terrificus are stable tetramers in vivo and in vitro.

Keywords: Crotalus durissus terrificus, Dimer-tetramer association constant, Hemoglobin, Liophis miliaris, Oxygen binding properties and SAXS.

Azevedo LS, Moraes FP, Xavier MM, Pantoja EO, Villavicencio B, Finck JA, Proenca, AM, Rocha, KB, de Azevedo, WF. Recent Progress of Molecular Docking Simulations Applied to Development of Drugs. Curr Bioinform. 2012; 7(4): 352–65.


In order to obtain structural information about intermolecular interactions between a protein target and a drug we could either solve the structure by experimental techniques (protein crystallography or nuclear magnetic resonance), or simulate the protein-drug complex computationally. Molecular docking is a computer simulation methodology that can predict the conformation of a protein-drug complex, with relatively high accuracy when compared with experimental structures. Although a plethora of algorithms has been applied to the problem of molecular docking simulation, recent results show that the most successful approaches are those based on evolutionary algorithms. Evolution as a source of inspiration has been shown to have a great positive impact on the progress of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a drug can be simulated by these evolutionary algorithms. These algorithms mimic evolution to create new paradigms for computation. This review provides a description of evolutionary algorithms and applications to molecular docking simulation. Special attention is dedicated to differential evolutionary algorithm and its implementation in the program molegro virtual docker. Recent applications of these methodologies to protein targets such as acetylcholinesterese, cyclin-dependent kinase 2, purine nucleoside phosphorylase, and shikimate kinase are described. Keywords: Differential evolution, evolutionary algorithms, molecular docking, protein-drug, simulation, structure-based virtual screening, chromosomes, Shoemake’s methodology, complex protein-ligand, crossdocking

de Azevedo WF Jr. Protein targets for development of drugs against Mycobacterium tuberculosis. Curr Med Chem. 2011; 18(9):1255–1257.


PMID: 21366537

Heberlé G, de Azevedo WF Jr. Bio-inspired algorithms applied to molecular docking simulations. Curr Med Chem. 2011; 18(9):1339–1352.


Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

PMID: 21366530

de Azevedo WF Jr. Molecular dynamics simulations of protein targets identified in Mycobacterium tuberculosis. Curr Med Chem. 2011; 18(9):1353–1366.


Application of molecular dynamics simulation technique has become a conventional computational methodology to calculate significant processes at the molecular level. This computational methodology is particularly useful for analyzing the dynamics of protein-ligand systems. Several uses of molecular dynamics simulation makes possible evaluation of important structural features found at interface between a ligand and a protein, such as intermolecular hydrogen bonds, contact area and binding energy. Considering structure-based virtual screening, molecular dynamics simulations play a pivotal role in understanding the features that are important for ligand-binding affinity. This information could be employed to select higher-affinity ligands obtained in screening processes. Many protein targets such as enoyl-[acyl-carrier-protein] reductase (InhA), purine nucleoside phosphorylase (PNP), and shikimate kinase have been submitted to these simulations and will be analyzed here. All command files used in this review are available for download at

PMID: 21366529

De Azevedo WF Jr. Structure-based virtual screening. Curr Drug Targets. 2010; 11(3):261–263.


PMID: 20214598

De Azevedo WF Jr. MolDock applied to structure-based virtual screening. Curr Drug Targets. 2010; 11(3):327–334.


Molecular docking is a simulation process where the binding of a small molecule is identified in the structure of a protein target. There are several different computational approaches to solve this problem. Here it will be described recent developments in application of evolutionary algorithms to molecular docking simulations. Evolutionary algorithms are classified as a group of computational techniques based on the concepts of Darwin's theory of evolution that are designed to the best possible find solution to optimisation problems. A successfully implementation of this algorithm can be found in the program MolDock. The main features of MolDock are reviewed here we also describe application of MolDock to purine nucleoside phosphorylase, shikimate kinase and cyclin-dependent kinase 2.

PMID: 20210757

Hernandes MZ, Cavalcanti SM, Moreira DR, de Azevedo Junior WF, Leite AC. Halogen atoms in the modern medicinal chemistry: hints for the drug design. Curr Drug Targets. 2010; 11(3):303–314.


