Strain Problems got you in a Twist? Try StrainRelief: A Quantum-Accurate Tool for Ligand Strain Calculations
원문 초록
Ligand strain energy, the energy difference between the bound and unbound conformations of a ligand, is an important component of structure-based small molecule drug design. A large majority of observed ligands in protein-small molecule co-crystal structures bind in low-strain conformations, making strain energy a useful filter for structure-based drug design. In this work we present a tool for calculating ligand strain with a high accuracy. StrainRelief uses a MACE Neural Network Potential (NNP), trained on a large database of Density Functional Theory (DFT) calculations to estimate ligand strain of neutral molecules with quantum accuracy. We show that this tool estimates strain energy differences relative to DFT to within 1.4 kcal/mol, more accurately than alternative NNPs. These results highlight the utility of NNPs in drug discovery, and provide a useful tool for drug discovery teams.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Assay2Mol: large language model-based drug design using BioAssay context
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
BioChemInsight: An Open-Source Toolkit for Automated Identification and Recognition of Optical Chemical Structures and Activity Data in Scientific Publications
Molecule Generation for Target Protein Binding with Hierarchical Consistency Diffusion Model
3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery
Test-Time Training Scaling Laws for Chemical Exploration in Drug Design
토론
이 논문과 연결된 포럼 글이 아직 없습니다.