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Review
. 2023 Jun 7:10:1194962.
doi: 10.3389/fmolb.2023.1194962. eCollection 2023.

HINT, a code for understanding the interaction between biomolecules: a tribute to Donald J. Abraham

Glen E Kellogg  1 , Anna Marabotti  2 , Francesca Spyrakis  3 , Andrea Mozzarelli  4
Affiliations
Review

HINT, a code for understanding the interaction between biomolecules: a tribute to Donald J. Abraham

Glen E Kellogg et al. Front Mol Biosci. .

Abstract

A long-lasting goal of computational biochemists, medicinal chemists, and structural biologists has been the development of tools capable of deciphering the molecule-molecule interaction code that produces a rich variety of complex biomolecular assemblies comprised of the many different simple and biological molecules of life: water, small metabolites, cofactors, substrates, proteins, DNAs, and RNAs. Software applications that can mimic the interactions amongst all of these species, taking account of the laws of thermodynamics, would help gain information for understanding qualitatively and quantitatively key determinants contributing to the energetics of the bimolecular recognition process. This, in turn, would allow the design of novel compounds that might bind at the intermolecular interface by either preventing or reinforcing the recognition. HINT, hydropathic interaction, was a model and software code developed from a deceptively simple idea of Donald Abraham with the close collaboration with Glen Kellogg at Virginia Commonwealth University. HINT is based on a function that scores atom-atom interaction using LogP, the partition coefficient of any molecule between two phases; here, the solvents are water that mimics the cytoplasm milieu and octanol that mimics the protein internal hydropathic environment. This review summarizes the results of the extensive and successful collaboration between Abraham and Kellogg at VCU and the group at the University of Parma for testing HINT in a variety of different biomolecular interactions, from proteins with ligands to proteins with DNA.