A significant number of drugs and drug candidates in clinical development are halogenated structures. For a long time, insertion of halogen atoms on hit or lead compounds was predominantly performed to exploit their steric effects, through the ability of these bulk atoms to occupy the binding site of molecular targets. However, halogens in drug - target complexes influence several processes rather than steric aspects alone. For example, the formation of halogen bonds in ligand-target complexes is now recognized as a kind of intermolecular interaction that favorably contributes to the stability of ligand-target complexes. This paper is aimed at introducing the fascinating versatility of halogen atoms. It starts summarizing the prevalence of halogenated drugs and their structural and pharmacological features. Next, we discuss the identification and prediction of halogen bonds in protein-ligand complexes, and how these bonds should be exploited. Interesting results of halogen insertions during the processes of hit-to-lead or lead-to-drug conversions are also detailed. Polyhalogenated anesthetics and protein kinase inhibitors that bear halogens are analyzed as cases studies. Thereby, this review serves as one guide for the virtual screening of libraries containing halogenated compounds and may be a source of inspiration for the medicinal chemists.

PMID: 20210755

Ducati RG, Souto AA, Caceres RA, de Azevedo Jr. WF, Basso LA, Santos DS. Purine Nucleoside Phosphorylase as a Molecular Target to Develop Active Compounds Against Mycobacterium Tuberculosis. International Review of Biophysical Chemistry 2010; Vol. 1, N. 1, 34–40.


Despite the availability of chemotherapic and prophylactic approaches to fight consumption, human tuberculosis (TB) continues to claim millions of lives annually, mostly in developing nations, generally due to limited resources available to ensure proper treatment and where human immunodeficiency virus infections are common. Moreover, rising drug-resistant cases have worsened even further this picture. Accordingly, new therapeutic approaches have become necessary. The use of defined molecular targets could be explored as an attempt to develop new and selective chemical compounds to be employed in the treatment of TB. The present review highlights purine nucleoside phosphorylase, a component enzyme of the purine salvage pathway, as an attractive target for the development of new antimycobacterial agents, since this enzyme has been numbered among targets for Mycobacterium tuberculosis persistence in the human host. Enzyme kinetics and structural data are discussed to provide a basis to guide the rational anti-TB drug design. Copyright © 2010 Praise Worthy Prize S.r.l. - All rights reserved.

Keywords: Enzyme Kinetics and Structural Analysis, Human Tuberculosis, Mycobacterium Tuberculosis, Purine Nucleoside Phosphorylase, Rational Drug Development

de Azevedo WF Jr, Caceres RA, Pauli I, Timmers LF, Barcellos GB, Rocha KB, Soares MB. Protein-drug interaction studies for development of drugs against Plasmodium falciparum. Curr Drug Targets. 2009; 10(3):271–278.


The study of protein-drug interaction is of pivotal importance to understand the structural features essential for ligand affinity. The explosion of information about protein structures has paved the way to develop structure-based virtual screening approaches. Parasitic protein kinases have been pointed out as potential targets for antiparasitic development. The identification of protein kinases in the Plasmodium falciparum genome has opened the possibility to test new families of inhibitors as potential antimalarial drugs. In addition, other key enzymes which play roles in biosynthetic pathways, such as enoyl reductase and chorismate synthase, can be valuable targets for drug development. This review is focused on these protein targets that may help to materialize new generations of antimalarial drugs.

PMID: 19275563

Timmers LF, Pauli I, Barcellos GB, Rocha KB, Caceres RA, de Azevedo WF Jr, Soares MB. Genomic databases and the search of protein targets for protozoan parasites. Curr Drug Targets. 2009; 10(3):240–245.


The development of databases devoted to biological information opened the possibility to integrate, query and analyze biological data obtained from several sources that otherwise would be scattered through the web. Several issues arise in the handling of biological information, mainly due to the diversity of biological subject matter and the complexity of biological approaches towards phenomena of the living world. The integration of genomic data, three-dimensional structures of proteins, biological activity, and drugs availability allows a system approach to the study of the biology. Here we review the current status of these research efforts to develop genomic databases for protozoan parasites, such as the apicomplexan parasites, Trypanosoma cruzi and Leishmania spp. These databases may help in the discovery and development of new drugs against parasite-mediated diseases.

