Weak interactions involving organic fluorine: analysis of structural motifs in Flunazirine and Haloperidol

The crystal structure of Flunazirine, an anticonvulsant drug, is analyzed in terms of intermolecular interactions involving fluorine. The structure displays motifs formed by only weak interactions C–H⋯F and C–H⋯π. The motifs thus generated show cavities, which could serve as hosts for complexation. The structure of Flunazirine displays cavities formed by C–H⋯F and C–H⋯π interactions. Haloperidol, an antipsychotic drug, shows F⋯F interactions in the crystalline lattice in lieu of Cl⋯Cl interactions. However, strong O–H⋯N interactions dominate packing. The salient features of the two structures in terms of intermolecular interactions reveal, even though organic fluorine has lower tendency to engage in hydrogen bonding and F⋯F interactions, these interactions could play a significant role in the design of molecular assemblies via crystal engineering.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Rationalization and prediction of drug resistant mutations in targets for clinical anti-tubercular drugs

Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

Network approaches to drug discovery

Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

Crystal structures and binding studies of atovaquone and its derivatives with cytochrome bc(1): a molecular basis for drug design

Crystal structure of trans-atovaquone (antimalarial drug), its polymorph and its stereoisomer (cis) along with five other derivatives with different functional groups have been analyzed. Based on the conformational features of these compounds and the characteristics of the nature of intermolecular interactions, valuable insights into the atomistic details of protein-inhibitor interactions have been derived by docking studies. Atovaquone and its derivatives pack in the crystal lattice using intermolecular O-H center dot center dot center dot O hydrogen bond dimer motifs supported by surrogate weak interactions including C-H center dot center dot center dot O and C-H center dot center dot center dot Cl hydrogen bonds. The docking results of these molecules with cytochrome bc(1) show preferences to form N-H center dot center dot center dot O, O-H center dot center dot center dot O and O-H center dot center dot center dot Cl hydrogen bonds. The involvement of halogen atoms in the binding pocket appears to be significant and is contrary to the theoretically predicted mechanism of protein-ligand docking reported earlier based on mimicking experimental binding results of stigmatellin with cytochrome bc(1). The significance of subtle energy factors controlled by weak intermolecular interactions appears to play a major role in drug binding.

Molecular dynamics simulations of PPI dendrimer-drug complexes

Dendrimeric nanoparticles are potential drug delivery devices which can enhance the solubility of hydrophobic drugs, thus increasing their bioavailability and sustained release action. A quantitative understanding of the dendrimer-drug interactions can give valuable insight into the solubility and release profile of hydrophobic drug molecules in various solvent conditions. Fully atomistic molecular dynamics (MD) simulations have been performed to study the interactions of G5 PPIEDA (G5 ethylenediamine cored poly(propylene imine)) dendrimer and two well known drugs (Famotidine and Indomethacin) at different pH conditions. The study suggested that at low pH the dendrimer-drug complexes are thermodynamically unstable as compared to neutral and high pH conditions. Calculated Potential of Mean Force (PMF) by umbrella sampling showed that the release of drugs from the dendrimer at low pH is spontaneous, median release at neutral pH and slow release at high pH. In addition, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding free energy calculations were also performed at each umbrella sampling window to identify the various energy contributions. To understand the effect of dendrimer chemistry and topology on the solubility and release profile of drugs, this study is extended to explore the solubility and release profile of phenylbutazone drug complexed with G3 poly(amidoamine) and G4 diaminobutane cored PPI dendrimers. The results indicate that the pH-induced conformational changes in dendrimer, ionization states, dendrimer type and pK(a) of the guest molecules influence the free energy barrier and stability of complexation, and thus regulate drug loading, solubility and release.

Flexible poly(vinyl alcohol-co-ethylene)/modified MMT moisture barrier composite for encapsulating organic devices

Flexible, nano-composite moisture barrier films of poly(vinyl alcohol-co-ethylene) with surface modified montmorillonite fabricated by solution casting were used to encapsulate organic devices. The composite films were characterized by FTIR, UV-visible spectroscopy and SEM imaging. Thermal and mechanical properties of the composite films were studied by DSC and UTM. Calcium degradation test was used to determine the transmission rate of water vapour through the composite films, which showed a gradual reduction from similar to 0.1 g m(-2) day(-1) to 0.0001 g m(-2) day(-1) with increasing modified montmorillonite loading in the neat copolymer. The increase in moisture barrier performance is attributed to the decreased water vapour diffusivity due to matrix-filler interactions in the composite. The accelerated aging test was carried out for non-encapsulated and encapsulated devices to evaluate the efficiency of the encapsulants. The encapsulated devices exhibited longer lifetimes indicating the efficacy of the encapsulant.

The Role of Weak Interactions in the Phase Transition and Distinct Mechanical Behavior of Two Structurally Similar Caffeine Co-crystal Polymorphs Studied by Nanoindentation

Although weak interactions, such as C-H center dot center dot center dot O and pi-stacking, are generally considered to be insignificant, it is their reorganization that holds the key for many a solid-state phenomenon, such as phase transitions, plastic deformation, elastic flexibility, and mechanochromic luminescence in solid-state fluorophores. Despite this, the role of weak interactions in these dynamic phenomena is poorly understood. In this study, we investigate two co-crystal polymorphs of caffeine:4-chloro-3-nitrobenzoic acid, which have close structural similarity (2D layered structures), but surprisingly show distinct mechanical behavior. Form I is brittle, but shows shear-induced phase instability and, upon grinding, converts to Form II, which is soft and plastically shearable. This observation is in contrast to those reported in earlier studies on aspirin, wherein the metastable drug forms are softer and convert to stable and harder forms upon stressing To establish a molecular level understanding, have investigated the two co-crystal polymorphs I and II by single crystal X-ray diffraction, nanoindentation to quantify mechanical properties, and theoretical calculations. The lower hardness (from nanoindentation) and smooth potential surfaces (from theoretical studies) for shearing of layers in Form II allowed us to rationalize the role of stronger intralayer (sp(2))C-H center dot center dot center dot O and nonspecific interlayer pi-stacking interactions in the structure of II. Although the Form I also possesses the same type of interactions, its strength is clearly opposite, that is, weaker intralayer (sp(3))C-H center dot center dot center dot O and specific interlayer pi-stacking interactions. Hence, Form I is harder than Form IL Theoretical calculations and indentation on (111) of Form I suggested the low resistance of this face to mechanical stress; thus, Form I converts to II upon mechanical action. Hence, our approach demonstrates the usefulness of multiple techniques for establishing the role of weak noncovalent interactions in solid-state dynamic phenomena, such as stress induced phase transformation, and hence is important in the context of solid-state pharmaceutical chemistry and crystal engineering.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Charge density distribution and electrostatic interactions of ethionamide: an inhibitor of the enoyl acyl carrier protein reductase (inhA) enzyme of Mycobacterium tuberculosis

An experimental charge density analysis of an anti-TB drug ethionamide was carried out from high resolution X-ray diffraction at 100 K to understand its charge density distribution and electrostatic properties. The experimental results were validated from periodic theoretical charge density calculations performed using CRYSTAL09 at the B3LYP/6-31G** level of theory. The electron density rho(bcp)(r) and the Laplacian of electron density del(2)(rho bcp)(r) of the molecule calculated from both the methods display the charge density distribution of the ethionamide molecule in the crystal field. The electrostatic potential map shows a large electropositive region around the pyridine ring and a large electronegative region at the vicinity of the thiol atom. The calculated experimental dipole moment is 10.6D, which is higher than the value calculated from theory (8.2D). The topological properties of C-H center dot center dot center dot S, N-H center dot center dot center dot N and N-H center dot center dot center dot S hydrogen bonds were calculated, revealing their strength. The charge density analysis of the ethionamide molecule determined from both the experiment and theory gives the topological and electrostatic properties of the molecule, which allows to precisely understand the nature of intra and intermolecular interactions.

An overview of recent advances in structural bioinformatics of protein-protein interactions and a guide to their principles

Rich data bearing on the structural and evolutionary principles of protein protein interactions are paving the way to a better understanding of the regulation of function in the cell. This is particularly the case when these interactions are considered in the framework of key pathways. Knowledge of the interactions may provide insights into the mechanisms of crucial `driver' mutations in oncogenesis. They also provide the foundation toward the design of protein protein interfaces and inhibitors that can abrogate their formation or enhance them. The main features to learn from known 3-D structures of protein protein complexes and the extensive literature which analyzes them computationally and experimentally include the interaction details which permit undertaking structure-based drug discovery, the evolution of complexes and their interactions, the consequences of alterations such as post-translational modifications, ligand binding, disease causing mutations, host pathogen interactions, oligomerization, aggregation and the roles of disorder, dynamics, allostery and more to the protein and the cell. This review highlights some of the recent advances in these areas, including design, inhibition and prediction of protein protein complexes. The field is broad, and much work has been carried out in these areas, making it challenging to cover it in its entirety. Much of this is due to the fast increase in the number of molecules whose structures have been determined experimentally and the vast increase in computational power. Here we provide a concise overview. (C) 2014 Elsevier Ltd. All rights reserved.

From Workstations to Workbenches: Towards Predicting Physicochemically Viable Protein-Protein Interactions Across a Host and a Pathogen

The understanding of protein-protein interactions is indispensable in comprehending most of the biological processes in a cell. Small-scale experiments as well as large-scale high-throughput techniques over the past few decades have facilitated identification and analysis of protein-protein interactions which form the basis of much of our knowledge on functional and regulatory aspects of proteins. However, such rich catalog of interaction data should be used with caution when establishing protein-protein interactions in silico, as the high-throughput datasets are prone to false positives. Numerous computational means developed to pursue genome-wide studies on protein-protein interactions at times overlook the mechanistic and molecular details, thus questioning the reliability of predicted protein-protein interactions. We review the development, advantages, and shortcomings of varied approaches and demonstrate that by providing a structural viewpoint in terms of shape complementarity and interaction energies at protein-protein interfaces coupled with information on expression and localization of proteins homologous to an interacting pair, it is possible to assess the credibility of predicted interactions in biological context. With a focus on human pathogen Mycobacterium tuberculosis H37Rv, we show that such scrupulous use of details at the molecular level can predict physicochemically viable protein-protein interactions across host and pathogen. Such predicted interactions have the potential to provide molecular basis of probable mechanisms of pathogenesis and hence open up ways to explore their usefulness as targets in the light of drug discovery. (c) 2014 IUBMB Life, 66(11):759-774, 2014

Differential Cocrystallization Behavior of Isomeric Pyridine Carboxamides toward Antitubercular Drug Pyrazinoic Acid

Pyrazinoic acid, the active form of the antitubercular pro-drug Pyrazinamide, is an amphiprotic molecule containing carboxylic acid and pyridine groups and therefore can form both salts and cocrystals with relevant partner molecules. Cocrystallization of pyrazinoic acid with isomeric pyridine carboxamide series resulted in a dimorphic mixed-ionic complex with isonicotinamide and in eutectics with nicotinamide and picolinamide, respectively. It is observed that with alteration of the carboxamide position, steric and electrostatic compatibility issues between molecules of the combination emerge and affect intermolecular interactions and supramolecular growth, thus leading to either cocrystal or eutectic for different pyrazinoic acid-pyridine carboxamide combinations. Intermolecular interaction energy calculations have been performed to understand the role of underlying energetics on the formation of cocrystal/eutectic in different combinations. On the other hand, two molecular salts with piperazine and cytosine and a gallic acid cocrystal of the drug were obtained, and their X-ray crystal structures were also determined in this work.