Solvent Networks Tune Thermodynamics of Oligosaccharide Complex Formation in an Extended Protein Binding Site

TWN-FS method: A novel fragment screening method for drug discovery

Fragment-based drug discovery (FBDD) is a well-established and effective method for generating diverse and novel hits in drug design. Kinases are suitable targets for FBDD due to their well-defined structure. Water molecules contribute to structure and function of proteins and also influence the environment within the binding pocket. Water molecules form a variety of hydrogen-bonded cyclic water-ring networks, collectively known as topological water networks (TWNs). Analyzing the TWNs in protein binding sites can provide valuable insights into potential locations and shapes for fragments within the binding site. Here, we introduce TWN-based fragment screening (TWN-FS) method, a novel screening method that suggests fragments through grouped TWN analysis within the protein binding site. We used this method to screen known CDK2, CHK1, IGF1R and ERBB4 inhibitors. Our findings suggest that TWN-FS method has the potential to effectively screen fragments. The TWN-FS method package is available on GitHub at https://github.com/pkj0421/TWN-FS.

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.

WaterKit: Thermodynamic Profiling of Protein Hydration Sites

Water desolvation is one of the key components of the free energy of binding of small molecules to their receptors. Thus, understanding the energetic balance of solvation and desolvation resulting from individual water molecules can be crucial when estimating ligand binding, especially when evaluating different molecules and poses as done in High-Throughput Virtual Screening (HTVS). Over the most recent decades, several methods were developed to tackle this problem, ranging from fast approximate methods (usually empirical functions using either discrete atom-atom pairwise interactions or continuum solvent models) to more computationally expensive and accurate ones, mostly based on Molecular Dynamics (MD) simulations, such as Grid Inhomogeneous Solvation Theory (GIST) or Double Decoupling. On one hand, MD-based methods are prohibitive to use in HTVS to estimate the role of waters on the fly for each ligand. On the other hand, fast and approximate methods show an unsatisfactory level of accuracy, with low agreement with results obtained with the more expensive methods. Here we introduce WaterKit, a new grid-based sampling method with explicit water molecules to calculate thermodynamic properties using the GIST method. Our results show that the discrete placement of water molecules is successful in reproducing the position of crystallographic waters with very high accuracy, as well as providing thermodynamic estimates with accuracy comparable to more expensive MD simulations. Unlike these methods, WaterKit can be used to analyze specific regions on the protein surface, (such as the binding site of a receptor), without having to hydrate and simulate the whole receptor structure. The results show the feasibility of a general and fast method to compute thermodynamic properties of water molecules, making it well-suited to be integrated in high-throughput pipelines such as molecular docking.

Understanding Conformational Properties and Role of Hydrogen Bonds in Glycosaminoglycans-Interleukin8 Complexes in Aqueous Medium by Molecular Dynamics Simulation

Atomistic molecular dynamics simulations were performed under ambient conditions to explore the conformational features and binding affinities of hexameric glycosaminoglycans (GAGs) with chemokine Interleukin8 (IL8) in an aqueous medium. We tried to understand the role of hydrogen bonds (HBs) involving conserved water in mediating the interactions. The Luzar-Chandler model was adopted to study the kinetics of HB breaking and formation concerning different water-mediated HBs. The conformational flexibilities of bound GAGs are due to the flexible glycosidic linkages than the occasional/rare ring pucker conformation. The free energy landscape constructed with ϕ, and ψ, depicted that different conformational minima associated with the glycosidic linkage flexibility of the GAGs in bound states are separated by energy barriers. The binding affinities of IL8 towards GAGs are favored through the electrostatic and non-polar solvation interactions. 4-different types of conserved water were explored in the solvent-mediated binding of GAGs with IL8. The average lifetime of the IL8-GAG direct HB pairs was ∼ten times less than the IL8-GAG-shared water HBs. This is due to the rapid establishment of HB breaking and reformation kinetics involving water of a shared layer. We find that despite the highly negatively charged surface of GAGs, the IL8 surface populated by non-cationic amino acids could serve as a promising binding site in addition to the cationic surface of the protein.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Binding Networks Identify Targetable Protein Pockets for Mechanism-Based Drug Design

The human genome codes only a few thousand druggable proteins, mainly receptors and enzymes. While this pool of available drug targets is limited, there is an untapped potential for discovering new drug-binding mechanisms and modes. For example, enzymes with long binding cavities offer numerous prerequisite binding sites that may be visited by an inhibitor during migration from a bulk solution to the destination site. Drug design can use these prerequisite sites as new structural targets. However, identifying these ephemeral sites is challenging. Here, we introduce a new method called NetBinder for the systematic identification and classification of prerequisite binding sites at atomic resolution. NetBinder is based on atomistic simulations of the full inhibitor binding process and provides a networking framework on which to select the most important binding modes and uncover the entire binding mechanism, including previously undiscovered events. NetBinder was validated by a study of the binding mechanism of blebbistatin (a potent inhibitor) to myosin 2 (a promising target for cancer chemotherapy). Myosin 2 is a good test enzyme because, like other potential targets, it has a long internal binding cavity that provides blebbistatin with numerous potential prerequisite binding sites. The mechanism proposed by NetBinder of myosin 2 structural changes during blebbistatin binding shows excellent agreement with experimentally determined binding sites and structural changes. While NetBinder was tested on myosin 2, it may easily be adopted to other proteins with long internal cavities, such as G-protein-coupled receptors or ion channels, the most popular current drug targets. NetBinder provides a new paradigm for drug design by a network-based elucidation of binding mechanisms at an atomic resolution.

A host-guest approach to combining enzymatic and artificial catalysis for catalyzing biomimetic monooxygenation

Direct transfer of protons and electrons between two tandem reactions is still a great challenge, because overall reaction kinetics is seriously affected by diffusion rate of the proton and electron carriers. We herein report a host–guest supramolecular strategy based on the incorporation of NADH mimics onto the surface of a metal-organic capsule to encapsulate flavin analogues for catalytic biomimetic monooxygenations in conjunction with enzymes. Coupling an artificial catalysis and a natural enzymatic catalysis in the pocket of an enzyme, this host–guest catalyst–enzyme system allows direct proton and electron transport between two catalytic processes via NADH mimics for the monooxygenation of both cyclobutanones and thioethers. This host–guest approach, which involves the direct coupling of abiotic and biotic catalysts via a NADH-containing host, is quite promising compared to normal catalyst–enzyme systems, as it offers the key advantages of supramolecular catalysis in integrated chemical and biological synthetic sequences.

Combining artificial and natural enzymes is a strategy to mimic biocatalytic processes with high efficiency and selectivity. This study reports a dual catalytic system composed of flavin adenine dinucleotide model and NADH mimics to catalyze the monooxygenation of cyclobutanones and thioethers.

Increasing the Affinity of an O-Antigen Polysaccharide Binding Site in Shigella flexneri Bacteriophage Sf6 Tailspike Protein

Broad and unspecific use of antibiotics accelerates spread of resistances. Sensitive and robust pathogen detection is thus important for a more targeted application. Bacteriophages contain a large repertoire of pathogen-binding proteins. These tailspike proteins (TSP) often bind surface glycans and represent a promising design platform for specific pathogen sensors. We analysed bacteriophage Sf6 TSP that recognizes the O-polysaccharide of dysentery-causing Shigella flexneri to develop variants with increased sensitivity for sensor applications. Ligand polyrhamnose backbone conformations were obtained from 2D 1 H,1 H-trNOESY NMR utilizing methine-methine and methine-methyl correlations. They agreed well with conformations obtained from molecular dynamics (MD), validating the method for further predictions. In a set of mutants, MD predicted ligand flexibilities that were in good correlation with binding strength as confirmed on immobilized S. flexneri O-polysaccharide (PS) with surface plasmon resonance. In silico approaches combined with rapid screening on PS surfaces hence provide valuable strategies for TSP-based pathogen sensor design.

A Fragmenting Protocol with Explicit Hydration for Calculation of Binding Enthalpies of Target-Ligand Complexes at a Quantum Mechanical Level

Optimization of the enthalpy component of binding thermodynamics of drug candidates is a successful pathway of rational molecular design. However, the large size and missing hydration structure of target-ligand complexes often hinder such optimizations with quantum mechanical (QM) methods. At the same time, QM calculations are often necessitated for proper handling of electronic effects. To overcome the above problems, and help the QM design of new drugs, a protocol is introduced for atomic level determination of hydration structure and extraction of structures of target-ligand complex interfaces. The protocol is a combination of a previously published program MobyWat, an engine for assigning explicit water positions, and Fragmenter, a new tool for optimal fragmentation of protein targets. The protocol fostered a series of fast calculations of ligand binding enthalpies at the semi-empirical QM level. Ligands of diverse chemistry ranging from small aromatic compounds up to a large peptide helix of a molecular weight of 3000 targeting a leukemia protein were selected for systematic investigations. Comparison of various combinations of implicit and explicit water models demonstrated that the presence of accurately predicted explicit water molecules in the complex interface considerably improved the agreement with experimental results. A single scaling factor was derived for conversion of QM reaction heats into binding enthalpy values. The factor links molecular structure with binding thermodynamics via QM calculations. The new protocol and scaling factor will help automated optimization of binding enthalpy in future molecular design projects.