PMID: 19275560

de Azevedo WF Jr, Dias R, Timmers LF, Pauli I, Caceres RA, Soares MB. Bioinformatics tools for screening of antiparasitic drugs. Curr Drug Targets. 2009; 10(3):232–239.


Drug development has become the Holy Grail of many structural bioinformatics groups. The explosion of information about protein structures, ligand-binding affinity, parasite genome projects, and biological activity of millions of molecules opened the possibility to correlate this scattered information in order to generate reliable computational models to predict the likelihood of being able to modulate a target with a small-molecule drug. Computational methods have shown their potential in drug discovery and development allied with in vitro and in vivo methodologies. The present review discusses the main bioinformatics tools available for drug discovery and development.

PMID: 19275559

de Azevedo WF Jr, Soares MB. Selection of targets for drug development against protozoan parasites. Curr Drug Targets. 2009; 10(3):193–201.


Sequencing of parasite genomes opened the possibility to identify potential protein targets for drug development. Several protein targets have been found in the genome of Plasmodium falciparum, Trypanosoma cruzi, Trypanosoma brucei and Leishmania major. Bioinformatics analysis is an important tool for the identification of protein targets for drug development against parasitic diseases. In this review we comment about three protein targets, identified in parasite genomes, and discuss the main features that may guide future efforts for virtual screening initiatives.

PMID: 19275556

Timmers LF, Pauli I, Caceres RA, de Azevedo WF Jr. Drug-binding databases. Curr Drug Targets. 2008; 9(12):1092–1099.


Recent developments in computer power and chemoinformatics methodology make possible that a huge amount of data become available through internet. These databases are devoted to a wide spectrum of scientific fields. Here we are concerned with databases related to protein-drug interactions. More specifically, databases where potential new molecules could be accessed to be used in virtual screening initiatives. In the past decade several databases have been developed where molecules to be used in the virtual screening could be easily identified, downloaded and even purchased. This review describes and summarizes the recent advances in the development of these databases, and also the main applications related to virtual screening projects.

PMID: 19128220

Barcellos GB, Pauli I, Caceres RA, Timmers LF, Dias R, de Azevedo WF Jr. Molecular modeling as a tool for drug discovery. Curr Drug Targets. 2008; 9(12):1084–1091.


With the progression of structural genomics projects, comparative modeling remains an increasingly important method of choice to obtain 3D structure of proteins. It helps to bridge the gap between the available sequence and structure information by providing reliable and accurate protein models. Comparative modeling based on more than 30% sequence identity is now approaching its natural template-based limits and further improvements require the development of effective refinement techniques capable of driving models toward native structure. For difficult targets, for which the most significant progress in recent years has been observed, optimal template selection and alignment accuracy are still the major problems. The past year has seen a maturation of molecular modeling, with an increasing number of comparative studies between established methods becoming possible, together with an explosion of new works especially in the areas of combinatorial chemistry and molecular diversity. To achieve this, knowledge about three-dimensional protein structures is crucial for the understanding of their functional mechanisms, and for a rational drug design. This review described recent progress in molecular modeling methodology.

PMID: 19128219

Caceres RA, Pauli I, Timmers LF, de Azevedo WF Jr. Molecular recognition models: a challenge to overcome. Curr Drug Targets. 2008; 9(12):1077–1083.


Molecular recognition process describes the interaction involving two molecules. In the case of biomolecules, these pairs of molecules could be protein-protein, protein-ligand or protein-nucleic acid. The first model to capture the essential features, behind the molecular recognition problem, was the lock-and-key paradigm. The overall analysis protein-protein, protein-nucleic acid and protein-ligand interaction based on the three-dimensional structures and physicochemical parameters, such as binding affinity, opened the possibility to provide further insights in this basic phenomenon. The main ideas behind the molecular recognition are discussed in the present review.

PMID: 19128218

de Azevedo WF Jr, Dias R. Experimental approaches to evaluate the thermodynamics of protein-drug interactions. Curr Drug Targets. 2008; 9(12):1071–1076.


