Designing electrostatic interactions in biological systems via charge optimization or combinatorial approaches: insights and challenges with a continuum electrostatic framework

Electrostatics-Based Computational Design and Experimental Analysis of Buforin II Antimicrobial Peptide Variants with Increased DNA Affinities

Antimicrobial peptides (AMPs) are promising alternatives to traditional antibiotics in the treatment of bacterial infections in part due to their targeting of generic bacterial structures that make it more difficult to develop drug resistance. In this study, we introduce and implement a design workflow to develop more potent AMPs by improving their electrostatic interactions with DNA, which is a putative intracellular target. Using the existing membrane-translocating AMP buforin II (BF2) as a starting point, we use a computational workflow that integrates electrostatic charge optimization, continuum electrostatics, and molecular dynamics simulations to suggest peptide positions at which a neutral BF2 residue could be substituted with arginine to increase DNA-binding affinity either significantly or minimally, with the latter choice done to determine whether AMP binding affinity depends on charge distribution and not just overall monopole. Our analyses predicted that T1R and L8R BF2 variants would yield substantial and minimal increases in DNA-binding affinity, respectively. These predictions were validated with experimental peptide-DNA binding assays with additional computational analyses providing structural insights. Additionally, experimental measurements of antimicrobial potency showed that a design to increase DNA binding can also yield greater potency. As a whole, this study takes initial steps to support the idea that (i) a design strategy aimed to increase AMP binding affinity to DNA by focusing only on electrostatic interactions can improve AMP potency and (ii) the effect on DNA binding of increasing the overall peptide monopole via arginine substitution depends on the position of the substitution. More broadly, this design strategy is a novel way to increase the potency of other membrane-translocating AMPs that target nucleic acids.

Macromolecular crowding effects on electrostatic binding affinity: Fundamental insights from theoretical, idealized models

The crowded cellular environment can affect biomolecular binding energetics, with specific effects depending on the properties of the binding partners and the local environment. Often, crowding effects on binding are studied on particular complexes, which provide system-specific insights but may not provide comprehensive trends or a generalized framework to better understand how crowding affects energetics involved in molecular recognition. Here, we use theoretical, idealized molecules whose physical properties can be systematically varied along with samplings of crowder placements to understand how electrostatic binding energetics are altered through crowding and how these effects depend on the charge distribution, shape, and size of the binding partners or crowders. We focus on electrostatic binding energetics using a continuum electrostatic framework to understand effects due to depletion of a polar, aqueous solvent in a crowded environment. We find that crowding effects can depend predictably on a system's charge distribution, with coupling between the crowder size and the geometry of the partners' binding interface in determining crowder effects. We also explore the effect of crowder charge on binding interactions as a function of the monopoles of the system components. Finally, we find that modeling crowding via a lowered solvent dielectric constant cannot account for certain electrostatic crowding effects due to the finite size, shape, or placement of system components. This study, which comprehensively examines solvent depletion effects due to crowding, complements work focusing on other crowding aspects to help build a holistic understanding of environmental impacts on molecular recognition.

Identification of Optimal Ligand Growth Vectors Using an Alchemical Free-Energy Method

In this work, a novel method to rationally design inhibitors with improved steric contacts and enhanced binding free energies is presented. This new method uses alchemical single step perturbation calculations to rapidly optimize the van der Waals interactions of a small molecule in a protein-ligand complex in order to maximize its binding affinity. The results of the optimizer are used to predict beneficial growth vectors on the ligand, and good agreement is found between the predictions from the optimizer and a more rigorous free energy calculation, with a Spearman's rank order correlation of 0.59. The advantage of the method presented here is the significant speed up of over 10-fold compared to traditional free energy calculations and sublinear scaling with the number of growth vectors assessed. Where experimental data were available, mutations from hydrogen to a methyl group at sites highlighted by the optimizer were calculated with MBAR, and the mean unsigned error between experimental and calculated values of the binding free energy was 0.83 kcal/mol.

Investigating the nucleic acid interactions of histone-derived antimicrobial peptides

While many antimicrobial peptides (AMPs) disrupt bacterial membranes, some translocate into bacteria and interfere with intracellular processes. Buforin II and DesHDAP1 are thought to kill bacteria by interacting with nucleic acids. Here, molecular modeling and experimental measurements are used to show that neither nucleic acid binding peptide selectively binds DNA sequences. Simulations and experiments also show that changing lysines to arginines enhances DNA binding, suggesting that including additional guanidinium groups is a potential strategy to engineer more potent AMPs. Moreover, the lack of binding specificity may make it more difficult for bacteria to evolve resistance to these and other similar AMPs.

Catalytic Mechanism of Mammalian Adenylyl Cyclase: A Computational Investigation

Adenylyl cyclase (AC) catalyzes the synthesis of cyclic AMP, an important intracellular regulatory molecule, from ATP. We propose a catalytic mechanism for class III mammalian AC based on density functional theory calculations. We employ a model of the AC active site derived from a crystal structure of mammalian AC activated by Gα·GTP and forskolin at separate allosteric sites. We compared the calculated activation free energies for 13 possible reaction sequences involving proton transfer, nucleophilic attack, and elimination of pyrophosphate. The proposed most probable mechanism is initiated by deprotonation of 3'OH and water-mediated transfer of the 3'H to the γ-phosphate. Proton transfer is followed by changes in coordination of the two magnesium ion cofactors and changes in the conformation of ATP to enhance the role of 3'O as a nucleophile and to bring 3'O close to Pα. The subsequent phosphoryl transfer step is concerted and rate-limiting. Comparison of the enzyme-catalyzed and nonenzymatic reactions reveals that the active site residues lower the free energy barrier for both phosphoryl transfer and proton transfer and significantly shift the proton transfer equilibrium. Calculations for mutants K1065A and R1029A demonstrate that K1065 plays a significant role in shifting the proton transfer equilibrium, whereas R1029 is important for making the transition state of concerted phosphoryl transfer tight rather than loose.

The effect of macromolecular crowding on the electrostatic component of barnase-barstar binding: a computational, implicit solvent-based study

Macromolecular crowding within the cell can impact both protein folding and binding. Earlier models of cellular crowding focused on the excluded volume, entropic effect of crowding agents, which generally favors compact protein states. Recently, other effects of crowding have been explored, including enthalpically-related crowder–protein interactions and changes in solvation properties. In this work, we explore the effects of macromolecular crowding on the electrostatic desolvation and solvent-screened interaction components of protein–protein binding. Our simple model enables us to focus exclusively on the electrostatic effects of water depletion on protein binding due to crowding, providing us with the ability to systematically analyze and quantify these potentially intuitive effects. We use the barnase–barstar complex as a model system and randomly placed, uncharged spheres within implicit solvent to model crowding in an aqueous environment. On average, we find that the desolvation free energy penalties incurred by partners upon binding are lowered in a crowded environment and solvent-screened interactions are amplified. At a constant crowder density (fraction of total available volume occupied by crowders), this effect generally increases as the radius of model crowders decreases, but the strength and nature of this trend can depend on the water probe radius used to generate the molecular surface in the continuum model. In general, there is huge variation in desolvation penalties as a function of the random crowder positions. Results with explicit model crowders can be qualitatively similar to those using a lowered “effective” solvent dielectric to account for crowding, although the “best” effective dielectric constant will likely depend on multiple system properties. Taken together, this work systematically demonstrates, quantifies, and analyzes qualitative intuition-based insights into the effects of water depletion due to crowding on the electrostatic component of protein binding, and it provides an initial framework for future analyses.

Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules

Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.