Automated docking in crystallography: analysis of the substrates of aconitase

MetaDOCK: A Combinatorial Molecular Docking Approach

Molecular docking plays a major role in academic and industrial drug screening and discovery processes. Despite the availability of numerous docking software packages, there is a lot of scope for improvement for the docking algorithms in terms of becoming more reliable to replicate the experimental binding results. Here, we propose a combinatorial or consensus docking approach where complementary powers of the existing methods are captured. We created a meta-docking protocol by combining the results of AutoDock4.2, LeDock, and rDOCK programs as these are freely available, easy to use, and suitable for large-scale analysis and produced better performance on benchmarking studies. Rigorous benchmarking analyses were undertaken to evaluate the scoring, posing, and screening capability of our approach. Further, the performance measures were compared against one standard state-of-the-art commercial docking software, GOLD, and one freely available software, PLANTS. Performances of MetaDOCK for scoring, posing, and screening the protein-ligand complexes were found to be quite superior compared to the reference programs. Exhaustive molecular dynamics simulation and molecular mechanics Poisson-Boltzmann and surface area-based free energy estimation also suggest better energetic stability of the docking solutions produced by our meta-approach. We believe that the MetaDOCK approach is a useful packaging of the freely available software and provides a better alternative to the scientific community who are unable to afford costly commercial packages.

Molecular Modeling Insights into the Structure and Behavior of Integrins: A Review

Integrins are heterodimeric glycoproteins crucial to the physiology and pathology of many biological functions. As adhesion molecules, they mediate immune cell trafficking, migration, and immunological synapse formation during inflammation and cancer. The recognition of the vital roles of integrins in various diseases revealed their therapeutic potential. Despite the great effort in the last thirty years, up to now, only seven integrin-based drugs have entered the market. Recent progress in deciphering integrin functions, signaling, and interactions with ligands, along with advancement in rational drug design strategies, provide an opportunity to exploit their therapeutic potential and discover novel agents. This review will discuss the molecular modeling methods used in determining integrins' dynamic properties and in providing information toward understanding their properties and function at the atomic level. Then, we will survey the relevant contributions and the current understanding of integrin structure, activation, the binding of essential ligands, and the role of molecular modeling methods in the rational design of antagonists. We will emphasize the role played by molecular modeling methods in progress in these areas and the designing of integrin antagonists.

Modeling of SARS-CoV-2 Virus Proteins: Implications on Its Proteome

COronaVIrus Disease 19 (COVID-19) is a severe acute respiratory syndrome (SARS) caused by a group of beta coronaviruses, SARS-CoV-2. The SARS-CoV-2 virus is similar to previous SARS- and MERS-causing strains and has infected nearly six hundred and fifty million people all over the globe, while the death toll has crossed the six million mark (as of December, 2022). In this chapter, we look at how computational modeling approaches of the viral proteins could help us understand the various processes in the viral life cycle inside the host, an understanding of which might provide key insights in mitigating this and future threats. This understanding helps us identify key targets for the purpose of drug discovery and vaccine development.

Interactions of a biological macromolecule with thermotropic liquid crystals: Applications of liquid crystals in biosensing platform

Liquid crystal biosensor was developed based on a 4'-octyl-4-biphenylcarbonitrile (8CB) by adsorption of biological macromolecule bovine serum albumin (BSA) at the 8CB interface. BSA was detected by examining the changes in the director configurations of 8CB molecules under a polarizing optical microscope. The transitions in the director configuration were due to the non-covalent bonds. This technique demonstrated high sensitivity at a concentration of 100 µM of BSA. The binding events between the 8CB and BSA were investigated through molecular docking studies that confirmed the protein-ligand interaction. The most probable binding location of 8CB to dock with BSA were determined at a subdomain IB of Sudlow's site I. The active residues on analyzing were found to stabilize the 8CB molecules through different interactions. These active residues that were involved in the protein-ligand interaction were further confirmed with Raman spectroscopy. This study provided the vibrational properties and structural changes that occurred due to the various interactions between the 8CB and BSA. The results presented in this work lead to a potential biosensing tool for detecting and sensing proteins using LCs.

Novel drug design and bioinformatics: an introduction

In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective

Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.