Precise experimental methods to determine ligand-binding affinity are needed to accelerate the discovery of new drugs. Assessing protein-ligand interaction is of great importance for drug development. One of the techniques that may be used to evaluate ligand-binding affinitty is isothermal titration calorimetry (ITC). This experimental methodology may be used to measure the heat of binding of a ligand to a protein. Furthermore, the development of new empirical scoring functions to assess evaluation protein-ligand interaction lack abundance of experimental information to be used to generate reliable scores. ITC technique may be used to fill this gap. Here we describe the application of this technique to ligand-binding affinity determination, and discuss the synergetic relationship between ITC data and the development of a new generation of empirical scoring functions.

PMID: 19128217

Dias R, Timmers LF, Caceres RA, de Azevedo WF Jr. Evaluation of molecular docking using polynomial empirical scoring functions. Curr Drug Targets. 2008; 9(12):1062–1070.


Molecular docking simulations are of pivotal importance for analysis of protein-ligand interactions and also an essential resource for virtual-screening initiatives. In molecular docking simulations several possible docked structures are generated, which create an ensemble of structures representing binary complexes. Therefore, it is crucial to find the best solution for the simulation. One approach to this problem is to employ empirical scoring function to identify the best docked structure. It is expected that scoring functions show a descriptive funnel-shaped energy surface without many false minima to impair the efficiency of conformational sampling. We employed this methodology against a test set with 300 docked structures. Docking simulations of these ligands against enzyme binding pocket indicated a funnel-shaped behavior of the complexation for this system. This review compares a set of recently proposed polynomial empirical scoring functions, implemented in a program called POLSCORE, with two popular scoring function programs (XSCORE and DrugScore). Overall comparison indicated that POLSCORE works better to predict the correct docked position, for the ensemble of docked structures analyzed in the present work.

PMID: 19128216

Pauli I, Timmers LF, Caceres RA, Soares MB, de Azevedo WF Jr. In silico and in vitro: identifying new drugs. Curr Drug Targets. 2008; 9(12):1054–1061.


Drug development is a high cost and laborious process, requiring a number of tests until a drug is made available in the market. Therefore, the use of methods to screen large number of molecules with less cost is crucial for faster identification of hits and leads. One strategy to identify drug-like molecules is the search for molecules able to interfere with a protein function, since protein interactions control most biological processes. Ideally the use of in silico screenings would make drug development faster and less expensive. Currently, however, the confirmation of biological activity is still needed. Due to the complexity of the task of drug discovery, an integrated and multi-disciplinary approach is ultimately required. Here we discuss examples of drugs developed through a combination of in silico and in vitro strategies. The potential use of these methodologies for the identification of active compounds as well as for early toxicity and bioavailability is also reviewed.

PMID: 19128215

Canduri F, de Azevedo WF. Protein crystallography in drug discovery. Curr Drug Targets. 2008; 9(12):1048–1053.


Protein crystallography is the main technique used to obtain three-dimensional information for binary complexes involving protein and drugs. Once a protein target has its three-dimensional structure elucidated, the next natural step is the solving of the structure complexed either with its natural substrate, or any ligand or even an inhibitor. Such information is of pivotal importance to understand the structural basis for inhibition of an enzyme. The relevant features, for application of protein crystallography to drug discovery, are discussed in this review.

PMID: 19128214

Dias R, de Azevedo WF Jr. Molecular docking algorithms. Curr Drug Targets. 2008; 9(12):1040–1047.


By means of virtual screening of small molecules databases it is possible to identify new potential inhibitors against a target of interest. Molecular docking is a computer simulation procedure to predict the conformation of a receptor-ligand complex. Each docking program makes use of one or more specific search algorithms, which are the methods used to predict the possible conformations of a binary complex. In the present review we describe several molecular-docking search algorithms, and the programs which apply such methodologies. We also discuss how virtual screening can be optimized, describing methods that may increase accuracy of the simulation process, with relatively fast docking algorithms.

PMID: 19128213

de Azevedo WF Jr, Dias R. Computational methods for calculation of ligand-binding affinity. Curr Drug Targets. 2008; 9(12):1031–1039.


