To further survey the effect of partial charge and conforma- tions of energetic and entropic significance, we trained different representations with the same procedure and test their performances on the same datasets. As shown in Table , introduction of partial charge into the ACSFs, great improvements could be achieved. For example, when scaling all partial charge to 1, the MAE (MSE) of ACSFs con f is 0.97(1.66), 0.83(1. diversity of the compounds, good prediction was achieved especially in the aspect of conformational entropy and polarity. Benefit from the high-dimensional neural network (HDNN) and atom-center symmetry functions (ACSFs), q -ACSFs con f not only could be able to give a partition coefficient for a single molecule, but also has the ability for deriving the contribution from a single atom, as our input is only dependent on the element and the surrounding environments. As a consequence, we decomposed the partition coefficient of all the molecules into single atoms and analyzed over three datasets. As shown in Figure , the values of contribution from single atom C ranges from -0.2 to 0.7, and they mainly concentrated above 0 which is guided by the black dashed line. For atom O and atom N, the values are almost negative. Same conclusion could be drawn from datasets Martel and Huuskonen (middle and right panel of Figure ). Intriguingly, this phenomenon is consistent with the simple model proposed by Mannhold where the partition coefficient is only related to the number of carbon atoms (NC) and number of hetero atoms (NHET ) (log P = 1.46(±0.02) + 0.11(±0.001)NC -0.11(±0.001)NHET ). When digging deep into the contribution from the element H, we found that the peak of the distribution is in accordance with the dashed line at 0, which means in some situations, it increased the partition coefficient, while decreased in the resting situations. Further analyses on dividing the contri-bution of each atoms according to the surrounding environments could be found in Figure -S8 and Table . From Figure and Table , we could see that atom H prefers to increase the partition coefficient when bonding with atom C independent of hybridization methods. To the contrary, when bonding with hetero atoms, atom H prefers to decrease the partition coefficient. In summary, we designed a new descriptor based on the conventional atom-centered symmetry functions (ACSFs) and we called it q -ACSFs con f . Polarization and entropy effects were treated explicitly by introducing the partial charges derived directly from force field and conformations of energetic and entropic significance sampled from molecular dynamics simulations. Different from atom-or fragment-additive models, our model do not need to pre-define the types of atom or fragment and could bypass the pitfall of missing atoms or fragments. In addition, no prior knowledge was introduced in our model compared with some models which need pre-calculated molecular descriptors. We further tested the effects of polarization and entropy on model performance, results and feature selection showed that the polarization is important in the prediction of partition coefficient, and significant improvement could be achieved on dataset Star & Non-Star (MAE increased from 0.83 to 0.48)and Huuskonen (MAE increased from 0.54 to 0.22). However, a slight improvement was observed for the introduction of different conformations, which may attribute to the conformational space we sampled is insufficient. As a result, to better improve the accuracy of the model, much more emphasis should be laid on the technology of enhanced sampling methods, especially for the target-free methods, such as the metadynamics, umbrella sampling, DAta-Driven acceleration method and so on. Some progress is still being made in our lab. In addition, inheriting the advantage of atomcentered symmetry functions, q -ACSFs con f has the ability to decompose the partition coefficient into each atoms. Interestingly, when we statistically analyzed the contributions from four distinct elements, we found that the contribution from element C are almost positive, while negative for the element O and N, the main conclusion is consistent with the linear model proposed previously. The present study supplies a new strategy for the prediction of partition coefficient and other physical properties, such as the distribution coefficient and aqueous solubility, in the drug and materials design.