Protein-Ligand Docking Methodologies and Its Application in Drug Discovery

Molecular docking is a key tool in structural biology and computer-assisted drug design. Molecular docking is a method which predicts the preferred orientation of a ligand when bound in an active site to form a stable complex. It is the most common method used as a structure-based drug design. Here, the authors intend to discuss the various types of docking methods and their development and applications in modern drug discovery. The important basic theories such as sampling algorithm and scoring functions have been discussed briefly. The performances of the different available docking software have also been discussed. This chapter also includes some application examples of docking studies in modern drug discovery such as targeted drug delivery using carbon nanotubes, docking of nucleic acids to find the binding modes and a comparative study between high-throughput screening and structure-based virtual screening.

Computational protein-ligand docking and virtual drug screening with the AutoDock suite

Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries containing tens of thousands of compounds. This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration. The entire protocol will require ∼5 h.

Molecular modeling and docking calculations of 4-acyloxy-biphenyl-4′-N-butylcarbamates as potential inhibitors of human butyrylcholinesterase

The kinetic studies and drug designs of butyrylcholinesterase play an important role in the development of Alzheimer’s disease therapeutics. In this research, automated docking studies were performed to provide useful insights into butyrylcholinesterase inhibition binding modes with designed 4-acyloxy-biphenyl-4′-N-butylcarbamates (compounds 1–8). Moreover, several significant linear correlations between experimental and calculated docking results are observed. Among compounds 1–7, compound 3, which exhibits the strongest hydrophobicity and has four carbonyl hydrogen bindings, shows the highest binding affinity (Ki = 1.4 μmol/L) with a binding energy of −7.99 kcal/mol. The observed linear correlation of experimental and calculated inhibition constants (Ki) indicates that the molecular docking results are reliable. Moreover, a good linear correlation is observed between calculated binding energies and experimental pKi. The experimental Hansch hydrophobicity constants (π values) are also correlated with the docked binding energy. This study reveals important correlations between butyrylcholinesterase experimental and docking results that contribute to the kinetic based identification of antagonists for the treatment of Alzheimer’s disease. Furthermore, these docked models provide important insights into a potential series of 4,4′-biphenol-based inhibitors of butyrylcholinesterase.

A virtual screen discovers novel, fragment-sized inhibitors of Mycobacterium tuberculosis InhA

Isoniazid (INH) is usually administered to treat latent Mycobacterium tuberculosis (Mtb) infections and is used in combination therapy to treat active tuberculosis (TB). Unfortunately, resistance to this drug is hampering its clinical effectiveness. INH is a prodrug that must be activated by Mtb catalase-peroxidase (KatG) before it can inhibit InhA (Mtb enoyl-acyl-carrier-protein reductase). Isoniazid-resistant cases of TB found in clinical settings usually involve mutations in or deletion of katG, which abrogate INH activation. Compounds that inhibit InhA without requiring prior activation by KatG would not be affected by this resistance mechanism and hence would display continued potency against these drug-resistant isolates of Mtb. Virtual screening experiments versus InhA in the GO Fight Against Malaria (GO FAM) project were designed to discover new scaffolds that display base-stacking interactions with the NAD cofactor. GO FAM experiments included targets from other pathogens, including Mtb, when they had structural similarity to a malaria target. Eight of the 16 soluble compounds identified by docking against InhA plus visual inspection were modest inhibitors and did not require prior activation by KatG. The best two inhibitors discovered are both fragment-sized compounds and displayed Ki values of 54 and 59 μM, respectively. Importantly, the novel inhibitors discovered have low structural similarity to known InhA inhibitors and thus help expand the number of chemotypes on which future medicinal chemistry efforts can be focused. These new fragment hits could eventually help advance the fight against INH-resistant Mtb strains, which pose a significant global health threat.

Synthesis and evaluation of a new series of tri-, di-, and mono-N-alkylcarbamylphloroglucinols as conformationally constrained inhibitors of cholesterol esterase

1,3,5-Tri-N-alkylcarbamylphloroglucinols (1-4) are synthesized as conformationally constrained analogs of triacylglycerols (TGs) to probe Jenck's proximity effect in the cholesterol esterase inhibition. For the cholesterol esterase inhibition, inhibitors 1-4 are 220-760-fold more potent than 1,2,3-tri-N-alkylcarbamylglycerols (13-15) that are substrate analogs of TG. Comparison of tridentate inhibitors 1-4, bidentate inhibitors 3,5-di-N-n-alkylcarbamyloxyphenols (5-8) and monodentate inhibitors 5-N-n-alkylcarbamyloxyresorcinols (9-12) indicates that inhibitory potencies are as followed: tridentate inhibitor > bidentate inhibitor > monodentate inhibitor. The log k(i) and pK(i) values of tridentate inhibitors, bidentate inhibitors, and monodentate inhibitors are linearly correlated with the alkyl chain length indicating a common mechanism in each inhibition. Also, positive slopes of these correlations indicate that the longer chain inhibitors bind more tightly to the enzyme than the shorter ones. Molecular dockings of tridentate 1, bidentate 5, and monodentate 9 into the X-ray crystal structure of cholesterol esterase suggest that one carbamyl group in the cis form of the inhibitor binds to the acyl chain-binding site of the enzyme. The second carbamyl groups in the trans forms of inhibitors 1 and 5 bind to the second acyl chain-binding site of the enzyme. The third carbamyl group in the trans form of inhibitor 1 binds to the third acyl chain-binding site of the enzyme. Moreover, the configuration of the inhibitor in the enzyme-inhibitor complex is the (1,3,5)-(cis, trans, trans)-tricarbamate form that mimics the (+gauche, -gauche)-conformation of TG.

Synthesis and evaluation of a new series of tri-, di-, and mono-N-alkylcarbamylphloroglucinols as bulky inhibitors of acetylcholinesterase

1,3,5-Tri-N-alkylcarbamylphloroglucinols (1-4) are synthesized as a new series of bulky inhibitors of acetylcholinesterase that may block the catalytic triad, the anionic substrate binding site, and the entrance of the enzyme simultaneously. Among three series of phloroglucinol-derived carbamates, tridentate inhibitors 1,3,5-tri-N-alkylcarbamylphloroglucinols (1-4), bidentate inhibitors 3,5-di-N-n-alkylcarbamyloxyphenols (5-8), and monodentate inhibitors 5-N-n-alkylcarbamyloxyresorcinols (9-12), tridentate inhibitors 1-4 are the most potent inhibitors of mouse acetylcholinesterase. When different n-alkylcarbamyl substituents in tridentate inhibitors 1-4 are compared, n-octylcarbamate 1 is the most potent inhibitor of the enzyme. All inhibitors 1-12 are characterized as the pseudo substrate inhibitors of acetylcholinesterase. Thus, tridentate inhibitors 1-4 are supposed to be hydrolyzed to bidentate inhibitors 5-8 after the enzyme catalysis. Subsequently, bidentate inhibitors 5-8 and monodentate inhibitors 9-12 are supposed to yield monodentate inhibitors 9-12 and phloroglucinol, respectively, after the enzyme catalysis. This means that tridentate inhibitors 1-4 may act as long period inhibitors of the enzyme. Therefore, inhibitors 1-4 may be considered as a new methodology to develop the long-acting drug for Alzheimer's disease. Automated dockings of inhibitor 1 into the X-ray crystal structure of acetylcholinesterase suggest that the most suitable configuration of inhibitor 1 to the enzyme binding is the (1,3,5)- (cis,trans,trans)-tricarbamate rotamer. The cis-carbamyl moiety of this rotamer does not bind into the acetyl group binding site of the enzyme but stretches out itself to the entrance. The other two trans-carbmayl moieties of this rotamer bulkily block the tryptophan 86 residue of the enzyme.

Molecular docking: a powerful approach for structure-based drug discovery

Molecular docking has become an increasingly important tool for drug discovery. In this review, we present a brief introduction of the available molecular docking methods, and their development and applications in drug discovery. The relevant basic theories, including sampling algorithms and scoring functions, are summarized. The differences in and performance of available docking software are also discussed. Flexible receptor molecular docking approaches, especially those including backbone flexibility in receptors, are a challenge for available docking methods. A recently developed Local Move Monte Carlo (LMMC) based approach is introduced as a potential solution to flexible receptor docking problems. Three application examples of molecular docking approaches for drug discovery are provided.