Precise computational methods to determine ligand-binding affinity are needed to accelerate the discovery of new drugs. Assessing protein-ligand interaction is of great importance for virtual screening initiatives. The affinity may be computational evaluated using scoring functions involving terms for intermolecular hydrogen bonds, contact surface, hydrophobic contacts, electrostatic interactions and others. Empirical scoring functions have been developed to evaluate ligand-binding affinity very rapidly. In addition to predict affinity, these scoring functions have been employed to identify the best results obtained from docking simulations. This review describes several computational methods, employed to estimate ligand-binding affinity and discuss their development and main applications.

PMID: 19128212

de Azevedo WF Jr. Protein-drug interactions. Curr Drug Targets. 2008; 9(12):1030.


PMID: 19128211

Canduri F, Perez PC, Caceres RA, de Azevedo WF Jr. CDK9 a potential target for drug development. Med Chem. 2008; 4(3):210–218.


The family of Cyclin-Dependent Kinases (CDKs) can be subdivided into two major functional groups based on their roles in cell cycle and/or transcriptional control. CDK9 is the catalytic subunit of positive transcription elongation factor b (P-TEFb). CDK9 is the kinase of the TAK complex (Tat-associated kinase complex), and binds to Tat protein of HIV, suggesting a possible role for CDK9 in AIDS progression. CDK9 complexed with its regulatory partner cyclin T1, serves as a cellular mediator of the transactivation function of the HIV Tat protein. P-TEFb is responsible for the phosphorylation of the carboxyl-terminal domain of RNA Pol II, resulting in stimulation of transcription. Furthermore, the complexes containing CDK9 induce the differentiation in distinct tissue. The CDK9/cyclin T1 complex is expressed at higher level in more differentiated primary neuroectodermal and neuroblastoma tumors, showing a correlation between the kinase expression and tumor differentiation grade. This may have clinical and therapeutical implications for these tumor types. Among the CDK inhibitors two have shown to be effective against CDK9: Roscovitine and Flavopiridol. These two inhibitors prevented the replication of human immunodeficiency virus (HIV) type 1 by blocking Tat transactivation of the HIV type 1 promoter. These compounds inhibit CDKs by binding to the catalytic domain in place of ATP, preventing transfer of a phosphate group to the substrate. More sensitive therapeutic agents of CDK9 can be designed, and structural studies can add information in the understanding of this kinase. The major features related to CDK9 inhibition will be reviewed in this article.

PMID: 18473913

Breda A, Basso LA, Santos DS, de Azevedo Jr WF. Virtual Screening of Drugs: Score Functions, Docking, and Drug Design. Current Computer Aided-Drug Design 2008; 4(4), 265–272.


The computational approach for new drug design and/or identification, was initially proposed in mid 70s. The virtual screening of chemical libraries against a biological target has proven its reliability on structure-based drug design, for instance, for many HIV virus protein inhibitors and for the development of Cyclin-Dependent Kinase inhibitors. Target- based virtual screening, allied to docking studies, enables searches on larger data set of probable ligands, with less costs than the traditional experimental screening. The increasing availability of small molecules databases and its free online distribution is now allowing not only pharmaceutical industries, but independent research labs as well, to apply this methodology on early stages of drug discovery. When the protein target structure is available, and a chemical virtual library is accessible, following questions need to be answered: how the target and the ligand interact and how these interactions may be evaluated? Several docking algorithms for the identification of the molecular features responsible for binding specificity are available. While such algorithms are very robust and accurate, the scoring functions remain more questionable in the sense of what parameters should be considered when defining protein-ligand binding affinity when ranking candidates pointed-out by the virtual screening to the next step on drug testing. Aside conformational and chemical information, pharmacokinetics properties should be considered as well when selecting potential new drugs. Along with structural well-match, appropriate molecular features that define desired kinetics characteristics should be consistently addressed for usefulness of virtual screening results. The present review is focused on these questions and their implication for virtual screening.

Keywords: Virtual screening, drug design, protein targets, filtering methods

Pereira JH, Vasconcelos IB, Oliveira JS, Caceres RA, de Azevedo WF Jr, Basso LA, Santos DS. Shikimate kinase: a potential target for development of novel antitubercular agents. Curr Drug Targets. 2007; 8(3):459–468.


