The Search for the Spatial and Electronic Requirements of a Drug

A new program called GAMMA (genetic algorithm for multiple molecule alignment) has been developed for the superimposition of several three-dimensional chemical structures. Superimposition of molecules and evaluation of structural similarity is an important task in drug design and pharmaceutical research. Similarities of compounds are determined by this program either based on their structural or their physicochemical properties by defining different matching criteria. These matching criteria are atomic properties such as atomic number or partial atomic charges. The program is based on a combination of a genetic algorithm with a numerical optimization process. A major goal of this hybrid procedure is to address the conformational flexibility of ligand molecules adequately. Thus, only one conformation per structure is necessary and the program can work even when only one conformation of a compound is stored in a database. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the overlay. The geometric fit of the conformations is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. The determination of the fitness of a superimposition is based on the Pareto optimization. As an application the superimposition of a set of Cytochrome P450c17 enzyme inhibitors has been performed.Electronic Supplementary Material available.     

Optimal operating mode for enantioseparation of SB-553261 racemate based on simulated moving bed technology

The performance of the simulated moving bed (SMB) technology and its modification, the Varicol process, was optimized using an experimentally verified model for the enantioseparation of SB-553261 racemate. Single and multiobjective optimizations have been carried out for both existing as well as design stage and their efficiencies were compared. The optimization problem involves a relatively large number of decision variables, both continuous variables such as flow rates, switching time and length of the columns, as well as discrete variables like number and distribution of columns. A state-of-the-art new optimization technique based on a genetic algorithm (nondominated sorting genetic algorithm with jumping genes) was utilized which allows handling of these complex optimization problems. The optimization results showed that significant improvement could be made to the chiral drug separation process using both the SMB and the Varicol process. It was found that the performance of a Varicol process is superior to that of a SMB process in terms of treating more feed using less desorbent or increasing productivity while at the same time achieving better product quality. Optimum results were explained using equilibrium theory by locating them in the pure separation region.     

Response surface methodology in docking study of small molecule BACE-1 inhibitors

Computational evaluation of ligand-receptor binding via docking strategy is a well established approach in structure-based drug design. This technique has been applied frequently in developing molecules of biological interest. However, any procedure would require an optimization set up to be more efficient, economic and time-saving. Advantages of modern statistical optimization methods over conventional one-factor-at-a-time studies have been well revealed. The optimization by experimental design provides a combination of factor levels simultaneously satisfying the requirements considered for each of the responses and factors. In this study, response surface method was applied to optimize the prominent factors (number of genetic algorithm runs, population size, maximum number of evaluations, torsion degrees for ligand and number of rotatable bonds in ligand) in AutoDock4.2-based binding study of small molecule β-secretase inhibitors as anti-alzheimer agents. Results revealed that a number of rotatable bonds in ligand and maximum number of docking evaluations were determinant variables affecting docking outputs. The interference between torsion degrees for ligand and number of genetic algorithm runs for docking procedure was found to be the significant interaction term in our model. Optimized docking outputs exhibited a high correlation with experimental fluorescence resonance energy transfer-based IC(50)s for β-secretase inhibitors (R(2)?=?0.9133).     

A hierarchical method for molecular docking using cloud computing

Discovering small molecules that interact with protein targets will be a key part of future drug discovery efforts. Molecular docking of drug-like molecules is likely to be valuable in this field; however, the great number of such molecules makes the potential size of this task enormous. In this paper, a method to screen small molecular databases using cloud computing is proposed. This method is called the hierarchical method for molecular docking and can be completed in a relatively short period of time. In this method, the optimization of molecular docking is divided into two subproblems based on the different effects on the protein–ligand interaction energy. An adaptive genetic algorithm is developed to solve the optimization problem and a new docking program (FlexGAsDock) based on the hierarchical docking method has been developed. The implementation of docking on a cloud computing platform is then discussed. The docking results show that this method can be conveniently used for the efficient molecular design of drugs.     

Molecular modeling and simulation of Mycobacterium tuberculosis cell wall permeability

The low permeability of the mycobacterial cell wall is thought to contribute to the intrinsic drug resistance of mycobacteria. In this study, the permeability of the Mycobacterium tuberculosis cell wall is studied by computer simulation. Thirteen known drugs with diverse chemical structures were modeled as solutes undergoing transport across a model for the M. tuberculosis cell wall. The properties of the solute-membrane complexes were investigated by means of molecular dynamics simulation, especially the diffusion coefficients of the solute molecules inside the cell wall. The molecular shape of the solute was found to be an important factor for permeation through the M. tuberculosis cell wall. Predominant lateral diffusion within, as opposed to transverse diffusion across, the membrane/cell wall system was observed for some solutes. The extent of lateral diffusion relative to transverse diffusion of a solute within a biological cell membrane may be an important finding with respect to absorption distribution, metabolism, elimination, and toxicity properties of drug candidates. Molecular similarity measures among the solutes were computed, and the results suggest that compounds having high molecular similarity will display similar transport behavior in a common membrane/cell wall environment. In addition, the diffusion coefficients of the solute molecules across the M. tuberculosis cell wall model were compared to those across the monolayers of dipalmitoylphosphatidylethanolamine and dimyristoylphosphatidylcholine, are two common phospholipids in bacterial and animal membranes. The differences among these three groups of diffusion coefficients were observed and analyzed.     

Crystal structures of Mycobacterium smegmatis RecA and its nucleotide complexes

The crystal structures of Mycobacterium smegmatis RecA (RecA(Ms)) and its complexes with ADP, ATPgammaS, and dATP show that RecA(Ms) has an expanded binding site like that in Mycobacterium tuberculosis RecA, although there are small differences between the proteins in their modes of nucleotide binding. Nucleotide binding is invariably accompanied by the movement of Gln 196, which appears to provide the trigger for transmitting the effect of nucleotide binding to the DNA-binding loops. These observations provide a framework for exploring the known properties of the RecA proteins.     

Mycobacterium smegmatis RecA protein is structurally similar to but functionally distinct from Mycobacterium tuberculosis RecA

In eubacteria, RecA proteins belong to a large superfamily of evolutionarily conserved, filament-forming, functional homologs of DNA strand exchange proteins. Here, we report the functional characterization of Mycobacterium smegmatis (Ms) and Mycobacterium tuberculosis (Mt) RecA proteins. Although in some respects Ms and Mt RecA proteins are structural and functional homologs of Escherichia coli (Ec) RecA, there are significant differences as well. The single-stranded DNA-binding property of RecA proteins was analyzed by electrophoretic mobility shift assays. We observed that Ms or Mt RecA proteins bound single-stranded DNA in a manner distinct from that of Ec RecA: The former two were able to form protein-DNA complexes in the presence of high salt. Further experiments indicated that Ms or Mt RecA proteins catalyzed adenosine triphosphate hydrolysis at approximately comparable rates across a wide range of pHs. Significantly, DNA strand invasion promoted by Ms or Mt RecA proteins displayed similar kinetics but distinctly different pH profiles. In contrast to MtRecA, MsRecA by itself was unable to form joint molecules across a wide range of pHs. However, regardless of the order in which SSB was added, it was able to stimulate MsRecA to form joint molecules within a narrow pH range, indicating that SSB is a required accessory factor. Together, these results provide a source of sharp contrast between EcRecA and mycobacterial RecAs on the one hand and Mt and Ms RecA proteins on the other.     

The majority of inducible DNA repair genes in Mycobacterium tuberculosis are induced independently of RecA

In many species of bacteria most inducible DNA repair genes are regulated by LexA homologues and are dependent on RecA for induction. We have shown previously by analysing the induction of recA that two mechanisms for the induction of gene expression following DNA damage exist in Mycobacterium tuberculosis. Whereas one of these depends on RecA and LexA in the classical way, the other mechanism is independent of both of these proteins and induction occurs in the absence of RecA. Here we investigate the generality of each of these mechanisms by analysing the global response to DNA damage in both wild-type M. tuberculosis and a recA deletion strain of M. tuberculosis using microarrays. This revealed that the majority of the genes that were induced remained inducible in the recA mutant stain. Of particular note most of the inducible genes with known or predicted functions in DNA repair did not depend on recA for induction. Amongst these are genes involved in nucleotide excision repair, base excision repair, damage reversal and recombination. Thus, it appears that this novel mechanism of gene regulation is important for DNA repair in M. tuberculosis.     

Protein splicing in the maturation of M. tuberculosis recA protein: a mechanism for tolerating a novel class of intervening sequence.

The M. tuberculosis recA locus comprises an 85 kd open reading frame but produced 38 kd RecA and 47 kd products in E. coli. No RNA processing was detected; rather, an 85 kd precursor protein was spliced, releasing a 47 kd spacer protein, and joining its terminal fragments to form mature RecA protein. "Spacer" protein was also produced in M. tuberculosis and from a hybrid spacer-LacZ alpha fusion molecule. Mutagenesis at codon wobble positions at one splice junction showed that protein rather than nucleotide sequence determined splicing activity. Other mutants defined additional regions needed for splicing and allowed processing to be followed. Splicing was essential for RecA activity in E. coli. The possibility that splicing is a manifestation of a novel class of genetic element is discussed.     

