Theoretical Aspects of Molecular Recognition

Molecular recognition is a key process in non-covalent interactions, which determines, among others, host-guest complexation, drug action and protein-protein interaction. A simple and attractive formulation is the lock-and-key analogy defining the host as a lock accommodating the guest as a key. We stress three major aspects of molecular recognition, determining both complementarity between host and guest and similarity within a group of guest molecules. These aspects are: steric, i.e. maximization of close contacts, electrostatic, i.e. maximization of electrostatic attraction between host and guest, as well as hydrophobic, i.e. avoiding hydrophobic hydration, which can be reached by the maximization of apolar contacts between interacting molecules. Some examples are presented from our laboratory: the complexes of acylaminoacyl peptidase with small peptides, the effect of heparin binding on inhibitory potency of C1- inhibitor as well as small-molecule ligand binding to prolyl oligopeptidase and calmodulin

How structural adaptability exists alongside HLA-A2 bias in the human alphabeta TCR repertoire

How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining alphabeta TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged hot-spot region that is almost exclusive to the alpha1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Valpha and Vbeta genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs

Testing Electrostatic Complementarity in Enzyme Catalysis: Hydrogen Bonding in the Ketosteroid Isomerase Oxyanion Hole

A longstanding proposal in enzymology is that enzymes are electrostatically and geometrically complementary to the transition states of the reactions they catalyze and that this complementarity contributes to catalysis. Experimental evaluation of this contribution, however, has been difficult. We have systematically dissected the potential contribution to catalysis from electrostatic complementarity in ketosteroid isomerase. Phenolates, analogs of the transition state and reaction intermediate, bind and accept two hydrogen bonds in an active site oxyanion hole. The binding of substituted phenolates of constant molecular shape but increasing p K (a) models the charge accumulation in the oxyanion hole during the enzymatic reaction. As charge localization increases, the NMR chemical shifts of protons involved in oxyanion hole hydrogen bonds increase by 0.50–0.76 ppm/p K (a) unit, suggesting a bond shortening of ˜0.02 Å/p K (a) unit. Nevertheless, there is little change in binding affinity across a series of substituted phenolates (ΔΔG = −0.2 kcal/mol/p K (a) unit). The small effect of increased charge localization on affinity occurs despite the shortening of the hydrogen bonds and a large favorable change in binding enthalpy (ΔΔH = −2.0 kcal/mol/p K (a) unit). This shallow dependence of binding affinity suggests that electrostatic complementarity in the oxyanion hole makes at most a modest contribution to catalysis of ˜300-fold. We propose that geometrical complementarity between the oxyanion hole hydrogen-bond donors and the transition state oxyanion provides a significant catalytic contribution, and suggest that KSI, like other enzymes, achieves its catalytic prowess through a combination of modest contributions from several mechanisms rather than from a single dominant contribution

Plausible blockers of Spike RBD in SARS-CoV2-molecular design and underlying interaction dynamics from high-level structural descriptors

COVID-19 is characterized by an unprecedented abrupt increase in the viral transmission rate (SARS-CoV-2) relative to its pandemic evolutionary ancestor, SARS-CoV (2003). The complex molecular cascade of events related to the viral pathogenicity is triggered by the Spike protein upon interacting with the ACE2 receptor on human lung cells through its receptor binding domain (RBDSpike). One potential therapeutic strategy to combat COVID-19 could thus be limiting the infection by blocking this key interaction. In this current study, we adopt a protein design approach to predict and propose non-virulent structural mimics of the RBDSpike which can potentially serve as its competitive inhibitors in binding to ACE2. The RBDSpike is an independently foldable protein domain, resilient to conformational changes upon mutations and therefore an attractive target for strategic re-design. Interestingly, in spite of displaying an optimal shape fit between their interacting surfaces (attributed to a consequently high mutual affinity), the RBDSpike-ACE2 interaction appears to have a quasi-stable character due to a poor electrostatic match at their interface. Structural analyses of homologous protein complexes reveal that the ACE2 binding site of RBDSpike has an unusually high degree of solvent-exposed hydrophobic residues, attributed to key evolutionary changes, making it inherently "reaction-prone." The designed mimics aimed to block the viral entry by occupying the available binding sites on ACE2, are tested to have signatures of stable high-affinity binding with ACE2 (cross-validated by appropriate free energy estimates), overriding the native quasi-stable feature. The results show the apt of directly adapting natural examples in rational protein design, wherein, homology-based threading coupled with strategic "hydrophobic ↔ polar" mutations serve as a potential breakthrough

Software for molecular docking: a review

Publshed ArticleMolecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homologymodeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate

Structure-function relations in phosphorylcholine-binding mouse myeloma proteins

The binding site interactions between the phosphorylcholine (phosphocholine)-binding mouse myeloma proteins TEPC 15, W3207, McPC 603, MOPC 167, and MOPC 511 and the isotopically substituted hapten phosphoryl-[methyl-13C]choline have been investigated using 13C and 31P nuclear magnetic resonance (NMR) spectroscopy. Each protein exhibits a unique NMR pattern, but extensive similarities in chemical shift parameters upon binding of hapten to immunoglobulin suggest a significant degree of conservation of important hapten-binding site interactions. Moreover, independent binding studies, in conjunction with the NMR data, allow construction of a simple model of the binding sites of these antibodies, analyzed in terms of the relative strength of interaction between hapten and two main subsites. The NMR evidence supports the view that the heavy chains of these proteins dominate in interacting with bound phosphorylcholine; the various subspecificities of these proteins for phosphorylcholine analogues can be accounted for by amino acid changes in the hypervariable regions of the heavy chains

PL-PatchSurfer: A Novel Molecular Local Surface-Based Method for Exploring Protein-Ligand Interactions

Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets