3D Interaction Homology: Hydropathic Analyses of the "π-Cation" and "π-π" Interaction Motifs in Phenylalanine, Tyrosine, and Tryptophan Residues

Three-Dimensional Interaction Homology: Deconstructing Residue-Residue and Residue-Lipid Interactions in Membrane Proteins

A method is described to deconstruct the network of hydropathic interactions within and between a protein's sidechain and its environment into residue-based three-dimensional maps. These maps encode favorable and unfavorable hydrophobic and polar interactions, in terms of spatial positions for optimal interactions, relative interaction strength, as well as character. In addition, these maps are backbone angle-dependent. After map calculation and clustering, a finite number of unique residue sidechain interaction maps exist for each backbone conformation, with the number related to the residue's size and interaction complexity. Structures for soluble proteins (~749,000 residues) and membrane proteins (~387,000 residues) were analyzed, with the latter group being subdivided into three subsets related to the residue's position in the membrane protein: soluble domain, core-facing transmembrane domain, and lipid-facing transmembrane domain. This work suggests that maps representing residue types and their backbone conformation can be reassembled to optimize the medium-to-high resolution details of a protein structure. In particular, the information encoded in maps constructed from the lipid-facing transmembrane residues appears to paint a clear picture of the protein-lipid interactions that are difficult to obtain experimentally.

Demonstration of π-π Stacking at Interfaces: Synthesis of an Indole-Modified Monodisperse Silica Microsphere SiO2@IN

In the present study, a novel silane coupling agent, designated INSi, was synthesized via a facile synthetic route, incorporating indole-functional moieties. This agent was further employed for the surface modification of homemade silica nanomicrospheres (SMPs). The ensuing nanomicrosphere composite, denoted as SiO2@IN, exemplified pronounced interfacial π-π interactions. Optimization of the reaction conditions was conducted using the response surface optimization technique. Subsequent validation of interfacial π-π interactions was accomplished through a synergistic approach, integrating theoretical calculations and comprehensive analyses of spectral and morphological attributes exhibited by the SiO2@IN.

Solvent-Exchange Triggered Solidification of Peptide/POM Coacervates for Enhancing the On-Site Underwater Adhesion

Peptide-based biomimetic underwater adhesives are emerging candidates for understanding the adhesion mechanism of natural proteins secreted by sessile organisms. However, there is a grand challenge in the functional recapitulation of the on-site interfacial spreading, adhesion and spontaneous solidification of native proteins in water using peptide adhesives without applied compressing pressure. Here, a solvent-exchange strategy was utilized to exert the underwater injection, on-site spreading, adhesion and sequential solidification of a series of peptide/polyoxometalate coacervates. The coacervates were first prepared in a mixed solution of water and organic solvents by rationally suppressing the non-covalent interactions. After switching to a water environment, the solvent exchange between bulk water and the organic solvent embedded in the matrix of the peptide/polyoxometalate coacervates recovered the hydrophobic effect by increasing the dielectric constant, resulting in a phase transition from soft coacervates to hard solid with enhanced bulk cohesion and thus compelling underwater adhesive performance. The key to this approach is the introduction of suitable organic solvents, which facilitate the control of the intermolecular interactions and the cross-linking density of the peptide/polyoxometalate adhesives in the course of solidification under the water line. The solvent-exchange method displays fascinating universality and compatibility with different peptide segments.

A Computational Workflow to Predict Biological Target Mutations: The Spike Glycoprotein Case Study

The biological target identification process, a pivotal phase in the drug discovery workflow, becomes particularly challenging when mutations affect proteins' mechanisms of action. COVID-19 Spike glycoprotein mutations are known to modify the affinity toward the human angiotensin-converting enzyme ACE2 and several antibodies, compromising their neutralizing effect. Predicting new possible mutations would be an efficient way to develop specific and efficacious drugs, vaccines, and antibodies. In this work, we developed and applied a computational procedure, combining constrained logic programming and careful structural analysis based on the Structural Activity Relationship (SAR) approach, to predict and determine the structure and behavior of new future mutants. "Mutations rules" that would track statistical and functional types of substitutions for each residue or combination of residues were extracted from the GISAID database and used to define constraints for our software, having control of the process step by step. A careful molecular dynamics analysis of the predicted mutated structures was carried out after an energy evaluation of the intermolecular and intramolecular interactions using the HINT (Hydrophatic INTeraction) force field. Our approach successfully predicted, among others, known Spike mutants.

Merging cultures and disciplines to create a drug discovery ecosystem at Virginia commonwealth university: Medicinal chemistry, structural biology, molecular and behavioral pharmacology and computational chemistry

The Department of Medicinal Chemistry, together with the Institute for Structural Biology, Drug Discovery and Development, at Virginia Commonwealth University (VCU) has evolved, organically with quite a bit of bootstrapping, into a unique drug discovery ecosystem in response to the environment and culture of the university and the wider research enterprise. Each faculty member that joined the department and/or institute added a layer of expertise, technology and most importantly, innovation, that fertilized numerous collaborations within the University and with outside partners. Despite moderate institutional support with respect to a typical drug discovery enterprise, the VCU drug discovery ecosystem has built and maintained an impressive array of facilities and instrumentation for drug synthesis, drug characterization, biomolecular structural analysis and biophysical analysis, and pharmacological studies. Altogether, this ecosystem has had major impacts on numerous therapeutic areas, such as neurology, psychiatry, drugs of abuse, cancer, sickle cell disease, coagulopathy, inflammation, aging disorders and others. Novel tools and strategies for drug discovery, design and development have been developed at VCU in the last five decades; e.g., fundamental rational structure-activity relationship (SAR)-based drug design, structure-based drug design, orthosteric and allosteric drug design, design of multi-functional agents towards polypharmacy outcomes, principles on designing glycosaminoglycans as drugs, and computational tools and algorithms for quantitative SAR (QSAR) and understanding the roles of water and the hydrophobic effect.

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

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.

3D interaction homology: The hydrophobic residues alanine, isoleucine, leucine, proline and valine play different structural roles in soluble and membrane proteins

The aliphatic hydrophobic amino acid residues—alanine, isoleucine, leucine, proline and valine—are among the most common found in proteins. Their structural role in proteins is seemingly obvious: engage in hydrophobic interactions to stabilize secondary, and to a lesser extent, tertiary and quaternary structure. However, favorable hydrophobic interactions involving the sidechains of these residue types are generally less significant than the unfavorable set arising from interactions with polar atoms. Importantly, the constellation of interactions between residue sidechains and their environments can be recorded as three-dimensional maps that, in turn, can be clustered. The clustered average map sets compose a library of interaction profiles encoding interaction strengths, interaction types and the optimal 3D position for the interacting partners. This library is backbone angle-dependent and suggests solvent and lipid accessibility for each unique interaction profile. In this work, in addition to analysis of soluble proteins, a large set of membrane proteins that contained optimized artificial lipids were evaluated by parsing the structures into three distinct components: soluble extramembrane domain, lipid facing transmembrane domain, core transmembrane domain. The aliphatic residues were extracted from each of these sets and passed through our calculation protocol. Notable observations include: the roles of aliphatic residues in soluble proteins and in the membrane protein’s soluble domains are nearly identical, although the latter are slightly more solvent accessible; by comparing maps calculated with sidechain-lipid interactions to maps ignoring those interactions, the potential extent of residue-lipid and residue-interactions can be assessed and likely exploited in structure prediction and modeling; amongst these residue types, the levels of lipid engagement show isoleucine as the most engaged, while the other residues are largely interacting with neighboring helical residues.

Carrier-free subunit nanovaccine amplifies immune responses against tumors and viral infections

Codelivering subunit antigens and Toll-like receptor (TLR) molecular adjuvants via nanocarriers can stimulate potent innate and specific immune responses. Simple and effective nanovaccines fabrication is crucial for application. However, most nanovaccines were fabricated by introducing additional delivery materials, increasing safety risk, cost and processing complexity. Herein, a carrier-free nanovaccine was facilely prepared using a TLR1/TLR2 adjuvant, Diprovocim, rich in benzene rings that could interact with aromatic residues in subunit antigens through π-π stacking without additional materials. The carrier-free nanovaccines with a narrow size distribution could target lymph nodes (LNs) after intravenous injection to mice. The carrier-free nanovaccines based on ovalbumin (OVA) can stimulate strong antibody titers and CD4⁺ and CD8⁺ T cell immune responses in mice, and it synergized with anti-PD1 showing a potent tumor suppression in B16F10-OVA tumor model of mice. Furthermore, the carrier-free nanovaccine with glycoprotein E (gE), a glycoprotein of the varicella-zoster virus (VZV), also showed potent humoral and cellular immune responses. Therefore, using subunit proteins to support Diprovocim by π-π stacking provides a new approach for the preparation and application of novel vaccines for tumor therapy and prevention of infectious diseases. STATEMENT OF SIGNIFICANCE: Codelivering subunit antigens and adjuvants via nanocarriers stimulate potent innate and specific immune responses. However, existing delivery materials for fabricating nanovaccines will inevitably increase the cost of preparation, controllability, process complexity and safety assessment. Therefore, this study easily prepared carrier-free nanovaccines using the benzene ring-rich TLR1/TLR2 adjuvant Diprovocim, which can interact with aromatic residues in subunit antigens via π-π stacking without additional materials. The carrier-free nanovaccines of OVA demonstrated a potent tumor inhibition in treating melanoma in combination with anti-PD1. And the nanovaccines of gE stimulated a strong antibody titer and cellular immune response for herpes zoster. Thus, the present study provides a new approach for the preparation of subunit vaccines to combat various cancers and virus infections.

