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ABSTRACT Diacylglycerol O‐acyltransferase 1 (DGAT1) is an integral membrane protein that uses acyl‐coenzyme A (acyl‐CoA) and diacylglycerol (DAG) to catalyze the formation of triacylglycerides (TAGs). The acyl transfer reaction occurs between the activated carboxylate group of the fatty acid and the free hydroxyl group on the glycerol backbone of DAG. However, how the two substrates enter DGAT1's catalytic reaction chamber and interact with DGAT1 remains elusive. This study aims to explore the structural basis of DGAT1's substrate recognition by investigating each substrate's pathway to the reaction chamber. Using a human DGAT1 cryo‐EM structure in complex with an oleoyl‐CoA substrate, we designed two different all‐atom molecular dynamics (MD) simulation systems: DGAT1^away(both acyl‐CoA and DAG away from the reaction chamber) and DGAT1^bound(acyl‐CoA bound in and DAG away from the reaction chamber). Our DGAT1^awaysimulations reveal that acyl‐CoA approaches the reaction chamber via interactions with positively charged residues in transmembrane helix 7. DGAT1^boundsimulations show DAGs entering into the reaction chamber from the cytosol leaflet. The bound acyl‐CoA's fatty acid lines up with the headgroup of DAG, which appears to be competent to TAG formation. We then converted them into TAG and coenzyme (CoA) and used adaptive biasing force (ABF) simulations to explore the egress pathways of the products. We identify their escape routes, which are aligned with their respective entry pathways. Visualization of the substrate and product pathways and their interactions with DGAT1 is expected to guide future experimental design to better understand DGAT1 structure and function. 

Abstract Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials.