ACES: Optimized Alchemically Enhanced Sampling.

We present an alchemical enhanced sampling (ACES) method implemented in the GPU-accelerated AMBER free energy MD engine. The methods hinges on the creation of an "enhanced sampling state" by reducing or eliminating selected potential energy terms and interactions that lead to kinetic traps and conformational barriers while maintaining those terms that curtail the need to otherwise sample large volumes of phase space. For example, the enhanced sampling state might involve transforming regions of a ligand and/or protein side chain into a noninteracting "dummy state" with internal electrostatics and torsion angle terms turned off. The enhanced sampling state is connected to a real-state end point through a Hamiltonian replica exchange (HREMD) framework that is facilitated by newly developed alchemical transformation pathways and smoothstep softcore potentials. This creates a counterdiffusion of real and enhanced-sampling states along the HREMD network. The effect of a differential response of the environment to the real and enhanced-sampling states is minimized by leveraging the dual topology framework in AMBER to construct a counterbalancing HREMD network in the opposite alchemical direction with the same (or similar) real and enhanced sampling states at inverted end points. The method has been demonstrated in a series of test cases of increasing complexity where traditional MD, and in several cases alternative REST2-like enhanced sampling methods, are shown to fail. The hydration free energy for acetic acid was shown to be independent of the starting conformation, and the values for four additional edge case molecules from the FreeSolv database were shown to have a significantly closer agreement with experiment using ACES. The method was further able to handle different rotamer states in a Cdk2 ligand identified as fractionally occupied in crystal structures. Finally, ACES was applied to T4-lysozyme and demonstrated that the side chain distribution of V111χ1 could be reliably reproduced for the apo state, bound to p-xylene, and in p-xylene→ benzene transformations. In these cases, the ACES method is shown to be highly robust and superior to a REST2-like enhanced sampling implementation alone.

AMBER Free Energy Tools: A New Framework for the Design of Optimized Alchemical Transformation Pathways.

We develop a framework for the design of optimized alchemical transformation pathways in free energy simulations using nonlinear mixing and a new functional form for so-called "softcore" potentials. We describe the implementation and testing of this framework in the GPU-accelerated AMBER software suite. The new optimized alchemical transformation pathways integrate a number of important features, including (1) the use of smoothstep functions to stabilize behavior near the transformation end points, (2) consistent power scaling of Coulomb and Lennard-Jones (LJ) interactions with unitless control parameters to maintain balance of electrostatic attractions and exchange repulsions, (3) pairwise form based on the LJ contact radius for the effective interaction distance with separation-shifted scaling, and (4) rigorous smoothing of the potential at the nonbonded cutoff boundary. The new softcore potential form is combined with smoothly transforming nonlinear λ weights for mixing specific potential energy terms, along with flexible λ-scheduling features, to enable robust and stable alchemical transformation pathways. The resulting pathways are demonstrated and tested, and shown to be superior to the traditional methods in terms of numerical stability and minimal variance of the free energy estimates for all cases considered. The framework presented here can be used to design new alchemical enhanced sampling methods, and leveraged in robust free energy workflows for large ligand data sets.

AMBER Drug Discovery Boost Tools: Automated Workflow for Production Free-Energy Simulation Setup and Analysis (ProFESSA).

We report an automated workflow for production free-energy simulation setup and analysis (ProFESSA) using the GPU-accelerated AMBER free-energy engine with enhanced sampling features and analysis tools, part of the AMBER Drug Discovery Boost package that has been integrated into the AMBER22 release. The workflow establishes a flexible, end-to-end pipeline for performing alchemical free-energy simulations that brings to bear technologies, including new enhanced sampling features and analysis tools, to practical drug discovery problems. ProFESSA provides the user with top-level control of large sets of free-energy calculations and offers access to the following key functionalities: (1) automated setup of file infrastructure; (2) enhanced conformational and alchemical sampling with the ACES method; and (3) network-wide free-energy analysis with the optional imposition of cycle closure and experimental constraints. The workflow is applied to perform absolute and relative solvation free-energy and relative ligand-protein binding free-energy calculations using different atom-mapping procedures. Results demonstrate that the workflow is internally consistent and highly robust. Further, the application of a new network-wide Lagrange multiplier constraint analysis that imposes key experimental constraints substantially improves binding free-energy predictions.

Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.

Synthesis of 5-Cyanomethyluridine (cnm5 U) and 5-Cyanouridine (cn5 U) Phosphoramidites and Their Incorporation into RNA Oligonucleotides.

This article contains detailed synthetic protocols for preparation of 5-cyanomethyluridine (cnm5 U) and 5-cyanouridine (cn5 U) phosphoramidites. The synthesis of the cnm5 U phosphoramidite building block starts with commercially available 5-methyluridine (m5 C), followed by bromination of the 5-methyl group to install the cyano moiety using TMSCN/TBAF. The cn5 U phosphoramidite is obtained by regular Vorbrüggen glycosylation of the protected ribofuranose with silylated 5-cyanouracil. These two modified phosphoramidites are suitable for synthesis of RNA oligonucleotides on solid phase using conventional amidite chemistry. Our protocol provides access to two novel building blocks for constructing RNA-based therapeutics. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Preparation of cnm5 U and cn5 U phosphoramidites Basic Protocol 2: Synthesis, purification, and characterization of cnm5 U- and cn5 U-modified RNA oligonucleotides.

Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials.

Progress in the development of GPU-accelerated free energy simulation software has enabled practical applications on complex biological systems and fueled efforts to develop more accurate and robust predictive methods. In particular, this work re-examines concerted (a.k.a., one-step or unified) alchemical transformations commonly used in the prediction of hydration and relative binding free energies (RBFEs). We first classify several known challenges in these calculations into three categories: endpoint catastrophes, particle collapse, and large gradient-jumps. While endpoint catastrophes have long been addressed using softcore potentials, the remaining two problems occur much more sporadically and can result in either numerical instability (i.e., complete failure of a simulation) or inconsistent estimation (i.e., stochastic convergence to an incorrect result). The particle collapse problem stems from an imbalance in short-range electrostatic and repulsive interactions and can, in principle, be solved by appropriately balancing the respective softcore parameters. However, the large gradient-jump problem itself arises from the sensitivity of the free energy to large values of the softcore parameters, as might be used in trying to solve the particle collapse issue. Often, no satisfactory compromise exists with the existing softcore potential form. As a framework for solving these problems, we developed a new family of smoothstep softcore (SSC) potentials motivated by an analysis of the derivatives along the alchemical path. The smoothstep polynomials generalize the monomial functions that are used in most implementations and provide an additional path-dependent smoothing parameter. The effectiveness of this approach is demonstrated on simple yet pathological cases that illustrate the three problems outlined. With appropriate parameter selection, we find that a second-order SSC(2) potential does at least as well as the conventional approach and provides vast improvement in terms of consistency across all cases. Last, we compare the concerted SSC(2) approach against the gold-standard stepwise (a.k.a., decoupled or multistep) scheme over a large set of RBFE calculations as might be encountered in drug discovery.

Validation of Free Energy Methods in AMBER.

Herein we provide high-precision validation tests of the latest GPU-accelerated free energy code in AMBER. We demonstrate that consistent free energy results are obtained in both the gas phase and in solution. We first show, in the context of thermodynamic integration (TI), that the results are invariant with respect to "split" (e.g., stepwise decharge-vdW-recharge) versus "unified" protocols. This brought to light a subtle inconsistency in previous versions of AMBER that was traced to the improper treatment of 1-4 vdW and electrostatic interactions involving atoms across the softcore boundary. We illustrate that under the assumption that the ensembles produced by different legs of the alchemical transformation between molecules A and B in the gas phase and aqueous phase are very small, the inconsistency in the relative hydration free energy ΔΔGhydr[A → B] = ΔGaq[A → B] - ΔGgas[A → B] is minimal. However, for general cases where the ensembles are shown to be substantially different, as expected in ligand-protein binding applications, these errors can be large. Finally, we demonstrate that results for relative hydration free energy simulations are independent of TI or multistate Bennett's acceptance ratio (MBAR) analysis, invariant to the specific choice of the softcore region, and in agreement with results derived from absolute hydration free energy values.

Cyano Modification on Uridine Decreases Base-Pairing Stability and Specificity through Neighboring Disruption in RNA Duplex.

5-Cyanomethyluridine (cnm5 U) and 5-cyanouridine (cn5 U), the two uridine analogues, were synthesized and incorporated into RNA oligonucleotides. Base-pairing stability and specificity studies in RNA duplexes indicated that cnm5 U slightly decreased the stability of the duplex but retained the base-pairing preference. In contrast, cn5 U dramatically decreased both base-pairing stability and specificity between U:A and other noncanonical U:G, U:U, and U:C pairs. In addition, the cn5 U:G pair was found to be stronger than the cn5 U:A pair and the other mismatched pairs in the context of a RNA duplex; this implied that cn5 U might slightly prefer to recognize G over A. Our mechanistic studies by molecular simulations showed that the cn5 U modification did not directly affect the base pairing of the parent nucleotide; instead, it weakened the neighboring base pair in the 5' side of the modification in the RNA duplexes. Consistent with the simulation data, replacing the Watson-Crick A:U pair to a mismatched C:U pair in the 5'-neighboring site did not affect the overall stability of the duplex. Our work reveals the significance of the electron-withdrawing cyano group in natural tRNA systems and provides two novel building blocks for constructing RNA-based therapeutics.