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Despite the pivotal role of molecular docking in modern drug discovery, the default docking scoring functions often fail to recognize active ligands in virtual screening campaigns. Negative image-based rescoring improves docking enrichment by comparing the shape/electrostatic potential (ESP) of the flexible docking poses against the target protein’s inverted cavity volume. By optimizing these negative image-based (NIB) models using a greedy search, the docking rescoring yield can be improved massively and consistently. Here, a fundamental modification is implemented to this shape-focused pharmacophore modelling approach—actual ligand 3D coordinates are incorporated into the NIB models for the optimization. This hybrid approach, labelled as ligand-enhanced brute-force negative image-based optimization (LBR-NiB), takes the best from both worlds, i.e., the all-roundedness of the NIB models and the difficult to emulate atomic arrangements of actual protein-bound small-molecule ligands. Thorough benchmarking, focused on proinflammatory targets, shows that the LBR-NiB routinely improves the docking enrichment over prior iterations of the R-NiB methodology. This boost can be massive, if the added ligand information provides truly essential binding information that was lacking or completely missing from the cavity-based NIB model. On a practical level, the results indicate that the LBR-NiB typically works well when the added ligand 3D data originates from a high-quality source, such as X-ray crystallography, and, yet, the NIB model compositions can also sometimes be improved by fusing into them, for example, with flexibly docked solvent molecules. In short, the study demonstrates that the protein-bound ligands can be used to improve the shape/ESP features of the negative images for effective docking rescoring use in virtual screening.

Molecular docking is a key in silico method used routinely in modern drug discovery projects. Although docking provides high-quality ligand binding predictions, it regularly fails to separate the active compounds from the inactive ones. In negative image-based rescoring (R-NiB), the shape/electrostatic potential (ESP) of docking poses is compared to the negative image of the protein's ligand binding cavity. While R-NiB often improves the docking yield considerably, the cavity-based models do not reach their full potential without expert editing. Accordingly, a greedy search-driven methodology, brute force negative image-based optimization (BR-NiB), is presented for optimizing the models via iterative editing and benchmarking. Thorough and unbiased training, testing and stringent validation with a multitude of drug targets, and alternative docking software show that BR-NiB ensures excellent docking efficacy. BR-NiB can be considered as a new type of shape-focused pharmacophore modeling, where the optimized models contain only the most vital cavity information needed for effectively filtering docked actives from the inactive or decoy compounds. Finally, the BR-NiB code for performing the automated optimization is provided free-of-charge under MIT license via GitHub (https://github.com/jvlehtonen/brutenib) for boosting the success rates of docking-based virtual screening campaigns.

In this study, we use an optogenetic inhibitor of c-Jun NH2-terminal kinase (JNK) in dendritic spine sub-compartments of rat hippocampal neurons. We show that JNK inhibition exerts rapid (within seconds) reorganization of actin in the spine-head., In this study, we use an optogenetic inhibitor of c-Jun NH2-terminal kinase (JNK) in dendritic spine sub-compartments of rat hippocampal neurons. We show that JNK inhibition exerts rapid (within seconds) reorganization of actin in the spine-head. Using real-time Förster resonance energy transfer (FRET) to measure JNK activity, we find that either excitotoxic insult (NMDA) or endocrine stress (corticosterone), activate spine-head JNK causing internalization of AMPARs and spine retraction. Both events are prevented upon optogenetic inhibition of JNK, and rescued by JNK inhibition even 2 h after insult. Moreover, we identify that the fast-acting anti-depressant ketamine reduces JNK activity in hippocampal neurons suggesting that JNK inhibition may be a downstream mediator of its anti-depressant effect. In conclusion, we show that JNK activation plays a role in triggering spine elimination by NMDA or corticosterone stress, whereas inhibition of JNK facilitates regrowth of spines even in the continued presence of glucocorticoid. This identifies that JNK acts locally in the spine-head to promote AMPAR internalization and spine shrinkage following stress, and reveals a protective function for JNK inhibition in preventing spine regression.

BODIL is a molecular modeling environment geared to help the user to quickly identify key features of proteins critical to molecular recognition, especially (1) in drug discovery applications, and (2) to understand the structural basis for function. The program incorporates state-of-the-art graphics, sequence and structural alignment methods, among other capabilities needed in modern structure-function-drug target research. BODIL has a flexible design that allows on-the-fly incorporation of new modules, has intelligent memory management, and fast multi-view graphics. A beta version of BODIL and an accompanying tutorial are available at http://www.abo.fi/fak/mnf/bkf/research/johnson/bodil.html.

The antiferritin variable light domain (VL) dimer binds human spleen ferritin (∼85% L subunits) but with ∼50-fold lower affinity, K a =4×10 7 M −1 , than the parent F11 antibody ( K a =2.1×10 9 M −1 ). The VL dimer does not recognize either rL (100% L subunits) or rH (100% H subunits) human ferritin, whereas the parent antibody recognizes rL-ferritin. To help explain the differences in ferritin binding affinities and specificities, the crystal structure of the VL domain (2.8 A resolution) was determined by molecular replacement and models of the antiferritin VL–VH dimer were made on the basis of antilysozyme antibody D1.3. The domain interface is smaller in the VL dimer but a larger number of interdomain hydrogen bonds may prevent rearrangement on antigen binding. The antigen binding surface of the VL dimer is flatter, lacking a negatively charged pocket found in the VL–VH models, contributed by the CDR3 loop of the VH domain. Loop CDR2 (VL dimer) is located away from the antigen binding site, while the corresponding loop of the VH domain would be located within the antigen binding site. Together these differences lead to 50-fold lower binding affinity in the VL dimer and to more restricted specificity than is seen for the parent antibody.

A detailed comparison of the structures of AspAT, TrpS(3, AlaR, D-AAT and GP has revealed seven common structural segments of the polypeptide chain, which form an extensive common structural organization of the backbone chain responsible for the appropriate disposition of “key” residues interacting with PLPs in these enzymes. Four of the seven fragments in TrpS13, AlaR, and GP share a similar α-β-α-β motif. In addition, this common α-β-α-β supersecondary structure contains an analogous hydrophobic “minicore” formed from three residues. Despite these similarities, the five enzyme families represented by spatial structures and compared within this study are not considered to be related through a common ancestral protein.

We have developed a generic tool for the automatic identification of regions of local structural similarity in unrelated proteins having different folds, as well as for defining more global similarities that result from homologous protein structures. The computer program GENFIT has evolved from the genetic algorithm-based three-dimensional protein structure comparison program GA_FIT.1, 2 GENFIT, however, can locate and superimpose regions of local structural homology regardless of their position in a pair of structures, the fold topology, or the chain direction. Furthermore, it is possible to restrict the search to a volume centered about a region of interest (e.g., catalytic site, ligand-binding site) in two protein structures. We present a number of examples to illustrate the function of the program, which is a parallel processing implementation designed for distribution to multiple machines over a local network or to run on a single multiprocessor computer. Proteins 1999;34:341–355. © 1999 Wiley-Liss, Inc.

Reliable and effective virtual high-throughput screening (vHTS) methods are desperately needed to minimize the expenses involved in drug discovery projects. Here, we present an improvement to the negative image-based (NIB) screening: the shape, the electrostatics, and the solvation state of the target protein’s ligand-binding site are included into the vHTS. Additionally, the initial vHTS results are postprocessed with molecular mechanics/generalized Born surface area (MMGBSA) calculations to estimate the favorability of ligand-protein interactions. The results show that docking produces very good early enrichment for phosphodiesterase-5 (PDE-5); however, in general, the NIB and the ligand-based screening performed better with or without the added electrostatics. Furthermore, the postprocessing of the NIB screening results using MMGBSA calculations improved the early enrichment for the PDE-5 considerably, thus, making hit discovery affordable.

Endosialidase (endo-N-acetylneuraminidase) is a tailspike enzyme of bacteriophages specific for human pathogenic Escherichia coli K1, which specifically recognizes and degrades polySia (polysialic acid). polySia is also a polysaccharide of the capsules of other meningitis- and sepsis-causing bacteria, and a post-translational modification of the NCAM (neural cell-adhesion molecule). We have cloned and sequenced three spontaneously mutated endosialidases of the PK1A bacteriophage and one of the PK1E bacteriophage which display lost or residual enzyme activity but retain the binding activity to polySia. Single to triple amino acid substitutions were identified, and back-mutation constructs indicated that single substitutions accounted for only partial reduction of enzymic activity. A homology-based structural model of endosialidase revealed that all substituted amino acid residues localize to the active site of the enzyme. The results reveal the importance of non-catalytic amino acid residues for the enzymatic activity. The results reveal the molecular background for the dissociation of the polySia binding and cleaving activities of endosialidase and for the evolvement of ‘host range’ mutants of E. coli K1 bacteriophages.

