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Abstract Background Tuberculosis (TB) still remains one of the most deadly infectious diseases in the world. Mycobacterium tuberculosis β-ketoacyl-ACP Reductase (MabA) is a member of the fatty acid elongation system type II, providing precursors of mycolic acids that are essential to the bacterial cell growth and survival. MabA has been shown to be essential for M. tuberculosis survival and to play a role in intracellular signal transduction of bacilli. Findings Here we describe site-directed mutagenesis, recombinant protein expression and purification, steady-state kinetics, fluorescence spectroscopy, and molecular modeling for S140T and S140A mutant MabA enzymes. No enzyme activity could be detected for S140T and S140A. Although the S140T protein showed impaired NADPH binding, the S140A mutant could bind to NADPH. Computational predictions for NADPH binding affinity to WT, S140T and S140A MabA proteins were consistent with fluorescence spectroscopy data. Conclusions The results suggest that the main role of the S140 side chain of MabA is in catalysis. The S140 side chain appears to also play an indirect role in NADPH binding. Interestingly, NADPH titrations curves shifted from sigmoidal for WT to hyperbolic for S140A, suggesting that the S140 residue may play a role in displacing the pre-existing equilibrium between two forms of MabA in solution. The results here reported provide a better understanding of the mode of action of MabA that should be useful to guide the rational (function-based) design of inhibitors of MabA enzyme activity which, hopefully, could be used as lead compounds with anti-TB action.

Despite new therapies against malaria, this disease remains one of the main causes of death affecting humanity. The phenomenon of resistance has caused concern as the drugs no longer have the same efficacy, forcing scientific research to develop new methods that prospect new molecules. With the advancement of artificial intelligence, it becomes possible to apply machine learning (ML) techniques in the discovery and evaluation of new molecules, by employing the quantitative structure-activity relationship (QSAR), a classic method that uses regressions to create a model that allows identifying and evaluating new drug candidates. This work combined QSAR with ML and developed a supervised model that modeled a fourth degree polynomial equation capable of identifying new drug candidates derived from the triclosan compound-a classic inhibitor of Plasmodium falciparum growth, the cause of severe malaria. The model produces an R 2 greater than 80% for training and concurrent testing, as well as a correlation index greater than 80% between the calculated and experimental pEC 50 (negative logarithm of half maximal effective concentration) data. In addition, a web software (PlasmoQSAR) was created that allows researchers to calculate the EC 50 (half maximal effective concentration) of new molecules using the developed analytical method., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Hypotension is one of the main characteristics of the systemic inflammation, basically caused by endothelial dysfunction. Studies have shown that the amino acid L-kynurenine (KYN) causes vasodilation in mammals, leading to hypotensive shock. In hypotensive shock, when activated by the KYN, the voltage-gated potassium channel encoded by the family KCNQ (Kv7) gene can cause vasodilation. Fructose-1,6-bisphosphate (FBP) it is being considered in studies an anti-inflammatory, antioxidant, immunomodulator, and a modulator of some ion channels (Ca2+, Na+, and K+). We analyzed the effects of KYN and FBP on mean blood pressure (MBP), systolic and diastolic (DBP) blood pressure, and heart rate variability (HRV) in Wistar rats. Results demonstrated that the administration of KYN significant decreased MBP, DBP, and increased HRV. Importantly, the FBP treatment reversed the KYN effects on MBP, DBP, and HRV. Molecular Docking Simulations suggested that KYN and FBP present a very close estimated free energy of binding and the same position into structure of KCNQ4. Our results did demonstrate that FBP blunted the decrease in BP, provoked by KYN. Results raise new hypotheses for future and studies in the treatment of hypotension resulting from inflammation., (© 2024 The Author(s). Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.)