Sulphate respiration from hydrogen in Desulfovibrio bacteria: a structural biology overview

Sulphate-reducing organisms are widespread in anaerobic enviroments, including the gastrointestinal tract of man and other animals. The study of these bacteria has attracted much attention over the years, due also to the fact that they can have important implications in industry (in biocorrosion and souring of oil and gas deposits), health (in inflamatory bowel diseases) and the environment (bioremediation). The characterization of the various components of the electron transport chain associated with the hydrogen metabolism in Desulfovibrio has generated a large and comprehensive list of studies. This review summarizes the more relevant aspects of the current information available on the structural data of various molecules associated with hydrogen metabolism, namely hydrogenases and cytochromes. The transmembrane redox complexes known to date are also described and discussed. Redox-Bohr and cooperativity effects, observed in a few cytochromes, and believed to be important for their functional role, are discussed. Kinetic studies performed with these redox proteins, showing clues to their functional inter-relationship, are also addressed. These provide the groundwork for the application of a variety of molecular modelling approaches to understanding electron transfer and protein interactions among redox partners, leading to the characterization of several transient periplasmic complexes. In contrast to the detailed understanding of the periplasmic hydrogen oxidation process, very little is known about the cytoplasmic side of the respiratory electron transfer chain, in terms of molecular components (with exception of the terminal reductases), their structure and the protein-protein interactions involved in sulphate reduction. Therefore, a thorough understanding of the sulphate respiratory chain in Desulfovibrio remains a challenging task.

A Combined STD-NMR/Molecular Modeling Protocol for Predicting the Binding Modes of the Glycosidase Inhibitors Kifunensine and Salacinol to Golgi α-Mannosidase II†

A combined STD-NMR/molecular modeling protocol to probe the binding modes of the glycosidase inhibitors kifunensine and salacinol to Drosophila melanogaster Golgi alpha-mannosidase II (dGMII) was tested. Saturation-transfer difference (STD) NMR experiments were carried out for the complexes of dGMII with these two inhibitors. The program AutoDock 3.0 was then used to optimize the interactions of the inhibitors with the residues in the active site of dGMII. Theoretical STD effects of the ligand protons in the complexes were calculated for the different binding modes with the recently developed CORCEMA-ST protocol. Comparison of experimental and theoretical effects then permitted selection of the likely binding modes of the ligands. The more rigid kifunensine was used initially to test the protocol. Excellent correlation between experimental and theoretical data was obtained for one of the binding modes that also corresponded to that observed in the crystal structure of the complex. The protocol was then extended to the more flexible salacinol. For the selected binding mode, good correlation of experimental and theoretical data for the five-membered ring was obtained; however, poor correlation for protons on the acyclic chain was obtained, suggesting flexibility in this portion of the molecule. Comparison of the selected binding mode with that from a crystal structure of salacinol with dGMII showed excellent superimposition of the five-membered ring but another orientation of the acyclic chain. The results suggest that reliable structural binding modes of a ligand to protein in aqueous solution can be provided with the combined use of STD-NMR spectroscopy, molecular modeling, and CORCEMA-ST calculations, although highly flexible portions of the ligand may be poorly defined.

Electric-field-induced redox potential shifts of tetraheme cytochromes c3 immobilized on self-assembled monolayers: surface-enhanced resonance Raman spectroscopy and simulation studies

The tetraheme protein cytochrome c(3) (Cyt-c(3)) from Desulfovibrio gigas, immobilized on a self-assembled monolayer (SAM) of 11-mercaptoundecanoic acid, is studied by theoretical and spectroscopic methods. Molecular dynamics simulations indicate that the protein docks to the negatively charged SAM via its lysine-rich domain around the exposed heme IV. Complex formation is associated with only little protein structural perturbations. This finding is in line with the resonance Raman and surface-enhanced resonance Raman (SERR) spectroscopic results that indicate essentially the same heme pocket structures for the protein in solution and adsorbed on SAM-coated Ag electrodes. Electron- and proton-binding equilibrium calculations reveal substantial negative shifts of the redox potentials compared to the protein in solution. The magnitude of these shifts decreases in the order heme IV (-161 mV) > heme III (-73 mV) > heme II (-57 mV) > heme I (-26 mV), resulting in a change of the order of reduction. These shifts originate from the distance-dependent electrostatic interactions between the SAM headgroups and the individual hemes, leading to a stabilization of the oxidized forms. The results of the potential-dependent SERR spectroscopic analyses are consistent with the theoretical predictions and afford redox potential shifts of -160 mV (heme IV), -90 mV (heme III), -70 mV (heme II), and +20 mV (heme I) relative to the experimental redox potentials for Cyt-c(3) in solution. SERR spectroscopic experiments reveal electric-field-induced changes of the redox potentials also for the structurally very similar Cyt-c(3) from Desulfovibrio vulgaris, although the shifts are somewhat smaller compared to Cyt-c(3) from D. gigas. This study suggests that electric-field-induced redox potential shifts may also occur upon binding to biomembranes or partner proteins and thus may affect biological electron transfer processes.

