Engineering the Reaction Pathway of a Non-heme Iron Oxygenase Using Ancestral Sequence Reconstruction.

Non-heme iron (Fe), α-ketoglutarate (α-KG)-dependent oxygenases are a family of enzymes that catalyze an array of transformations that cascade forward after the formation of radical intermediates. Achieving control over the reaction pathway is highly valuable and a necessary step toward broadening the applications of these biocatalysts. Numerous approaches have been used to engineer the reaction pathway of Fe/α-KG-dependent enzymes, including site-directed mutagenesis, DNA shuffling, and site-saturation mutagenesis, among others.

Accuracy and Reproducibility of Lipari-Szabo Order Parameters From Molecular Dynamics.

The Lipari-Szabo generalized order parameter probes the picosecond to nanosecond time scale motions of a protein and is useful for rationalizing a multitude of biological processes such as protein recognition and ligand binding. Although these fast motions are an important and intrinsic property of proteins, it remains unclear what simulation conditions are most suitable to reproduce methyl symmetry axis side chain order parameter data () from molecular dynamics simulations. In this study, we show that, while tends to converge within tens of nanoseconds, it is essential to run 10 to 20 replicas starting from configurations close to the experimental structure to obtain the best agreement with experimental values.

Ancestral Sequence Reconstruction to Enable Biocatalytic Synthesis of Azaphilones.

Biocatalysis can be powerful in organic synthesis but is often limited by enzymes' substrate scope and selectivity. Developing a biocatalytic step involves identifying an initial enzyme for the target reaction followed by optimization through rational design, directed evolution, or both. These steps are time consuming, resource-intensive, and require expertise beyond typical organic chemistry.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published.

Identifying Artifacts from Large Library Docking.

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown the hit lists can become dominated by rare artifacts that cheat our scoring functions. Here, we investigate rescoring top-ranked docked molecules with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation as cross-filters. In retrospective studies, this approach deprioritized high-ranking nonbinders for nine targets while leaving true ligands relatively unaffected.

Small molecule FICD inhibitors suppress endogenous and pathologic FICD-mediated protein AMPylation.

The AMP transferase, FICD, is an emerging drug target finetuning stress signaling in the endoplasmic reticulum (ER). FICD is a bi-functional enzyme, catalyzing both AMP addition (AMPylation) and removal (deAMPylation) from the ER resident chaperone BiP/GRP78. Despite increasing evidence linking excessive BiP/GRP78 AMPylation to human diseases, small molecules to inhibit pathogenic FICD variants are lacking.

Identifying Artifacts from Large Library Docking.

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown, the very top of the hit-lists can become populated with artifacts that cheat our scoring functions. Though these cheating molecules are rare, they become ever-more dominant with library growth. Here, we investigate rescoring top-ranked molecules from docking screens with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation (AB-FEP) as cross-filters.

How to Sample Dozens of Substitutions per Site with λ Dynamics.

Alchemical free energy methods are useful in computer-aided drug design and computational protein design because they provide rigorous statistical mechanics-based estimates of free energy differences from molecular dynamics simulations. λ dynamics is a free energy method with the ability to characterize combinatorial chemical spaces spanning thousands of related systems within a single simulation, which gives it a distinct advantage over other alchemical free energy methods that are mostly limited to pairwise comparisons. Recently developed methods have improved the scalability of λ dynamics to perturbations at many sites; however, the size of chemical space that can be explored at each individual site has previously been limited to fewer than ten substituents.

Exploring the Limits of the Generalized CHARMM and AMBER Force Fields through Predictions of Hydration Free Energy of Small Molecules.

Accurate force field parameters, potential energy functions, and receptor-ligand models are essential for modeling the solvation and binding of drug-like molecules to a receptor. A large and ever-growing chemical space of medicinally relevant scaffolds has also required these factors, especially force field parameters, to be highly transferable. Generalized force fields such as the CHARMM General Force Field (CGenFF) and the generalized AMBER force field (GAFF) have accomplished this feat along with other contemporaneous ones like OPLS.

Investigating Polypharmacology through Targeting Known Human Neutrophil Elastase Inhibitors to Proteinase 3.

Using a combination of multisite λ-dynamics (MSλD) together with IC assays, we evaluated the polypharmacological potential of a scaffold currently in clinical trials for inhibition of human neutrophil elastase (HNE), targeting cardiopulmonary disease, for efficacious inhibition of Proteinase 3 (PR3), a related neutrophil serine proteinase. The affinities we observe suggest that the dihydropyrimidinone scaffold can serve as a suitable starting point for the establishment of polypharmacologically targeting both enzymes and enhancing the potential for treatments addressing diseases like chronic obstructive pulmonary disease.

Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design.

Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions.

Biomolecular dynamics in the 21st century.

The relevance of motions in biological macromolecules has been clear since the early structural analyses of proteins by X-ray crystallography. Computer simulations have been applied to provide a deeper understanding of the dynamics of biological macromolecules since 1976, and are now a standard tool in many labs working on the structure and function of biomolecules. In this mini-review we highlight some areas of current interest and active development for simulations, in particular all-atom molecular dynamics simulations.

FASTDock: A Pipeline for Allosteric Drug Discovery.

