SeeSAR/HYDE: scientific background

abstract

It is highly desirable to have a scoring function that provides guidance for the design of compounds with optimized bioactivity. HYDE [1], as implemented in the SeeSAR software package, is such a scoring function. Its basic principle is a balanced assessment of the energetics of desolvation. Optimizing the signal-to-noise ratio, three major factors are taken into consideration:

  1. local hydrophobicity,
  2. solvent accessible surface, and
  3. contact surface area.

Based on these, energetically favorable and unfavorable contributions to the binding affinity can be assessed on an atomic level. The HYdration and DEsolvation terms are determined using octanol/water partition coefficients of small molecules. We do not calibrate based on affinity data or otherwise! Therefore HYDE is generally applicable to all protein targets. It reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes.

HYDE successfully selects the correct binding mode in 93% of complexes in re-docking calculations on the Astex diverse set. Also, the performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls. On the PDBbind 2007 coreset, HYDE achieves a correlation coefficient of 0.62 between the experimental binding constants and the predicted binding energy, performing best on this dataset compared all other well-established scoring functions that have not been trained on this data. Furthermore, it has been demonstrated that HYDE is able to distinguish in congeneric compound series between strong binders, weak binders, and non-binders [2]. Previously missing terms regarding repulsion and strain which rendered HYDE not entirely applicable to conformationally strained or clashing poses are now considered in an optimization phase prior to the actual score assessment.

The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. The user may immediately identify energetically unfavorable arrangements, like an H-bonding group without a counter-part in an otherwise hydrophobic pocket. Medicinal chemists will immediately have ideas how to alter a given structure in order to gain activity. The interface allows these changes to be tried out in an interactive manner like on a virtual workbench.

See the slide show, with plenty details about HYDE

use cases

One of the great advantages of HYDE is that it is solely based on physicochemical properties and reflects energy-estimates cited in standard literature for multiple decades very well without being calibrated or adjusted based on experimental data. Therefore HYDE is a generally applicable scoring function and it works well in a range of different scenarios.

  1. First of all, HYDE is great to do an assessment of the validity of your protein structure at hand. If you have a protein-ligand complex and an experimentally determined binding affinity that deviates significantly from the HYDE-estimate, then we highly recommend you to take a close look at your structure. Among the things we observed in crystal structures are these issues the most frequent:
    1. soaking artifacts (close contacts, crystal contacts, few H-bonds)
    2. poor electron density for the ligand (load the structure in COOT, e.g., you will be surprised how often the ligand is basically modeled (in part) into the structure.
    3. misassignment of the usual ambiguities (e.g. NO flips etc)
    4. misplaced water molecules (often enough placed simply to minimize the difference electron density).
    5. also, watch out for extreme crystallization conditions (pH, buffer, ...), and be careful with low-resolution structures.
  2. Assuming that the above assessment went well, the primary use of HYDE is obviously the assessment of the affinity of the given complex, but also for related structures, analogs, and design compounds. This can best and comfortably be done with the SeeSAR software package. Next comes virtual screening, in this domain too HYDE has demonstrated its predictive power [2].
  3. Further use-cases are the assessment of the stability of proteins. HYDE has a temperature-dependent formula, so it can be used to see at which point a structure becomes instable and whether a mutation increases or decreases the stability. HYDE has also been used successfully to study the stability of protein-protein interfaces and could well differentiate transient from permanent interactions.

literature

ours

Towards an integrated description of hydrogen bonding and dehydration: II. Reducing false positives in virtual screening using the HYDE scoring function
Reulecke, I., Lange, G., Albrecht, J., Klein, R., Rarey, M.
Chem. Med. Chem. 2008, 3(6): 885-897
HYDE theory
HYDE: An integrated description of dehydration and H-bonding within protein ligand interfaces
Lange, G., Reulecke, I., Rarey, M., Klein, R.
International Conference on Chemical Structure (ICCS) 2008
70% hit rate through HYDE
Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function
Schneider, N., Hindle, S., Lange, G., Klein, R., Albrecht, J., Briem, H., Beyer, K., Claußen, H., Gastreich, M., Lemmen, C., Rarey, M.
Journal of Computer-Aided Molecular Design 2011, 26(6): 701-723
>90% re-dockings correct
Nearly no Scoring Function without a Hansch-Analysis
Schneider, N., Klein, R., Lange, G., Rarey, M.
Molecular Informatics 2012, 31(6-7): 503-507
the logP foundation of HYDE
A consistent description of HYdrogen bond and DEhydration energies in protein–ligand complexes: methods behind the HYDE scoring function
Schneider, N., Lange, G., Hindle, S., Klein, R., Rarey, M.
Journal of Computer-Aided Molecular Design 2013, 27(1): 15-29
HYDE outperforms competition
In silico Design, Synthesis and Screening of Novel Deoxyhypusine Synthase Inhibitors Targeting HIV-1 Replication
Schröder, M., Kolodzik, A., Pfaff, K., Priyadarshini, P., Krepstakies, M., Hauber, J., Rarey, M., Meier, C.
Chem. Med. Chem. 2014, 9: 940-952
HYDE helps finding HIV inhibitors
Indazole- and Indole-5-carboxamides: Selective and Reversible Monoamine Oxidase B Inhibitors with Subnanomolar Potency
Tzvetkov, N.T., Hinz, S., Küppers, P., Gastreich, M., Müller, C.E.
J. Med. Chem. 2014, 57(15): 6679-6703
HYDE crucial to explain SAR for MAO-B inhibitors

external

N-Acyl Derivatives of 4-Phenoxyaniline as Neuroprotective Agents
Barho, M.T., Oppermann, S., Schrader, F.C., Degenhardt, I., Elsässer, K., Wegscheid-Gerlach, C., Culmsee, C., Schlitzer, M.
Chem. Med. Chem. 2014, DOI: 10.1002/cmdc.201402195
HYDE helps designing neuroprotective agents
Structure-Based Design of Inhibitors of the Aspartic Protease Endothiapepsin by Exploiting Dynamic Combinatorial Chemistry
Mondal, M., Radeva, N., Köster, H., Park, A., Potamitis, C., Zervou, M., Klebe, G., Hirsch, A.K.H.
Angewandte Chemie International Edition 2014, 53(12): 3259-3263
HYDE predictions correlate well with experimental data
In silico identification of potent inhibitors of alpha-synuclein aggregation and its in vivo evaluation using MPTP induced Parkinson mice model
Jayaraj, R.L., Elangovan, N.
Biomedicine & Aging Pathology 2014, 4(2): 147-152
HYDE helps identify potent inhibitors in Parkinson project
De novo fragment-based design of inhibitors of DXS guided by spin-diffusion-based NMR spectroscopy
Masini, T., Pilger, J., Kroezen, B.S., Illarionov, B., Lottmann, P., Fischer, M., Griesinger, C., Hirsch, A.K.H.
Chem. Sci. 2014, 5: 3543-3551
HYDE helps finding DXS inhibitors
3,6-Diamino-4-(2-halophenyl)-2-benzoylthieno[2,3-b]pyridine-5-carbonitriles Are Selective Inhibitors of Plasmodium falciparum Glycogen Synthase Kinase-3
Fugel, W., Oberholzer, A.E., Gschloessl, B., Dzikowski, R., Pressburger, N., Preu, L., Pearl, L.H., Baratte, B., Ratin, M., Okun, I., Doerig, C., Kruggel, S., Lemcke, T., Meijer, L., Kunick, C.
J. Med. Chem. 2013, 56 (1): 264-275
selectivity predicted by HYDE
Molecular and functional characterization of CYP6BQ23, a cytochrome P450 conferring resistance to pyrethroids in European populations of pollen beetle, Meligethes aeneus
Zimmer, C.T., Bass, C., Williamson, M.S., Kaussmann, M., Wölfel, K., Gutbrod, O., Nauen, R.
Insect Biochemistry and Molecular Biology 2014, 45: 18-29
HYDE helps functionally characterizing CYP6BQ23
Synthesis, cyclooxygenase inhibitory effects, and molecular modeling study of 4-aryl-5-(4-(methylsulfonyl)phenyl)-2-alkylthio and -2-alkylsulfonyl-1H-imidazole derivatives
Assadieskandar, A., Amirhamzeh, A., Marjan Salehi, M., Ozadali, K., Ostad, S.N., Shafiee, A., Amini, M.
Bioorganic & Medicinal Chemistry 2013, 21(8): 2355-2362
HYDE helps identifying potent&selective COX inhibitors

NEWS

stay tuned with all the breaking news.

FOLLOW US

© 2017 BioSolveIT GmbH,   all rights reserved