Docking and scoring in virtual screening for drug discovery: methods and applications

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

Modeling electron transfer thermodynamics in protein complexes: interaction between two cytochromes c(3)

Redox protein complexes between type I and type II tetraheme cytochromes c(3) from Desulfovibrio vulgaris Hildenborough are here analyzed using theoretical methodologies. Various complexes were generated using rigid-body docking techniques, and the two lowest energy complexes (1 and 2) were relaxed using molecular dynamics simulations with explicit solvent and subjected to further characterization. Complex 1 corresponds to an interaction between hemes I from both cytochromes c(3). Complex 2 corresponds to an interaction between the heme IV from type I and the heme I from type II cytochrome c(3). Binding free energy calculations using molecular mechanics, Poisson-Boltzmann, and surface accessibility methods show that complex 2 is more stable than complex 1. Thermodynamic calculations on complex 2 show that complex formation induces changes in the reduction potential of both cytochromes c(3), but the changes are larger in the type I cytochrome c(3) (the largest one occurring on heme IV, of approximately 80 mV). These changes are sufficient to invert the global titration curves of both cytochromes, generating directionally in electron transfer from type I to type II cytochrome c(3), a phenomenon of obvious thermodynamic origin and consequences, but also with kinetic implications. The existence of processes like this occurring at complex formation may constitute a natural design of efficient redox chains.

Protein structure and dynamics in nonaqueous solvents: insights from molecular dynamics simulation studies

Protein structure and dynamics in nonaqueous solvents are here investigated using molecular dynamics simulation studies, by considering two model proteins (ubiquitin and cutinase) in hexane, under varying hydration conditions. Ionization of the protein groups is treated assuming "pH memory," i.e., using the ionization states characteristic of aqueous solution. Neutralization of charged groups by counterions is done by considering a counterion for each charged group that cannot be made neutral by establishing a salt bridge with another charged group; this treatment is more physically reasonable for the nonaqueous situation, contrasting with the usual procedures. Our studies show that hydration has a profound effect on protein stability and flexibility in nonaqueous solvents. The structure becomes more nativelike with increasing values of hydration, up to a certain point, when further increases render it unstable and unfolding starts to occur. There is an optimal amount of water, approximately 10% (w/w), where the protein structure and flexibility are closer to the ones found in aqueous solution. This behavior can explain the experimentally known bell-shaped dependence of enzyme catalysis on hydration, and the molecular reasons for it are examined here. Water and counterions play a fundamental and dynamic role on protein stabilization, but they also seem to be important for protein unfolding at high percentages of bound water.

Aspergillus aculeatus beta-1,4-galactanase: substrate recognition and relations to other glycoside hydrolases in clan GH-A

The three-dimensional structure of Aspergillus aculeatus beta-1,4-galactanase (AAGAL), an enzyme involved in pectin degradation, has been determined by multiple isomorphous replacement to 2.3 and 1.8 A resolution at 293 and 100 K, respectively. It represents the first known structure for a polysaccharidase with this specificity and for a member of glycoside hydrolase family 53 (GH-53). The enzyme folds into a (beta/alpha)(8) barrel with the active site cleft located at the C-terminal side of the barrel consistent with the classification of GH-53 in clan GH-A, a superfamily of enzymes with common fold and catalytic machinery but diverse specificities. Putative substrate-enzyme interactions were elucidated by modeling of beta-1,4-linked galactobioses into the possible substrate binding subsites. The structure and modeling studies identified five potential subsites for the binding of galactans, of which one is a pocket suited for accommodating the arabinan side chain in arabinogalactan, one of the natural substrates. A comparison with the substrate binding grooves of other Clan GH-A enzymes suggests that shape complementarity is crucial in determining the specificity of polysaccharidases.