Receptor–ligand molecular docking

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein–ligand applications. We summarise the main topics and recent computational and methodological advances in protein–ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.     

Separation of recombination and SOS response in Escherichia coli RecA suggests LexA interaction sites

RecA plays a key role in homologous recombination, the induction of the DNA damage response through LexA cleavage and the activity of error-prone polymerase in Escherichia coli. RecA interacts with multiple partners to achieve this pleiotropic role, but the structural location and sequence determinants involved in these multiple interactions remain mostly unknown. Here, in a first application to prokaryotes, Evolutionary Trace (ET) analysis identifies clusters of evolutionarily important surface amino acids involved in RecA functions. Some of these clusters match the known ATP binding, DNA binding, and RecA-RecA homo-dimerization sites, but others are novel. Mutation analysis at these sites disrupted either recombination or LexA cleavage. This highlights distinct functional sites specific for recombination and DNA damage response induction. Finally, our analysis reveals a composite site for LexA binding and cleavage, which is formed only on the active RecA filament. These new sites can provide new drug targets to modulate one or more RecA functions, with the potential to address the problem of evolution of antibiotic resistance at its root.     

A novel numerical optimization algorithm inspired from weed colonization

This paper introduces a novel numerical stochastic optimization algorithm inspired from colonizing weeds. Weeds are plants whose vigorous, invasive habits of growth pose a serious threat to desirable, cultivated plants making them a threat for agriculture. Weeds have shown to be very robust and adaptive to change in environment. Thus, capturing their properties would lead to a powerful optimization algorithm. It is tried to mimic robustness, adaptation and randomness of colonizing weeds in a simple but effective optimizing algorithm designated as Invasive Weed Optimization (IWO). The feasibility, the efficiency and the effectiveness of IWO are tested in details through a set of benchmark multi-dimensional functions, of which global and local minima are known. The reported results are compared with other recent evolutionary-based algorithms: genetic algorithms, memetic algorithms, particle swarm optimization, and shuffled frog leaping. The results are also compared with different versions of simulated annealing — a generic probabilistic meta-algorithm for the global optimization problem — which are simplex simulated annealing, and direct search simulated annealing. Additionally, IWO is employed for finding a solution for an engineering problem, which is optimization and tuning of a robust controller. The experimental results suggest that results from IWO are better than results from other methods. In conclusion, the performance of IWO has a reasonable performance for all the test functions.     

Problems and Paradigms: Relating biochemistry to biology: How the recombinational repair function of RecA protein is manifested in its molecular properties

The multiple activities of the RecA protein in DNA metabolism have inspired over a decade of research in dozens of laboratories around the world. This effort has nevertheless failed to yield an understanding of the mechanism of several RecA protein-mediated processes, the DNA strand exchange reactions prominent among them. The major factors impeding progress are the invalid constraints placed upon the problem by attempting to understand RecA protein-mediated DNA strand exchange within the context of an inappropriate biological paradigm – namely, homologous genetic recombination as a mechanism for generating genetic diversity. In this essay I summarize genetic and biochemical data demonstrating that RecA protein evolved as the central component of a recombinational DNA repair system, with the generation of genetic diversity being a sometimes useful byproduct, and review the major in vitro activities of RecA protein from a repair perspective. While models proposed for both recombination and recombinational repair often make use of DNA strand cleavage and transfer steps that appear to be quite similar, the molecular and thermodynamic requirements of the two processes are very different. The recombinational repair function provides a much more logical and informative framework for thinking about the biochemical properties of RecA and the strand exchange reactions it facilitates.     

Multidrug resistant to extensively drug resistant tuberculosis: What is next?

Drug resistant tuberculosis is a man made problem. While tuberculosis is hundred percent curable, multidrug resistant tuberculosis (MDR-TB) is difficult to treat. Inadequate and incomplete treatment and poor treatment adherence has led to a newer form of drug resistance known as extensively drug resistant tuberculosis (XDR-TB). XDR-TB is defined as tuberculosis caused by Mycobacterium tuberculosis strain, which is resistant to at least rifampicin and isoniazid among the first line anti tubercular drugs (MDR-TB) in addition to resistance to any fluroquinolones and at least one of three injectable second line anti tubercular drugs i.e. amikacin, kanamycin and/or capreomycin. Mismanagement of tuberculosis paves the way to drug resistant tuberculosis. Emergence of XDR-TB is reported world wide. Reported prevalence rates of XDR-TB of total MDR cases are; 6.6% overall worldwide, 6.5% in industrialized countries, 13.6% in Russia and Eastern Europe, 1.5% in Asia, 0.6% in Africa and Middle East and 15.4% in Republic of Korea. Better management and control of tuberculosis specially drug resistant TB by experienced and qualified doctors, access to standard microbiology laboratory, co-morbitidy of HIV and tuberculosis, new anti-TB drug regimens, better diagnostic tests, international standards for second line drugs (SLD)-susceptibility testing, invention of newer antitubercular molecules and vaccines and knowing the real magnitude of XDR-TB are some of the important issues to be addressed for effective prevention and management of XDR-TB.     

Automatic identification and representation of protein binding sites for molecular docking.

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.     

Time Varying Optimization for Monitoring Multiple Contaminants under Uncertain Hydrogeology

This study presents a method for identifying cost effective sampling designs for long-term monitoring of remediation of groundwater over multiple monitoring periods under uncertain flow conditions. A contaminant transport model is used to simulate plume migration under many equally likely stochastic hydraulic conductivity fields and provides representative samples of contaminant concentrations. Monitoring costs are minimized under a constraint to meet an acceptable level of error in the estimation of total mass for multiple contaminants simultaneously over many equiprobable realizations of hydraulic conductivity field. A new myopic heuristic algorithm (MS-ER) that combines a new error-reducing search neighborhood is developed to solve the optimization problem. A simulated annealing algorithm using the error-reducing neighborhood (SA-ER) and a genetic algorithm (GA) are also considered for solving the optimization problem. The method is applied to a hypothetical aquifer where enhanced anaerobic bioremediation of four toxic chlorinated ethene species is modeled using a complex contaminant transport model. The MS-ER algorithm consistently performed better in multiple trials of each algorithm when compared to SA-ER and GA. The best design of MS-ER algorithm produced a savings of nearly 25% in project cost over a conservative sampling plan that uses all possible locations and samples.     

Cisplatin inhibits protein splicing, suggesting inteins as therapeutic targets in mycobacteria

Mycobacterium tuberculosis harbors three protein splicing elements, called inteins, in critical genes and their protein products. Post-translational removal of the inteins occurs autocatalytically and is required for function of the respective M. tuberculosis proteins. Inteins are therefore potential targets for antimycobacterial agents. In this work, we report that the splicing activity of the intein present in the RecA recombinase of M. tuberculosis is potently inhibited by the anticancer drug cisplatin (cis-diamminedichloro-platinum(II)). This previously unrecognized activity of cisplatin was established using both an in vitro intein splicing assay, which yielded an IC(50) of ～2 μM, and a genetic reporter for intein splicing in Escherichia coli. Testing of related platinum(II) complexes indicated that the inhibition activity is highly structure-dependent, with cisplatin exhibiting the best inhibitory effect. Finally, we report that cisplatin is toxic toward M. tuberculosis with a minimum inhibitory concentration of ～40 μM, and in genetic experiments conducted with the related Mycobacterium bovis bacillus Calmette-Guérrin (BCG) strain, we show that cisplatin toxicity can be mitigated by intein overexpression. We propose that cisplatin inhibits intein activity by modifying at least one conserved cysteine residue that is required for splicing. Together these results identify a novel active site inhibitor of inteins and validate inteins as viable targets for small molecule inhibition in mycobacteria.     

Time Varying Optimization for Monitoring Multiple Contaminants under Uncertain Hydrogeology

This study presents a method for identifying cost effective sampling designs for long-term monitoring of remediation of groundwater over multiple monitoring periods under uncertain flow conditions. A contaminant transport model is used to simulate plume migration under many equally likely stochastic hydraulic conductivity fields and provides representative samples of contaminant concentrations. Monitoring costs are minimized under a constraint to meet an acceptable level of error in the estimation of total mass for multiple contaminants simultaneously over many equiprobable realizations of hydraulic conductivity field. A new myopic heuristic algorithm (MS-ER) that combines a new error-reducing search neighborhood is developed to solve the optimization problem. A simulated annealing algorithm using the error-reducing neighborhood (SA-ER) and a genetic algorithm (GA) are also considered for solving the optimization problem. The method is applied to a hypothetical aquifer where enhanced anaerobic bioremediation of four toxic chlorinated ethene species is modeled using a complex contaminant transport model. The MS-ER algorithm consistently performed better in multiple trials of each algorithm when compared to SA-ER and GA. The best design of MS-ER algorithm produced a savings of nearly 25% in project cost over a conservative sampling plan that uses all possible locations and samples.