CHARMM‐GUI ligand reader and modeler for CHARMM force field generation of small molecules

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM‐GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM‐GUI modules to build a protein‐ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM‐GUI at http://www.charmm-gui.org/input/ligandrm . © 2017 Wiley Periodicals, Inc.     

In silico based virtual screening and mixed mode QM/MM calculation identifies caffeine scaffold for designing potential inhibitors for tyrosyl tRNA synthetase of Mycobacterium tuberculosis

Aminoacyl tRNA synthetases are novel antibacterial drug target because of their important role in protein synthesis. In this study, we performed high throughput virtual screening of 205883 compounds from Asinex ligand database to identify potential specific inhibitors for Tyrosyl tRNA synthetase of Mycobacterium tuberculosis (MtbTyrRS). Compounds are ranked based on the glide extra precision docking score. It is noted that the top ranked compounds have caffeine scaffold. The top five caffeine analogs are further evaluated for other drug‐like properties. The binding energies of caffeine analogs are estimated using mixed mode quantum mechanics/molecular mechanics calculation. The results show that these caffeine analogs have good absorption, distribution, metabolism, and excretion properties and high binding affinity to the MtbTyrRS. This suggests that caffeine could be a new scaffold for designing inhibitors against Tyrosyl tRNA synthetase of M. tuberculosis. The top five caffeine analogs are also subjected to docking calculations with human cytosolic and mitochondrial Tyrosyl tRNA synthetases to ascertain their specificities toward MtbTyrRS. The comparative docking studies indicate that the top five caffeine analogs are specific for MtbTyrRS. © 2014 Wiley Periodicals, Inc.     

Supramolecular Fluorescence Resonance Energy Transfer in Nucleobase‐Modified Fluorogenic RNA Aptamers

RNA aptamers form compact tertiary structures and bind their ligands in specific binding sites. Fluorescence‐based strategies reveal information on structure and dynamics of RNA aptamers. Herein, we report the incorporation of the universal emissive nucleobase analog 4‐cyanoindole into the fluorogenic RNA aptamer Chili, and its application as a donor for supramolecular FRET to the bound ligands DMHBI⁺ or DMHBO⁺. The photophysical properties of the new nucleobase–ligand‐FRET pair revealed structural restraints for the overall RNA aptamer organization and identified nucleotide positions suitable for FRET‐based readout of ligand binding. This strategy is generally suitable for binding‐site mapping and may also be applied for responsive aptamer devices.     

Expanding molecular modeling and design tools to non‐natural sidechains

Protein–protein interactions encode the wiring diagram of cellular signaling pathways and their deregulations underlie a variety of diseases, such as cancer. Inhibiting protein–protein interactions with peptide derivatives is a promising way to develop new biological and therapeutic tools. Here, we develop a general framework to computationally handle hundreds of non‐natural amino acid sidechains and predict the effect of inserting them into peptides or proteins. We first generate all structural files (pdb and mol2), as well as parameters and topologies for standard molecular mechanics software (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non‐natural sidechains are useful to increase peptide ligand binding affinity. Our results obtained on non‐natural mutants of a BCL9 peptide targeting beta‐catenin show very good correlation between predicted and experimental binding free‐energies, indicating that such predictions can be used to design new inhibitors. Data generated in this work, as well as PyMOL and UCSF Chimera plug‐ins for user‐friendly visualization of non‐natural sidechains, are all available at http://www.swisssidechain.ch . Our results enable researchers to rapidly and efficiently work with hundreds of non‐natural sidechains. © 2012 Wiley Periodicals, Inc.     

Development and screening of epoxy‐spacer‐phage cryogels for affinity chromatography: Enhancing the binding capacity

Macroporous epoxy cryogels can be used as an alternative for classical matrices in affinity chromatography. Due to the structural properties of cryogels, with pores of up to 100 μm, crude samples can be processed at high speed without previous manipulations such as clarification or centrifugation. Also, we previously used a peptide‐expressing M13 bacteriophage as an affinity ligand. These ligands show high specificity toward the target to be purified. Combination of both, leads to a relative cost‐effective one‐step chromatographic set‐up delivering a high purity sample (>95%), however, so far with limited capacity. To increase the binding capacity of the affinity columns, we now inserted spacers between the chromatographic matrix and the phage ligand. Both linear spacers, di‐amino‐alkanes (C₂–C₁₀), and branched polyethyleneimine spacers with different molecular weights (800 Da–10 kDa) were analyzed. Two types of peptide expressing phage ligands, a linear 15‐mer and a cyclic 6‐mer, were used for screening. Up to a tenfold increase in binding capacity was observed depending on the combination of phage ligand and spacer type.     

Transition metals as electron traps. I. Structures,energetics, electron capture,and electron‐transfer‐induced dissociations of ternary copper–peptide complexes in the gas phase

Electron‐induced dissociations of gas‐phase ternary copper‐2,2′‐bipyridine complexes of Gly‐Gly‐Gly and Gly‐Gly‐Leu were studied on a time scale ranging from 130 ns to several milliseconds using a combination of charge‐reversal (⁺CR^?) and electron‐capture‐induced dissociation (ECID) measured on a beam instrument and electron capture dissociation (ECD) measured in a Penning trap. Charge‐reduced intermediates were observed on the short time scale in the ⁺CR^? and ECID experiments but not in ECD. Ion dissociations following electron transfer or capture mostly occurred by competitive bpy or peptide ligand loss, whereas peptide backbone fragmentations were suppressed in the presence of the ligated metal ion. Extensive electron structure theory calculations using density functional theory and large basis sets provided optimized structures and energies for the precursor ions, charge‐reduced intermediates, and dissociation products. The Cu complexes underwent substantial structure changes upon electron capture. Cu was calculated to be pentacoordinated in the most stable singly charged complexes of the [Cu(peptide ? H)bpy]^{+ ?} type where it carried a ～+ 1 atomic charge. Cu coordination in charge‐reduced [Cu(peptide ? H)bpy] intermediates depended on the spin state. The themodynamically more stable singlet states had tricoordinated Cu, whereas triplet states had a tetracoordinated Cu. Cu was tricoordinated in stable [Cu(peptide ? H)bpy]^{? ?} products of electron transfer. [Cu(peptide)bpy]^{2 + ?} complexes contained the peptide ligand in a zwitterionic form while Cu was tetracoordinated. Upon electron capture, Cu was tri‐ or tetracoordinated in the [Cu(peptide)bpy]⁺ charge‐reduced analogs and the peptide ligands underwent prototropic isomerization to canonical forms. The role of excited singlet and triplet electronic states is assessed. Copyright © 2009 John Wiley & Sons, Ltd.     

Allosteric Modulation of Human Serum Albumin Induced by Peptide Ligand

Human serum albumin (HSA ) is an abundant protein in plasma that can bind and transport many small molecules, and the corresponding affinity‐controlled drug delivery shows great advantage in the biological system. Peptide SA06 is a reported ligand comprising 20 amino acids, and is known to non‐covalently bind with HSA to extend the lifetime and improve the pharmacokinetic performance. The structural information of the HSA ‐peptide complex is keen for obtaining molecular insight of the binding mechanism. We studied the secondary structural change and structure‐affinity relations of Peptide SA06 with HSA by using circular dichroism (CD ) spectroscopy in solution. Noticeable allosteric effect can be identified by compositional increase of α ‐helix structures when the peptide was co‐incubated with HSA . Furthermore, the equilibrium dissociation constant of Peptide SA06 with HSA can be determined by CD ‐based method. This work provides structural evidence on the allosteric interaction between peptide ligand and HSA , and sheds light on optimization of therapeutic properties in the affinity‐controlled delivery systems.     

Structural Investigations on the SH3b Domains of Clostridium perfringens Autolysin through NMR Spectroscopy and Structure Simulation Enlighten the Cell Wall Binding Function

Clostridium perfringens autolysin (CpAcp) is a peptidoglycan hydrolase associated with cell separation, division, and growth. It consists of a signal peptide, ten SH3b domains, and a catalytic domain. The structure and function mechanisms of the ten SH3bs related to cell wall peptidoglycan binding remain unclear. Here, the structures of CpAcp SH3bs were studied through NMR spectroscopy and structural simulation. The NMR structure of SH3b6 was determined at first, which adopts a typical β-barrel fold and has three potential ligand-binding pockets. The largest pocket containing eight conserved residues was suggested to bind with peptide ligand in a novel model. The structures of the other nine SH3bs were subsequently predicted to have a fold similar to SH3b6. Their ligand pockets are largely similar to those of SH3b6, although with varied size and morphology, except that SH3b1/2 display a third pocket markedly different from those in other SH3bs. Thus, it was supposed that SH3b3-10 possess similar ligand-binding ability, while SH3b1/2 have a different specificity and additional binding site for ligand. As an entirety, ten SH3bs confer a capacity for alternatively binding to various peptidoglycan sites in the cell wall. This study presents an initial insight into the structure and potential function of CpAcp SH3bs.     

Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes

Many molecular docking programs are available nowadays, and thus it is of great practical value to evaluate and compare their performance. We have conducted an extensive evaluation of four popular commercial molecular docking programs, including Glide, GOLD, LigandFit, and Surflex. Our test set consists of 195 protein‐ligand complexes with high‐resolution crystal structures (resolution ≤2.5 Å) and reliable binding data [dissociation constant (K_d) or inhibition constant (K_i)], which are selected from the PDBbind database with an emphasis on diversity. The top‐ranked solutions produced by these programs are compared to the native ligand binding poses observed in crystal structures. Glide and GOLD demonstrate better accuracy than the other two on the entire test set. Their results are also less sensitive to the starting structures for docking. Comparison of the results produced by these programs at three different computation levels reveal that their accuracy are not always proportional to CPU cost as one may expect. The binding scores of the top‐ranked solutions produced by these programs are in low to moderate correlations with experimentally measured binding data. Further analyses on the outcomes of these programs on three suites of subsets of protein‐ligand complexes indicate that these programs are less capable to handle really flexible ligands and relatively flat binding sites, and they have different preferences to hydrophilic/hydrophobic binding sites. Our evaluation can help other researchers to make reasonable choices among available molecular docking programs. It is also valuable for program developers to improve their methods further. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Connectivity and binding‐site recognition: Applications relevant to drug design

Here, we describe a family of methods based on residue–residue connectivity for characterizing binding sites and apply variants of the method to various types of protein–ligand complexes including proteases, allosteric‐binding sites, correctly and incorrectly docked poses, and inhibitors of protein–protein interactions. Residues within ligand‐binding sites have about 25% more contact neighbors than surface residues in general; high‐connectivity residues are found in contact with the ligand in 84% of all complexes studied. In addition, a k‐means algorithm was developed that may be useful for identifying potential binding sites with no obvious geometric or connectivity features. The analysis was primarily carried out on 61 protein–ligand structures from the MEROPS protease database, 250 protein–ligand structures from the PDBSelect (25%), and 30 protein–protein complexes. Analysis of four proteases with crystal structures for multiple bound ligands has shown that residues with high connectivity tend to have less variable side‐chain conformation. The relevance to drug design is discussed in terms of identifying allosteric‐binding sites, distinguishing between alternative docked poses and designing protein interface inhibitors. Taken together, this data indicate that residue–residue connectivity is highly relevant to medicinal chemistry. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Peptide‐Stabilized,Fluorescent Silver Nanoclusters: Solid‐Phase Synthesis and Screening

Few‐atom silver nanoclusters (AgNCs) can exhibit strong fluorescence; however, they require ligands to prevent aggregation into larger nanoparticles. Fluorescent AgNCs in biopolymer scaffolds have so far mainly been synthesized in solution, and peptides have only found limited use compared to DNA. Herein, we demonstrate how solid‐phase methods can increase throughput dramatically in peptide ligand screening and in initial evaluation of fluorescence intensity and chemical stability of peptide‐stabilized AgNCs (P‐AgNCs). 9‐Fluorenylmethyloxycarbonyl (Fmoc) solid‐phase peptide synthesis on a hydroxymethyl‐benzoic acid (HMBA) polyethylene glycol polyacrylamide copolymer (PEGA) resin enabled on‐resin screening and evaluation of a peptide library, leading to identification of novel peptide‐stabilized, fluorescent AgNCs. Using systematic amino acid substitutions, we synthesized and screened a 144‐member library. This allowed us to evaluate the effect of length, charge, and Cys content in peptides used as ligands for AgNC stabilization. The results of this study will enable future spectroscopic studies of these peptide‐stabilized AgNCs for bioimaging and other applications.     

IADE: a system for intelligent automatic design of bioisosteric analogs

IADE, a software system supporting molecular modellers through the automatic design of non-classical bioisosteric analogs, scaffold hopping and fragment growing, is presented. The program combines sophisticated cheminformatics functionalities for constructing novel analogs and filtering them based on their drug-likeness and synthetic accessibility using automatic structure-based design capabilities: the best candidates are selected according to their similarity to the template ligand and to their interactions with the protein binding site. IADE works in an iterative manner, improving the fitness of designed molecules in every generation until structures with optimal properties are identified. The program frees molecular modellers from routine, repetitive tasks, allowing them to focus on analysis and evaluation of the automatically designed analogs, considerably enhancing their work efficiency as well as the area of chemical space that can be covered. The performance of IADE is illustrated through a case study of the design of a nonclassical bioisosteric analog of a farnesyltransferase inhibitor??an analog that has won a recent ??Design a Molecule?? competition.     

Organic Ligand Binding by a Hydrophobic Cavity in a Designed Tetrameric Coiled‐Coil Protein

The design and characterization of a hydrophobic cavity in de novo designed proteins provides a wide range of information about the functions of de novo proteins. We designed a de novo tetrameric coiled‐coil protein with a hydrophobic pocketlike cavity. Tetrameric coiled coils with hydrophobic cavities have previously been reported. By replacing one Leu residue at the a position with Ala, hydrophobic cavities that did not flatten out due to loose peptide chains were reliably created. To perform a detailed examination of the ligand‐binding characteristics of the cavities, we originally designed two other coiled‐coil proteins: AM2, with eight Ala substitutions at the adjacent a and d positions at the center of a bundled structure, and AM2W, with one Trp and seven Ala substitutions at the same positions. To increase the association of the helical peptides, each helical peptide was connected with flexible linkers, which resulted in a single peptide chain. These proteins exhibited CD spectra corresponding to superhelical structures, despite weakened hydrophobic packing. AM2W exhibited binding affinity for size‐complementary organic compounds. The dissociation constants, K_d, of AM2W were 220 nM for adamantane, 81 μM for 1‐adamantanol, and 294 μM for 1‐adamantaneacetic acid, as measured by fluorescence titration analyses. Although it was contrary to expectations, AM2 did not exhibit any binding affinity, probably due to structural defects around the designed hydrophobic cavity. Interestingly, AM2W exhibited incremental structure stability through ligand binding. Plugging of structural defects with organic ligands would be expected to facilitate protein folding.     

DOX: A new computational protocol for accurate prediction of the protein–ligand binding structures

Molecular docking techniques have now been widely used to predict the protein–ligand binding modes, especially when the structures of crystal complexes are not available. Most docking algorithms are able to effectively generate and rank a large number of probable binding poses. However, it is hard for them to accurately evaluate these poses and identify the most accurate binding structure. In this study, we first examined the performance of some docking programs, based on a testing set made of 15 crystal complexes with drug statins for the human 3‐hydroxy‐3‐methylglutaryl coenzyme A reductase (HMGR). We found that most of the top ranking HMGR–statin binding poses, predicted by the docking programs, were energetically unstable as revealed by the high theoretical‐level calculations, which were usually accompanied by the large deviations from the geometric parameters of the corresponding crystal binding structures. Subsequently, we proposed a new computational protocol, DOX, based on the joint use of molecular Docking, ONIOM, and eXtended ONIOM (XO) methods to predict the accurate binding structures for the protein–ligand complexes of interest. Our testing results demonstrate that the DOX protocol can efficiently predict accurate geometries for all 15 HMGR‐statin crystal complexes without exception. This study suggests a promising computational route, as an effective alternative to the experimental one, toward predicting the accurate binding structures, which is the prerequisite for all the deep understandings of the properties, functions, and mechanisms of the protein–ligand complexes. © 2015 Wiley Periodicals, Inc.     

Receptor‐Bound Conformation of Cilengitide Better Represented by Its Solution‐State Structure than the Solid‐State Structure

The X‐ray crystal and NMR spectroscopic structures of the peptide drug candidate Cilengitide (cyclo(RGDf(NMe)Val)) in various solvents are obtained and compared in addition to the integrin receptor bound conformation. The NMR‐based solution structures exhibit conformations closely resembling the X‐ray structure of Cilengitide bound to the head group of integrin αvβ3. In contrast, the structure of pure Cilengitide recrystallized from methanol reveals a different conformation controlled by the lattice forces of the crystal packing. Molecular modeling studies of the various ligand structures docked to the αvβ3 integrin revealed that utilization of the solid‐state conformation of Cilengitide leads—unlike the solution‐based structures—to a mismatch of the ligand–receptor interactions compared with the experimentally determined structure of the protein–ligand complex. Such discrepancies between solution and crystal conformations of ligands can be misleading during the structure‐based lead optimization process and should thus be taken carefully into account in ligand orientated drug design.     