Understanding protein structure-function relationships in Family 47 alpha-1,2-mannosidases through computational docking of ligands

Family 47 alpha-1,2-mannosidases are crucial enzymes involved in N-glycan maturation in the endoplasmic reticula and Golgi apparati of eukaryotic cells. High-resolution crystal structures of the human and yeast endoplasmic reticulum alpha-1,2-mannosidases have been recently determined, the former complexed with the inhibitors 1-deoxymannojirimycin and kifunensine, both of which bind in its active site in the unusual 1C4 conformation. However, unambiguous identification of the catalytic proton donor and nucleophile involved in glycoside bond hydrolysis was not possible from this structural information. In this work, alpha-D-galactose, alpha-D-glucose, and alpha-D-mannose were computationally docked in the active site in the energetically stable 4C1 conformation as well as in the 1C4 conformation to compare their interaction energetics. From these docked structures, a model for substrate and conformer selectivity based on the dimensions of the active site was proposed. Alpha-D-galactopyranosyl-(1-->2)-alpha-D-mannopyranose, alpha-D-glucopyranosyl-(1-->2)-alpha-D-mannopyranose, and alpha-D-mannopyranosyl-(1-->2)-alpha-D-mannopyranose were also docked into the active site with their nonreducing-end residues in the 1C4 and E4 (representing the transition state) conformations. Based on the docked structure of alpha-D-mannopyranosyl-E4-(1-->2)-alpha-D-mannopyranose, the catalytic acid and base are Glu132 and Glu435, respectively.

Automated docking of alpha-(1-->4)- and alpha-(1-->6)-linked glucosyl trisaccharides and maltopentaose into the soybean beta-amylase active site

The Lamarckian genetic algorithm of AutoDock 3.0 was used to dock alpha-maltotriose, methyl alpha-panoside, methyl alpha-isopanoside, methyl alpha-isomaltotrioside, methyl alpha-(6(1)-alpha-glucopyranosyl)-maltoside, and alpha-maltopentaose into the closed and, except for alpha-maltopentaose, into the open conformation of the soybean beta-amylase active site. In the closed conformation, the hinged flap at the mouth of the active site closes over the substrate. The nonreducing end of alpha-maltotriose docks preferentially to subsites -2 or +1, the latter yielding nonproductive binding. Some ligands dock into less optimal conformations with the nonreducing end at subsite -1. The reducing-end glucosyl residue of nonproductively-bound alpha-maltotriose is close to residue Gln194, which likely contributes to binding to subsite +3. In the open conformation, the substrate hydrogen-bonds with several residues of the open flap. When the flap closes, the substrate productively docks if the nonreducing end is near subsites -2 or -1. Trisaccharides with alpha-(1-->6) bonds do not successfully dock except for methyl alpha-isopanoside, whose first and second glucosyl rings dock exceptionally well into subsites -2 and -1. The alpha-(1-->6) bond between the second and third glucosyl units causes the latter to be improperly positioned into subsite +1; the fact that isopanose is not a substrate of beta-amylase indicates that binding to this subsite is critical for hydrolysis.

Automated docking of ligands to antibodies: methods and applications

Many approaches to studying protein-ligand interactions by computational docking are currently available. Given the structures of a protein and a ligand, the ultimate goal of all docking methods is to predict the structure of the resulting complex. This requires a suitable representation of molecular structures and properties, search algorithms to efficiently scan the configuration space for favorable interaction geometries, and accurate scoring functions to evaluate and rank the generated orientations. For many of the available methods, tests on experimentally known antibody-antigen or antibody-hapten complexes have appeared in the literature. In addition, some of them have been used in predictive studies on antibody-ligand interactions to provide structural insights where adequate experimental information is missing. The AutoDock program is presented as example of a method for flexibly docking ligands to antibodies. Applying parameters of the second-generation AMBER force field, three antibody-hapten complexes (AN02, DB3, NC6.8) are used as new test cases to analyze the ability of the method to reproduce experimental findings. The X-ray structures could be reconstituted and the corresponding solutions were ranked with best energy score in all cases. Docking to the free instead of the complexed NC6.8 structure indicated the limits of the rigid protein treatment, although fairly good guesses about the location of the binding site and the contact residues could still be obtained if conformational flexibility was allowed at least in the ligand.

