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Lactate in tumors has long been considered "metabolic junk" derived from the glycolysis of cancer cells and utilized only as a biomarker of malignancy, but is presently believed to be a pivotal regulator of tumor development, maintenance and metastasis. Indeed, tumor lactate can be a "fuel" for energy supply and functions as a signaling molecule, which actively contributes to tumor progression, angiogenesis, immunosuppression, therapeutic resistance, etc., thus providing promising opportunities for cancer treatment. However, the current approaches for regulating lactate homeostasis with available agents are still challenging, which is mainly due to the short half-life, low bioavailability and poor specificity of these agents and their unsatisfactory therapeutic outcomes. In recent years, lactate modulation nanomedicines have emerged as a charming and efficient strategy for fighting cancer, which play important roles in optimizing the delivery of lactate-modulating agents for more precise and effective modulation and treatment. Integrating specific lactate-modulating functions in diverse therapeutic nanomedicines may overcome the intrinsic restrictions of different therapeutic modalities by remodeling the pathological microenvironment for achieving enhanced cancer therapy. In this review, the most recent advances in the engineering of functional nanomedicines that can modulate tumor lactate for cancer therapy are summarized and discussed, and the fundamental mechanisms by which lactate modulation benefits various therapeutics are elucidated. Finally, the challenges and perspectives of this emerging strategy in the anti-tumor field are highlighted. [ABSTRACT FROM AUTHOR]

The identification and optimization of lead compounds are inalienable components in drug design and discovery pipelines. As a powerful computational approach for the identification of hits with novel structural scaffolds, structure-based virtual screening (SBVS) has exhibited a remarkably increasing influence in the early stages of drug discovery. During the past decade, a variety of techniques and algorithms have been proposed and tested with different purposes in the scope of SBVS. Although SBVS has been a common and proven technology, it still shows some challenges and problems that are needed to be addressed, where the negative influence regardless of protein flexibility and the inaccurate prediction of binding affinity are the two major challenges. Here, focusing on these difficulties, we summarize a series of combined strategies or workflows developed by our group and others. Furthermore, several representative successful applications from recent publications are also discussed to demonstrate the effectiveness of the combined SBVS strategies in drug discovery campaigns. [ABSTRACT FROM AUTHOR]