Tuberculosis (TB) remains the leading cause of mortality due to a bacterial pathogen, Mycobacterium tuberculosis. However, no new classes of drugs for TB have been developed in the past 30 years. Therefore there is an urgent need to develop faster acting and effective new antitubercular agents, preferably belonging to new structural classes, to better combat TB, including MDR-TB, to shorten the duration of current treatment to improve patient compliance, and to provide effective treatment of latent tuberculosis infection. The enzymes in the shikimate pathway are potential targets for development of a new generation of antitubercular drugs. The shikimate pathway has been shown by disruption of aroK gene to be essential for the Mycobacterium tuberculosis. The shikimate kinase (SK) catalyses the phosphorylation of the 3-hydroxyl group of shikimic acid (shikimate) using ATP as a co-substrate. SK belongs to family of nucleoside monophosphate (NMP) kinases. The enzyme is an alpha/beta protein consisting of a central sheet of five parallel beta-strands flanked by alpha-helices. The shikimate kinases are composed of three domains: Core domain, Lid domain and Shikimate-binding domain. The Lid and Shikimate-binding domains are responsible for large conformational changes during catalysis. More recently, the precise interactions between SK and substrate have been elucidated, showing the binding of shikimate with three charged residues conserved among the SK sequences. The elucidation of interactions between MtSK and their substrates is crucial for the development of a new generation of drugs against tuberculosis through rational drug design.

PMID: 17348838

Marques MR, Pereira JH, Oliveira JS, Basso LA, de Azevedo WF Jr, Santos DS, Palma MS. The inhibition of 5-enolpyruvylshikimate-3-phosphate synthase as a model for development of novel antimicrobials. Curr Drug Targets. 2007; 8(3):445–457.


EPSP synthase (EPSPS) is an essential enzyme in the shikimate pathway, transferring the enolpyruvyl group of phosphoenolpyruvate to shikimate-3-phosphate to form 5-enolpyruvyl-3-shikimate phosphate and inorganic phosphate. This enzyme is composed of two domains, which are formed by three copies of betaalphabetaalphabetabeta-folding units; in between there are two crossover chain segments hinging the nearly topologically symmetrical domains together and allowing conformational changes necessary for substrate conversion. The reaction is ordered with shikimate-3-phosphate binding first, followed by phosphoenolpyruvate, and then by the subsequent release of phosphate and EPSP. N-[phosphomethyl]glycine (glyphosate) is the commercial inhibitor of this enzyme. Apparently, the binding of shikimate-3-phosphate is necessary for glyphosate binding, since it induces the closure of the two domains to form the active site in the interdomain cleft. However, it is somehow controversial whether binding of shikimate-3-phosphate alone is enough to induce the complete conversion to the closed state. The phosphoenolpyruvate binding site seems to be located mainly on the C-terminal domain, while the binding site of shikimate-3-phosphate is located primarily in the N-terminal domain residues. However, recent results demonstrate that the active site of the enzyme undergoes structural changes upon inhibitor binding on a scale that cannot be predicted by conventional computational methods. Studies of molecular docking based on the interaction of known EPSPS structures with (R)- phosphonate TI analogue reveal that more experimental data on the structure and dynamics of various EPSPS-ligand complexes are needed to more effectively apply structure-based drug design of this enzyme in the future.

PMID: 17348837

Dias MV, Ely F, Palma MS, de Azevedo WF Jr, Basso LA, Santos DS. Chorismate synthase: an attractive target for drug development against orphan diseases. Curr Drug Targets. 2007; 8(3):437–444.