Automated docking of maltose, 2-deoxymaltose, and maltotetraose into the soybean beta-amylase active site

In this study, products and substrates were docked into the active site of beta-amylase using the simulated annealing algorithm AutoDock. Lowest-energy conformers reproduced known crystallographic atom positions within 0.4 to 0.8 A rmsd. Docking studies were carried out with both open and closed configurations of the beta-amylase mobile flap, a loop comprising residues 96 to 103. Ligands with two rings docked within the cleft near the active site when the flap was open, but those with four rings did not. The flap must be closed for alpha-maltotetraose to adopt a conformation allowing it to dock near the crystallographically determined subsites. The closed flap is necessary for productive but not for nonproductive binding, and therefore it plays a essential role in catalysis. The gain in total binding energy upon closing of the flap for alpha-maltose docked to subsites -2, -1 and +1, +2 is about 22 kcal/mol, indicating more favorable interactions are possible with the flap closed. Larger intermolecular interaction energies are observed for two alpha-maltose molecules docked to subsites -2, -1 and +1, +2 than for one alpha-maltotetraose molecule docked from subsites -2 to +2, suggesting that it is only upon cleavage of the alpha-1,4 linkage that optimal closed-flap binding can occur with the crytallographically determined enzyme structure.

Three-dimensional models of alpha(2A)-adrenergic receptor complexes provide a structural explanation for ligand binding

We have compared bacteriorhodopsin-based (alpha(2A)-AR(BR)) and rhodopsin-based (alpha(2A)-AR(R)) models of the human alpha(2A)-adrenengic receptor (alpha(2A)-AR) using both docking simulations and experimental receptor alkylation studies with chloroethylclonidine and 2-aminoethyl methanethiosulfonate hydrobromide. The results indicate that the alpha(2A)-AR(R) model provides a better explanation for ligand binding than does our alpha(2A)-AR(BR) model. Thus, we have made an extensive analysis of ligand binding to alpha(2A)-AR(R) and engineered mutant receptors using clonidine, para-aminoclonidine, oxymetazoline, 5-bromo-N-(4, 5-dihydro-1H-imidazol-2-yl)-6-quinoxalinamine (UK14,304), and norepinephrine as ligands. The representative docked ligand conformation was chosen using extensive docking simulations coupled with the identification of favorable interaction sites for chemical groups in the receptor. These ligand-protein complex studies provide a rational explanation at the atomic level for the experimentally observed binding affinities of each of these ligands to the alpha(2A)-adrenergic receptor.

Ligand binding by antibody IgE Lb4: assessment of binding site preferences using microcalorimetry, docking, and free energy simulations

Antibody IgE Lb4 interacts favorably with a large number of different compounds. To improve the current understanding of the structural basis of this vast cross-reactivity, the binding of three dinitrophenyl (DNP) amino acids (DNP-alanine, DNP-glycine, and DNP-serine) is investigated in detail by means of docking and molecular dynamics free energy simulations. Experimental binding energies obtained by isothermal titration microcalorimetry are used to judge the results of the computational studies. For all three ligands, the docking procedure proposes two plausible subsites within the binding region formed by the antibody CDR loops. By subsequent molecular dynamics simulations and calculations of relative free energies of binding, one of these subsites, a tyrosine-surrounded pocket, is revealed as the preferred point of complexation. For this subsite, results consistent with experimental observations are obtained; DNP-glycine is found to bind better than DNP-serine, and this, in turn, is found to bind better than DNP-alanine. The suggested binding mode makes it possible to explain both the moderate binding affinity and the differences in binding energy among the three ligands.

The role of waters in docking strategies with incremental flexibility for carbohydrate derivatives: heat-labile enterotoxin, a multivalent test case

Molecular docking studies of carbohydrate derivatives in protein binding sites are often challenging because of water-mediated interactions and the inherent flexibility of the many terminal hydroxyl groups. Using the recognition process between heat-labile enterotoxin from Escherichia coli and ganglioside GM1 as a paradigm, we developed a modeling protocol that includes incremental conformational flexibility of the ligand and predicted water interactions. The strategy employs a modified version of the Monte Carlo docking program AUTODOCK and water affinity potentials calculated with GRID. After calibration of the protocol on the basis of the known binding modes of galactose and lactose to the toxin, blind predictions were made for the binding modes of four galactose derivatives: lactulose, melibionic acid, thiodigalactoside, and m-nitrophenyl-alpha-galactoside. Subsequent crystal structure determinations have demonstrated that our docking strategy can predict the correct binding modes of carbohydrate derivatives within 1.0 A from experiment. In addition, it is shown that repeating the docking simulations in each of the seemingly identical binding sites of the multivalent toxin increases the chance of finding the correct binding mode.

Automated docking of monosaccharide substrates and analogues and methyl alpha-acarviosinide in the glucoamylase active site

Glucoamylase is an important industrial glucohydrolase with a large specificity range. To investigate its interaction with the monosaccharides D-glucose, D-mannose, and D-galactose and with the substrate analogues 1-deoxynojirimycin, D-glucono-1,5-lactone, and methyl alpha-acarviosinide, MM3(92)-optimized structures were docked into its active site using AutoDock 2.1. The results were compared to structures of glucoamylase complexes obtained by protein crystallography. Charged forms of some substrate analogues were also docked to assess the degree of protonation possessed by glucoamylase inhibitors. Many forms of methyl alpha-acarviosinide were conformationally mapped by using MM3(92), characterizing the conformational pH dependence found for the acarbose family of glucosidase inhibitors. Their significant conformers, representing the most common states of the inhibitor, were used as initial structures for docking. This constitutes a new approach for the exploration of binding modes of carbohydrate chains. Docking results differ slightly from x-ray crystallographic data, the difference being of the order of the crystallographic error. The estimated energetic interactions, even though agreeing in some cases with experimental binding kinetics, are only qualitative due to the large approximations made by AutoDock force field.

Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4

AutoDock 2.4 predicts the bound conformations of a small, flexible ligand to a nonflexible macromolecular target of known structure. The technique combines simulated annealing for conformation searching with a rapid grid-based method of energy evaluation based on the AMBER force field. AutoDock has been optimized in performance without sacrificing accuracy; it incorporates many enhancements and additions, including an intuitive interface. We have developed a set of tools for launching and analyzing many independent docking jobs in parallel on a heterogeneous network of UNIX-based workstations. This paper describes the current release, and the results of a suite of diverse test systems. We also present the results of a systematic investigation into the effects of varying simulated-annealing parameters on molecular docking. We show that even for ligands with a large number of degrees of freedom, root-mean-square deviations of less than 1 A from the crystallographic conformation are obtained for the lowest-energy dockings, although fewer dockings find the crystallographic conformation when there are more degrees of freedom.

Comparative docking studies on ligand binding to the multispecific antibodies IgE-La2 and IgE-Lb4

A large comparative study is presented in which the binding of approximately 30 different ligands to two IgE antibodies (La2 and Lb4) is analyzed by means of an automated-docking procedure based on simulated annealing. The method is able to reproduce experimentally verified binding orientations, as shown by application to the Ig-AN02-hapten complex. The main address of the study is to investigate the concept of antibody multispecificity. Problems and usefulness of docking in this context are discussed. The results indicate reasons for multispecific binding properties and how they can be understood from the topology of the binding site. Though similar in general behaviour, the two antibodies show interesting differences in their binding characteristics. The binding sites of both antibodies are described and the main interacting residues revealed.

Conservation of aconitase residues revealed by multiple sequence analysis. Implications for structure/function relationships

Aconitases have recently regained much attention, because one member of this family, iron regulatory protein-1 (IRP-1), has been found to play a dual role as a cytoplasmic aconitase and a regulatory RNA-binding protein. This finding has highlighted a novel role for Fe-S clusters as post-translational regulatory switches. We have aligned 28 members of the Fe-S isomerase family, identified highly conserved amino acid residues, and integrated this information with data on the crystallographic structure of mammalian mitochondrial aconitase. We propose structural and/or functional roles for the previously unrecognized conserved residues. Our findings illustrate the value of detailed protein sequence analysis when high-resolution crystallographic data are already available.