Systematized analysis of secondary structure dependence of key structural features of residues in soluble and membrane-bound proteins

Knowledge of three-dimensional protein structure is integral to most modern drug discovery efforts. Recent advancements have highlighted new techniques for 3D protein structure determination and, where structural data cannot be collected experimentally, prediction of protein structure. We have undertaken a major effort to use existing protein structures to collect, characterize, and catalogue the inter-atomic interactions that define and compose 3D structure by mapping hydropathic interaction environments as maps in 3D space. This work has been performed on a residue-by-residue basis, where we have seen evidence for relationships between environment character, residue solvent-accessible surface areas and their secondary structures. In this graphical review, we apply principles from our earlier studies and expand the scope to all common amino acid residue types in both soluble and membrane proteins. Key to this analysis is parsing the Ramachandran plot to an 8-by-8 chessboard to define secondary structure bins. Our analysis yielded a number of quantitative discoveries: 1) increased fraction of hydrophobic residues (alanine, isoleucine, leucine, phenylalanine and valine) in membrane proteins compared to their fractions in soluble proteins; 2) less burial coupled with significant increases in favorable hydrophobic interactions for hydrophobic residues in membrane proteins compared to soluble proteins; and 3) higher burial and more favorable polar interactions for polar residues now preferring the interior of membrane proteins. These observations and the supporting data should provide benchmarks for current studies of protein residues in different environments and may be able to guide future protein structure prediction efforts.

3D Interaction Homology: Computational Titration of Aspartic Acid, Glutamic Acid and Histidine Can Create pH-Tunable Hydropathic Environment Maps

Aspartic acid, glutamic acid and histidine are ionizable residues occupying various protein environments and perform many different functions in structures. Their roles are tied to their acid/base equilibria, solvent exposure, and backbone conformations. We propose that the number of unique environments for ASP, GLU and HIS is quite limited. We generated maps of these residue's environments using a hydropathic scoring function to record the type and magnitude of interactions for each residue in a 2703-protein structural dataset. These maps are backbone-dependent and suggest the existence of new structural motifs for each residue type. Additionally, we developed an algorithm for tuning these maps to any pH, a potentially useful element for protein design and structure building. Here, we elucidate the complex interplay between secondary structure, relative solvent accessibility, and residue ionization states: the degree of protonation for ionizable residues increases with solvent accessibility, which in turn is notably dependent on backbone structure.

Functional and protective hole hopping in metalloenzymes

Electrons can tunnel through proteins in microseconds with a modest release of free energy over distances in the 15 to 20 Å range. To span greater distances, or to move faster, multiple charge transfers (hops) are required. When one of the reactants is a strong oxidant, it is convenient to consider the movement of a positively charged "hole" in a direction opposite to that of the electron. Hole hopping along chains of tryptophan (Trp) and tyrosine (Tyr) residues is a critical function in several metalloenzymes that generate high-potential intermediates by reactions with O2 or H2O2, or by activation with visible light. Examination of the protein structural database revealed that Tyr/Trp chains are common protein structural elements, particularly among enzymes that react with O2 and H2O2. In many cases these chains may serve a protective role in metalloenzymes by deactivating high-potential reactive intermediates formed in uncoupled catalytic turnover.

3D interaction homology: Hydropathic interaction environments of serine and cysteine are strikingly different and their roles adapt in membrane proteins

Atomic-resolution protein structural models are prerequisites for many downstream activities like structure-function studies or structure-based drug discovery. Unfortunately, this data is often unavailable for some of the most interesting and therapeutically important proteins. Thus, computational tools for building native-like structural models from less-than-ideal experimental data are needed. To this end, interaction homology exploits the character, strength and loci of the sets of interactions that define a structure. Each residue type has its own limited set of backbone angle-dependent interaction motifs, as defined by their environments. In this work, we characterize the interactions of serine, cysteine and S-bridged cysteine in terms of 3D hydropathic environment maps. As a result, we explore several intriguing questions. Are the environments different between the isosteric serine and cysteine residues? Do some environments promote the formation of cystine S-S bonds? With the increasing availability of structural data for water-insoluble membrane proteins, are there environmental differences for these residues between soluble and membrane proteins? The environments surrounding serine and cysteine residues are dramatically different: serine residues are about 50% solvent exposed, while cysteines are only 10% exposed; the latter are more involved in hydrophobic interactions although there are backbone angle-dependent differences. Our analysis suggests that one driving force for -S-S- bond formation is a rather substantial increase in burial and hydrophobic interactions in cystines. Serine and cysteine become less and more, respectively, solvent-exposed in membrane proteins. 3D hydropathic environment maps are an evolving structure analysis tool showing promise as elements in a new protein structure prediction paradigm.