Keywords: HINT; LogP; hydrophatic interactions; protein–DNA complexes; protein–ligand; protein–protein; water thermodynamics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Schematic representation of the molecular events that take place when a ligand binds to a protein site: (a) several interactions between ligand polar and apolar groups and protein sidechain residues are formed, and (b) water molecules within the active site and bound to the ligand are released into the solvent. These interactions determine the strength of the protein–ligand complex and are computationally evaluated by HINT. (C) The toolboxes of HINT for the evaluation of ligand–protein interactions, including water molecules.
FIGURE 2
FIGURE 2
Correlation between experimental ∆G and HINT score units for 53 protein–ligand complexes from more than 10 distinct proteins (A) characterized by a wide range of ligand polarity as indicated by their LogP values (B) (Cozzini et al., 2002). The line is the best least-squares fit.
FIGURE 3
FIGURE 3
Flowchart of the computational titration.
FIGURE 4
FIGURE 4
Structural water molecules in the HIV-1 protease binding site. The residues lining the pocket (light blue), the ligand (pink), and the water molecules are shown in capped sticks. The protein is displayed in cartoons, and H-bonds involving water molecules are shown by gray dashed lines (PDB ID: 1HIH). The image has been obtained with PyMol version 2.x.
FIGURE 5
FIGURE 5
Cavity is formed during the association of the human placental RNase inhibitor (hRI) and human angiogenin (hAng) proteins to form the complex (pdbid: 1a4y). A closeup view of a portion of this inter-protein interface is shown. The cavity’s extents are depicted by rendering in white dots; the green and purple contours represent the character of the proteins surrounding that cavity, hydrophobic and polar, respectively. What we are terming a “hydrophobic bubble” is found in the upper left region of the cavity as it encloses or traps three non-relevant waters in a largely hydrophobic (green) environment, where their strongest interactions may be amongst themselves. The other two waters in the cavity are in a polar (purple) region and are more relevant. See the study of Ahmed et al. (2011) for a further discussion on water molecules at protein–protein interfaces. Note that displacement of the three non-relevant “hot” waters, likely as a cluster, may reveal a pocket large enough for targeting as a site for protein–protein inhibition.
FIGURE 6
FIGURE 6
(A) Unsolvated docking results for the HyHEL-63/HEL complex. The left panels overlay the predicted ligand poses (cyan) with the crystal structure (red), and the right panels illustrate the interactions of B/Tyr58 with ligand residues. This model is representative of 40% of generated poses found after clustering of the complete set of docking solutions but does not show native residue–residue contacts. (B) Solvated docking results for the HyHEL-63/HEL complex. This model shows native water-mediated residue-residue contacts, with B/Tyr58 showing a water-mediated hydrogen-bonding network with C/Val99 and C/Asp101 (see the study of Parikh and Kellogg, 2014).
FIGURE 7
FIGURE 7
Example contoured hydropathic interaction basis maps for six residue sidechain types. The full set for all residue types includes about 18,000 such maps. Each of these maps illustrate one observed collection of interactions—discovered by 3D map clustering—between the named residue and its environment, including all other residues and water. Each map is taken from the set calculated in the same alpha helix region of the Ramachandran plot, and all are contoured at largely similar iso-density levels. Two views are plotted for each case: left- the CA–CB (z) axis is pointed up, and right- the CA–CB axis is pointed out of the page. The interaction types are color-coded by type: green- favorable hydrophobic interactions, i.e., depicting hydrophobic interactions between the residue depicted and other atoms in its environment; purple- unfavorable hydrophobic (i.e., hydrophobic-polar) interactions; blue- favorable polar (e.g., hydrogen bonding) interactions; and red- unfavorable polar interactions. For more explanation, see the following: alanine- Ahmed et al. (2019), isoleucine- AL Mughram et al. (2023), serine and cysteine- Catalano et al. (2021), phenylalanine- AL Mughram et al. (2023), aspartic acid- Herrington and Kellogg (2021).
FIGURE 8
FIGURE 8
Residue interaction character as a function of solvent-accessible surface area. Each data point represents a cluster of interaction maps. The size of each marker is representative of the number of residues within that cluster (see legend). Left: the character of interactions made by serine residues are dominated (∼60%) by favorable polar (blue) with very minor contributions from hydrophobic interactions (green) that decrease from ∼5% at low solvent accessibility to near zero at fully exposed. On average, serine’s solvent exposure is around 50% (vertical line). Center: same graph for cysteine. The overall trends are quite similar, except that, on average, cysteine’s solvent exposure is only ∼10%, indicating that cysteine is far more likely to be found buried in a protein than on its surface. Right: same graph for S–S bridged cysteine (cystine), where the average solvent exposure is now only about 7%. Also, the character of interactions made by cystine is dominated by unfavorable hydrophobic interactions (purple), followed by favorable hydrophobic. Thus, -S–S- bridged cysteines are found most frequently in strongly hydrophobic environments that are buried. These data may provide insight into predictions of cysteine -S–S- bridge formation in protein structures (see the study of Catalano et al., 2021).
FIGURE 9
FIGURE 9
Complex between the wild-type gene-regulating protein ARC and the DNA (PDB ID: 1BDN). The four chains of the protein are represented with different shades of pink and with highlighted solvent-accessible surface area. In transparency, it is possible to see the secondary structure elements composing the protein. The color code for the nucleotides is as follows: A: red, T: blue, G: green, and C: yellow. Cyan balls represent water molecules. The image has been obtained with UCSF ChimeraX (version 1.5).
FIGURE 10
FIGURE 10
Heat map describing the water enhancement factor (WEF), i.e., the HINT score enhancement due to water contribution, calculated for each amino acid–base pair. A water enhancement factor of 1 indicates an amino acid (AA)–base (B) interaction with no significant bridging water molecules. Data are extracted from Marabotti et al. (2008).
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References

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Grants and funding

This work was supported by the University of Salerno (grant numbers ORSA199808, ORSA208455, and ORSA219407); MIUR (grant FFABR2017 and PRIN 2017 program, grant number 2017483NH8); BANCA D’ITALIA (AMa); and the University of Turin (Ricerca Locale 2020, 2021) SPY_RILO_20_01, SPY_RILO_21_01 (FS).
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