Background: The molecular dynamics is an approach to obtain kinetic and thermodynamic characteristics of biomolecular structures. The molecular dynamics simulation softwares are very useful, however, most of them are used in command line form and continue with the same common implementation difficulties that plague researchers who are not computer specialists., Results: Here, we have developed the VisualDynamics-a WEB tool developed to automate biological simulations performed in Gromacs using a graphical interface to make molecular dynamics simulation user-friendly task. In this new application the researcher can submit a simulation of the protein in the free form or complexed with a ligand. Can also download the graphics analysis and log files at the end of the simulation., Conclusions: VisualDynamics is a tool that will accelerate implementations and learning in the area of molecular dynamics simulation. Freely available at https://visualdynamics.fiocruz.br/login , is supported by all major web browsers. VisualDynamics was developed with Flask, which is a Python-based free and open-source framework for web development. The code is freely available for download at GitHub https://github.com/LABIOQUIM/visualdynamics ., (© 2023. The Author(s).)

Due to the high rate of transmissibility, Brazil became the new COVID-19 outbreak epicenter and, since then, is being monitored to understand how SARS-CoV-2 mutates and spreads. We combined genomic and structural analysis to evaluate genomes isolated from different regions of Brazil and show that the most prevalent mutations were located in the S, N, ORF3a and ORF6 genes, which are involved in different stages of viral life cycle and its interaction with the host cells. Structural analysis brought to light the positions of these mutations on protein structures, contributing towards studies of selective structure-based drug discovery and vaccine development.

In this study, we have investigated the enzyme shikimate 5-dehydrogenase from the causative agent of tuberculosis, Mycobacterium tuberculosis. We have employed a mixture of computational techniques, including molecular dynamics, hybrid quantum chemical/molecular mechanical potentials, relaxed surface scans, quantum chemical descriptors and free-energy simulations, to elucidate the enzyme's reaction pathway. Overall, we find a two-step mechanism, with a single transition state, that proceeds by an energetically uphill hydride transfer, followed by an energetically downhill proton transfer. Our mechanism and calculated free energy barrier for the reaction, 64.9 kJ mol - 1 , are in good agreement with those predicted from experiment. An analysis of quantum chemical descriptors along the reaction pathway indicated a possibly important, yet currently unreported, role of the active site threonine residue, Thr65.

Although molecular dynamics encompasses several applications, studies focusing on biomolecular systems are central issues of this research area. Such simulations require the generation of trajectory files, which provide a path for the analysis and interpretation of results with biological significance. However, although several programs have been developed in Python language for the analyses of molecular dynamics (MD) trajectories, they usually require some knowledge of programming languages in order to write or run the scripts using command lines, which certainly hinders the access of MD simulations to many scientists with the necessary biological background to interpret their results. To ease the access to Python packages focusing on MD trajectory analyses, we built a user-friendly and easy-to-install graphical PyMOL interface. Geo-Measures integrates the PyMOL functionalities with MDTraj, a powerful library of trajectory analyses, allowing the users to access up to 14 different types of analyses. Two sample cases are reported here to demonstrate the use of Geo-Measures. In the first example, which involves the use a MD trajectory file of hemoglobin from the MoDEL MD bank, we exemplified the analyses of the following variables: root mean square deviation, radius of gyration, free energy landscape and principal component analysis. In the second case, we built a trajectory file for the ecto-5'-nucleotidase using the LiGRO program to study the carbon alpha pincer angles, to define the secondary structure of the proteins and to analyze the Modevectors. This user-friendly graphical PyMOL plugin, which can be used to generate several descriptive analyses for protein structures, is open source and can be downloaded at: https://pymolwiki.org/index.php/Geo_Measures_Plugin., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The PI3K/Akt/mTOR pathway is an important intracellular signaling pathway in cell cycle regulation and its dysregulation is associated with various types of diseases. mTOR (mechanistic or mammalian target of rapamycin) is the main enzyme that performs intermediate control of the signaling pathway through a phosphotransfer process. The classical inhibition of the mTOR pathway is effected by rapamycin and its analogous blocking allosterically the catalytic phosphorylation site, avoiding the deleterious side effects induced by ATP-competitive inhibitors. We employed ligand-based drug design strategies such as pharmacophore searching and analysis, molecular docking, absorption, distribution, metabolism, excretion and toxicity (ADMETox) properties filtering, and molecular dynamics to select potential molecules to become non-ATP competitive inhibitors of the mTOR complex. According to our findings, we propose eight novel potential mTOR inhibitors with similar or better properties than the classic inhibitor complex, rapamycin., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.

