Accurate in silico predictions of modified RNA interactions to a prototypical RNA-binding protein with λ-dynamics.

RNA-binding proteins shape biology through their widespread functions in RNA biochemistry. Their function requires the recognition of specific RNA motifs for targeted binding. These RNA binding elements can be composed of both unmodified and chemically modified RNAs, of which over 170 chemical modifications have been identified in biology.

Superimposing Ligands with a Ligand Overlay as an Alternate Topology Model for λ-Dynamics-Based Calculations.

Alchemical free energy (AFE) calculations can predict binding affinity changes as a function of structural modifications and have become powerful tools for lead optimization and drug discovery. Central to the setup and performance of AFE calculations is the manner of mapping alchemical transformations, known as the topology model. Single, dual, and hybrid topology models have been used with various AFE methods in the field.

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.

A λ-Dynamics Investigation of Insulin and Other A3 Variant Binding Affinities to the Insulin Receptor.

Insulin is a clinical insulin variant where a conserved valine at the third residue on insulin's A chain (Val) is replaced with a leucine (Leu), weakening insulin receptor (IR) binding by 140-500-fold. This severe impact on binding from a subtle modification has posed an intriguing problem for decades. Although experimental investigations of natural and unnatural A3 mutations have highlighted the sensitivity of insulin-IR binding at this site, atomistic explanations of these binding trends have remained elusive.

A λ-dynamics investigation of insulin and other A3 variant binding affinities to the insulin receptor.

Insulin is a clinical insulin variant where a conserved valine at the third residue on insulin's A chain (Val) is replaced with a leucine (Leu), impairing insulin receptor (IR) binding by 140-500 fold. This severe impact on binding from such a subtle modification has posed an intriguing problem for decades. Although experimental investigations of natural and unnatural A3 mutations have highlighted the sensitivity of insulin-IR binding to minor changes at this site, an atomistic explanation of these binding trends has remained elusive.

In silico λ-dynamics predicts protein binding specificities to modified RNAs.

RNA modifications shape gene expression through a smorgasbord of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications.

Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling.

Relative binding free energy calculations have become an integral computational tool for lead optimization in structure-based drug design. Classical alchemical methods, including free energy perturbation or thermodynamic integration, compute relative free energy differences by transforming one molecule into another. However, these methods have high operational costs due to the need to perform many pairwise perturbations independently.

Chemically induced partial unfolding of the multifunctional Apurinic/apyrimidinic endonuclease 1.

Targeting of the multifunctional enzyme apurinic/apyrimidinic endonuclease I/redox factor 1 (APE1) has produced small molecule inhibitors of both its endonuclease and redox activities. While one of the small molecules, the redox inhibitor APX3330, completed a Phase I clinical trial for solid tumors and a Phase II clinical trial for Diabetic Retinopathy/Diabetic Macular Edema, the mechanism of action for this drug has yet to be fully understood. Here, we demonstrate through HSQC NMR studies that APX3330 induces chemical shift perturbations (CSPs) of both surface and internal residues in a concentration-dependent manner, with a cluster of surface residues defining a small pocket on the opposite face from the endonuclease active site of APE1.

Identification of nonhistone substrates of the lysine methyltransferase PRDM9.

Lysine methylation is a dynamic, posttranslational mark that regulates the function of histone and nonhistone proteins. Many of the enzymes that mediate lysine methylation, known as lysine methyltransferases (KMTs), were originally identified to modify histone proteins but have also been discovered to methylate nonhistone proteins. In this work, we investigate the substrate selectivity of the KMT PRDM9 to identify both potential histone and nonhistone substrates.

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.

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.

Improved Cell-Potent and Selective Peptidomimetic Inhibitors of Protein N-Terminal Methyltransferase 1.

Protein N-terminal methyltransferase 1 (NTMT1) recognizes a unique N-terminal X-P-K/R motif (X represents any amino acid other than D/E) and transfers 1-3 methyl groups to the N-terminal region of its substrates. Guided by the co-crystal structures of NTMT1 in complex with the previously reported peptidomimetic inhibitor DC113, we designed and synthesized a series of new peptidomimetic inhibitors. Through a focused optimization of DC113, we discovered a new cell-potent peptidomimetic inhibitor GD562 (IC = 0.

Exploring Unconventional SAM Analogues To Build Cell-Potent Bisubstrate Inhibitors for Nicotinamide N-Methyltransferase.

Nicotinamide N-methyltransferase (NNMT) methylates nicotinamide and has been associated with various diseases. Herein, we report the first cell-potent NNMT bisubstrate inhibitor II399, demonstrating a K of 5.9 nM in a biochemical assay and a cellular IC value of 1.

Generalizing the Discrete Gibbs Sampler-Based λ-Dynamics Approach for Multisite Sampling of Many Ligands.

In this work, the discrete λ variant of the Gibbs sampler-based λ-dynamics (-GSλD) method is developed to enable multiple functional group perturbations to be investigated at one or more sites of substitution off a common ligand core. The theoretical framework and special considerations for constructing discrete λ states for multisite -GSλD are presented. The precision and accuracy of the -GSλD method is evaluated with three test cases of increasing complexity.

Gas-Phase Ion/Ion Chemistry for Structurally Sensitive Probes of Gaseous Protein Ion Structure: Electrostatic and Electrostatic to Covalent Cross-Linking.

