Benjamin D. Madej

The AMBER lipid force field has been updated to create Lipid14, allowing tensionless simulation of a number of lipid types with the AMBER MD package. The modular nature of this force field allows numerous combinations of head and tail groups to create different lipid types, enabling the easy insertion of new lipid species. The Lennard-Jones and torsion parameters of both the head and tail groups have been revised and updated partial charges calculated. The force field has been validated by simulating bilayers of six different lipid types for a total of 0.5 μs each without applying a surface tension; with favorable comparison to experiment for properties such as area per lipid, volume per lipid, bilayer thickness, NMR order parameters, scattering data, and lipid lateral diffusion. As the derivation of this force field is consistent with the AMBER development philosophy, Lipid14 is compatible with the AMBER protein, nucleic acid, carbohydrate, and small molecule force fields.

Accurate simulation of complex lipid bilayers has long been a goal in condensed phase molecular dynamics (MD). Structure and function of membrane-bound proteins are highly dependent on the lipid bilayer environment and are challenging to study through experimental methods. Within Amber, there has been limited focus on lipid simulations, although some success has been seen with the use of the General Amber Force Field (GAFF). However, to date there are no dedicated Amber lipid force fields. In this paper we describe a new charge derivation strategy for lipids consistent with the Amber RESP approach and a new atom and residue naming and type convention. In the first instance, we have combined this approach with GAFF parameters. The result is LIPID11, a flexible, modular framework for the simulation of lipids that is fully compatible with the existing Amber force fields. The charge derivation procedure, capping strategy, and nomenclature for LIPID11, along with preliminary simulation results and a discussion of the planned long-term parameter development are presented here. Our findings suggest that LIPID11 is a modular framework feasible for phospholipids and a flexible starting point for the development of a comprehensive, Amber-compatible lipid force field.

Conventional drug discovery is long and costly, and suffers from high attrition rates, often leaving patients with limited or expensive treatment options. Recognizing the overwhelming need to accelerate this process and increase success, the ATOM consortium was formed by government, industry, and academic partners in October 2017. ATOM applies a team science and open-source approach to foster a paradigm shift in drug discovery. ATOM is developing and validating a precompetitive, preclinical, small molecule drug discovery platform that simultaneously optimizes pharmacokinetics, toxicity, protein-ligand interactions, systems-level models, molecular design, and novel compound generation. To achieve this, the ATOM Modeling Pipeline (AMPL) has been developed to enable advanced and emerging machine learning (ML) approaches to build models from diverse historical drug discovery data. This modular pipeline has been designed to couple with a generative algorithm that optimizes multiple parameters necessary for drug discovery. ATOM's approach is to consider the full pharmacology and therapeutic window of the drug concurrently, through computationally-driven design, thereby reducing the number of molecules that are selected for experimental validation. Here, we discuss the role of collaborative efforts such as consortia and public-private partnerships in accelerating cross disciplinary innovation and the development of open-source tools for drug discovery.

The Amber Lipid14 force field is expanded to include cholesterol parameters for all-atom cholesterol and lipid bilayer molecular dynamics simulations. The General Amber and Lipid14 force fields are used as a basis for assigning atom types and basic parameters. A new RESP charge derivation for cholesterol is presented, and tail parameters are adapted from Lipid14 alkane tails. 1,2-Dimyristoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers are simulated at a range of cholesterol contents. Experimental bilayer structural properties are compared with bilayer simulations and are found to be in good agreement. With this parameterization, another component of complex membranes is available for molecular dynamics with the Amber Lipid14 force field.

This communication reports the first example of spontaneous lipid bilayer formation in unbiased all-atom molecular dynamics (MD) simulations. Using two different lipid force fields we show simulations started from random mixtures of lipids and water in which four different types of phospholipids self-assemble into organized bilayers in under 1 microsecond.