Micelle‐Triggered β‐Hairpin to α‐Helix Transition in a 14‐Residue Peptide from a Choline‐Binding Repeat of the Pneumococcal Autolysin LytA

Choline‐binding modules (CBMs) have a ββ‐solenoid structure composed of choline‐binding repeats (CBR), which consist of a β‐hairpin followed by a short linker. To find minimal peptides that are able to maintain the CBR native structure and to evaluate their remaining choline‐binding ability, we have analysed the third β‐hairpin of the CBM from the pneumococcal LytA autolysin. Circular dichroism and NMR data reveal that this peptide forms a highly stable native‐like β‐hairpin both in aqueous solution and in the presence of trifluoroethanol, but, strikingly, the peptide structure is a stable amphipathic α‐helix in both zwitterionic (dodecylphosphocholine) and anionic (sodium dodecylsulfate) detergent micelles, as well as in small unilamellar vesicles. This β‐hairpin to α‐helix conversion is reversible. Given that the β‐hairpin and α‐helix differ greatly in the distribution of hydrophobic and hydrophilic side chains, we propose that the amphipathicity is a requirement for a peptide structure to interact and to be stable in micelles or lipid vesicles. To our knowledge, this “chameleonic” behaviour is the only described case of a micelle‐induced structural transition between two ordered peptide structures.     

Q‐DockLHM: Low‐resolution refinement for ligand comparative modeling

The success of ligand docking calculations typically depends on the quality of the receptor structure. Given improvements in protein structure prediction approaches, approximate protein models now can be routinely obtained for the majority of gene products in a given proteome. Structure‐based virtual screening of large combinatorial libraries of lead candidates against theoretically modeled receptor structures requires fast and reliable docking techniques capable of dealing with structural inaccuracies in protein models. Here, we present Q‐Dock^LHM, a method for low‐resolution refinement of binding poses provided by FINDSITE^LHM, a ligand homology modeling approach. We compare its performance to that of classical ligand docking approaches in ligand docking against a representative set of experimental (both holo and apo) as well as theoretically modeled receptor structures. Docking benchmarks reveal that unlike all‐atom docking, Q‐Dock^LHM exhibits the desired tolerance to the receptor's structure deformation. Our results suggest that the use of an evolution‐based approach to ligand homology modeling followed by fast low‐resolution refinement is capable of achieving satisfactory performance in ligand‐binding pose prediction with promising applicability to proteome‐scale applications. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Protein:Ligand binding free energies: A stringent test for computational protein design

A computational protein design method is extended to allow Monte Carlo simulations where two ligands are titrated into a protein binding pocket, yielding binding free energy differences. These provide a stringent test of the physical model, including the energy surface and sidechain rotamer definition. As a test, we consider tyrosyl‐tRNA synthetase (TyrRS), which has been extensively redesigned experimentally. We consider its specificity for its substrate l ‐tyrosine (l ‐Tyr), compared to the analogs d ‐Tyr, p‐acetyl‐, and p‐azido‐phenylalanine (ac‐Phe, az‐Phe). We simulate l ‐ and d ‐Tyr binding to TyrRS and six mutants, and compare the structures and binding free energies to a more rigorous “MD/GBSA” procedure: molecular dynamics with explicit solvent for structures and a Generalized Born + Surface Area model for binding free energies. Next, we consider l ‐Tyr, ac‐ and az‐Phe binding to six other TyrRS variants. The titration results are sensitive to the precise rotamer definition, which involves a short energy minimization for each sidechain pair to help relax bad contacts induced by the discrete rotamer set. However, when designed mutant structures are rescored with a standard GBSA energy model, results agree well with the more rigorous MD/GBSA. As a third test, we redesign three amino acid positions in the substrate coordination sphere, with either l ‐Tyr or d ‐Tyr as the ligand. For two, we obtain good agreement with experiment, recovering the wildtype residue when l ‐Tyr is the ligand and a d ‐Tyr specific mutant when d ‐Tyr is the ligand. For the third, we recover His with either ligand, instead of wildtype Gln. © 2015 Wiley Periodicals, Inc.