02679naa a2200421 a 450000100080000000500110000800800410001902200140006002400520007410000170012624501710014326000090031452013160032365300210163965300350166065300280169565300300172365300220175365300270177565300370180265300210183965300390186065300310189965300280193065300240195865300220198270000170200470000150202170000160203670000140205270000230206670000210208970000210211070000140213170000160214570000160216177300800217721690212024-11-18       2024    bl uuuu     u00u1 u    #d  a2001-03707 ahttps://doi.org/10.1016/j.csbj.2024.10.0362DOI1 aOMAGE, F. B.  aProtein allosteric site identification using machine learning and per amino acid residue reported internal protein nanoenvironment descriptors.h[electronic resource]  c2024  aAllosteric regulation plays a crucial role in modulating protein functions and represents a promising strategy in drug development, offering enhanced specificity and reduced toxicity compared to traditional active site inhi- bition. Existing computational methods for predicting allosteric sites on proteins often rely on static protein surface pocket features, normal mode analysis or extensive molecular dynamics simulations encompassing both the protein function modulator and the protein itself. In this study, we introduce an innovative methodology that employs a per amino acid residue classifier to distinguish allosteric site-forming residues (AFRs) from non-allosteric, or free residues (FRs). Our model, STINGAllo, exhibits robust performance, achieving Distance Center Center (DCC) success rate when all AFRs were predicted within pockets identified by FPocket, overall DCC, F1 score and a Matthews correlation coefficient (MCC) of 78 %, 60 %, 64 % and 64 % respectively. Furthermore, we identified key descriptors that characterize the internal protein nanoenvironment of AFRs, setting them apart from FRs. These descriptors include the sponge effect, distance to the protein centre of geometry (cg), hydro- phobic interactions, electrostatic potentials, eccentricity, and graph bottleneck features.  aAllosteric sites  aAnálise da estrutura proteica  aAprendizado de máquina  aComputational drug design  aDescritores STING  aDistance center center  aInternal protein nanoenvironment  aMachine learning  aNanoambiente interno de proteínas  aProtein structure analysis  aRegulação alostérica  aSitios alostéricos  aSTING descriptors1 aSALIM, J. A.1 aMAZONI, I.1 aYANO, I. H.1 aBORRO, L.1 aGONZALEZ, J. E. H.1 aMORAES, F. R. de1 aGIACHETTO, P. F.1 aTASIC, L.1 aARNI, R. K.1 aNESHICH, G.  tComputational and Structural Biotechnologygv. 23, p. 3907-3919, Dec. 2024.