Allostery is involved in innumerable biological processes and plays a fundamental role in human disease. Thus, the exploration of allosteric modulation is crucial for research on biological mechanisms and in the development of novel therapeutics. The development of small-molecule allosteric effectors can be used as tools to probe biological mechanisms of interest.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors.

TMPRSS2 Inhibitor Discovery Facilitated through an and Biochemical Screening Platform.

The COVID-19 pandemic has highlighted the need for new antiviral approaches because many of the currently approved drugs have proven ineffective against mitigating SARS-CoV-2 infections. The host transmembrane serine protease TMPRSS2 is a promising antiviral target because it plays a role in priming the spike protein before viral entry occurs for the most virulent variants. Further, TMPRSS2 has no established physiological role, thereby increasing its attractiveness as a target for antiviral agents.

pyCHARMM: Embedding CHARMM Functionality in a Python Framework.

CHARMM is rich in methodology and functionality as one of the first programs addressing problems of molecular dynamics and modeling of biological macromolecules and their partners, e.g., small molecule ligands.

Deciphering the evolution of flavin-dependent monooxygenase stereoselectivity using ancestral sequence reconstruction.

Controlling the selectivity of a reaction is critical for target-oriented synthesis. Accessing complementary selectivity profiles enables divergent synthetic strategies, but is challenging to achieve in biocatalytic reactions given enzymes' innate preferences of a single selectivity. Thus, it is critical to understand the structural features that control selectivity in biocatalytic reactions to achieve tunable selectivity.

QSAR via multisite λ-dynamics in the orphaned TSSK1B kinase.

Multisite λ-dynamics (MSλD) is a novel method for the calculation of relative free energies of binding for ligands to their targeted receptors. It can be readily used to examine a large number of molecules with multiple functional groups at multiple sites around a common core. This makes MSλD a powerful tool in structure-based drug design.

Free Gangliosides Can Alter Amyloid-β Aggregation.

A recently proposed lipid-chaperone hypothesis suggests that free lipid molecules, not bound to membranes, affect the aggregation of amyloidogenic peptides such as amyloid-β (Aβ) peptides, whose aggregates are the hallmarks of Alzheimer's disease. Here, we combine experiments with all-atom molecular dynamics simulations in explicit solvent to explore the effects of neuronal ganglioside GM1, abundant in mammalian brains, on the aggregation of two principal isoforms of Aβ, Aβ40 and Aβ42. Our simulations show that free GM1 forms stable, highly water-soluble complexes with both isoforms, and nuclear magnetic resonance experiments support the formation of well-ordered, structurally compact GM1+Aβ complexes.

A fine balance of hydrophobic-electrostatic communication pathways in a pH-switching protein.

Allostery is the phenomenon of coupling between distal binding sites in a protein. Such coupling is at the crux of protein function and regulation in a myriad of scenarios, yet determining the molecular mechanisms of coupling networks in proteins remains a major challenge. Here, we report mechanisms governing pH-dependent myristoyl switching in monomeric hisactophilin, whereby the myristoyl moves between a sequestered state, i.

Allostery in the dynamic coactivator domain KIX occurs through minor conformational micro-states.

The coactivator KIX of CBP uses two binding surfaces to recognize multiple activators and exhibits allostery in ternary complex formation. Activator•coactivator interactions are central to transcriptional regulation, yet the microscopic origins of allostery in dynamic proteins like KIX are largely unknown. Here, we investigate the molecular recognition and allosteric manifestations involved in two KIX ternary systems c-Myb•KIX•MLL and pKID•KIX•MLL.

Optimizing Multisite λ-Dynamics Throughput with Charge Renormalization.

With the ability to sample combinations of alchemical perturbations at multiple sites off a small molecule core, multisite λ-dynamics (MSλD) has become an attractive alternative to conventional alchemical free energy methods for exploring large combinatorial chemical spaces. However, current software implementations dictate that combinatorial sampling with MSλD must be performed with a multiple topology model (MTM), which is nontrivial to create by hand, especially for a series of ligand analogues which may have diverse functional groups attached. This work introduces an automated workflow, referred to as , to assist in the creation of a MTM for use with MSλD.

Alchemical Free Energy Methods Applied to Complexes of the First Bromodomain of BRD4.

Accurate and rapid predictions of the binding affinity of a compound to a target are one of the ultimate goals of computer aided drug design. Alchemical approaches to free energy estimations follow the path from an initial state of the system to the final state through alchemical changes of the energy function during a molecular dynamics simulation. Herein, we explore the accuracy and efficiency of two such techniques: relative free energy perturbation (FEP) and multisite lambda dynamics (MSλD).

Addressing Intersite Coupling Unlocks Large Combinatorial Chemical Spaces for Alchemical Free Energy Methods.

Alchemical free energy methods are playing a growing role in molecular design, both for computer-aided drug design of small molecules and for computational protein design. Multisite λ dynamics (MSλD) is a uniquely scalable alchemical free energy method that enables more efficient exploration of combinatorial alchemical spaces encountered in molecular design, but simulations have typically been limited to a few hundred ligands or sequences. Here, we focus on coupling between sites to enable scaling to larger alchemical spaces.