What Can Molecular Dynamics Legitimately Claim in Pharmaceutical Research? A Critical Review of Sampling, Validation, and Mechanistic Interpretation

Molecular dynamics simulation has become central to pharmaceutical research because it can represent time-dependent molecular behaviour at spatial and temporal resolutions that are difficult to access experimentally. Its interpretive reach, however, is often extended beyond what a simulated trajectory can directly support. Structural persistence may be described as thermodynamic stability, incomplete sampling may be presented as a conformational ensemble, binding-pose retention may be treated as evidence of affinity, and correlated motions may be interpreted as causal mechanisms. This critical methodological review examines the evidential conditions under which such claims are defensible. A transparent, question-led search and appraisal approach was used to compare literature addressing conformational sampling, energy landscapes, force-field dependence, free-energy estimation, binding kinetics, allostery, convergence, reproducibility, and experimental validation. The appraisal focused on the proximity between computational output and stated conclusion, the adequacy of sampling, sensitivity to modelling assumptions, treatment of uncertainty, replication, external validation, and relevance to pharmaceutical decisions. The reviewed evidence indicates that molecular dynamics can robustly support bounded descriptions of behaviour produced by a specified model and, under stronger conditions, conditional inferences about conformational populations, thermodynamics, kinetics, and functional mechanisms. Confidence decreases when trajectory-local observations are converted into equilibrium, causal, or translational claims without independent replication, model-sensitivity analysis, quantity-matched validation, or experimental triangulation. The central judgement is that the legitimacy of a molecular-dynamics claim depends less on trajectory length or visual plausibility than on whether the evidence addresses the inferential step being made. Molecular dynamics is therefore most informative when claims remain proportional to sampling coverage, model fidelity, uncertainty, and external validation. The resulting framework is intended as a critical interpretive guide rather than a validated scoring system, clinical recommendation, regulatory standard, or universally applicable readiness framework.