Three ATP-dependent enzymes with different folds, cAMP-dependent protein kinase, D-Ala:D-Ala ligase and the alpha-subunit of the alpha2beta2 ribonucleotide reductase, have a similar organization of their ATP-binding sites. The most meaningful similarity was found over 23 structurally equivalent residues in each protein and includes three strands each from their beta-sheets, in addition to a connecting loop. The equivalent secondary structure elements in each of these enzymes donate four amino acids forming key hydrogen bonds responsible for the common orientation of the "AMP" moieties of their ATP-ligands. One lysine residue conserved throughout the three families binds the alpha-phosphate in each protein. The common fragments of structure also position some, but not all, of the equivalent residues involved in hydrophobic contacts with the adenine ring. These examples of convergent evolution reinforce the view that different proteins can fold in different ways to produce similar structures locally, and nature can take advantage of these features when structure and function demand it, as shown here for the common mode of ATP-binding by three unrelated proteins.

We introduce a statistical method for evaluating atomic level 3D interaction patterns of protein-ligand contacts. Such patterns can be used for fast separation of likely ligand and ligand binding site combinations out of all those that are geometrically possible. The practical purpose of this probabilistic method is for molecular docking and scoring, as an essential part of a scoring function. Probabilities of interaction patterns are calculated conditional on structural x-ray data and predefined chemical classification of molecular fragment types. Spatial coordinates of atoms are modeled using a Bayesian statistical framework with parametric 3D probability densities. The parameters are given distributions a priori, which provides the possibility to update the densities of model parameters with new structural data and use the parameter estimates to create a contact hierarchy. The contact preferences can be defined for any spatial area around a specified type of fragment. We compared calculated contact point hierarchies with the number of contact atoms found near the contact point in a reference set of x-ray data, and found that these were in general in a close agreement. Additionally, using substrate binding site in cathechol-O-methyltransferase and 27 small potential binder molecules, it was demonstrated that these probabilities together with auxiliary parameters separate well ligands from decoys (true positive rate 0.75, false positive rate 0). A particularly useful feature of the proposed Bayesian framework is that it also characterizes predictive uncertainty in terms of probabilities, which have an intuitive interpretation from the applied perspective.

Background Soluble inorganic pyrophosphatase (PPase), an essential enzyme central to phosphorus metabolism, catalyzes the hydrolysis of the phosphoanhydride bond in inorganic pyrophosphate. Catalysis requires divalent metal ions which affect the apparent p K a s of the essential general acid and base on the enzyme, and the p K a of the substrate. Three to five metal ions are required for maximal activity, depending on pH and enzyme source. A detailed understanding of catalysis would aid both in understanding the nature of biological mechanisms of phosphoryl transfer, and in understanding the role of divalent cations. Without a high-resolution complex structure such a model has previously been unobtainable. Results We report the first two high-resolution structures of yeast PPase, at 2.2 and 2.0 a resolution with R factors of around 17%. One structure contains the two activating metal ions; the other, the product (MnP i ) 2 as well. The latter structure shows an extensive network of hydrogen bond and metal ion interactions that account for virtually every lone pair on the product phosphates. It also contains a water molecule/hydroxide ion bridging two metal ions and, uniquely, a phosphate bound to four Mn 2+ ions. Conclusions Our structure-based model of the PPase mechanism posits that the nucleophile is the hydroxide ion mentioned above. This aspect of the mechanism is formally analogous to the ‘two-metal ion' mechanism of alkaline phosphatase, exonucleases and polymerases. A third metal ion coordinates another water molecule that is probably the required general acid. Extensive Lewis acid coordination and hydrogen bonds provide charge shielding of the electrophile and lower the p K a of the leaving group. This ‘three-metal ion' mechanism is in detail different from that of other phosphoryl transfer enzymes, presumably reflecting how ancient the reaction is.