Sarfaraz K. Niazi

Drugging the Undruggable in Oncology: Structural Computation, Machine Learning, and Generative AI for Historically Intractable Targets

For four decades the central oncogenic drivers of human cancer the RAS GTPases, the transcription-factor MYC, mutant p53, and the protein-tyrosine phosphatases, fusion oncoproteins and intrinsically disordered regulators that surround them were regarded as undruggable: lacking de...

Current translational perspectives for diagnosis and individualized therapy in rare genetic diseases

Rare diseases affect hundreds of millions of individuals worldwide, primarily resulting from genetic factors, with many presenting during childhood. Advances in genome sequencing increasingly enable identification of the responsible gene in more patients; however, only a limited...

Dynamic Protein Structure Paradox: An Integrative Framework for Endpoint-Conditioned Evidentiary Sufficiency in Structure-to-Function Claims

Accurate coordinates for a represented protein state do not, by themselves, establish activity or any other condition-specific function. This article defines the Dynamic Protein Structure Paradox (DPSP) as the apparent conflict between structural accuracy and functional underdete...