To speed up the drug-discovery process, molecular dynamics (MD) calculations performed in GROMACS can be coupled to docking simulations for the post-screening analyses of large compound libraries. This requires generating the topology of the ligands in different software, some basic knowledge of Linux command lines, and a certain familiarity in handling the output files. LiGRO-the python-based graphical interface introduced here-was designed to overcome these protein-ligand parameterization challenges by allowing the graphical (non command line-based) control of GROMACS (MD and analysis), ACPYPE (ligand topology builder) and PLIP (protein-binder interactions monitor)-programs that can be used together to fully perform and analyze the outputs of complex MD simulations (including energy minimization and NVT/NPT equilibration). By allowing the calculation of linear interaction energies in a simple and quick fashion, LiGRO can be used in the drug-discovery pipeline to select compounds with a better protein-binding interaction profile. The design of LiGRO allows researchers to freely download and modify the software, with the source code being available under the terms of a GPLv3 license from http://www.ufrgs.br/lasomfarmacia/ligro/ .

The neurohormone oxytocin is a key player in the modulation of reproductive and social behavioral traits, such as parental care. Recently, a correlation between different forms of oxytocin and behavioral phenotypes has been described in the New World Monkeys (NWMs). Here, we demonstrate that, compared with the Leu 8 OXT found in most placental mammals, the Cebidae Pro 8 OXT and Saguinus Val 3 Pro 8 OXT taxon-specific variants act as equi-efficacious agonists for the G q -dependent pathway but are weaker agonists for the β-arrestin engagement and subsequent endocytosis toward the oxytocin receptor (OXTR). Upon interaction with the AVPR1a, Pro 8 OXT and the common Leu 8 OXT yielded similar signaling profiles, being equally efficacious on G q and β-arrestin, while Val 3 Pro 8 OXT showed reduced relative efficacy toward β-arrestin. Intranasal treatment with either of the variants increased maternal behavior and also promoted unusual paternal care in rats, as measured by pup-retrieval tests. We therefore suggest that Val 3 Pro 8 OXT and Pro 8 OXT are functional variants, which might have been evolutionarily co-opted as an essential part of the adaptive genetic repertoire that allowed the emergence of taxon-specific complex social behaviors, such as intense parental care in the Cebidae and the genus Saguinus ., Competing Interests: The authors declare no conflict of interest.

Anthracyclines, e.g., doxorubicin (DOX), and anthracenediones, e.g., mitoxantrone (MTX), are drugs used in the chemotherapy of several cancer types, including solid and non-solid malignancies such as breast cancer, leukemia, lymphomas, and sarcomas. Although they are effective in tumor therapy, treatment with these two drugs may lead to side effects such as arrhythmia and heart failure. At the same clinically equivalent dose, MTX causes slightly reduced cardiotoxicity compared with DOX. These drugs interact with iron to generate reactive oxygen species (ROS), target topoisomerase 2 (Top2), and impair mitochondria. These are some of the mechanisms through which these drugs induce late cardiomyopathy. In this review, we compare the cardiotoxicities of these two chemotherapeutic drugs, DOX and MTX. As described here, even though they share similarities in their modes of toxicant action, DOX and MTX seem to differ in a key aspect. DOX is a more redox-interfering drug, while MTX induces energy imbalance. In addition, DOX toxicity can be explained by underlying mechanisms that include targeting of Top2 beta, mitochondrial impairment, and increases in ROS generation. These modes of action have not yet been demonstrated for MTX, and this knowledge gap needs to be filled.

Consumption has been a scourge of mankind since ancient times. This illness has charged a high price to human lives. Many efforts have been made to defeat Mycobacterium tuberculosis (Mt). The M. tuberculosis purine nucleoside phosphorylase (MtPNP) is considered an interesting target to pursuit new potential inhibitors, inasmuch it belongs to the purine salvage pathway and its activity might be involved in the mycobacterial latency process. Here we present the MtPNP crystallographic structure associated with acyclovir and phosphate (MtPNP:ACY:PO(4)) at 2.10 Å resolution. Molecular dynamics simulations were carried out in order to dissect MtPNP:ACY:PO(4) structural features, and the influence of the ligand in the binding pocket stability. Our results revealed that the ligand leads to active site lost of stability, in agreement with experimental results, which demonstrate a considerable inhibitory activity against MtPNP (K(i) = 150 nM). Furthermore, we observed that some residues which are important in the proper ligand's anchor into the human homologous enzyme do not present the same importance to MtPNP. Therewithal, these findings contribute to the search of new specific inhibitors for MtPNP, since peculiarities between the mycobacterial and human enzyme binding sites have been identified, making a structural-based drug design feasible., (Copyright © 2011 Elsevier Masson SAS. All rights reserved.)

Cytidine deaminase (CDA) is a key enzyme in the pyrimidine salvage pathway. It is involved in the hydrolytic deamination of cytidine or 2'-deoxycytidine to uridine or 2'-deoxyuridine, respectively. Here we report the crystal structures of Mycobacterium tuberculosis CDA (MtCDA) in complex with uridine (2.4 Å resolution) and deoxyuridine (1.9 Å resolution). Molecular dynamics (MD) simulation was performed to analyze the physically relevant motions involved in the protein-ligand recognition process, showing that structural flexibility of some protein regions are important to product binding. In addition, MD simulations allowed the analysis of the stability of tetrameric MtCDA structure. These findings open-up the possibility to use MtCDA as a target in future studies aiming to the rational design of new inhibitor of MtCDA-catalyzed chemical reaction with potential anti-proliferative activity on cell growth of M. tuberculosis, the major causative agent of tuberculosis., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Purine nucleoside phosphorylase (PNP) (EC.2.4.2.1) is an enzyme that catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is involved in purine-salvage pathway and has been proposed as a promising target for design and development of antimalarial and antibacterial drugs. Recent elucidation of the three-dimensional structure of PNP by X-ray protein crystallography left open the possibility of structure-based virtual screening initiatives in combination with molecular dynamics simulations focused on identification of potential new antimalarial drugs. Most of the previously published molecular dynamics simulations of PNP were carried out on human PNP, a trimeric PNP. The present article describes for the first time molecular dynamics simulations of hexameric PNP from Plasmodium falciparum (PfPNP). Two systems were simulated in the present work, PfPNP in ligand free form, and in complex with immucillin and sulfate. Based on the dynamical behavior of both systems the main results related to structural stability and protein-drug interactions are discussed.

In humans, purine nucleoside phosphorylase (HsPNP) is responsible for degradation of deoxyguanosine, and genetic deficiency of this enzyme leads to profound T-cell mediated immunosuppression. HsPNP is a target for inhibitor development aiming at T-cell immune response modulation. Here we report the crystal structure of HsPNP in complex with 7-deazaguanine (HsPNP:7DG) at 2.75 A. Molecular dynamics simulations were employed to assess the structural features of HsPNP in both free form and in complex with 7DG. Our results show that some regions, responsible for entrance and exit of substrate, present a conformational variability, which is dissected by dynamics simulation analysis. Enzymatic assays were also carried out and revealed that 7-deazaguanine presents a lower inhibitory activity against HsPNP (K(i)=200 microM). The present structure may be employed in both structure-based design of PNP inhibitors and in development of specific empirical scoring functions., ((c) 2009 Elsevier Inc. All rights reserved.)

Purine nucleoside phosphorylase (PNP) catalyzes the reversible phosphorolysis of N-ribosidic bonds of purine nucleosides and deoxynucleosides, except adenosine, to generate ribose 1-phosphate and the purine base. This work describes for the first time a structural model of PNP from Bacteroides fragilis (Bf). We modeled the complexes of BfPNP with six different ligands in order to determine the structural basis for specificity of these ligands against BfPNP. Comparative analysis of the model of BfPNP and the structure of HsPNP allowed identification of structural features responsible for differences in the computationally determined ligand affinities. The molecular dynamics (MD) simulation was assessed to evaluate the overall stability of the BfPNP model. The superposition of the final onto the initial minimized structure shows that there are no major conformational changes from the initial model, which is consistent with the relatively low root mean square deviation (RMSD). The results indicate that the structure of the model was stable during MD, and does not exhibit loosely structured loop regions or domain terminals.

Purine Nucleoside Phosphorylase (PNP) catalyzes the reversible phosphorolysis of N-glycosidic bonds of purine nucleosides and deoxynucleosides, except for adenosine, to generate ribose 1-phosphate and the purine base. PNP has been submitted to intensive structural studies. This work describes for the first time a structural model of PNP from Streptococcus pyogenes (SpPNP). We modeled the complexes of SpPNP with six different ligands in order to determine the structural basis for specificity of these ligands against SpPNP. Molecular dynamics (MD) simulations were performed in order to evaluate the overall stability of SpPNP model. The analysis of the MD simulation was assessed mainly by principal component analysis (PCA) to explore the trimeric structure behavior. Structural comparison, between SpPNP and human PNP, was able to identify the main features responsible for differences in ligand-binding affinities, such as mutation in the purine-binding site and in the second phosphate-binding site. The PCA analysis suggests a different behavior for each subunit in the trimer structure.

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.

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.

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.

Bacillus anthracis has been employed as an agent of bioterrorism, with high mortality, despite anti-microbial treatment, which strongly indicates the need of new drugs to treat anthrax. Shikimate pathway is a seven step biosynthetic route which generates chorismic acid from phosphoenol pyruvate and erythrose-4-phosphate. Chorismic acid is the major branch point in the synthesis of aromatic amino acids, ubiquinone, and secondary metabolites. The shikimate pathway is essential for many pathological organisms, whereas it is absent in mammals. Therefore, these enzymes are potential targets for the development of nontoxic antimicrobial agents and herbicides and have been submitted to intensive structural studies. The forth enzyme of this pathway is responsible for the conversion of dehydroshikimate to shikimate in the presence of NADP. In order to pave the way for structural and functional efforts toward development of new antimicrobials we describe the molecular modeling of shikimate dehydrogenase from Bacillus anthracis complexed with the cofactor NADP. This study was able to identify the main residues of the NADP binding site responsible for ligand affinities. This structural study can be used in the design of more specific drugs against infectious diseases.

The complex CDK3-cyclin is involved in the control of the progression of G0. While the mechanisms governing early and late G1 progression are well understood, very little is known about the G0-G1 transition. Human CDK3 is closely related to cyclin-dependent kinase 2 (CDK2). Since there is no crystallographic structure of human CDK3, this work describes for the first time a molecular model of human CDK3 complexed with several inhibitors. Comparison of the binary complexes with different inhibitors strongly indicates that those inhibitors should inhibit CDK3 as well as CDK2.

Toxoplasmosis is a chronic infection that affects approximately 30% of the human population and is caused by Toxoplasma gondii. Determination of the three dimensional structure of PNP from T. gondii could provide new insights into the purine binding site and sub-strate binding, and could be used for future rational design of new drugs against toxoplasmosis. This work describes the molecular model for three dimensional structure of PNP from T.gondii using, as a template, PNP from Plasmodium falciparum. Molecular dynamics showed that this model is stable during a trajectory of 3 ns.

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.

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.

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.

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.

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.

Currently, in order to accelerate the process of drug development and also reduce costs, many of the experimental assays related to lead discovery and lead optimization processes are being replaced by computational, in silico, methods. In this context, the LIE (linear interaction energy) method has been used to calculate binding free energies for widely different compounds by averaging interaction energies obtained from molecular dynamics (MD) or Monte Carlo (MC) simulations. In particular, the combination of docking and affinity predictions with the LIE method can thus save valuable resources in lead discovery and optimization projects. This review presents a description of LIE methodology and some recent studies that illustrate the importance and utility of the method in the field of pharmaceutical research.

Human purine nucleoside phosphorylase (HsPNP) is a target for inhibitor development aiming at T-cell immune response modulation. In this work, we report the development of a new set of empirical scoring functions and its application to evaluate binding affinities and docking results. To test these new functions, we solved the structure of HsPNP and 2-mercapto-4(3H)-quinazolinone (HsPNP:MQU) binary complex at 2.7A resolution using synchrotron radiation, and used these functions to predict ligand position obtained in docking simulations. We also employed molecular dynamics simulations to analyze HsPNP in two conditions, as apoenzyme and in the binary complex form, in order to assess the structural features responsible for stability. Analysis of the structural differences between systems provides explanation for inhibitor binding. The use of these scoring functions to evaluate binding affinities and molecular docking results may be used to guide future efforts on virtual screening focused on HsPNP.

Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT. A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT is stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution., (2008 Wiley-Liss, Inc.)

Bacillus anthracis has been used as weapon in bioterrorist activities, with high mortality, despite anti-microbial treatment, which strongly indicates a need of new drugs to treat anthrax. Shikimate Pathway is a seven-step biosynthetic route which generates chorismic acid. The shikimate pathway is essential for many pathological organisms, whereas it is absent in mammals. Therefore, these enzymes are potential targets for the development of non-toxic anti-microbial agents and herbicides and have been submitted to intensive structural studies. Shikimate Kinase is the fifth enzyme of shikimate pathway and catalyzes the specific phosphorylation of the 3-hydroxyl group of shikimate using ATP as a co-substrate, resulting in shikimate-3-phosphate and ADP. The present work describes for the first time a structural model for the Shikimate Kinase from B. anthracis using molecular modeling approach and molecular dynamics simulations. This study was able to identify the main residues of the ATP-binding and the shikimate pockets responsible for ligand affinities. Analysis of the molecular dynamics simulations indicates the structural features responsible for the stability of the structure. This study may help in the identification of new inhibitors for this enzyme.

Bacterial cytidylate kinase or cytidine monophosphate kinase (CMP kinase) catalyses the phosphoryl transfer from ATP to CMP and dCMP, resulting in the formation nucleoside diphosphates. In eukaryotes, CMP/UMP kinase catalyses the conversion of UMP and CMP to, respectively, UDP and CDP with high efficiency. This work describes for the first time a model of bacterial cytidylate kinase or cytidine monophosphate kinase (CMP kinase) from mycobacterium tuberculosis (MtCMPK). We modeled MtPCMPK in apo form and in complex with cytidine 5'-monophosphate (CMP) to try to determine the structural basis for specificity. Comparative analysis of the model of MtCMPK allowed identification of structural features responsible for ligand affinities. Analysis of the molecular dynamics simulations of these two systems indicates the structural features responsible for the stability of the structure, and may help in the identification of new inhibitors for this enzyme.

This work describes for the first time a structural model of purine nucleoside phosphorylase from Streptococcus agalactiae (SaPNP). PNP catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is a potential target for the development of antibacterial drugs. We modeled the complexes of SaPNP with 15 different ligands in order to determine the structural basis for the specificity of these ligands against SaPNP. The application of a novel empirical scoring function to estimate the affinity of a ligand for a protein was able to identify the ligands with high affinity for PNPs. The analysis of molecular dynamics trajectory for SaPNP indicates that the functionally important motifs have a very stable structure. This new structural model together with a novel empirical scoring function opens the possibility to explorer larger library of compounds in order to identify the new inhibitors for PNPs in virtual screening projects.

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.

This work describes for the first time a model of Purine Nucleoside Phosphorylase from Listeria monocytogenes (LmPNP). We modeled the complexes of LmPNP with ligands in order to determine the structural basis for specificity. Comparative analysis of the model of LmPNP allowed identification of structural features responsible for ligand affinities.

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.

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.