Covalent virtual screening requires ranking compounds according to both noncovalent recognition and their ability to adopt a reaction-competent geometry with an appropriately reactive warhead. Here, we introduce BCover, a reaction-aware scoring suite that combines pre-reactive docking with quantum-chemistry-derived ligand reactivity descriptors, the electrostatic properties of the protein pocket. Quantum-chemical descriptors are aggregated using a nonlinear tree-based scoring model. BCover was evaluated retrospectively on the COValid benchmark, comprising nine targets and ten reactive sites, and compared with AutoDock, DOCK6, DOCKovalent, AlphaFold3 with Rosetta rescoring, and AlphaFold3 confidence-based ranking. BCover achieved an average adjusted LogAUC of 31% (57% max), an average ROC-AUC of 0.88 (0.96 max), an average EF1 of 18 (33 max). Its average LogAUC exceeded those of the classical docking methods and AlphaFold3-Rosetta, although AlphaFold3-mPAE provided the strongest overall enrichment. At an average runtime of about 10~s per ligand, BCover was approximately 25-fold faster than the evaluated AlphaFold3 workflows and achieved the highest average time-adjusted virtual-screening productivity index. Redocking experiments further showed that the method recovered near-native ligand conformations. These results demonstrate that combining docking-derived geometry with ligand local electronic reactivity and pocket electrostatics provides an efficient and interpretable strategy for covalent ligand prioritization. BCover is intended as a high-throughput screening method that complements more computationally demanding QM/MM and free-energy calculations during subsequent lead optimization.
Q-Score is introduced, encoding GNN-predicted orbital donor-acceptor energies into a weighted graph and scoring binding by solving a maximum-weight vertex clique problem via Digitized-Counterdiabatic QAOA, enriching for strong orbital interactions at twice the random rate.
Kangyu Zheng, Yidong Zhou, Ruihao Li et al.· 0 citations
Structural investigation of re-docked actives showed that re-ranked poses were more native-like, with improved binding-site occupancy, reduced centroid displacement, and greater recovery of co-crystal interactions.
Lai Hoang Son Le, Thanh-An Pham, Ngoc Nguyen Tran et al.· bioRxiv· 0 citations
A category-stratified, statistically powered benchmark comparing pose prediction from receptor conformational ensembles against AlphaFold2, used as a matched static-structure baseline, across 29 protein–ligand systems spanning cryptic-pocket, induced-fit, water-mediated, and autoimmune-indication target classes is presented.
Ryan Varghese, Pooja Tiwary, Krishil Oswal· bioRxiv· 0 citations
A practical guide and a warning for researchers who are designing metallodrugs by using docking is offered, concentrating on the application of inorganic complexes in the field of anticancer.
Y. J. Sahar, A. Yasir, H. A. Kyhoiesh· Discover Chemistry· 0 citations
An integrated computational strategy involving pharmacophore mapping, molecular docking, molecular dynamics simulations, and density functional theory (DFT) analysis was employed to identify potential SaFtsZ inhibitors, highlighting compound 15 as a computationally predicted scaffold for the development of SaFtsZ-targeted antibacterial agents.
Sundarrajan T., Neerugatti Dora Babu, A. K. N. et al.· RSC Advances· 0 citations