The increase in incidence of infectious diseases worldwide, particularly in developing countries, is worrying. Each year, 14 million people are killed by infectious diseases, mainly HIV/AIDS, respiratory infections, malaria and tuberculosis.. Despite the great burden in the poor countries, drug discovery to treat tropical diseases has come to a standstill. There is no interest by the pharmaceutical industry in drug development against the major diseases of the poor countries, since the financial return cannot be guaranteed. This has created an urgent need for new therapeutics to neglected diseases. A possible approach has been the exploitation of the inhibition of unique targets, vital to the pathogen such as the shikimate pathway enzymes, which are present in bacteria, fungi and apicomplexan parasites but are absent in mammals. The chorismate synthase (CS) catalyses the seventh step in this pathway, the conversion of 5-enolpyruvylshikimate-3-phosphate to chorismate. The strict requirement for a reduced flavin mononucleotide and the anti 1,4 elimination are both unusual aspects which make CS reaction unique among flavin-dependent enzymes, representing an important target for the chemotherapeutic agents development. In this review we present the main biochemical features of CS from bacterial and fungal sources and their difference from the apicomplexan CS. The CS mechanisms proposed are discussed and compared with structural data. The CS structures of some organisms are compared and their distinct features analyzed. Some known CS inhibitors are presented and the main characteristics are discussed. The structural and kinetics data reviewed here can be useful for the design of inhibitors.

PMID: 17348836

Canduri F, Perez PC, Caceres RA, de Azevedo WF Jr. Protein kinases as targets for antiparasitic chemotherapy drugs. Curr Drug Targets. 2007; 8(3):389–398.


Parasitic protozoa infecting humans have a great impact on public health, especially in the developing countries. In many instances, the parasites have developed resistance against available chemotherapeutic agents, making the search for alternative drugs a priority. In line with the current interest in Protein Kinase (PK) inhibitors as potential drugs against a variety of diseases, the possibility that PKs may represent targets for novel anti-parasitic agents is being explored. Research into parasite PKs has benefited greatly from genome and EST sequencing projects, with the genomes from a few species fully sequenced (notably that from the malaria parasite Plasmodium falciparum) and several more under way, the structural features that are important to design specific inhibitors against these PKs will be reviewed in the present work.

PMID: 17348832

da Silveira NJF, Bonalumi, CE, Arcuri HA, de Azevedo Jr., WF. Molecular Modeling Databases: A New Way in the Search of Proteins Targets for Drug Development. Curr Bioinform 2007; 2(1): 1–10.


DBMODELING is a relational database of annotated comparative protein structure models and their metabolic pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at DBMODELING user interface provides users friendly menus, so that all information can be printed in one step from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article.

Keywords: Structural bioinformatics; databases; drug design; molecular modeling; protein prediction servers

Basso LA, da Silva LH, Fett-Neto AG, de Azevedo WF Jr, Moreira Ide S, Palma MS, Calixto JB, Astolfi Filho S, dos Santos RR, Soares MB, Santos DS. The use of biodiversity as source of new chemical entities against defined molecular targets for treatment of malaria, tuberculosis, and T-cell mediated diseases--a review. Mem Inst Oswaldo Cruz. 2005; 100(6):475–506.


The modern approach to the development of new chemical entities against complex diseases, especially the neglected endemic diseases such as tuberculosis and malaria, is based on the use of defined molecular targets. Among the advantages, this approach allows (i) the search and identification of lead compounds with defined molecular mechanisms against a defined target (e.g. enzymes from defined pathways), (ii) the analysis of a great number of compounds with a favorable cost/benefit ratio, (iii) the development even in the initial stages of compounds with selective toxicity (the fundamental principle of chemotherapy), (iv) the evaluation of plant extracts as well as of pure substances. The current use of such technology, unfortunately, is concentrated in developed countries, especially in the big pharma. This fact contributes in a significant way to hamper the development of innovative new compounds to treat neglected diseases. The large biodiversity within the territory of Brazil puts the country in a strategic position to develop the rational and sustained exploration of new metabolites of therapeutic value. The extension of the country covers a wide range of climates, soil types, and altitudes, providing a unique set of selective pressures for the adaptation of plant life in these scenarios. Chemical diversity is also driven by these forces, in an attempt to best fit the plant communities to the particular abiotic stresses, fauna, and microbes that co-exist with them. Certain areas of vegetation (Amazonian Forest, Atlantic Forest, Araucaria Forest, Cerrado-Brazilian Savanna, and Caatinga) are rich in species and types of environments to be used to search for natural compounds active against tuberculosis, malaria, and chronic-degenerative diseases. The present review describes some strategies to search for natural compounds, whose choice can be based on ethnobotanical and chemotaxonomical studies, and screen for their ability to bind to immobilized drug targets and to inhibit their activities. Molecular cloning, gene knockout, protein expression and purification, N-terminal sequencing, and mass spectrometry are the methods of choice to provide homogeneous drug targets for immobilization by optimized chemical reactions. Plant extract preparations, fractionation of promising plant extracts, propagation protocols and definition of in planta studies to maximize product yield of plant species producing active compounds have to be performed to provide a continuing supply of bioactive materials. Chemical characterization of natural compounds, determination of mode of action by kinetics and other spectroscopic methods (MS, X-ray, NMR), as well as in vitro and in vivo biological assays, chemical derivatization, and structure-activity relationships have to be carried out to provide a thorough knowledge on which to base the search for natural compounds or their derivatives with biological activity.

PMID: 16302058 DOI: /S0074-02762005000600001

Canduri F, de Azevedo Jr. WF. Structural Basis for Interaction of Inhibitors with Cyclin-Dependent Kinase 2. Curr Comput Aided Drug Des, 2005; 1(1): 53–64.


Cell cycle progression is tightly controlled by the activity of cyclin-dependent kinases (CDKs). CDKs are inactive as monomers, and activation requires binding to cyclins, a diverse family of proteins whose levels oscillate during the cell cycle, and phosphorylation by CDK-activating kinase (CAK) on a specific threonine residue. The central role of CDKs in cell cycle regulation makes them a promising target for studying inhibitory molecules that can modify the degree of cell proliferation, the discovery of specific inhibitors of CDKs such as polyhydroxylated flavones has opened the way to investigation and design of antimitotic compounds. A chlorinated form, flavopiridol, is currently in phase II clinical trials as a drug against breast tumors. The aromatic portion of the inhibitor binds to the adenine-binding pocket of CDK2, and the position of the phenyl group of the inhibitor enables the inhibitor to make contacts with the enzyme not observed in the ATP complex structure, the analysis of the position of this phenyl ring not only explains the great differences of kinase inhibition among the flavonoid inhibitors but also explains the specificity of roscovitine and olomoucine to inhibit CDK2. There is strong interest in CDKs inhibitors that could play an important role in the discovery of a new family of antitumor agents. The crystallographic analysis together with bioinformatics studies of CDKs are generating new information about the structural basis for inhibition of CDKs. The relevant structural features that may guide the structure based-design of a new generation of CDK inhibitors are discussed in this review.

Keywords: cdk2, drug design, flavopiridol, roscovitine, inhibitor, indirubin

Ward RJ, de Azevedo WF Jr, Arni RK. At the interface: crystal structures of phospholipases A2. Toxicon. 1998; 36(11): 1623–1633.


The protein content of many snake venoms often includes one or more phospholipases A2 (PLA2). In recent years a growing number of venoms from snakes of Agkistrodon, Bothrops and Trimeresurus species have been shown to contain a catalytically inactive PLA2-homologue in which the highly conserved aspartic acid at position 49 (Asp49) is substituted by lysine (Lys49). Although demonstrating little or no catalytic activity, these Lys49-PLA2s disrupt membranes by a Ca2+-independent mechanism of action. In addition, this family of PLA2s demonstrates myotoxic and cytolytic pharmacological activities, however the structural bases underlying these functional properties are poorly understood. Through the application of X-ray crystallography in combination with biophysical and bioinformatics techniques, we are studying structure/function relationships of Lys49-PLA2s. We here present results of a systematic X-ray crystallographic and amino acid sequence analysis study of Lys49 PLA2s and propose a model to explain the Ca2+-independent membrane damaging activity.

PMID: 9792179

Kim SH, Schulze-Gahmen U, Brandsen J, de Azevedo Júnior WF. Structural basis for chemical inhibition of CDK2. Prog Cell Cycle Res. 1996; 2: 137–145.


The central role of cyclin-dependent kinases (CDKs) in cell cycle regulation makes them a promising target for discovering small inhibitory molecules that can modify the degree of cell proliferation. The three-dimensional structure of CDK2 provides a structural foundation for understanding the mechanisms of activation and inhibition of CDK2 and for the discovery of inhibitors. In this article five structures of human CDK2 are summarised: apoprotein, ATP complex, olomoucine complex, isopentenyladenine complex, and des-chloro-flavopiridol complex.

PMID: 9552391