Intramolecular interactions within a protein are key in maintaining protein tertiary structure and understanding how proteins function. Ion mobility-mass spectrometry (IM-MS) has become a widely used approach in structural biology since it provides rapid measurements of collision cross sections (CCS), which inform on the gas-phase conformation of the biomolecule under study. Gas-phase ion/ion reactions target amino acid residues with specific chemical properties and the modified sites can be identified by MS.

Mutant thermal proteome profiling for characterization of missense protein variants and their associated phenotypes within the proteome.

Temperature-sensitive (TS) missense mutants have been foundational for characterization of essential gene function. However, an unbiased approach for analysis of biochemical and biophysical changes in TS missense mutants within the context of their functional proteomes is lacking. We applied MS-based thermal proteome profiling (TPP) to investigate the proteome-wide effects of missense mutations in an application that we refer to as utant hermal roteome rofiling (mTPP).

Exploring pH Dependent Host/Guest Binding Affinities.

When the electrostatic environment surrounding binding partners changes between unbound and bound states, the net uptake or release of a proton is possible by either binding partner. This process is pH-dependent in that the free energy required to uptake or release the proton varies with pH. This pH-dependence is typically not considered in conventional free energy methods where the use of fixed protonation states is the norm.

Accelerated CDOCKER with GPUs, Parallel Simulated Annealing, and Fast Fourier Transforms.

Fast Fourier transform (FFT)-based protein ligand docking together with parallel simulated annealing for both rigid and flexible receptor docking are implemented on graphical processing unit (GPU) accelerated platforms to significantly enhance the throughput of the CDOCKER and flexible CDOCKER - the docking algorithms in the CHARMM program for biomolecule modeling. The FFT-based approach for docking, first applied in protein-protein docking to efficiently search for the binding position and orientation of proteins, is adapted here to search ligand translational and rotational spaces given a ligand conformation in protein-ligand docking. Running on GPUs, our implementation of FFT docking in CDOCKER achieves a 15 000 fold speedup in the ligand translational and rotational space search in protein-ligand docking problems.

Absolute Free Energy of Binding Calculations for Macrophage Migration Inhibitory Factor in Complex with a Druglike Inhibitor.

Calculation of the absolute free energy of binding (Δ) for a complex in solution is challenging owing to the need for adequate configurational sampling and an accurate energetic description, typically with a force field (FF). In this study, Monte Carlo (MC) simulations with improved side-chain and backbone sampling are used to assess Δ for the complex of a druglike inhibitor (MIF180) with the protein macrophage migration inhibitory factor (MIF) using free energy perturbation (FEP) calculations. For comparison, molecular dynamics (MD) simulations were employed as an alternative sampling method for the same system.

Overcoming Challenging Substituent Perturbations with Multisite λ-Dynamics: A Case Study Targeting β-Secretase 1.

Alchemical free energy calculations have made a dramatic impact upon the field of structure-based drug design by allowing functional group modifications to be explored computationally prior to experimental synthesis and assay evaluation, thereby informing and directing synthetic strategies. In furthering the advancement of this area, a series of 21 β-secretase 1 (BACE1) inhibitors developed by Janssen Pharmaceuticals were examined to evaluate the ability to explore large substituent perturbations, some of which contain scaffold modifications, with multisite λ-dynamics (MSλD), an innovative alchemical free energy framework. Our findings indicate that MSλD is able to efficiently explore all structurally diverse ligand end-states within a MD simulation with a high degree of precision and with reduced computational costs compared to the widely used approach TI/MBAR.

Fast Solver for Large Scale Multistate Bennett Acceptance Ratio Equations.

The multistate Bennett acceptance ratio method (MBAR) and unbinned weighted histogram analysis method (UWHAM) are widely employed approaches to calculate relative free energies of multiple thermodynamic states that gain statistical precision by employing free energy contributions from configurations sampled at each of the simulated λ states. With the increasing availability of high throughput computing resources, a large number of configurations can be sampled from hundreds or even thousands of states. Combining sampled configurations from all states to calculate relative free energies requires the iterative solution of large scale MBAR/UWHAM equations.

Approaching protein design with multisite λ dynamics: Accurate and scalable mutational folding free energies in T4 lysozyme.

The estimation of changes in free energy upon mutation is central to the problem of protein design. Modern protein design methods have had remarkable success over a wide range of design targets, but are reaching their limits in ligand binding and enzyme design due to insufficient accuracy in mutational free energies. Alchemical free energy calculations have the potential to supplement modern design methods through more accurate molecular dynamics based prediction of free energy changes, but suffer from high computational cost.

Predicting Binding Free Energies in a Large Combinatorial Chemical Space Using Multisite λ Dynamics.

In this study, we demonstrate the extensive scalability of the biasing potential replica exchange multisite λ dynamics (BP-REX MSλD) free energy method by calculating binding affinities for 512 inhibitors to HIV Reverse Transcriptase (HIV-RT). This is the largest exploration of chemical space using free energy methods known to date, requires only a few simulations, and identifies 55 new inhibitor designs against HIV-RT predicted to be at least as potent as a tight binding reference compound (i.e.

Enhanced Monte Carlo Methods for Modeling Proteins Including Computation of Absolute Free Energies of Binding.

The generation of a complete ensemble of geometrical configurations is required to obtain reliable estimations of absolute binding free energies by alchemical free energy methods. Molecular dynamics (MD) is the most popular sampling method, but the representation of large biomolecular systems may be incomplete owing to energetic barriers that impede efficient sampling of the configurational space. Monte Carlo (MC) methods can possibly overcome this issue by adapting the attempted movement sizes to facilitate transitions between alternative local-energy minima.

CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2.

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and [Formula: see text]-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained.